research article floristic composition, structure, and

16
Research Article Floristic Composition, Structure, and Species Associations of Dry Miombo Woodland in Tanzania Ezekiel Edward Mwakalukwa, 1,2 Henrik Meilby, 1 and Thorsten Treue 1 1 Department of Food and Resource Economics, Faculty of Science, University of Copenhagen, Rolighedsvej 23, 1958 Frederiksberg C, Denmark 2 Department of Forest Biology, Faculty of Forestry and Nature Conservation, Sokoine University of Agriculture, P.O. Box 3010, Chuo Kikuu, Morogoro, Tanzania Correspondence should be addressed to Ezekiel Edward Mwakalukwa; [email protected] Received 20 December 2013; Accepted 4 February 2014; Published 8 May 2014 Academic Editors: M. Drielsma, H. Ford, M. Tigabu, and A. Vi˜ na Copyright © 2014 Ezekiel Edward Mwakalukwa et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For the majority of forest reserves in Tanzania, biodiversity is poorly documented. is study was conducted to assess species richness (woody species), diversity, and forest structure and to examine relationships between species occurrence and topographic and edaphic factors in the Gangalamtumba Village Land Forest Reserve, a dry Miombo woodland area in Tanzania. A total of 35 nested circular plots with radii of 5, 15, and 20m were used to collect data on woody species and soil samples across the 6,065 ha community-managed forest reserve. Stumps were measured 20cm above ground. A total of 88 species belonging to 29 families were identified. Generally forest structure parameters and diversity indices indicated the forest to be in a good condition and have high species richness and diversity. Vegetation analysis revealed four communities of which two were dominated by the family Caesalpiniaceae, indicating large variation of site conditions and possible disturbances in the study area. e high level of diversity of woody species and the high basal area and volume indicate that the forest is in good condition, but the effect of anthropogenic activities is evident and stresses the need for proper management to maintain or enhance the present species diversity. 1. Introduction Miombo woodland is the most widespread and dominant dry forest formation in Eastern, Central, and Southern Africa. It is characterized by an abundance of tree species in the legume subfamily Caesalpinoideae, including the three dominant genera of Brachystegia, Julbernardia, and Isoberlinia [1, 2]. Covering an area of about 3.6 million km 2 , miombo wood- land supports the livelihoods of more than 100 million rural and urban dwellers by providing a wide range of products such as firewood, charcoal, timber, and forage and services such as soil conservation and water catchment [35]. How- ever, due to the rapid population growth and the high level of poverty across the Miombo region, the human pressure on its woodlands has steadily increased over the last decades, lead- ing to increasing deforestation and forest degradation [68]. e effects of increasing rates of deforestation and forest degradation on biodiversity in developing countries have been thoroughly studied [912]. Habitat loss due to deforesta- tion reduces not only the number of species in the ecosystem but also the number and extent of places where species coexist. Activities such as charcoal production, firewood col- lection for subsistence use and for tobacco curing, conversion of woodlands to farmland, and seasonal forest fires are among the major drivers of deforestation and forest degradation in the Miombo region [1317]. It is estimated that 1.4 million ha of woodlands is lost annually in the countries where Miombo woodlands dominate, leading to a loss of carbon stocks, biodiversity, and, through soil degradation, loss of plant nutrients [4, 5]. Syampungani et al. [5, p. 151] stated that “loss of biodiversity and extinction of most of the woodland resources are imminent if the current intensive exploitation of Miombo resources continues unchecked.” More specifically, FAO (2000a, cited by Syampungani et al. [5]) reported that 191 tree species in the Miombo ecoregion are endangered due Hindawi Publishing Corporation ISRN Biodiversity Volume 2014, Article ID 153278, 15 pages http://dx.doi.org/10.1155/2014/153278

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Page 1: Research Article Floristic Composition, Structure, and

Research ArticleFloristic Composition Structure and Species Associations ofDry Miombo Woodland in Tanzania

Ezekiel Edward Mwakalukwa12 Henrik Meilby1 and Thorsten Treue1

1 Department of Food and Resource Economics Faculty of Science University of Copenhagen Rolighedsvej 231958 Frederiksberg C Denmark

2Department of Forest Biology Faculty of Forestry and Nature Conservation Sokoine University of AgriculturePO Box 3010 Chuo Kikuu Morogoro Tanzania

Correspondence should be addressed to Ezekiel Edward Mwakalukwa ezedwayahoocom

Received 20 December 2013 Accepted 4 February 2014 Published 8 May 2014

Academic Editors M Drielsma H Ford M Tigabu and A Vina

Copyright copy 2014 Ezekiel Edward Mwakalukwa et al This is an open access article distributed under the Creative CommonsAttribution License which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

For the majority of forest reserves in Tanzania biodiversity is poorly documented This study was conducted to assess speciesrichness (woody species) diversity and forest structure and to examine relationships between species occurrence and topographicand edaphic factors in the Gangalamtumba Village Land Forest Reserve a dry Miombo woodland area in Tanzania A total of 35nested circular plots with radii of 5 15 and 20m were used to collect data on woody species and soil samples across the 6065 hacommunity-managed forest reserve Stumps were measured 20 cm above ground A total of 88 species belonging to 29 familieswere identified Generally forest structure parameters and diversity indices indicated the forest to be in a good condition and havehigh species richness and diversity Vegetation analysis revealed four communities of which two were dominated by the familyCaesalpiniaceae indicating large variation of site conditions and possible disturbances in the study area The high level of diversityof woody species and the high basal area and volume indicate that the forest is in good condition but the effect of anthropogenicactivities is evident and stresses the need for proper management to maintain or enhance the present species diversity

1 Introduction

Miombowoodland is themost widespread and dominant dryforest formation in Eastern Central and Southern Africa Itis characterized by an abundance of tree species in the legumesubfamily Caesalpinoideae including the three dominantgenera of Brachystegia Julbernardia and Isoberlinia [1 2]Covering an area of about 36 million km2 miombo wood-land supports the livelihoods of more than 100 million ruraland urban dwellers by providing a wide range of productssuch as firewood charcoal timber and forage and servicessuch as soil conservation and water catchment [3ndash5] How-ever due to the rapid population growth and the high level ofpoverty across theMiombo region the human pressure on itswoodlands has steadily increased over the last decades lead-ing to increasing deforestation and forest degradation [6ndash8]

The effects of increasing rates of deforestation and forestdegradation on biodiversity in developing countries have

been thoroughly studied [9ndash12] Habitat loss due to deforesta-tion reduces not only the number of species in the ecosystembut also the number and extent of places where speciescoexist Activities such as charcoal production firewood col-lection for subsistence use and for tobacco curing conversionof woodlands to farmland and seasonal forest fires are amongthe major drivers of deforestation and forest degradation inthe Miombo region [13ndash17] It is estimated that 14 millionha of woodlands is lost annually in the countries whereMiombo woodlands dominate leading to a loss of carbonstocks biodiversity and through soil degradation loss ofplant nutrients [4 5] Syampungani et al [5 p 151] stated thatldquoloss of biodiversity and extinction of most of the woodlandresources are imminent if the current intensive exploitation ofMiombo resources continues uncheckedrdquo More specificallyFAO (2000a cited by Syampungani et al [5]) reported that191 tree species in theMiombo ecoregion are endangered due

Hindawi Publishing CorporationISRN BiodiversityVolume 2014 Article ID 153278 15 pageshttpdxdoiorg1011552014153278

2 ISRN Biodiversity

N

PlotsVillagesDirt roads

Forest roadsGangalamtumba forest reserve

Tanzania

Iringa region 0 25 5 10

(km) To Iringa

Airport

Itagutwa

IkengezaTo Dodoma

Mfyome

Kiwele

Luganga

Figure 1 Map showing the location of the study area The inserted map of Tanzania shows the location of the Iringa region

to conversion of forest areas into agricultural lands or throughcharcoal production

GangalamtumbaVillage LandForest Reserve (GVLFR) inIringa rural district Tanzania which is owned and managedby the village of Mfyome was established in 2002 underTanzaniarsquos national participatory forest management pro-gramme and thus represents one of approximately 1500 Vil-lage Land Forest Reserves (covering some 24 million ha) theprogressive establishment of which is intended to promoteconservation of approximately 165 million ha of hithertounreserved forest on general and village land [18ndash21] Villagesrsquocontrol over Village Land Forest Reserves is conditional ontheir conservationprotection of these forests and the exec-utive management is performed by an environmentalforestmanagement committee whose members are directly electedfor five-year terms by all members of the village above theage of 18 [18] As such GVLFR is a typical example of anarea which at least until 2002 might have experienced lossof biodiversity due to increasing human activity includingcharcoal production and extraction of wood for tobaccocuring giving cause for concern with respect to the main-tenance of forest biodiversity [15] The extent to which theactivities have led to loss of biodiversity and deterioration ofthe plant community structure is so far unknown but for thedevelopment of sustainablewoodlandmanagement strategies

and for planning of future management and conservationinformation on these issues is urgently needed

Although many quantitative ecological studies have beenundertaken in places where Miombo dominates its exten-siveness and the large between-site variation which is causedby climatic and edaphic factors and anthropogenic activitiesappear to warrant further case studies [20 22ndash29] Ecologicalcase studies are particularly relevant when the informationgenerated is required for sound decision making about forestmanagement conservation strategies and determination ofsustainable harvesting levels Hence the objectives of thisstudy were (1) to provide a detailed assessment of the currentstanding stock species diversity richness and structure and(2) to understand the relationship between species abundanceand a range of environmental and topographic factors thatshape plant communities and species associations in theGVLFR

2 Materials and Methods

21 Study Site Gangalamtumba Village Land Forest Reserveis located in central-southern Tanzania (7∘351015840S 35∘351015840E)about 30 km north of Iringa town the administrative capitalof the Iringa region (Figure 1)The forest covers 6065 hectaresand is part of the Mfyome village area which is located in

ISRN Biodiversity 3

the ward of Kiwele The forest vegetation has been describedas dry Miombo woodland similar to the dry woodlandtype described from other countries such as Zimbabwe andMozambique [1] The forest is located in a relatively flat areaat an elevation of 850ndash1300 metres above sea level Theregion is characterised by distinct wet and dry seasons withalmost no rain in the four months of June-September andabout 80 of the annual precipitation falling in DecemberndashMarch Average rainfall data covering the last 50 years (1960ndash2010) were obtained from the meteorological station at Nduliairport which is located about 30 km from the forest andindicate that the area receives an average annual precipitation(mean plusmn standard error) of 617plusmn17mm (448ndash1085mm)Themean annual temperature is 198∘C and the average relativehumidities at 0600 and 1200GMT are 539 and 514respectively

The GVLFR is a production forest which is managedby the Mfyome village under a community-based forestmanagement (CBFM) arrangement established in 2002 com-pare above The primary economic activity in Mfyome issmallholder agriculture and the main economic uses of theforest are production of timber charcoal and firewood [20]The woodland is also used for grazing and is an importantsource of subsistence products such as firewood constructionmaterials fruit mushrooms wild vegetables and medicinalplants [18]

22 Vegetation Survey The field survey was conducted inJuly and August 2009 and involved establishment of a totalof 35 permanent nested circular sample plots distributedacross the entire forest Plots were established along transectlines and the distance between plots was approximately2 km (Figure 1) The radii of the nested circular plots were5m (00079 ha) 15m (00707 ha) and 20m (01257 ha) Thefollowing parameters were recorded within each of the 35plots within the 5m radius all small trees and shrubs(lt150 cm tall or ge150 cm but lt1 cm Dbh) were counted andtheir species were identified and medium-size trees andshrubs (ge1 cm Dbh but lt5 cm Dbh) were identified andmeasured with respect to diameter Within 15m radius thespecies were identified and the diameter was measured for alllarge trees and shrubs with Dbh ge5 cm Within 20m radiusall stumps of trees and shrubs were identified to specieslevel and measured for diameter 20 cm above ground Initialidentification of species for both standing treesshrubs andstumps relied on the knowledge of local botanists (usinglocal vernacular species names and features such as colorof the bark smell and leaves) and was later confirmed bybotanists from Tanzania Forest Research Institute (TAFORI)based at Lushoto Silviculture Research Station For speciesthat were difficult to identify in the field samples weretaken to the herbarium at Lushoto for reidentification Othermeasurements taken within the plots were geographicallocation (UTMcoordinates) and elevation (m) usingGPS andslope () using a Suunto clinometer

23 Soil Sampling Soil samples were collected from fivepoints which were located at the centre of the plot and 10mfrom the centre in the four cardinal directions (North East

South and West) At each point two samples were taken 0ndash15 cm and 15ndash30 cm below the surfaceThe five samples takenfrom each depth range were mixed in the field to obtain onecomposite sample per depth range and plot Thus 70 soilsamples (35 from each depth range) were collected from the35 plots In addition a soil core device with an inner diameterof 5 cm and a length of 5 cm was used for extracting soilbulk density samples from the centre of each plot and at eachdepth Hence a total of 70 samples were collected for bulkdensity determination

24 Laboratory Analyses In the laboratory all soil sam-ples were ground and passed through a 2mm sieve toremove stones and gravel Fine and coarse roots were alsoremoved Subsequently soil samples collected at 0ndash15 cmdepth were analysed for soil pH soil texture cation-exchangecapacity (CEC cmol(+)kg) available phosphorus (ppm)and exchangeable bases (Ca2+ Mg2+ and K+ cmol(+)kg)Samples from both depth ranges (0ndash15 and 15ndash30 cm) wereanalysed for percentages of organic carbon and total nitrogenStandard methods for soil analysis were used in order toobtain estimates for each of the mentioned variables that canbe compared with results reported in the literature [30ndash34]Soil pH was determined electrometrically using 10 g of soilsample diluted in 25mL distilled water that is using a 1 25ratio of soil to water Soil texture was determined by thehydrometer method and the textural classification was doneby the use of the soil texture triangle [35]

The Bray 1 method was used for the determination ofextractable P for acidic soils with pH less than 7 while theOlsen method was used for soils with pH above 7 (alkalinesoils) The ammonium acetate method at pH 7 was used indetermination ofCEC and by the use of an atomic absorptionspectrophotometer in a UNICAM 919 AA Spectrometer allexchangeable cations (Ca2+ Mg2+ and K+) were determinedSubsamples were finely ground into powder form (lt1mm) inan agate mortar and analyzed for total percentages of organicC and N by dry combustion (Dumas method) in a Leco CNS2000 analyzer [33] Samples for bulk density estimation wereoven-dried at 105∘C to constant weight and the weight wasrecorded (accuracy 001 g) The volume was calculated fromlength and cross-sectional area of the soil core and bulk den-sity was determined as dry weight (g) per unit volume (cm3)Most analyses were conducted at the Laboratory of ForestBiology Sokoine University of Agriculture (SUA) but C andN analyses were conducted at the Soil Science Laboratory attheDepartment of Forest andLandscape (nowDepartment ofGeosciences and Natural Resource Management) Universityof Copenhagen Denmark

25 Data Analysis Based on the data collected the followingmeasures were analysed species composition was expressedthrough species richness and diversity measures forest struc-ture was expressed through stem density basal area andvolume for plant communities species groups and diameterclasses Total species richness was computed as the totalnumber of species across all 35 plots Species diversity wascomputed using Shannonrsquos and Simpsonrsquos Diversity Indices

4 ISRN Biodiversity

[36]The volume of stumpswas calculated as cylinder volumewhile total volume for standing trees was calculated usinga regression equation developed for GVLFR by the authors[37 38] ln(V)= minus84554 + 23236 times ln(Dbh) (R2 = 0983RMSE = 0248 Dbh range 14ndash62 cm 119899 = 104) where V isvolume (m3tree) Dbh is diameter at breast height (ge1 cm)RMSE is the residual standard error R2 is the coefficientof determination n is the total sample size and ln is thenatural logarithmThe ImportanceValue Index (IVI) for eachspecies in each plot was calculated as the sum of relativedensity and dominance (basal area) and expressed in percent[39] Percentage base saturation (BS) was determined asthe ratio of total base cation concentration to CEC whilethe C N ratio was determined using the estimated elementalpercentages of carbon and nitrogen [35]

Using IVI for each species plots were classified byagglomerative hierarchical cluster analysis using Soslashrensenrsquosdistance measure and a group linkage method with flexible120573 of minus050 The 35 plots were ordinated by nonmetricmultidimensional scaling (NMS) using the PC ORDsoftwareversion 60 [40] Topographic variables (elevation and slope)and edaphic variables (pH bulk density texture extractableP CEC exchangeable base cations BS C N ratio Cand N) were correlated with the NMS ordination axesIndicatordominant species in each cluster were determinedusing percentage indicator values (IV) where values of 0correspond to no indication and 100 is perfect indication [4142] The first three to five names of these Indicatordominantspecies with the highest percentage indicator values (IV)constancy and significant indicator values (119875 lt 005) wereused to assign names to the clustersplant community types[29 41 42] The Steinhaus (SoslashrensenCzekanowski) coeffi-cient was used to assess the similaritydissimilarity of thespecies compositions of the plant communities [39]

3 Results

31 Species Richness Including all size categories a totalof 88 species (29 plant families) of standing trees andshrubssmall trees were identified in the GVLFR (Table 1)Trees contributed 60 (21 plant families) and shrubs 40(15 plant families) of the species For stumps a total of 42species (20 plant families) of trees and shrubssmall treeswith basal diameter ranging from 2 to 50 cm were identifiedFor stumps trees contributed 76 (13 plant families) of thespecies while shrubs contributed 24 (10 plant families)All species represented by stumps were also represented bystanding treesshrubs In general tree and shrub speciesfrom the family Caesalpiniaceae contributed most (13) tothe total number of species (standing individuals) followedby those from the families Mimosaceae (10) Rubiaceae(10) Fabaceae (9) and Euphorbiaceae (9) (Table 1)Among standing trees the greatest number of species wasfound in the four plant families Caesalpiniaceae (17)Mimosaceae (15) Fabaceae (13) and Combretaceae (9)while shrubssmall trees included most species from thefamilies Rubiaceae (26) Euphorbiaceae (17) and Cap-paraceae (9) For stumps tree and shrub species from

0 5 10 15 20 25 30 35

0

20

40

60

80

Sites

Spec

ies r

ichn

ess

Figure 2 Species accumulation curve for large individuals (Dbhge5 cm) measured within circular plots with a radius of 15m in theGangalamtumba VLFR Vertical lines indicate standard deviations(range 0ndash49)

the family Mimosaceae contributed most (17) to the totalnumber of species followed by species from the familiesCaesalpiniaceae (14) Combretaceae (10) and Fabaceae(7) Among species categorised as trees the families Cae-salpiniaceae (19) and Mimosaceae (19) contributed equalnumbers of species followed by Combretaceae (13) andFabaceae (9) With respect to shrubs each of the familieswas represented by a single species (10 see Table 1)

When considering different size categories and includingboth trees and shrubs (small sizes Dbhlt 5 cm and large sizesDbh ge 5 cm) a total of 78 species (28 families) were foundamong large sizes with Caesalpiniaceae (13) Mimosaceae(12) and Fabaceae (10) being the most species-rich plantfamilies while among small sizes a total of 69 species (27families) were observed with Rubiaceae (13) Caesalpini-aceae (12) andMimosaceae (10) contributing the greatestnumber of species (Table 1) In general the average number ofspecies per plot was found to be 14 species (range 5ndash24 speciesper plot)

The species accumulation curve (Figure 2) shows thatthe 35 sitesplots used in this study were sufficient to covermuch (but not all) of the variation and species diversity ofthe study area At 35 plots the graph has not yet reached itsasymptotic level but is starting to converge implying that anyfurther increase of sample size would be expected to lead toinclusion of additional rare species However although thesample size was small (35 plots) and does not quite capturethe full woody plant biodiversity of the reserve the results arestill useful for characterizing the treeshrub species diversityand relationships between species and site

32 Species Diversity Shannon-Wiener diversity indices forlarge and small individuals were found to be 344 and 326respectively and the Simpson index for large individuals was

ISRN Biodiversity 5

Table1Ch

ecklist

oftre

eand

shrubspeciesrecordedin

Gangalamtumba

VLF

Rshow

ingfre

quency

()density

(meanplusmnSE

)basalarea(meanplusmnSE

)dispersio

nindex(D

I)and

Impo

rtance

ValueInd

ex(IVI)bothforthe

currentp

opulationof

largeind

ividuals(plotsize=

15m

radiusm

inim

umDbh

=5c

m)a

ndforstumps

(plotsize=

20m

radiusm

inim

umbasald

iameter

=2c

m)SH

shrub

ST

smalltreeandT

tree

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

1Mgiha

Dalbergia

arbutifolia

Fabaceae

subfam

ilyPapilio

noideae

ST60

247plusmn69136plusmn037

224

4765

1468plusmn41006plusmn005

170

2Mtono

Commiphora

afric

ana

Burseraceae

T77

110plusmn23159plusmn037

175

1142

1414plusmn06001plusmn001

111

3Mlama

Combretum

molleG

Don

Com

bretaceae

T74

116plusmn27069plusmn015

132

1523

3468plusmn19005plusmn002

307

4Mku

ngugu

Acacia

sp

Mim

osaceae

T23

40plusmn22102plusmn054

111

2873

920plusmn14001plusmn001

65

5Mkw

eeBrachyste

gia

spiciform

isBe

nth

Caesalpiniaceae

T37

58plusmn20118plusmn034

110

1731

2661plusmn24020plusmn009

308

6Mkalala

Albiziapetersiana

(Belle)O

liv

Mim

osaceae

T40

80plusmn30055plusmn020

85

2711

636plusmn29005plusmn004

94

7Mlyasenga

Combretum

zeyheri

Soun

dCom

bretaceae

T43

60plusmn20030plusmn011

741597

2020plusmn08001plusmn001

47

8Mkombivawo

Bauh

iniapetersiana

Caesalpiniaceae

SH34

54plusmn21029plusmn010

64

2000

9Muguvani

Markham

iaobtusifolia

Bign

oniaceae

T60

65plusmn13038plusmn010

64

647

605plusmn03

00

23

10Mdeke

Hym

enodictyon

parvifoliu

mOliv

Rubiaceae

ST31

50plusmn24048plusmn024

58

2749

302plusmn02

00

17

11Mub

wegele

Sclerocarryabirrea

sbspbirr

eaAnacardiaceae

T34

21plusmn6061plusmn023

58

441

605plusmn03001plusmn001

28

12Mmem

enam

ene

Margaritaria

discoidea(Bail)

Euph

orbiaceae

SH51

68plusmn24032plusmn013

57

2073

307plusmn07

00

06

13Mkambala

Acaciamellifera

(Vahl)Be

nth

Mim

osaceae

T29

14plusmn5049plusmn019

50

359

302plusmn02

00

08

14Mugegere

Dich

rosta

chys

cinerea

(L)Wight

ampArn

Mim

osaceae

ST31

53plusmn26017plusmn009

47

3086

2959plusmn19003plusmn002

178

15Mbata

AcaciaseyalD

elvar

seyal

Mim

osaceae

T34

30plusmn10019plusmn006

45

887

311plusmn11001plusmn001

46

16Mgulumo

Lann

easchw

einfurthiiAnacardiaceae

T43

24plusmn7032plusmn009

39

544

907plusmn04002plusmn001

22

17Muyom

boBrachyste

giaboehmii

Caesalpiniaceae

T11

11plusmn7019plusmn015

38

1309

607plusmn05001plusmn001

22

18Mmulim

uli

Cassiaabbreviata

Caesalpiniaceae

T34

31plusmn13017plusmn007

36

1353

916plusmn12001plusmn001

49

19Mdavi

Cordiasin

ensis

Lam

Boraginaceae

ST6

23plusmn23011plusmn010

34

5498

302plusmn02

00

06

6 ISRN Biodiversity

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

20Mdw

endw

eTerm

inaliabrow

nii

Com

bretaceae

T17

14plusmn8019plusmn009

32

1129

305plusmn05

00

12

21Mfilafila

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T31

25plusmn8015plusmn005

30

646

605plusmn03

00

35

22Mkw

ata

Codyladensiflora

Caesalpiniaceae

T9

4plusmn2033plusmn019

28

282

334plusmn34004plusmn004

83

23Mgung

aAc

aciaabyssin

ica(H

ochst)

Mim

osaceae

T17

12plusmn7014plusmn007

24

1140

614plusmn12001plusmn001

39

24Mkole

Grew

iabicolor

Tiliaceae

ST26

21plusmn10008plusmn003

21

1078

605plusmn03

00

15

25Mparapand

eStrychnosp

otatorum

Lf

Loganiaceae

T23

23plusmn11014plusmn009

20

1331

607plusmn05

00

17

26Kitim

bwi

Orm

ocarpum

kirkii

Fabaceae

SH29

18plusmn6007plusmn003

19492

27Mtabagila

Lonchocarpus

capassa

Fabaceae

T26

11plusmn5014plusmn006

17550

302plusmn02

00

04

28Muw

otapon

ziOzoroainsig

nsssp

retic

ulata

Anacardiaceae

T14

10plusmn5010plusmn005

16564

1411plusmn05001plusmn000

31

29Msanzi

Gardeniaresin

iflua

Hiern

Rubiaceae

ST9

13plusmn8008plusmn005

161229

30Mkoga

Vitexpayos

Verbenaceae

ST17

12plusmn5011plusmn004

15605

302plusmn02

00

02

31Mpelem

eleGr

ewiaforbesiiHaw

Ex

Mast

Tiliaceae

ST14

16plusmn9005plusmn002

147

1246

32Mny

wenyw

eeDalbergiaboehmii

Fabaceae

T14

11plusmn7009plusmn007

151221

33Mulagavega

Albiziaam

ara(Roxb)

Boiv

Mim

osaceae

T14

9plusmn5004plusmn003

14712

34Mkola

Afzelia

quan

zensis

Caesalpiniaceae

T11

6plusmn3015plusmn009

14532

35Mugusi

Brachyste

giamanga

Caesalpiniaceae

T20

11plusmn6010plusmn007

13824

618plusmn13002plusmn002

25

36Mwaham

aShrebera

trichoclada

Oleaceae

T17

11plusmn6005plusmn002

12697

309plusmn09001plusmn001

15

37Mpingo

Dalbergia

mela

noxylon

Fabaceae

T11

11plusmn9004plusmn003

121655

314plusmn14001plusmn001

26

38Mub

aya

Strychnosinn

ocua

Loganiaceae

T17

8plusmn4011plusmn008

12375

302plusmn02001plusmn001

06

39Msisina

AlbiziaharveyiF

ournMim

osaceae

T14

5plusmn3008plusmn005

11359

305plusmn05002plusmn002

15

40Mlim

boEu

phorbiacuneata

Valh

Euph

orbiaceae

ST14

12plusmn6004plusmn002

11699

41Mwam

biElaeodendron

buchan

annii

Cela

steraceae

T3

8plusmn8003plusmn003

102000

42Mvembadand

aXe

roderris

stuhlmannii

Fabaceae

T14

4plusmn2011plusmn005

09

191

43Mtelela

Brachyste

giabu

ssei

Harms

Caesalpiniaceae

T6

2plusmn1012plusmn010

09

253

ISRN Biodiversity 7

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

44Mteresi

Prem

naholstiiGurke

Verbenaceae

ST9

8plusmn5003plusmn002

09

899

45Mkongolo

Commiphora

ugogensis

Burseraceae

T6

1plusmn1008plusmn006

08

097

302plusmn02001plusmn001

09

46Muw

isaBo

sciaangustifolia

A

Rich

varangustifo

liaCa

pparaceae

T17

8plusmn4004plusmn002

08

426

47Mnyalup

uko

Canthium

pseudoverticillatum

Hien

Rubiaceae

ST20

8plusmn4004plusmn002

07

414

48Mnyaluh

anga

Brideliascleu

roneura

MuellArg

Euph

orbiaceae

ST14

6plusmn3004plusmn002

07

341

49Mdide

Manilkaramochisia

(Bak)Dub

ard

Sapo

taceae

T9

5plusmn4002plusmn001

07

793

50Muh

emi

Erythrinaabyssin

icaFabaceae

T6

1plusmn1007plusmn006

07

163

51Msambarawe

Vangueria

infausta

BurchSspRo

tund

ataRu

biaceae

ST6

8plusmn5002plusmn002

06

925

52Mhehefu

Allophylu

sferrugineus

Taub

Sapind

aceae

SH9

5plusmn3002plusmn001

05

540

314plusmn14001plusmn001

14

53Mnyengrsquoenyengrsquoe

Excoecariabu

ssei

(Pax)

Euph

orbiaceae

ST11

4plusmn2001plusmn001

05

321

54Muganga

Berchemiadiscolor

Rham

naceae

T6

4plusmn3004plusmn003

04

717

55Mning

aPterocarpu

sangolensis

Fabaceae

T6

2plusmn1005plusmn004

04

253

309plusmn09006plusmn006

25

56Mtanang

we

Zizip

husm

ucronata

Rham

naceae

T3

4plusmn4003plusmn003

04

900

57Muh

ekele

Eucle

adivinorum

Hiern

Ebenaceae

ST3

3plusmn3001plusmn001

04

800

302plusmn02

00

49

58Mub

umila

Cassipourea

mollis

(REfr)Alstom

Rhizop

horaceae

T9

4plusmn3002plusmn001

04

526

302plusmn02

00

04

59Mkw

ambe

Flueggea

virosa

Willd

Euph

orbiaceae

SH6

3plusmn2003plusmn003

03

406

60Kivang

aZa

nhaafric

ana

(Radlk)Ex

ell

Sapind

aceae

T9

2plusmn1001plusmn001

02

212

302plusmn02

00

02

61Mning

amaji

Pterocarpu

stinctorius

Fabaceae

T3

0002plusmn002

02

100

62Mtosi

MaeruatriphyllaA

Rich

Capp

araceae

ST3

2plusmn2001plusmn001

02

600

63Mugosa

Ehretia

amoena

Boraginaceae

ST9

1plusmn1

00

01

094

64Mnyon

gamem

beStegan

otaenia

araliacea

Apiaceae

T6

1plusmn1

001

01

163

65Mvelevele

Vernoniaam

ygdalin

aAs

teraceae

SH3

2plusmn2001plusmn001

01

400

66Mpo

ngolo

Catunaregam

spinosa

(Thun

b)

Rubiaceae

ST3

1plusmn1001plusmn001

01

200

8 ISRN Biodiversity

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

67Mbo

liboli

Acaciadrepanolobium

(Harms)

Mim

osaceae

T3

000

01

100

68Mwim

akigulu

Maeruaangolen

sisCa

pparaceae

SH3

1plusmn1

00

01

300

69Mnyali

Tamarindu

sind

icaCa

esalpiniaceae

T6

1plusmn1001plusmn001

01

097

70Mgombw

ani

Combretum

aculeatum

Com

bretaceae

T6

1plusmn1

00

01

097

302plusmn02

00

04

71Msang

ala

Burkea

afric

anaHoo

kCa

esalpiniaceae

T3

0001plusmn001

01

100

302plusmn02

00

04

72Mkokonza

Opilia

amentacea

Roxb

Opiliaceae

SH3

000

00

100

311plusmn11

00

42

73Mfumbi

Kigelia

afric

ana

Bign

oniaceae

T3

000

00

100

74Mlang

ali

Euphorbia

cand

elabrum

Euph

orbiaceae

T3

000

00

100

75Mpu

lulu

Term

inaliaseric

eaCom

bretaceae

T3

000

00

100

76Mdaha

Diospyros

usam

barensisFWhite

Ebenaceae

T3

000

00

100

305plusmn05001plusmn001

15

77Mtund

wa

XimeniacaffraSond

Olacaceae

ST3

000

00

100

78Mwim

aperu

Tarenn

agla

veolens(S

Moo

re)B

rem

Rubiaceae

ST+

79Mwesa

Boscia

mossambicensisKl

Capp

araceae

ST+

80Musasam

ulo

Psychotria

schu

mmaniana

Rubiaceae

ST+

81Muh

anza

Senn

asin

gueana

Caesalpiniaceae

ST+

82Mtund

wahavi

Ximeniaam

erica

naOlacaceae

ST+

83Mtin

giligiti

Phyllanthu

sengler

iPax

Euph

orbiaceae

T+

84Msada

Vangueria

madagascarie

nsis

Gmel

Rubiaceae

ST+

85Mku

nung

uZa

nthoxylum

chalybeum

Rutaceae

T+

86Lu

kali

Croton

scheffleriP

axEu

phorbiaceae

SH+

87Kilim

andembw

eGardeniaternifolia

KSchu

mamp

Thon

nRu

biaceae

ST+

88MpelaM

buyu

Adan

soniadigitata

Bombacaceae

T++

Total(allspecies)

13511521plusmn5941355plusmn552

200

294

60plusmn30072plusmn049

200

+indicatesspecies

identifi

edam

ongsm

allerind

ividualswith

in5m

radius

plots(Dbhlt5c

m)and++

indicatesthata

largeind

ividualw

asidentifi

edwith

ina1

5-radius

plot

butw

asno

tincludedin

thea

nalyseso

fste

mdensitybasalareaand

volumea

sitw

asconsidered

anou

tlier

duetoits

tremendo

ussiz

e(Dbh

=340c

m)

ISRN Biodiversity 9

005 and that of small individuals was 006 The followingspecies were observed to have the greatest contributionsto the Shannon-Wiener diversity index of large individualsDalbergia arbutifolia (contributing 030) Combretum molle(020) Commiphora africana (019) Albizia petersiana (016)and Margaritaria discoidea (014) while for smaller ones thegreatest contributions were found for Brachystegia spiciformis(026) Dalbergia arbutifolia (024) Grewia forbesii (023)Margaritaria discoidea (020) and Dichrostachys cinerea(016) In terms of frequency of occurrence for standingindividuals (large sizes) Commiphora africana was the mostfrequent species (77 of plots) followed by Combretummolle (74) and Dalbergia arbutifolia (60) while for smallsizes Margaritaria discoidea (66) Markhamia obtusifolia(63) and Dalbergia arbutifolia (57) were the most fre-quent species The Importance Value Index (IVI) for largeindividuals (Dbh ge 5 cm) shows that Dalbergia arbutifolia(224) Commiphora africana (175) and Combretum molle(132) were the most important species among standingindividuals while Brachystegia spiciformis (308)Combretummolle (307) and Dichrostachys cinerea (178) appeared to bethe most important among harvested individuals (stumps)These species were also found to have higher frequencies thanany other harvested species observed in the GVLFR (Table 1)

33 Stem Density The total mean stem density for large indi-viduals with Dbh ge5 cm was 1521 plusmn 594 stemsha (Table 1)and that of small individuals with Dbh lt5 cm (includingindividuals with Dbh lt1 cm) was 14318 plusmn 6956 stemshaAmong large individuals the most abundant species wereDalbergia arbutifolia (162 of 1521 stemsha) Combretummolle (8) Commiphora africana (72) and Albizia peter-siana (53) Among small individuals the most abundantspecies were Brachystegia spiciformis (13 of 14318 stemsha)followed by Dalbergia arbutifolia (11) and Grewia forbesii(10) For stumps the overall mean density was 60 plusmn38 stemsha with Combretum molle (12) Dalbergia arbuti-folia (12) Brachystegia spiciformis (10) and Dichrostachyscinerea (10) contributing the most (Table 1) Generally thedistribution of standing trees to size classes showed the usualreverse J shape which was also approximately observed forstumps (Figure 3) However for stumps the density of stemsin the 1ndash10 cm diameter class was slightly lower than whatwould be expected if tree felling had been a random event

34 Basal Area For the GVLFR as a whole the meanbasal areas for large (ge5 cm Dbh) and small individuals(lt5 cm Dbh) were 1355 plusmn 552m2ha (Table 1 Figure 4)and 305 plusmn 002m2ha respectively The species contributingmost to the basal area of large individuals were Commiphoraafricana (12) Dalbergia arbutifolia (10) and Brachystegiaspiciformis (9) while those contributing most to the basalarea of smaller individuals were Dalbergia arbutifolia (16)Grewia forbesii (15) and Dichrostachys cinerea (13) Themean basal area for stumps was 072m2ha with Brachystegiaspiciformis contributing the greatest individual proportion(28) 41 species made up the rest (Figure 4)

60542

3335

530

113

28 24

346166

34

11

02

01

10

100

1000

10000

100000

Diameter classes (cm)

Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Stem

s (ha

minus1)

Figure 3 Density of standing trees ge1 cmDbh and stumps ge1 cm bydiameter class in Gangalamtumba VLFR (119899 = 35) NB logarithmicscale on vertical axis

744477

241

103041 055

014025 018

010004

001

01

1

10

Diameter classes (cm)Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Mea

n ba

sal a

rea (

m2

haminus1)

Figure 4 Distribution of basal area per hectare for standingtrees ge1 cm Dbh and stumps ge1 cm by diameter classes in theGangalamtumba VLFR (119899 = 35) NB logarithmic scale on verticalaxis

35 Volume The mean volumes for large (ge5 cm Dbh) andsmall individuals (lt5 cm Dbh) were 9217 plusmn 390m3ha and1257 plusmn 635m3ha respectively (not shown in tables) Thespecies contributing most to the volume of large individualswere Commiphora africana (12) Brachystegia spiciformis(10) Acacia sp (9) and Dalbergia arbutifolia (9) Forsmaller individuals the species that contributed most tovolume were Dalbergia arbutifolia (16) Grewia forbesii(14) and Dichrostachys cinerea (13) The mean remainingvolume of stumps was found to be 015 plusmn 01m3ha withBrachystegia spiciformis contributing the greatest individualpercentage (28) 41 species made up the rest

10 ISRN Biodiversity

36 Spatial Distribution Dispersion indices (DI) are pre-sented for individual species in Table 1 The dispersion indexvalues range from 094 indicating almost complete spatialrandomness or slight underdispersion to 5498 indicatingconsiderable overdispersion that is a patchy or clustereddistributionOut of 77 species excluding the single very largeAdansonia digitata that was considered an outlier 64 species(83) 9 species (12) and 4 species (5) were found tohave DI gt 1 DI = 1 and DI lt 1 respectively so the majorityof species are characterised by a patchy distribution acrossthe forest The species with the lowest estimated DI wasEhretia amoena (094) while the highest DI was estimated forCordia sinensis (5498)Themost abundant species includingDalbergia arbutifolia (DI = 4765) Combretum molle (DI =1523) and Commiphora africana (DI = 1142) are stronglyoverdispersed

37 Plant Communities and Species Association Four plantcommunities were identified through cluster analysis basedon the statistical significance (5) of the observed maximumindicator values (Table 2) Only two of these plant commu-nities were dominated by species from the family Caesalpini-aceae (Communities 1 and 24) The other two showed greatvariationoverlap between species of different plant families(Communities 3 and 5) The estimated Steinhaus similarityindices between pairs of plant communities varied from 32for Communities 1 and 3 and Communities 5 and 24 to 37for Communities 3 and 5 (not shown in tables)

The ordination diagram (Figure 5) shows that one topo-graphic and six edaphic variables appear to be associatedwiththe four plant communities and the species distribution inthe study area The strongest correlation with communitycomposition was observed for elevation followed by soilpH at 0ndash15 cm depth base cation Ca2+ at 0ndash15 cm depthpercent base saturation (BS) at 0ndash15 cm depth percent clayat 0ndash15 cm depth C N ratio at 15ndash30 cm depth and percentsand at 0ndash15 cm depth The base cations magnesium (Mg2+)and potassium (K+) were not directly correlated with thecommunity composition but since they are included in thebase saturation percentage they are indirectly related Plantcommunities were ordered along the second ordination axiswhich was positively correlated with pH15 (119903 = 071) Ca15(119903 = 069) BS (119903 = 065) andClay15 (119903 = 052) and negativelycorrelated with Sand15 (119903 = minus046) Axis 1 of the ordinationwas positively correlated with Elev (119903 = 085) and CNrat30(119903 = 051) As shown in Table 3 and indicated graphically inFigure 5 correlations between many of the edaphic variablesare strong particularly between pH15 Sand15 Clay15 Ca15and BS whereas correlation between topographic and mostedaphic variables is small and nonsignificant However thereis a significant negative correlation (119903 = minus042) between Elevand Sand15 indicating that sandy soils are mostly found atlower elevations

4 Discussion

41 Species Composition The results reported in this studyshow that the composition of the vegetation types found in

Elev

pH15Ca15

Sand15

Clay15

CNrat30

BS

Axis 1

Axis 2

Community 1Community 3

Community 5Community 24

Figure 5 Compositional gradients and plant communities in NMSordination of 35 vegetation plots for trees ge5 cm in GangalamtumbaVLFR Four plant communities are recognized (cf Table 2) Com-munity 1 = Brachystegia spiciformis Diplorynchus condylocarponand Lannea schweinfurthii woodland Community 3 = Dalbergiaarbutifolia Commiphora africana and Albizia petersianawoodlandCommunity 5 = Acacia sp Acacia abyssinica and Albizia amarawoodland and Community 24 = Bauhinia petersiana and Shreberatrichoclada woodland Elev elevation (m) CNrat30 C N ratio at15ndash30 cm depth Sand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm Ca15 = Ca2+ (cmol(+)kg) at 0ndash15 cm pH15 = soil pH at 0ndash15 cm BS base saturation at 0ndash15 cm

the GVLFR especially the dominance of species from thefamily Caesalpiniaceae agreed well with previous descrip-tions and classifications of plant communities commonlyfound in miombo woodlands [1] However the observeddominance based on IVI of the genera Dalbergia Com-miphora and Combretum contrasts with patterns usuallyconsidered common for miombo woodlands The frequencyof species in these genera was also high compared to otherspecies observed in the GVLFR (Table 1) Similar deviationsexist between the results obtained by Banda et al [26]in the Katavi-Rukwa ecosystem where they observed thatTerminalia and Combretum were the dominant genera andthe findings of Giliba et al [27] and Njana [43] whoboth noted the dominance of the two common miombogenera Brachystegia and Julbernardia However Combretumalso occurred in their study areas The results suggest thaton a larger spatial scale the species diversity of miombowoodlands is very high and that the three common generaBrachystegia Julbernadia and Isoberlinia are not alwaysdominant at the local scale

The species richness observed in the GVLFR compareswell with miombo community studies in other areas of drymiombo in Tanzania and elsewhere which receive an average

ISRN Biodiversity 11

Table2Plantcom

mun

itiesandspeciesa

ssociatio

nsin

thed

ryMiombo

woo

dlands

ofGangalamtumba

VLF

RCom

mun

itynu

mbers135and24

representthe

different

plantassociatio

ns

119899speciesnu

mbero

fspecies

(77in

total)with

Dbhge5c

mIV+

speciesind

icator

valuemeanplusmnstd

errorand

BAisbasalarea

Com

mun

ityAs

sociated

species

Family

Habit

IV+

()

Con

stancy

()119875value

Stem

sha

BA m2 ha

MeanDbh

Brachyste

giaspiciform

ismdashDiplorhynchus

cond

ylocarponmdashLa

nnea

schw

einfurthiiw

oodland

1(n s

pecies

=47

nplots=9)

Sitevariables(meanplusmnSE

)Elev

=1200plusmn20pH15

=644plusmn013C

a15=604plusmn128

Sand

15=721plusmn431C

lay15=137plusmn188Silt15

=142plusmn335C

Nrat30=135plusmn05andBS

=526plusmn65

Brachyste

gia

spiciform

isCa

esalpiniaceae

T820

100

000

02164plusmn59356plusmn077138plusmn07

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T759

89000

0866plusmn18044plusmn01382plusmn05

Lann

easchw

einfurthii

Anacardiaceae

T719

100

000

0449plusmn14072plusmn022126plusmn09

Bosciaangustifolia

Capp

araceae

T536

5600056

27plusmn12014plusmn00776plusmn06

Euphorbiacuneata

Euph

orbiaceae

ST428

4400200

42plusmn19012plusmn00665plusmn06

Other

species

mdashmdash

mdashmdash

mdash1075plusmn5741007plusmn647102plusmn03

Subtotal

1423plusmn174

1505plusmn178

109plusmn03

DalbergiaarbutifoliamdashCo

mmiphora

afric

anamdash

Albizia

petersiana

woo

dland

3(n

species=55n

plots=

16)Site

variables(meanplusmnSE

)Elev

=986plusmn19pH15

=648plusmn009C

a15=856plusmn109

Sand

15=767plusmn156C

lay15=135plusmn155Silt15

=97plusmn096C

Nrat30=106plusmn03andBS

=744plusmn44

Dalbergiaarbutifolia

Fabaceae

subfam

ilyPapilio

noideae

ST793

100

000

02500plusmn123263plusmn06477plusmn02

Commiphora

afric

ana

Burseraceae

T542

9400026

187plusmn40272plusmn064119plusmn06

Albiziapetersiana

Mim

osacea

T536

7500200

157plusmn57103plusmn04084plusmn02

Sclerocarryabirrea

Anacardiaceae

T504

6300186

40plusmn11128plusmn045168plusmn17

Other

species

mdashmdash

mdashmdash

mdash852plusmn449669plusmn37788plusmn03

Subtotal

1735plusmn166

1435plusmn071

92plusmn02

Acaciaspmdash

Acaciaabyssin

icamdash

Albiziaam

arawoo

dland

5(n

species=33n

plots=5)

Sitevariables(m

eanplusmnSE

)Elev

=986plusmn52pH15

=734plusmn023C

a15=139plusmn33

Sand

15=745plusmn678C

lay15=148plusmn47Silt15

=107plusmn26C

Nrat30=106plusmn07andBS

=963plusmn89

Acaciasp

Mim

osaceae

T981

100

000

02269plusmn111662plusmn286172plusmn14

Acaciaabyssin

icaMim

osaceae

T594

8000030

31plusmn9060plusmn03299plusmn08

Albiziaam

ara

Mim

osaceae

T552

60000

6654plusmn30023plusmn01671plusmn08

Grew

iabicolor

Tiliaceae

ST533

6000106

113plusmn52040plusmn01770plusmn04

Acaciaseyal

Mim

osaceae

T433

6000526

62plusmn34034plusmn01790plusmn05

Other

species

mdashmdash

mdashmdash

mdash665plusmn533552plusmn49872plusmn04

Subtotal

1194plusmn169

1367plusmn347

101plusmn05

Bauh

iniapetersiana

mdashShrebera

trichoclada

woo

dland

24(n

species=35n

plots=5)

Sitevariables(meanplusmnSE

)Elev

=1175plusmn25pH15

=73plusmn04C

a15=254plusmn69

Sand

15=522plusmn68C

lay15=331plusmn28

Silt15=147plusmn44C

Nrat30=961plusmn13andBS

=1041plusmn204

Bauh

iniapetersiana

Caesalpiniaceae

SH551

8000118192plusmn121111plusmn05075plusmn03

Shrebera

trichoclada

Oleaceae

T505

6000110

57plusmn32022plusmn01380plusmn05

Manilkaramochisia

Sapo

taceae

T376

4000332

34plusmn27014plusmn00969plusmn10

Dalbergia

mela

noxylon

Fabaceae

T370

4000380

68plusmn58026plusmn02266plusmn03

Ehretia

amoena

Boraginaceae

ST347

4000344

6plusmn4

002plusmn00170plusmn04

Other

species

mdashmdash

mdashmdash

mdash982plusmn759643plusmn47999plusmn05

Subtotal

1338plusmn137

817plusmn087

91plusmn04

Total

1521plusmn5941355plusmn55298plusmn01

Elevelevatio

n(m

)CN

rat30CN

ratio

at15ndash30c

mdepthSand

15sand(

)at0

ndash15c

mC

lay15clay

()at0

ndash15c

mSilt15silt

()at0

ndash15c

mC

a15Ca2+(cmol(+)kg)at0

ndash15c

mpH15soilp

Hat0ndash

15cm

BS

base

saturatio

nat0ndash

15cm

12 ISRN Biodiversity

Table 3 Pearson-correlation matrix for two topographic and eight edaphic variablesdagger associated with the classified plant communities in theGangalamtumba VLFR (119899 = 35) Applied significance levels lowast5 lowastlowast1 and lowastlowastlowast01 +not significant

Elev Slope pH15 Ca15 K15 N15 Sand15 Clay15 CNrat30Slope 019+

pH15 minus013+ minus033lowast

Ca15 002+ minus020+ 083lowastlowastlowast

K15 minus029+ 000+ 010+ 012+

N15 006+ 036lowast 010+ 041lowastlowast 033lowast

Sand15 minus042lowastlowast 003+ minus053lowastlowastlowast minus074lowastlowastlowast 006+ minus046lowastlowast

Clay15 031+ minus012+ 051lowastlowast 076lowastlowastlowast minus001+ 047lowastlowast minus086lowastlowastlowast

CNrat30 036lowast 010+ minus039lowast minus051lowastlowast minus015+ minus019+ 040lowast minus048lowastlowast

BS minus024+ minus017+ 084lowastlowastlowast 091lowastlowastlowast 015+ 037lowast minus058lowastlowastlowast 060lowastlowastlowast minus051lowastlowastdaggerElev elevation (m) pH15 soil pH at 0ndash15 cm Ca15 Ca2+ (cmol(+)kg) at 0ndash15 cm K15 K+ (cmol(+)kg) at 0ndash15 cm N15 N concentration at 0ndash15 cmSand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm CNrat30 C N ratio at 15ndash30 cm depth BS base saturation at 0ndash15 cm 119905-value was calculated as119905 = 119903radic(119899 minus 2)(1 minus 119903

2) where 119903 is the Pearson-correlation coefficient and 119899 is the total sample size

Table 4 Species richness observed in other studies from drymiombo woodlands

Plot size(ha)

Totalnumberof plots

Total samplearea(ha)

Total numberof species References

0071 70 495 82 [43]0071 80 565 110 [27]0071 133 940 229 [26]0071 247 1746 102 [44]004 40 160 81 [45]025 14 350 69 [25]01 2 020 40 [28]01 152 1520 92 genera [22]0071 35 247 88 This study

annual rainfall of 565ndash1500mm (Table 4) Using plot sizes of004ndash025 ha and sample sizes of 2ndash247 plots a total numberof species ranging from40 (Dbhge 10 cm) to 229 (Dbhge 2 cm)have been reported fromMiombowoodlands [22 25ndash28 43ndash45]

The high number of species reported by Banda et al [26]Chidumayo [22] Isango [45] and Chamshama et al [44] islikely to be a consequence of the spatial scale and coverage ofthese studies as they all cover large areas include more thanone site and operate with large sample sizes For exampleChidumayo [22] included species from both wet and dryMiombo areas in Zambia The study by Sauer and Abdallah[15] who reported a total of 131 species occurring in thetobacco growing zone of Iringa rural district included twoforest reserves and three family-managed forests Thereforeconsidering the climatic conditions in the GVLFR (617mmof rainfall per year) and the sample size (35 plots) thespecies richness reported in this study can be ranked atleast as high or higher than those found in the studiesmentioned The selective sampling approach focusing onvarious microhabitat types adopted by Banda et al [26] mayhave contributed to the large number of species observed

in their study area Similarly the higher number of speciesfound by Giliba et al [27] was probably due to the presenceof riverine forest offering site conditions favourable formanyspecies

The values of the Shannon-Wiener (1198671015840 = 344) andSimpson indices (119863 = 005) reported for large individ-uals in this study are within the range observed for mostcommunities of particular life forms [36] For example 1198671015840usually does not exceed 5 although this maximum valuevaries depending on the type of the biological communitysampled and the sampling approach applied (eg minimumdiameter and size of sample units) A threshold value of 2 for1198671015840 has been mentioned as a minimum value above which

an ecosystem can be regarded as medium to highly diverse[27] Chamshama et al [44] reported three 1198671015840 values of31 32 and 33 from Kitulangalo Miombo forest in EasternTanzania while Njana [43] reported a 1198671015840 value of 340from dry Miombo forest in Western Tanzania The studiesby Sauer and Abdallah [15] and Giliba et al [27] reportedparticularly high values of 346 and 427 respectively Thiscould be attributed to the very large sample sizes used inboth studies and the presence of riverine forest where thechance of encountering many rare species is likely to be highThe forests examined in the mentioned studies receive anaverage annual rainfall of 700ndash1000mm compared to whichthe rainfall in the GVLFR is low (617mm on average per yearcf above)The relatively high diversity found inGVLFRmusttherefore be attributed to other factors than climate The soilanalyses indicate that the soil fertility level in the GVLFRis relatively high with considerable proportions of all 2 1lattice clay minerals (114) (ie illite montmorillonite andvermiculite) plus a good amount of organic matter whichmay suggest that the soil has large reserves of important plantnutrients for example K Mg and Fe The base saturationpercentage (BS) which is normally used to indicate the soilfertility status (Landon 1991) was also high 76 on averageand with 86 of the samples (30 samples) with BS valuesgt50 (fertile soil) and only 14 of the samples (5 samples)with BS below 50 (less fertile soil) As another indicationof high soil fertility status the mean C N ratio was 12 plusmn 043

ISRN Biodiversity 13

(range 7ndash19) for top soil (0ndash15 cm) and 11 plusmn 036 (range 5ndash16) for subsoil (15ndash30 cm) In general the values for both soilstrata fall within the expected range of 8ndash17 Soil pH values(mean 67 plusmn 01 range 567ndash852)were alsowithin the optimalrangewhere all the nutrients that aremost important for plantgrowth (Ca Mg K and P) are available and accessible toplants [46] In this study 97 of the soil samples had pHbelow 8 (one sample had a pH of 852) Fisher and Binkley[47] noted that high pH is almost never a problem in forestsas most trees do well across the full range of common pHvaluesTherefore considering the low average annual rainfallcompared to other forests the relatively high fertility of theGVLFR may be the main factor creating an environmentfavourable to many species thus leading to a quite highspecies diversity observed in this forest

Based on the Importance Value Index Brachystegia spi-ciformis and Combretum molle appeared to be the mostimportant species among harvested trees (stumps) in thestudy area This result agreed very well with the large valuesof basal area and volume and the information obtained fromlocal scouts and members of the village environmental com-mittee who said that the most frequently harvested speciesfor charcoal making include all Brachystegia species found inthe forest (ie Brachystegia spiciformis Brachystegia mangaBrachystegia boehmii and Brachystegia bussei) Among theCombretum species the most important one (based on IVI)Combretum molle is mostly used for house construction andfirewood rather than for charcoal making Apart from theBrachystegia species the only other species mentioned asimportant for charcoal making was Acacia mellifera Otherspecies are only used in case they happen to fall when fellingthe preferred species during the preparation of charcoal kilnsWith respect to stumps Brachystegia spiciformis Brachystegiamanga and Combretum molle are among the ten mostabundant species in terms of density basal area and volumeper hectare Stumps of the other species mentioned are notcommonly found a factwhichmay be due to the small samplesize being unable to capture sites where these species areharvested but may also be related to their limited distributionin the forest as indicated by the estimated dispersion indices(see Table 1)

42 Forest Structure Species densities reported from otherMiombo woodland areas in Tanzania are typically 348ndash1495stemsha for trees with Dbh gt4 cm [24 43 45] Comparedwith this the GVLFR is highly stocked as the estimateddensity is 2296 stemsha for trees with Dbh gt4 cmThemeanstem density of 1521 plusmn 594ha for trees with Dbh ge5 cmis also more than twice as large as values found in otherstudies [25ndash27 44 45 48] A similar pattern is seen whencomparing the density of regeneration between the studiesThe diameter distribution is characterised by a very cleartrend of decreasing stem density with increasing diameterThe shape of the distribution is thus an inverted ldquoJrdquo (Figure 3)which is a common feature of natural forests with activeregeneration and recruitment [49] However not many largetrees were captured by the sample whereas a considerablenumber of relatively large stumps were observed suggestingthat anthropogenic activities such as charcoal making may

have affected the structure and ecological balance of the forest(see Figure 3) Since the woodlands are often hit by fire whichtends to kill the seedlings (especially the late fires) and thusonly few seedlings can be expected to reach larger diameterclasses lack of mature trees and the resulting lack of seedsmay eventually threaten the biodiversity of the forest

The mean basal area of 1355 plusmn 552m2ha observedin this study is slightly above the range of values typicallyreported from the miombo region 75ndash126m2ha [26 28 4344 50] However the basal areas reported by Isango [45] werea bit higher (1504ndash1563m2ha) than observed in this study

Themean total volume inGVLFRwas estimated at 9217plusmn390m3ha for trees with Dbh ge5 cm Other studies in dryMiombo woodlands have reported mean volumes of 167ndash7603m3ha [24 44 45 50] The current standing volume ofGVLFR is thus slightly higher than values typically reportedfor forests in the Miombo ecoregion A plausible reason forthis may be that compared to other forests the GVLFR isstill well stocked despite ongoing human activities such ascharcoalmakingThebasal area observed for stumpswas only072m2ha so there is no indication of intensive extractionover many years This corresponds well with the findings ofTreue et al [20] who conclude that the estimated 04m3haannual extraction of woody biomass from GVLFR is consid-erably below its estimated annual increment of 15m3ha andthat the local forest managers seem capable of regulating theharvesting activities which in addition to village membersrsquocollection for subsistence uses also included commercialcharcoal production by external companies that pay a fee perbag of charcoal extracted to the village government

43 Plant Communities and Species Associations Except forBrachystegia spiciformis the majority of the Brachystegia andJulbernardia species that are common to miombo wood-lands elsewhere are not among the species most commonlyobserved in this study A similar pattern was observed byBanda et al [26] in the Katavi-Rukwa ecosystem wherethe genera that are most common in miombo woodlandsBrachystegia Julbernardia and Isoberlinia were not commonin their study sites Furthermore the four plant communi-ties distinguished in this study are comparable with thosereported by other studies in Tanzania including the work byMunishi et al [29] in theMiombowoodlands of Rukwa basinChunya district Tanzania and the study by Banda et al [26]in the Katavi-Rukwa ecosystem

Elevation was noted by Munishi et al [29] to be themost important factor shaping the species communities intheir study area This study found a similar pattern with thehighest coefficient of correlation observed for elevation sug-gesting that topographical variation is among the strongestdeterminants of community composition in dry Miombowoodlands hence influencing the spatial distribution ofspecies strongly However in our study area edaphic factorsalso influenced the species distribution directly Two plantcommunities occurredmainly on clayey soils with high pH atintermediate elevations one on sandy soils with lowpHat lowelevations and one on sandy-clayey soils at higher elevationsand with neutral soil pH (Figure 5) Specifically it appeared

14 ISRN Biodiversity

that the Acacia woodland category (Community 5) grows atlow elevations around temporary streams (or at least wherethe ground water table is relatively high) and the Bauhiniawoodland category (Community 24) appearsmostly in placeswith a relatively high percentage of clay (and therefore highvalues of pH Ca and BS) By contrast it appeared that theDalbergia woodland category (Community 3) is located atmore sandy sites (with low values of pH Ca and BS) andthe Brachystegia woodland category (Community 1) seemedto be located mostly at higher elevations where the CN-ratio is quite high Correlations between elevation and thebasic soil variables pH Ca and percentages of sand andclay were low (cf Figure 5) Thus the results indicate thatthe plant communities of the dry miombo woodlands inGVLFR are not only shaped by the topographic variation(elevation) and the groundwater level but also by basic soilcharacteristics The results thus confirm findings from otherstudies detecting effects of elevation and soil characteristicson species composition [51 52]

5 Conclusion

Considering that the sample size used in this study wassmaller than samples used in other studies in dry miombowoodlands the results show that the species diversity inGVLFR is relatively high compared to other forest reservesThe vegetation of GVLFR is characterised by high densitybasal area and volume and despite the scarcity of largediameter trees this indicates that the forest is in a goodcondition The effect of anthropogenic activities is neverthe-less evident and stresses the need for proper managementespecially for economically important species preferred forcharcoalmaking (egBrachystegia spiciformis) if the currentspecies diversity is to be maintained or enhanced A repeatedfuture study would be needed to assess whether the currentcommunity-based management regime yields this intendedoutcome but the available information and analyses allow forsome optimism in this respect

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors wish to thank people from Mfyome villagefor their invaluable assistance during field work Mzee IddiKaheya Damian Chotamasege AugustinoMkwama Libera-tus Simime and Mawazo Nyangwa Furthermore thanks aredue to Venancia Mlelwa from Sokoine University and MadsMadsen Krag from University of Copenhagen for doing thelaboratory work The authors also wish to thank GoodluckMoshi their driverMarcoNjana andNassoroHMagogo theTAFORI botanist for assisting with species identification andKlaus Dons for preparing a study site map Financial supportwas provided by Danida through the ENRECA Project

ldquoParticipatory forest management for rural livelihoods forestconservation and good governance in Tanzaniardquo (no 725)

References

[1] P G H Frost ldquoThe Ecology of Miombo Woodlandsrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 11ndash57 1996

[2] N Burgess J Hales E Underwood et al Terrestrial Ecoregionsof Africa and Madagascar A Conservation Assessment IslandPress World Wildlife Fund 2004

[3] J Clarke W Cavendish and C Coote ldquoRural householdsand miombo woodlands use value and managementrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 101ndash135 1996

[4] B M Campbell A Angelsen A Cunningham Y KaterereA Sitoe and S Wunder ldquoMiombo woodlandsmdashopportunitiesand barriers to sustainable forest managementrdquo httpsener-gypediainfoimages66dMiombo2007pdf

[5] S Syampungani P W Chirwa F K Akinnifesi G Sileshi andO C Ajayi ldquoTheMiombo woodlands at the cross roads poten-tial threats sustainable livelihoods policy gaps and challengesrdquoNatural Resources Forum vol 33 no 2 pp 150ndash159 2009

[6] J I O Abbot and K Homewood ldquoA history of change causesof miombo woodland decline in a protected area in MalawirdquoJournal of Applied Ecology vol 36 no 3 pp 422ndash433 1999

[7] E J Luoga E T F Witkowski and K Balkwill ldquoLand coverand use changes in relation to the institutional frameworkand tenure of land and resources in eastern Tanzania Miombowoodlandsrdquo Environment Development and Sustainability vol7 no 1 pp 71ndash93 2005

[8] FAO The State of Food and Agriculture 2010-2011 Forest andAgriculture Organization Rome Italy 2010

[9] A H Gentry ldquoTropical forest biodiversity distributional pat-terns and their conservational significancerdquo Oikos vol 63 no1 pp 19ndash28 1992

[10] O E Sala F S Chapin III J J Armesto et al ldquoGlobalbiodiversity scenarios for the year 2100rdquo Science vol 287 no5459 pp 1770ndash1774 2000

[11] H J Geist and E F Lambin ldquoProximate causes and underlyingdriving forces of tropical deforestationrdquo BioScience vol 52 no2 pp 143ndash150 2002

[12] R S DeFries ldquoTropical forests deforestation and ecosystemsservices Contributions of remote sensingrdquo in GeoinformaticsFor Tropical Ecosystems P S Roy Ed pp 1ndash32 2003

[13] B M Campbell P Frost and N Bryon ldquoMiombo woodlandsand their use overview and key issuesrdquo in The Miombo inTransition Woodlands and Welfare in Africa B Campbell Edpp 1ndash10 2006

[14] H J Geist ldquoGlobal assessment of deforestation related totobacco farmingrdquo Tobacco Control vol 8 no 1 pp 18ndash28 1999

[15] J Sauer and J M Abdallah ldquoForest diversity tobacco produc-tion and resource management in Tanzaniardquo Forest Policy andEconomics vol 9 no 5 pp 421ndash439 2007

[16] E N Chidumayo and K J Mbata ldquoShifting cultivation ediblecaterpillars and livelihoods in the Kopa area of northernZambiardquo Forests Trees and Livelihoods vol 12 no 3 pp 175ndash1932002

[17] E N Chidumayo and L Kwibisa ldquoEffects of deforestation ongrass biomass and soil nutrient status in miombo woodlandZambiardquo Agriculture Ecosystems and Environment vol 96 no1ndash3 pp 97ndash105 2003

ISRN Biodiversity 15

[18] J F Lund and T Treue ldquoAre we getting there Evidence ofdecentralized forest management from the Tanzanian miombowoodlandsrdquoWorld Development vol 36 no 12 pp 2780ndash28002008

[19] T Blomley and S Iddi Participatory Forest Management inTanzania 1993ndash2009mdashLessons Learned and Experiences toDate Ministry of Natural Resources and Tourism Forestry andBeekeeping Division Dar es Salaam Tanzania 2009

[20] T Treue Y M Ngaga H Meilby et al ldquoDoes participatoryforest management promote sustainable forest utilisation inTanzaniardquo International Forestry Review vol 16 no 1 pp 1ndash162014

[21] Ministry ofNatural Resources andTourismParticipatory ForestManagement in Tanzania Facts and Figures Forestry andBeekeeping Division Dar es Salaam Tanzania 2008

[22] E N Chidumayo ldquoSpecies structure in Zambian miombowoodlandrdquo Journal of Tropical Ecology vol 3 no 2 pp 109ndash1181987

[23] J D Lowore ldquoCoppice regeneration in some miombo wood-lands of Malawirdquo FRIM Report 99001 Forestry ResearchInstitute of Malawi 1999

[24] E J Luoga E T F Witkowski and K Balkwill ldquoHarvestedand standing wood stocks in protected and communal miombowoodlands of eastern Tanzaniardquo Forest Ecology and Manage-ment vol 164 no 1ndash3 pp 15ndash30 2002

[25] M Williams C M Ryan R M Rees E Sambane J Fernandoand J Grace ldquoCarbon sequestration and biodiversity of re-growing miombo woodlands in Mozambiquerdquo Forest Ecologyand Management vol 254 no 2 pp 145ndash155 2008

[26] T Banda NMwangulango BMeyer et al ldquoThewoodland veg-etation of the Katavi-Rukwa ecosystem in western TanzaniardquoForest Ecology andManagement vol 255 no 8-9 pp 3382ndash33952008

[27] R A Giliba E K Boon C J Kayombo E B Musamba AM Kashindye and P F Shayo ldquoSpecies composition richnessand diversity in Miombo Woodland of Bereku Forest ReserveTanzaniardquo Journal of Biodiversity vol 2 no 1 pp 1ndash7 2011

[28] D D Shirima P K T Munishi S L Lewis et al ldquoCarbonstorage structure and composition of miombo woodlands inTanzaniarsquos Eastern Arc Mountainsrdquo African Journal of Ecologyvol 49 no 3 pp 332ndash342 2011

[29] P K T Munishi R A P C Temu and G Soka ldquoPlant com-munities and tree species associations in a Miombo ecosystemin the Lake Rukwa basin Southern Tanzania implications forconservationrdquo Journal of Ecology and Natural Environment vol3 no 2 pp 63ndash71 2011

[30] J Dewis and F Freitas ldquoPhysical analysis of soilsrdquo in Physicaland Chemical Methods of Soil andWater Analysis FAO Bulletinno 10 pp 51ndash57 2nd edition 1970

[31] S R Olsen and L E Sommers ldquoPhosphorusrdquo inMethods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 403ndash430 American Societyof Agronomy Madson Wis USA 1982

[32] J D Rhoades ldquoCation exchange capacityrdquo in Methods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 149ndash157 American Society ofAgronomy Madson Wis USA 1982

[33] IMatejovic ldquoDetermination of carbon hydrogen and nitrogenin soils by automated elemental analysis (dry combustionmethod)rdquo Communications in Soil Science and Plant Analysisvol 24 no 17-18 pp 2213ndash2222 1993

[34] J P Moslashberg Soil Analysis Manual Revised Edition Laboratoryof Soil Sciences Department of Soil Science SokoineUniversityof Agriculture Morogoro Tanzania 2001

[35] N C BradyThe Nature and Properties of Soils Macmillan 8thedition 1974

[36] C J Krebs Ecological Methodology Hamper Collins PublishersNew York NY USA 2nd edition 1999

[37] B Husch T W Beers and J A Kershaw Forest MensurationJohn Wiley amp Sons Hoboken NJ USA 4th edition 2003

[38] E E Mwakalukwa H Meilby and T Treue ldquoVolume andaboveground biomass models for dry Miombo Woodland inTanzaniardquo In press

[39] M Kent Vegetation Description and Analysis A PracticalApproach Wiley-Blackwell John Wiley amp Sons Hoboken NJUSA 2nd edition 2012

[40] B McCune and M J Mefford PC-ORD Multivariate Analysisof Ecological Data Version 6 MjM Software Gleneden BeachOre USA 2011

[41] MDufrene andP Legendre ldquoSpecies assemblages and indicatorspecies the need for a flexible asymmetrical approachrdquo EcologyMonography vol 67 pp 777ndash795 1997

[42] J E PeckMultivariate Analysis for Community Ecologists Step-by-Step using PC-ORD MjM Software Design Gleneden BeachOre USA 2010

[43] M A Njana Arborescent species diversity and stocking inMiombo Woodland of Urumwa forest reserve and their contri-bution to Livelihoods Tabora Tanzania [MS thesis] SokoineUniversity of Agriculture Morogoro Tanzania 2008

[44] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal no 200 pp 59ndash70 2004

[45] J Isango ldquoStand structure and tree species composition ofTanzania miombo woodlands a case study from miombowoodlands of community based forest management in Iringadistrictrdquo in MITMIOMBOmdashManagement of Indigenous TreeSpecies For EcosystemRestoration andWood Production in Semi-Arid Miombo Woodlands in Eastern Africa Proceedings ofthe 1st MITMIOMBO Project Workshop held in MorogoroTanzania 6th-12th February 2007 Working Papers of theFinnish Forest Research Institute no 50 pp 43ndash56 2007

[46] J R Landon Booker Tropical Soil Manual A Handbook ForSoil Survey and Agricultural Land Evaluation in the Tropics andSubtropics Longman Scientific amp Technical and John Wiley ampSons 1991

[47] R F Fisher and D Binkley Ecology and Management of ForestSoils John Wiley amp Sons 3rd edition 2000

[48] W A Rees ldquoPreliminary studies into bush utilization by Cattlein Zambiardquo Journal of Applied Ecology vol 11 pp 207ndash214 1974

[49] S M Philip Measuring Trees and Forests CAB InternationalWallingford UK 2nd edition 1994

[50] J D Lowore P G Abbot and M Werren ldquoStackwood volumeestimations formiombowoodlands inMalawirdquoCommonwealthForestry Review vol 73 no 3 pp 193ndash197 1994

[51] D Kubota T Masunaga Hermansah et al ldquoSoil environmentand tree species diversity in tropical rain forest West SumatraIndonesiardquo in Soils of Tropical Forest Ecosystems CharacteristicsEcology and Management A Schulte and D Ruhiyat Eds pp159ndash167 1998

[52] P K T Munishi T H Shear T Wentworth and R A PC Temu ldquoCompositional gradients of plant communities insubmontane rainforests of EasternTanzaniardquo Journal of TropicalForest Science vol 19 no 1 pp 35ndash45 2007

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

EcosystemsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MeteorologyAdvances in

EcologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Marine BiologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental Chemistry

Atmospheric SciencesInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Geological ResearchJournal of

EarthquakesJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BiodiversityInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

Page 2: Research Article Floristic Composition, Structure, and

2 ISRN Biodiversity

N

PlotsVillagesDirt roads

Forest roadsGangalamtumba forest reserve

Tanzania

Iringa region 0 25 5 10

(km) To Iringa

Airport

Itagutwa

IkengezaTo Dodoma

Mfyome

Kiwele

Luganga

Figure 1 Map showing the location of the study area The inserted map of Tanzania shows the location of the Iringa region

to conversion of forest areas into agricultural lands or throughcharcoal production

GangalamtumbaVillage LandForest Reserve (GVLFR) inIringa rural district Tanzania which is owned and managedby the village of Mfyome was established in 2002 underTanzaniarsquos national participatory forest management pro-gramme and thus represents one of approximately 1500 Vil-lage Land Forest Reserves (covering some 24 million ha) theprogressive establishment of which is intended to promoteconservation of approximately 165 million ha of hithertounreserved forest on general and village land [18ndash21] Villagesrsquocontrol over Village Land Forest Reserves is conditional ontheir conservationprotection of these forests and the exec-utive management is performed by an environmentalforestmanagement committee whose members are directly electedfor five-year terms by all members of the village above theage of 18 [18] As such GVLFR is a typical example of anarea which at least until 2002 might have experienced lossof biodiversity due to increasing human activity includingcharcoal production and extraction of wood for tobaccocuring giving cause for concern with respect to the main-tenance of forest biodiversity [15] The extent to which theactivities have led to loss of biodiversity and deterioration ofthe plant community structure is so far unknown but for thedevelopment of sustainablewoodlandmanagement strategies

and for planning of future management and conservationinformation on these issues is urgently needed

Although many quantitative ecological studies have beenundertaken in places where Miombo dominates its exten-siveness and the large between-site variation which is causedby climatic and edaphic factors and anthropogenic activitiesappear to warrant further case studies [20 22ndash29] Ecologicalcase studies are particularly relevant when the informationgenerated is required for sound decision making about forestmanagement conservation strategies and determination ofsustainable harvesting levels Hence the objectives of thisstudy were (1) to provide a detailed assessment of the currentstanding stock species diversity richness and structure and(2) to understand the relationship between species abundanceand a range of environmental and topographic factors thatshape plant communities and species associations in theGVLFR

2 Materials and Methods

21 Study Site Gangalamtumba Village Land Forest Reserveis located in central-southern Tanzania (7∘351015840S 35∘351015840E)about 30 km north of Iringa town the administrative capitalof the Iringa region (Figure 1)The forest covers 6065 hectaresand is part of the Mfyome village area which is located in

ISRN Biodiversity 3

the ward of Kiwele The forest vegetation has been describedas dry Miombo woodland similar to the dry woodlandtype described from other countries such as Zimbabwe andMozambique [1] The forest is located in a relatively flat areaat an elevation of 850ndash1300 metres above sea level Theregion is characterised by distinct wet and dry seasons withalmost no rain in the four months of June-September andabout 80 of the annual precipitation falling in DecemberndashMarch Average rainfall data covering the last 50 years (1960ndash2010) were obtained from the meteorological station at Nduliairport which is located about 30 km from the forest andindicate that the area receives an average annual precipitation(mean plusmn standard error) of 617plusmn17mm (448ndash1085mm)Themean annual temperature is 198∘C and the average relativehumidities at 0600 and 1200GMT are 539 and 514respectively

The GVLFR is a production forest which is managedby the Mfyome village under a community-based forestmanagement (CBFM) arrangement established in 2002 com-pare above The primary economic activity in Mfyome issmallholder agriculture and the main economic uses of theforest are production of timber charcoal and firewood [20]The woodland is also used for grazing and is an importantsource of subsistence products such as firewood constructionmaterials fruit mushrooms wild vegetables and medicinalplants [18]

22 Vegetation Survey The field survey was conducted inJuly and August 2009 and involved establishment of a totalof 35 permanent nested circular sample plots distributedacross the entire forest Plots were established along transectlines and the distance between plots was approximately2 km (Figure 1) The radii of the nested circular plots were5m (00079 ha) 15m (00707 ha) and 20m (01257 ha) Thefollowing parameters were recorded within each of the 35plots within the 5m radius all small trees and shrubs(lt150 cm tall or ge150 cm but lt1 cm Dbh) were counted andtheir species were identified and medium-size trees andshrubs (ge1 cm Dbh but lt5 cm Dbh) were identified andmeasured with respect to diameter Within 15m radius thespecies were identified and the diameter was measured for alllarge trees and shrubs with Dbh ge5 cm Within 20m radiusall stumps of trees and shrubs were identified to specieslevel and measured for diameter 20 cm above ground Initialidentification of species for both standing treesshrubs andstumps relied on the knowledge of local botanists (usinglocal vernacular species names and features such as colorof the bark smell and leaves) and was later confirmed bybotanists from Tanzania Forest Research Institute (TAFORI)based at Lushoto Silviculture Research Station For speciesthat were difficult to identify in the field samples weretaken to the herbarium at Lushoto for reidentification Othermeasurements taken within the plots were geographicallocation (UTMcoordinates) and elevation (m) usingGPS andslope () using a Suunto clinometer

23 Soil Sampling Soil samples were collected from fivepoints which were located at the centre of the plot and 10mfrom the centre in the four cardinal directions (North East

South and West) At each point two samples were taken 0ndash15 cm and 15ndash30 cm below the surfaceThe five samples takenfrom each depth range were mixed in the field to obtain onecomposite sample per depth range and plot Thus 70 soilsamples (35 from each depth range) were collected from the35 plots In addition a soil core device with an inner diameterof 5 cm and a length of 5 cm was used for extracting soilbulk density samples from the centre of each plot and at eachdepth Hence a total of 70 samples were collected for bulkdensity determination

24 Laboratory Analyses In the laboratory all soil sam-ples were ground and passed through a 2mm sieve toremove stones and gravel Fine and coarse roots were alsoremoved Subsequently soil samples collected at 0ndash15 cmdepth were analysed for soil pH soil texture cation-exchangecapacity (CEC cmol(+)kg) available phosphorus (ppm)and exchangeable bases (Ca2+ Mg2+ and K+ cmol(+)kg)Samples from both depth ranges (0ndash15 and 15ndash30 cm) wereanalysed for percentages of organic carbon and total nitrogenStandard methods for soil analysis were used in order toobtain estimates for each of the mentioned variables that canbe compared with results reported in the literature [30ndash34]Soil pH was determined electrometrically using 10 g of soilsample diluted in 25mL distilled water that is using a 1 25ratio of soil to water Soil texture was determined by thehydrometer method and the textural classification was doneby the use of the soil texture triangle [35]

The Bray 1 method was used for the determination ofextractable P for acidic soils with pH less than 7 while theOlsen method was used for soils with pH above 7 (alkalinesoils) The ammonium acetate method at pH 7 was used indetermination ofCEC and by the use of an atomic absorptionspectrophotometer in a UNICAM 919 AA Spectrometer allexchangeable cations (Ca2+ Mg2+ and K+) were determinedSubsamples were finely ground into powder form (lt1mm) inan agate mortar and analyzed for total percentages of organicC and N by dry combustion (Dumas method) in a Leco CNS2000 analyzer [33] Samples for bulk density estimation wereoven-dried at 105∘C to constant weight and the weight wasrecorded (accuracy 001 g) The volume was calculated fromlength and cross-sectional area of the soil core and bulk den-sity was determined as dry weight (g) per unit volume (cm3)Most analyses were conducted at the Laboratory of ForestBiology Sokoine University of Agriculture (SUA) but C andN analyses were conducted at the Soil Science Laboratory attheDepartment of Forest andLandscape (nowDepartment ofGeosciences and Natural Resource Management) Universityof Copenhagen Denmark

25 Data Analysis Based on the data collected the followingmeasures were analysed species composition was expressedthrough species richness and diversity measures forest struc-ture was expressed through stem density basal area andvolume for plant communities species groups and diameterclasses Total species richness was computed as the totalnumber of species across all 35 plots Species diversity wascomputed using Shannonrsquos and Simpsonrsquos Diversity Indices

4 ISRN Biodiversity

[36]The volume of stumpswas calculated as cylinder volumewhile total volume for standing trees was calculated usinga regression equation developed for GVLFR by the authors[37 38] ln(V)= minus84554 + 23236 times ln(Dbh) (R2 = 0983RMSE = 0248 Dbh range 14ndash62 cm 119899 = 104) where V isvolume (m3tree) Dbh is diameter at breast height (ge1 cm)RMSE is the residual standard error R2 is the coefficientof determination n is the total sample size and ln is thenatural logarithmThe ImportanceValue Index (IVI) for eachspecies in each plot was calculated as the sum of relativedensity and dominance (basal area) and expressed in percent[39] Percentage base saturation (BS) was determined asthe ratio of total base cation concentration to CEC whilethe C N ratio was determined using the estimated elementalpercentages of carbon and nitrogen [35]

Using IVI for each species plots were classified byagglomerative hierarchical cluster analysis using Soslashrensenrsquosdistance measure and a group linkage method with flexible120573 of minus050 The 35 plots were ordinated by nonmetricmultidimensional scaling (NMS) using the PC ORDsoftwareversion 60 [40] Topographic variables (elevation and slope)and edaphic variables (pH bulk density texture extractableP CEC exchangeable base cations BS C N ratio Cand N) were correlated with the NMS ordination axesIndicatordominant species in each cluster were determinedusing percentage indicator values (IV) where values of 0correspond to no indication and 100 is perfect indication [4142] The first three to five names of these Indicatordominantspecies with the highest percentage indicator values (IV)constancy and significant indicator values (119875 lt 005) wereused to assign names to the clustersplant community types[29 41 42] The Steinhaus (SoslashrensenCzekanowski) coeffi-cient was used to assess the similaritydissimilarity of thespecies compositions of the plant communities [39]

3 Results

31 Species Richness Including all size categories a totalof 88 species (29 plant families) of standing trees andshrubssmall trees were identified in the GVLFR (Table 1)Trees contributed 60 (21 plant families) and shrubs 40(15 plant families) of the species For stumps a total of 42species (20 plant families) of trees and shrubssmall treeswith basal diameter ranging from 2 to 50 cm were identifiedFor stumps trees contributed 76 (13 plant families) of thespecies while shrubs contributed 24 (10 plant families)All species represented by stumps were also represented bystanding treesshrubs In general tree and shrub speciesfrom the family Caesalpiniaceae contributed most (13) tothe total number of species (standing individuals) followedby those from the families Mimosaceae (10) Rubiaceae(10) Fabaceae (9) and Euphorbiaceae (9) (Table 1)Among standing trees the greatest number of species wasfound in the four plant families Caesalpiniaceae (17)Mimosaceae (15) Fabaceae (13) and Combretaceae (9)while shrubssmall trees included most species from thefamilies Rubiaceae (26) Euphorbiaceae (17) and Cap-paraceae (9) For stumps tree and shrub species from

0 5 10 15 20 25 30 35

0

20

40

60

80

Sites

Spec

ies r

ichn

ess

Figure 2 Species accumulation curve for large individuals (Dbhge5 cm) measured within circular plots with a radius of 15m in theGangalamtumba VLFR Vertical lines indicate standard deviations(range 0ndash49)

the family Mimosaceae contributed most (17) to the totalnumber of species followed by species from the familiesCaesalpiniaceae (14) Combretaceae (10) and Fabaceae(7) Among species categorised as trees the families Cae-salpiniaceae (19) and Mimosaceae (19) contributed equalnumbers of species followed by Combretaceae (13) andFabaceae (9) With respect to shrubs each of the familieswas represented by a single species (10 see Table 1)

When considering different size categories and includingboth trees and shrubs (small sizes Dbhlt 5 cm and large sizesDbh ge 5 cm) a total of 78 species (28 families) were foundamong large sizes with Caesalpiniaceae (13) Mimosaceae(12) and Fabaceae (10) being the most species-rich plantfamilies while among small sizes a total of 69 species (27families) were observed with Rubiaceae (13) Caesalpini-aceae (12) andMimosaceae (10) contributing the greatestnumber of species (Table 1) In general the average number ofspecies per plot was found to be 14 species (range 5ndash24 speciesper plot)

The species accumulation curve (Figure 2) shows thatthe 35 sitesplots used in this study were sufficient to covermuch (but not all) of the variation and species diversity ofthe study area At 35 plots the graph has not yet reached itsasymptotic level but is starting to converge implying that anyfurther increase of sample size would be expected to lead toinclusion of additional rare species However although thesample size was small (35 plots) and does not quite capturethe full woody plant biodiversity of the reserve the results arestill useful for characterizing the treeshrub species diversityand relationships between species and site

32 Species Diversity Shannon-Wiener diversity indices forlarge and small individuals were found to be 344 and 326respectively and the Simpson index for large individuals was

ISRN Biodiversity 5

Table1Ch

ecklist

oftre

eand

shrubspeciesrecordedin

Gangalamtumba

VLF

Rshow

ingfre

quency

()density

(meanplusmnSE

)basalarea(meanplusmnSE

)dispersio

nindex(D

I)and

Impo

rtance

ValueInd

ex(IVI)bothforthe

currentp

opulationof

largeind

ividuals(plotsize=

15m

radiusm

inim

umDbh

=5c

m)a

ndforstumps

(plotsize=

20m

radiusm

inim

umbasald

iameter

=2c

m)SH

shrub

ST

smalltreeandT

tree

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

1Mgiha

Dalbergia

arbutifolia

Fabaceae

subfam

ilyPapilio

noideae

ST60

247plusmn69136plusmn037

224

4765

1468plusmn41006plusmn005

170

2Mtono

Commiphora

afric

ana

Burseraceae

T77

110plusmn23159plusmn037

175

1142

1414plusmn06001plusmn001

111

3Mlama

Combretum

molleG

Don

Com

bretaceae

T74

116plusmn27069plusmn015

132

1523

3468plusmn19005plusmn002

307

4Mku

ngugu

Acacia

sp

Mim

osaceae

T23

40plusmn22102plusmn054

111

2873

920plusmn14001plusmn001

65

5Mkw

eeBrachyste

gia

spiciform

isBe

nth

Caesalpiniaceae

T37

58plusmn20118plusmn034

110

1731

2661plusmn24020plusmn009

308

6Mkalala

Albiziapetersiana

(Belle)O

liv

Mim

osaceae

T40

80plusmn30055plusmn020

85

2711

636plusmn29005plusmn004

94

7Mlyasenga

Combretum

zeyheri

Soun

dCom

bretaceae

T43

60plusmn20030plusmn011

741597

2020plusmn08001plusmn001

47

8Mkombivawo

Bauh

iniapetersiana

Caesalpiniaceae

SH34

54plusmn21029plusmn010

64

2000

9Muguvani

Markham

iaobtusifolia

Bign

oniaceae

T60

65plusmn13038plusmn010

64

647

605plusmn03

00

23

10Mdeke

Hym

enodictyon

parvifoliu

mOliv

Rubiaceae

ST31

50plusmn24048plusmn024

58

2749

302plusmn02

00

17

11Mub

wegele

Sclerocarryabirrea

sbspbirr

eaAnacardiaceae

T34

21plusmn6061plusmn023

58

441

605plusmn03001plusmn001

28

12Mmem

enam

ene

Margaritaria

discoidea(Bail)

Euph

orbiaceae

SH51

68plusmn24032plusmn013

57

2073

307plusmn07

00

06

13Mkambala

Acaciamellifera

(Vahl)Be

nth

Mim

osaceae

T29

14plusmn5049plusmn019

50

359

302plusmn02

00

08

14Mugegere

Dich

rosta

chys

cinerea

(L)Wight

ampArn

Mim

osaceae

ST31

53plusmn26017plusmn009

47

3086

2959plusmn19003plusmn002

178

15Mbata

AcaciaseyalD

elvar

seyal

Mim

osaceae

T34

30plusmn10019plusmn006

45

887

311plusmn11001plusmn001

46

16Mgulumo

Lann

easchw

einfurthiiAnacardiaceae

T43

24plusmn7032plusmn009

39

544

907plusmn04002plusmn001

22

17Muyom

boBrachyste

giaboehmii

Caesalpiniaceae

T11

11plusmn7019plusmn015

38

1309

607plusmn05001plusmn001

22

18Mmulim

uli

Cassiaabbreviata

Caesalpiniaceae

T34

31plusmn13017plusmn007

36

1353

916plusmn12001plusmn001

49

19Mdavi

Cordiasin

ensis

Lam

Boraginaceae

ST6

23plusmn23011plusmn010

34

5498

302plusmn02

00

06

6 ISRN Biodiversity

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

20Mdw

endw

eTerm

inaliabrow

nii

Com

bretaceae

T17

14plusmn8019plusmn009

32

1129

305plusmn05

00

12

21Mfilafila

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T31

25plusmn8015plusmn005

30

646

605plusmn03

00

35

22Mkw

ata

Codyladensiflora

Caesalpiniaceae

T9

4plusmn2033plusmn019

28

282

334plusmn34004plusmn004

83

23Mgung

aAc

aciaabyssin

ica(H

ochst)

Mim

osaceae

T17

12plusmn7014plusmn007

24

1140

614plusmn12001plusmn001

39

24Mkole

Grew

iabicolor

Tiliaceae

ST26

21plusmn10008plusmn003

21

1078

605plusmn03

00

15

25Mparapand

eStrychnosp

otatorum

Lf

Loganiaceae

T23

23plusmn11014plusmn009

20

1331

607plusmn05

00

17

26Kitim

bwi

Orm

ocarpum

kirkii

Fabaceae

SH29

18plusmn6007plusmn003

19492

27Mtabagila

Lonchocarpus

capassa

Fabaceae

T26

11plusmn5014plusmn006

17550

302plusmn02

00

04

28Muw

otapon

ziOzoroainsig

nsssp

retic

ulata

Anacardiaceae

T14

10plusmn5010plusmn005

16564

1411plusmn05001plusmn000

31

29Msanzi

Gardeniaresin

iflua

Hiern

Rubiaceae

ST9

13plusmn8008plusmn005

161229

30Mkoga

Vitexpayos

Verbenaceae

ST17

12plusmn5011plusmn004

15605

302plusmn02

00

02

31Mpelem

eleGr

ewiaforbesiiHaw

Ex

Mast

Tiliaceae

ST14

16plusmn9005plusmn002

147

1246

32Mny

wenyw

eeDalbergiaboehmii

Fabaceae

T14

11plusmn7009plusmn007

151221

33Mulagavega

Albiziaam

ara(Roxb)

Boiv

Mim

osaceae

T14

9plusmn5004plusmn003

14712

34Mkola

Afzelia

quan

zensis

Caesalpiniaceae

T11

6plusmn3015plusmn009

14532

35Mugusi

Brachyste

giamanga

Caesalpiniaceae

T20

11plusmn6010plusmn007

13824

618plusmn13002plusmn002

25

36Mwaham

aShrebera

trichoclada

Oleaceae

T17

11plusmn6005plusmn002

12697

309plusmn09001plusmn001

15

37Mpingo

Dalbergia

mela

noxylon

Fabaceae

T11

11plusmn9004plusmn003

121655

314plusmn14001plusmn001

26

38Mub

aya

Strychnosinn

ocua

Loganiaceae

T17

8plusmn4011plusmn008

12375

302plusmn02001plusmn001

06

39Msisina

AlbiziaharveyiF

ournMim

osaceae

T14

5plusmn3008plusmn005

11359

305plusmn05002plusmn002

15

40Mlim

boEu

phorbiacuneata

Valh

Euph

orbiaceae

ST14

12plusmn6004plusmn002

11699

41Mwam

biElaeodendron

buchan

annii

Cela

steraceae

T3

8plusmn8003plusmn003

102000

42Mvembadand

aXe

roderris

stuhlmannii

Fabaceae

T14

4plusmn2011plusmn005

09

191

43Mtelela

Brachyste

giabu

ssei

Harms

Caesalpiniaceae

T6

2plusmn1012plusmn010

09

253

ISRN Biodiversity 7

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

44Mteresi

Prem

naholstiiGurke

Verbenaceae

ST9

8plusmn5003plusmn002

09

899

45Mkongolo

Commiphora

ugogensis

Burseraceae

T6

1plusmn1008plusmn006

08

097

302plusmn02001plusmn001

09

46Muw

isaBo

sciaangustifolia

A

Rich

varangustifo

liaCa

pparaceae

T17

8plusmn4004plusmn002

08

426

47Mnyalup

uko

Canthium

pseudoverticillatum

Hien

Rubiaceae

ST20

8plusmn4004plusmn002

07

414

48Mnyaluh

anga

Brideliascleu

roneura

MuellArg

Euph

orbiaceae

ST14

6plusmn3004plusmn002

07

341

49Mdide

Manilkaramochisia

(Bak)Dub

ard

Sapo

taceae

T9

5plusmn4002plusmn001

07

793

50Muh

emi

Erythrinaabyssin

icaFabaceae

T6

1plusmn1007plusmn006

07

163

51Msambarawe

Vangueria

infausta

BurchSspRo

tund

ataRu

biaceae

ST6

8plusmn5002plusmn002

06

925

52Mhehefu

Allophylu

sferrugineus

Taub

Sapind

aceae

SH9

5plusmn3002plusmn001

05

540

314plusmn14001plusmn001

14

53Mnyengrsquoenyengrsquoe

Excoecariabu

ssei

(Pax)

Euph

orbiaceae

ST11

4plusmn2001plusmn001

05

321

54Muganga

Berchemiadiscolor

Rham

naceae

T6

4plusmn3004plusmn003

04

717

55Mning

aPterocarpu

sangolensis

Fabaceae

T6

2plusmn1005plusmn004

04

253

309plusmn09006plusmn006

25

56Mtanang

we

Zizip

husm

ucronata

Rham

naceae

T3

4plusmn4003plusmn003

04

900

57Muh

ekele

Eucle

adivinorum

Hiern

Ebenaceae

ST3

3plusmn3001plusmn001

04

800

302plusmn02

00

49

58Mub

umila

Cassipourea

mollis

(REfr)Alstom

Rhizop

horaceae

T9

4plusmn3002plusmn001

04

526

302plusmn02

00

04

59Mkw

ambe

Flueggea

virosa

Willd

Euph

orbiaceae

SH6

3plusmn2003plusmn003

03

406

60Kivang

aZa

nhaafric

ana

(Radlk)Ex

ell

Sapind

aceae

T9

2plusmn1001plusmn001

02

212

302plusmn02

00

02

61Mning

amaji

Pterocarpu

stinctorius

Fabaceae

T3

0002plusmn002

02

100

62Mtosi

MaeruatriphyllaA

Rich

Capp

araceae

ST3

2plusmn2001plusmn001

02

600

63Mugosa

Ehretia

amoena

Boraginaceae

ST9

1plusmn1

00

01

094

64Mnyon

gamem

beStegan

otaenia

araliacea

Apiaceae

T6

1plusmn1

001

01

163

65Mvelevele

Vernoniaam

ygdalin

aAs

teraceae

SH3

2plusmn2001plusmn001

01

400

66Mpo

ngolo

Catunaregam

spinosa

(Thun

b)

Rubiaceae

ST3

1plusmn1001plusmn001

01

200

8 ISRN Biodiversity

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

67Mbo

liboli

Acaciadrepanolobium

(Harms)

Mim

osaceae

T3

000

01

100

68Mwim

akigulu

Maeruaangolen

sisCa

pparaceae

SH3

1plusmn1

00

01

300

69Mnyali

Tamarindu

sind

icaCa

esalpiniaceae

T6

1plusmn1001plusmn001

01

097

70Mgombw

ani

Combretum

aculeatum

Com

bretaceae

T6

1plusmn1

00

01

097

302plusmn02

00

04

71Msang

ala

Burkea

afric

anaHoo

kCa

esalpiniaceae

T3

0001plusmn001

01

100

302plusmn02

00

04

72Mkokonza

Opilia

amentacea

Roxb

Opiliaceae

SH3

000

00

100

311plusmn11

00

42

73Mfumbi

Kigelia

afric

ana

Bign

oniaceae

T3

000

00

100

74Mlang

ali

Euphorbia

cand

elabrum

Euph

orbiaceae

T3

000

00

100

75Mpu

lulu

Term

inaliaseric

eaCom

bretaceae

T3

000

00

100

76Mdaha

Diospyros

usam

barensisFWhite

Ebenaceae

T3

000

00

100

305plusmn05001plusmn001

15

77Mtund

wa

XimeniacaffraSond

Olacaceae

ST3

000

00

100

78Mwim

aperu

Tarenn

agla

veolens(S

Moo

re)B

rem

Rubiaceae

ST+

79Mwesa

Boscia

mossambicensisKl

Capp

araceae

ST+

80Musasam

ulo

Psychotria

schu

mmaniana

Rubiaceae

ST+

81Muh

anza

Senn

asin

gueana

Caesalpiniaceae

ST+

82Mtund

wahavi

Ximeniaam

erica

naOlacaceae

ST+

83Mtin

giligiti

Phyllanthu

sengler

iPax

Euph

orbiaceae

T+

84Msada

Vangueria

madagascarie

nsis

Gmel

Rubiaceae

ST+

85Mku

nung

uZa

nthoxylum

chalybeum

Rutaceae

T+

86Lu

kali

Croton

scheffleriP

axEu

phorbiaceae

SH+

87Kilim

andembw

eGardeniaternifolia

KSchu

mamp

Thon

nRu

biaceae

ST+

88MpelaM

buyu

Adan

soniadigitata

Bombacaceae

T++

Total(allspecies)

13511521plusmn5941355plusmn552

200

294

60plusmn30072plusmn049

200

+indicatesspecies

identifi

edam

ongsm

allerind

ividualswith

in5m

radius

plots(Dbhlt5c

m)and++

indicatesthata

largeind

ividualw

asidentifi

edwith

ina1

5-radius

plot

butw

asno

tincludedin

thea

nalyseso

fste

mdensitybasalareaand

volumea

sitw

asconsidered

anou

tlier

duetoits

tremendo

ussiz

e(Dbh

=340c

m)

ISRN Biodiversity 9

005 and that of small individuals was 006 The followingspecies were observed to have the greatest contributionsto the Shannon-Wiener diversity index of large individualsDalbergia arbutifolia (contributing 030) Combretum molle(020) Commiphora africana (019) Albizia petersiana (016)and Margaritaria discoidea (014) while for smaller ones thegreatest contributions were found for Brachystegia spiciformis(026) Dalbergia arbutifolia (024) Grewia forbesii (023)Margaritaria discoidea (020) and Dichrostachys cinerea(016) In terms of frequency of occurrence for standingindividuals (large sizes) Commiphora africana was the mostfrequent species (77 of plots) followed by Combretummolle (74) and Dalbergia arbutifolia (60) while for smallsizes Margaritaria discoidea (66) Markhamia obtusifolia(63) and Dalbergia arbutifolia (57) were the most fre-quent species The Importance Value Index (IVI) for largeindividuals (Dbh ge 5 cm) shows that Dalbergia arbutifolia(224) Commiphora africana (175) and Combretum molle(132) were the most important species among standingindividuals while Brachystegia spiciformis (308)Combretummolle (307) and Dichrostachys cinerea (178) appeared to bethe most important among harvested individuals (stumps)These species were also found to have higher frequencies thanany other harvested species observed in the GVLFR (Table 1)

33 Stem Density The total mean stem density for large indi-viduals with Dbh ge5 cm was 1521 plusmn 594 stemsha (Table 1)and that of small individuals with Dbh lt5 cm (includingindividuals with Dbh lt1 cm) was 14318 plusmn 6956 stemshaAmong large individuals the most abundant species wereDalbergia arbutifolia (162 of 1521 stemsha) Combretummolle (8) Commiphora africana (72) and Albizia peter-siana (53) Among small individuals the most abundantspecies were Brachystegia spiciformis (13 of 14318 stemsha)followed by Dalbergia arbutifolia (11) and Grewia forbesii(10) For stumps the overall mean density was 60 plusmn38 stemsha with Combretum molle (12) Dalbergia arbuti-folia (12) Brachystegia spiciformis (10) and Dichrostachyscinerea (10) contributing the most (Table 1) Generally thedistribution of standing trees to size classes showed the usualreverse J shape which was also approximately observed forstumps (Figure 3) However for stumps the density of stemsin the 1ndash10 cm diameter class was slightly lower than whatwould be expected if tree felling had been a random event

34 Basal Area For the GVLFR as a whole the meanbasal areas for large (ge5 cm Dbh) and small individuals(lt5 cm Dbh) were 1355 plusmn 552m2ha (Table 1 Figure 4)and 305 plusmn 002m2ha respectively The species contributingmost to the basal area of large individuals were Commiphoraafricana (12) Dalbergia arbutifolia (10) and Brachystegiaspiciformis (9) while those contributing most to the basalarea of smaller individuals were Dalbergia arbutifolia (16)Grewia forbesii (15) and Dichrostachys cinerea (13) Themean basal area for stumps was 072m2ha with Brachystegiaspiciformis contributing the greatest individual proportion(28) 41 species made up the rest (Figure 4)

60542

3335

530

113

28 24

346166

34

11

02

01

10

100

1000

10000

100000

Diameter classes (cm)

Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Stem

s (ha

minus1)

Figure 3 Density of standing trees ge1 cmDbh and stumps ge1 cm bydiameter class in Gangalamtumba VLFR (119899 = 35) NB logarithmicscale on vertical axis

744477

241

103041 055

014025 018

010004

001

01

1

10

Diameter classes (cm)Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Mea

n ba

sal a

rea (

m2

haminus1)

Figure 4 Distribution of basal area per hectare for standingtrees ge1 cm Dbh and stumps ge1 cm by diameter classes in theGangalamtumba VLFR (119899 = 35) NB logarithmic scale on verticalaxis

35 Volume The mean volumes for large (ge5 cm Dbh) andsmall individuals (lt5 cm Dbh) were 9217 plusmn 390m3ha and1257 plusmn 635m3ha respectively (not shown in tables) Thespecies contributing most to the volume of large individualswere Commiphora africana (12) Brachystegia spiciformis(10) Acacia sp (9) and Dalbergia arbutifolia (9) Forsmaller individuals the species that contributed most tovolume were Dalbergia arbutifolia (16) Grewia forbesii(14) and Dichrostachys cinerea (13) The mean remainingvolume of stumps was found to be 015 plusmn 01m3ha withBrachystegia spiciformis contributing the greatest individualpercentage (28) 41 species made up the rest

10 ISRN Biodiversity

36 Spatial Distribution Dispersion indices (DI) are pre-sented for individual species in Table 1 The dispersion indexvalues range from 094 indicating almost complete spatialrandomness or slight underdispersion to 5498 indicatingconsiderable overdispersion that is a patchy or clustereddistributionOut of 77 species excluding the single very largeAdansonia digitata that was considered an outlier 64 species(83) 9 species (12) and 4 species (5) were found tohave DI gt 1 DI = 1 and DI lt 1 respectively so the majorityof species are characterised by a patchy distribution acrossthe forest The species with the lowest estimated DI wasEhretia amoena (094) while the highest DI was estimated forCordia sinensis (5498)Themost abundant species includingDalbergia arbutifolia (DI = 4765) Combretum molle (DI =1523) and Commiphora africana (DI = 1142) are stronglyoverdispersed

37 Plant Communities and Species Association Four plantcommunities were identified through cluster analysis basedon the statistical significance (5) of the observed maximumindicator values (Table 2) Only two of these plant commu-nities were dominated by species from the family Caesalpini-aceae (Communities 1 and 24) The other two showed greatvariationoverlap between species of different plant families(Communities 3 and 5) The estimated Steinhaus similarityindices between pairs of plant communities varied from 32for Communities 1 and 3 and Communities 5 and 24 to 37for Communities 3 and 5 (not shown in tables)

The ordination diagram (Figure 5) shows that one topo-graphic and six edaphic variables appear to be associatedwiththe four plant communities and the species distribution inthe study area The strongest correlation with communitycomposition was observed for elevation followed by soilpH at 0ndash15 cm depth base cation Ca2+ at 0ndash15 cm depthpercent base saturation (BS) at 0ndash15 cm depth percent clayat 0ndash15 cm depth C N ratio at 15ndash30 cm depth and percentsand at 0ndash15 cm depth The base cations magnesium (Mg2+)and potassium (K+) were not directly correlated with thecommunity composition but since they are included in thebase saturation percentage they are indirectly related Plantcommunities were ordered along the second ordination axiswhich was positively correlated with pH15 (119903 = 071) Ca15(119903 = 069) BS (119903 = 065) andClay15 (119903 = 052) and negativelycorrelated with Sand15 (119903 = minus046) Axis 1 of the ordinationwas positively correlated with Elev (119903 = 085) and CNrat30(119903 = 051) As shown in Table 3 and indicated graphically inFigure 5 correlations between many of the edaphic variablesare strong particularly between pH15 Sand15 Clay15 Ca15and BS whereas correlation between topographic and mostedaphic variables is small and nonsignificant However thereis a significant negative correlation (119903 = minus042) between Elevand Sand15 indicating that sandy soils are mostly found atlower elevations

4 Discussion

41 Species Composition The results reported in this studyshow that the composition of the vegetation types found in

Elev

pH15Ca15

Sand15

Clay15

CNrat30

BS

Axis 1

Axis 2

Community 1Community 3

Community 5Community 24

Figure 5 Compositional gradients and plant communities in NMSordination of 35 vegetation plots for trees ge5 cm in GangalamtumbaVLFR Four plant communities are recognized (cf Table 2) Com-munity 1 = Brachystegia spiciformis Diplorynchus condylocarponand Lannea schweinfurthii woodland Community 3 = Dalbergiaarbutifolia Commiphora africana and Albizia petersianawoodlandCommunity 5 = Acacia sp Acacia abyssinica and Albizia amarawoodland and Community 24 = Bauhinia petersiana and Shreberatrichoclada woodland Elev elevation (m) CNrat30 C N ratio at15ndash30 cm depth Sand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm Ca15 = Ca2+ (cmol(+)kg) at 0ndash15 cm pH15 = soil pH at 0ndash15 cm BS base saturation at 0ndash15 cm

the GVLFR especially the dominance of species from thefamily Caesalpiniaceae agreed well with previous descrip-tions and classifications of plant communities commonlyfound in miombo woodlands [1] However the observeddominance based on IVI of the genera Dalbergia Com-miphora and Combretum contrasts with patterns usuallyconsidered common for miombo woodlands The frequencyof species in these genera was also high compared to otherspecies observed in the GVLFR (Table 1) Similar deviationsexist between the results obtained by Banda et al [26]in the Katavi-Rukwa ecosystem where they observed thatTerminalia and Combretum were the dominant genera andthe findings of Giliba et al [27] and Njana [43] whoboth noted the dominance of the two common miombogenera Brachystegia and Julbernardia However Combretumalso occurred in their study areas The results suggest thaton a larger spatial scale the species diversity of miombowoodlands is very high and that the three common generaBrachystegia Julbernadia and Isoberlinia are not alwaysdominant at the local scale

The species richness observed in the GVLFR compareswell with miombo community studies in other areas of drymiombo in Tanzania and elsewhere which receive an average

ISRN Biodiversity 11

Table2Plantcom

mun

itiesandspeciesa

ssociatio

nsin

thed

ryMiombo

woo

dlands

ofGangalamtumba

VLF

RCom

mun

itynu

mbers135and24

representthe

different

plantassociatio

ns

119899speciesnu

mbero

fspecies

(77in

total)with

Dbhge5c

mIV+

speciesind

icator

valuemeanplusmnstd

errorand

BAisbasalarea

Com

mun

ityAs

sociated

species

Family

Habit

IV+

()

Con

stancy

()119875value

Stem

sha

BA m2 ha

MeanDbh

Brachyste

giaspiciform

ismdashDiplorhynchus

cond

ylocarponmdashLa

nnea

schw

einfurthiiw

oodland

1(n s

pecies

=47

nplots=9)

Sitevariables(meanplusmnSE

)Elev

=1200plusmn20pH15

=644plusmn013C

a15=604plusmn128

Sand

15=721plusmn431C

lay15=137plusmn188Silt15

=142plusmn335C

Nrat30=135plusmn05andBS

=526plusmn65

Brachyste

gia

spiciform

isCa

esalpiniaceae

T820

100

000

02164plusmn59356plusmn077138plusmn07

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T759

89000

0866plusmn18044plusmn01382plusmn05

Lann

easchw

einfurthii

Anacardiaceae

T719

100

000

0449plusmn14072plusmn022126plusmn09

Bosciaangustifolia

Capp

araceae

T536

5600056

27plusmn12014plusmn00776plusmn06

Euphorbiacuneata

Euph

orbiaceae

ST428

4400200

42plusmn19012plusmn00665plusmn06

Other

species

mdashmdash

mdashmdash

mdash1075plusmn5741007plusmn647102plusmn03

Subtotal

1423plusmn174

1505plusmn178

109plusmn03

DalbergiaarbutifoliamdashCo

mmiphora

afric

anamdash

Albizia

petersiana

woo

dland

3(n

species=55n

plots=

16)Site

variables(meanplusmnSE

)Elev

=986plusmn19pH15

=648plusmn009C

a15=856plusmn109

Sand

15=767plusmn156C

lay15=135plusmn155Silt15

=97plusmn096C

Nrat30=106plusmn03andBS

=744plusmn44

Dalbergiaarbutifolia

Fabaceae

subfam

ilyPapilio

noideae

ST793

100

000

02500plusmn123263plusmn06477plusmn02

Commiphora

afric

ana

Burseraceae

T542

9400026

187plusmn40272plusmn064119plusmn06

Albiziapetersiana

Mim

osacea

T536

7500200

157plusmn57103plusmn04084plusmn02

Sclerocarryabirrea

Anacardiaceae

T504

6300186

40plusmn11128plusmn045168plusmn17

Other

species

mdashmdash

mdashmdash

mdash852plusmn449669plusmn37788plusmn03

Subtotal

1735plusmn166

1435plusmn071

92plusmn02

Acaciaspmdash

Acaciaabyssin

icamdash

Albiziaam

arawoo

dland

5(n

species=33n

plots=5)

Sitevariables(m

eanplusmnSE

)Elev

=986plusmn52pH15

=734plusmn023C

a15=139plusmn33

Sand

15=745plusmn678C

lay15=148plusmn47Silt15

=107plusmn26C

Nrat30=106plusmn07andBS

=963plusmn89

Acaciasp

Mim

osaceae

T981

100

000

02269plusmn111662plusmn286172plusmn14

Acaciaabyssin

icaMim

osaceae

T594

8000030

31plusmn9060plusmn03299plusmn08

Albiziaam

ara

Mim

osaceae

T552

60000

6654plusmn30023plusmn01671plusmn08

Grew

iabicolor

Tiliaceae

ST533

6000106

113plusmn52040plusmn01770plusmn04

Acaciaseyal

Mim

osaceae

T433

6000526

62plusmn34034plusmn01790plusmn05

Other

species

mdashmdash

mdashmdash

mdash665plusmn533552plusmn49872plusmn04

Subtotal

1194plusmn169

1367plusmn347

101plusmn05

Bauh

iniapetersiana

mdashShrebera

trichoclada

woo

dland

24(n

species=35n

plots=5)

Sitevariables(meanplusmnSE

)Elev

=1175plusmn25pH15

=73plusmn04C

a15=254plusmn69

Sand

15=522plusmn68C

lay15=331plusmn28

Silt15=147plusmn44C

Nrat30=961plusmn13andBS

=1041plusmn204

Bauh

iniapetersiana

Caesalpiniaceae

SH551

8000118192plusmn121111plusmn05075plusmn03

Shrebera

trichoclada

Oleaceae

T505

6000110

57plusmn32022plusmn01380plusmn05

Manilkaramochisia

Sapo

taceae

T376

4000332

34plusmn27014plusmn00969plusmn10

Dalbergia

mela

noxylon

Fabaceae

T370

4000380

68plusmn58026plusmn02266plusmn03

Ehretia

amoena

Boraginaceae

ST347

4000344

6plusmn4

002plusmn00170plusmn04

Other

species

mdashmdash

mdashmdash

mdash982plusmn759643plusmn47999plusmn05

Subtotal

1338plusmn137

817plusmn087

91plusmn04

Total

1521plusmn5941355plusmn55298plusmn01

Elevelevatio

n(m

)CN

rat30CN

ratio

at15ndash30c

mdepthSand

15sand(

)at0

ndash15c

mC

lay15clay

()at0

ndash15c

mSilt15silt

()at0

ndash15c

mC

a15Ca2+(cmol(+)kg)at0

ndash15c

mpH15soilp

Hat0ndash

15cm

BS

base

saturatio

nat0ndash

15cm

12 ISRN Biodiversity

Table 3 Pearson-correlation matrix for two topographic and eight edaphic variablesdagger associated with the classified plant communities in theGangalamtumba VLFR (119899 = 35) Applied significance levels lowast5 lowastlowast1 and lowastlowastlowast01 +not significant

Elev Slope pH15 Ca15 K15 N15 Sand15 Clay15 CNrat30Slope 019+

pH15 minus013+ minus033lowast

Ca15 002+ minus020+ 083lowastlowastlowast

K15 minus029+ 000+ 010+ 012+

N15 006+ 036lowast 010+ 041lowastlowast 033lowast

Sand15 minus042lowastlowast 003+ minus053lowastlowastlowast minus074lowastlowastlowast 006+ minus046lowastlowast

Clay15 031+ minus012+ 051lowastlowast 076lowastlowastlowast minus001+ 047lowastlowast minus086lowastlowastlowast

CNrat30 036lowast 010+ minus039lowast minus051lowastlowast minus015+ minus019+ 040lowast minus048lowastlowast

BS minus024+ minus017+ 084lowastlowastlowast 091lowastlowastlowast 015+ 037lowast minus058lowastlowastlowast 060lowastlowastlowast minus051lowastlowastdaggerElev elevation (m) pH15 soil pH at 0ndash15 cm Ca15 Ca2+ (cmol(+)kg) at 0ndash15 cm K15 K+ (cmol(+)kg) at 0ndash15 cm N15 N concentration at 0ndash15 cmSand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm CNrat30 C N ratio at 15ndash30 cm depth BS base saturation at 0ndash15 cm 119905-value was calculated as119905 = 119903radic(119899 minus 2)(1 minus 119903

2) where 119903 is the Pearson-correlation coefficient and 119899 is the total sample size

Table 4 Species richness observed in other studies from drymiombo woodlands

Plot size(ha)

Totalnumberof plots

Total samplearea(ha)

Total numberof species References

0071 70 495 82 [43]0071 80 565 110 [27]0071 133 940 229 [26]0071 247 1746 102 [44]004 40 160 81 [45]025 14 350 69 [25]01 2 020 40 [28]01 152 1520 92 genera [22]0071 35 247 88 This study

annual rainfall of 565ndash1500mm (Table 4) Using plot sizes of004ndash025 ha and sample sizes of 2ndash247 plots a total numberof species ranging from40 (Dbhge 10 cm) to 229 (Dbhge 2 cm)have been reported fromMiombowoodlands [22 25ndash28 43ndash45]

The high number of species reported by Banda et al [26]Chidumayo [22] Isango [45] and Chamshama et al [44] islikely to be a consequence of the spatial scale and coverage ofthese studies as they all cover large areas include more thanone site and operate with large sample sizes For exampleChidumayo [22] included species from both wet and dryMiombo areas in Zambia The study by Sauer and Abdallah[15] who reported a total of 131 species occurring in thetobacco growing zone of Iringa rural district included twoforest reserves and three family-managed forests Thereforeconsidering the climatic conditions in the GVLFR (617mmof rainfall per year) and the sample size (35 plots) thespecies richness reported in this study can be ranked atleast as high or higher than those found in the studiesmentioned The selective sampling approach focusing onvarious microhabitat types adopted by Banda et al [26] mayhave contributed to the large number of species observed

in their study area Similarly the higher number of speciesfound by Giliba et al [27] was probably due to the presenceof riverine forest offering site conditions favourable formanyspecies

The values of the Shannon-Wiener (1198671015840 = 344) andSimpson indices (119863 = 005) reported for large individ-uals in this study are within the range observed for mostcommunities of particular life forms [36] For example 1198671015840usually does not exceed 5 although this maximum valuevaries depending on the type of the biological communitysampled and the sampling approach applied (eg minimumdiameter and size of sample units) A threshold value of 2 for1198671015840 has been mentioned as a minimum value above which

an ecosystem can be regarded as medium to highly diverse[27] Chamshama et al [44] reported three 1198671015840 values of31 32 and 33 from Kitulangalo Miombo forest in EasternTanzania while Njana [43] reported a 1198671015840 value of 340from dry Miombo forest in Western Tanzania The studiesby Sauer and Abdallah [15] and Giliba et al [27] reportedparticularly high values of 346 and 427 respectively Thiscould be attributed to the very large sample sizes used inboth studies and the presence of riverine forest where thechance of encountering many rare species is likely to be highThe forests examined in the mentioned studies receive anaverage annual rainfall of 700ndash1000mm compared to whichthe rainfall in the GVLFR is low (617mm on average per yearcf above)The relatively high diversity found inGVLFRmusttherefore be attributed to other factors than climate The soilanalyses indicate that the soil fertility level in the GVLFRis relatively high with considerable proportions of all 2 1lattice clay minerals (114) (ie illite montmorillonite andvermiculite) plus a good amount of organic matter whichmay suggest that the soil has large reserves of important plantnutrients for example K Mg and Fe The base saturationpercentage (BS) which is normally used to indicate the soilfertility status (Landon 1991) was also high 76 on averageand with 86 of the samples (30 samples) with BS valuesgt50 (fertile soil) and only 14 of the samples (5 samples)with BS below 50 (less fertile soil) As another indicationof high soil fertility status the mean C N ratio was 12 plusmn 043

ISRN Biodiversity 13

(range 7ndash19) for top soil (0ndash15 cm) and 11 plusmn 036 (range 5ndash16) for subsoil (15ndash30 cm) In general the values for both soilstrata fall within the expected range of 8ndash17 Soil pH values(mean 67 plusmn 01 range 567ndash852)were alsowithin the optimalrangewhere all the nutrients that aremost important for plantgrowth (Ca Mg K and P) are available and accessible toplants [46] In this study 97 of the soil samples had pHbelow 8 (one sample had a pH of 852) Fisher and Binkley[47] noted that high pH is almost never a problem in forestsas most trees do well across the full range of common pHvaluesTherefore considering the low average annual rainfallcompared to other forests the relatively high fertility of theGVLFR may be the main factor creating an environmentfavourable to many species thus leading to a quite highspecies diversity observed in this forest

Based on the Importance Value Index Brachystegia spi-ciformis and Combretum molle appeared to be the mostimportant species among harvested trees (stumps) in thestudy area This result agreed very well with the large valuesof basal area and volume and the information obtained fromlocal scouts and members of the village environmental com-mittee who said that the most frequently harvested speciesfor charcoal making include all Brachystegia species found inthe forest (ie Brachystegia spiciformis Brachystegia mangaBrachystegia boehmii and Brachystegia bussei) Among theCombretum species the most important one (based on IVI)Combretum molle is mostly used for house construction andfirewood rather than for charcoal making Apart from theBrachystegia species the only other species mentioned asimportant for charcoal making was Acacia mellifera Otherspecies are only used in case they happen to fall when fellingthe preferred species during the preparation of charcoal kilnsWith respect to stumps Brachystegia spiciformis Brachystegiamanga and Combretum molle are among the ten mostabundant species in terms of density basal area and volumeper hectare Stumps of the other species mentioned are notcommonly found a factwhichmay be due to the small samplesize being unable to capture sites where these species areharvested but may also be related to their limited distributionin the forest as indicated by the estimated dispersion indices(see Table 1)

42 Forest Structure Species densities reported from otherMiombo woodland areas in Tanzania are typically 348ndash1495stemsha for trees with Dbh gt4 cm [24 43 45] Comparedwith this the GVLFR is highly stocked as the estimateddensity is 2296 stemsha for trees with Dbh gt4 cmThemeanstem density of 1521 plusmn 594ha for trees with Dbh ge5 cmis also more than twice as large as values found in otherstudies [25ndash27 44 45 48] A similar pattern is seen whencomparing the density of regeneration between the studiesThe diameter distribution is characterised by a very cleartrend of decreasing stem density with increasing diameterThe shape of the distribution is thus an inverted ldquoJrdquo (Figure 3)which is a common feature of natural forests with activeregeneration and recruitment [49] However not many largetrees were captured by the sample whereas a considerablenumber of relatively large stumps were observed suggestingthat anthropogenic activities such as charcoal making may

have affected the structure and ecological balance of the forest(see Figure 3) Since the woodlands are often hit by fire whichtends to kill the seedlings (especially the late fires) and thusonly few seedlings can be expected to reach larger diameterclasses lack of mature trees and the resulting lack of seedsmay eventually threaten the biodiversity of the forest

The mean basal area of 1355 plusmn 552m2ha observedin this study is slightly above the range of values typicallyreported from the miombo region 75ndash126m2ha [26 28 4344 50] However the basal areas reported by Isango [45] werea bit higher (1504ndash1563m2ha) than observed in this study

Themean total volume inGVLFRwas estimated at 9217plusmn390m3ha for trees with Dbh ge5 cm Other studies in dryMiombo woodlands have reported mean volumes of 167ndash7603m3ha [24 44 45 50] The current standing volume ofGVLFR is thus slightly higher than values typically reportedfor forests in the Miombo ecoregion A plausible reason forthis may be that compared to other forests the GVLFR isstill well stocked despite ongoing human activities such ascharcoalmakingThebasal area observed for stumpswas only072m2ha so there is no indication of intensive extractionover many years This corresponds well with the findings ofTreue et al [20] who conclude that the estimated 04m3haannual extraction of woody biomass from GVLFR is consid-erably below its estimated annual increment of 15m3ha andthat the local forest managers seem capable of regulating theharvesting activities which in addition to village membersrsquocollection for subsistence uses also included commercialcharcoal production by external companies that pay a fee perbag of charcoal extracted to the village government

43 Plant Communities and Species Associations Except forBrachystegia spiciformis the majority of the Brachystegia andJulbernardia species that are common to miombo wood-lands elsewhere are not among the species most commonlyobserved in this study A similar pattern was observed byBanda et al [26] in the Katavi-Rukwa ecosystem wherethe genera that are most common in miombo woodlandsBrachystegia Julbernardia and Isoberlinia were not commonin their study sites Furthermore the four plant communi-ties distinguished in this study are comparable with thosereported by other studies in Tanzania including the work byMunishi et al [29] in theMiombowoodlands of Rukwa basinChunya district Tanzania and the study by Banda et al [26]in the Katavi-Rukwa ecosystem

Elevation was noted by Munishi et al [29] to be themost important factor shaping the species communities intheir study area This study found a similar pattern with thehighest coefficient of correlation observed for elevation sug-gesting that topographical variation is among the strongestdeterminants of community composition in dry Miombowoodlands hence influencing the spatial distribution ofspecies strongly However in our study area edaphic factorsalso influenced the species distribution directly Two plantcommunities occurredmainly on clayey soils with high pH atintermediate elevations one on sandy soils with lowpHat lowelevations and one on sandy-clayey soils at higher elevationsand with neutral soil pH (Figure 5) Specifically it appeared

14 ISRN Biodiversity

that the Acacia woodland category (Community 5) grows atlow elevations around temporary streams (or at least wherethe ground water table is relatively high) and the Bauhiniawoodland category (Community 24) appearsmostly in placeswith a relatively high percentage of clay (and therefore highvalues of pH Ca and BS) By contrast it appeared that theDalbergia woodland category (Community 3) is located atmore sandy sites (with low values of pH Ca and BS) andthe Brachystegia woodland category (Community 1) seemedto be located mostly at higher elevations where the CN-ratio is quite high Correlations between elevation and thebasic soil variables pH Ca and percentages of sand andclay were low (cf Figure 5) Thus the results indicate thatthe plant communities of the dry miombo woodlands inGVLFR are not only shaped by the topographic variation(elevation) and the groundwater level but also by basic soilcharacteristics The results thus confirm findings from otherstudies detecting effects of elevation and soil characteristicson species composition [51 52]

5 Conclusion

Considering that the sample size used in this study wassmaller than samples used in other studies in dry miombowoodlands the results show that the species diversity inGVLFR is relatively high compared to other forest reservesThe vegetation of GVLFR is characterised by high densitybasal area and volume and despite the scarcity of largediameter trees this indicates that the forest is in a goodcondition The effect of anthropogenic activities is neverthe-less evident and stresses the need for proper managementespecially for economically important species preferred forcharcoalmaking (egBrachystegia spiciformis) if the currentspecies diversity is to be maintained or enhanced A repeatedfuture study would be needed to assess whether the currentcommunity-based management regime yields this intendedoutcome but the available information and analyses allow forsome optimism in this respect

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors wish to thank people from Mfyome villagefor their invaluable assistance during field work Mzee IddiKaheya Damian Chotamasege AugustinoMkwama Libera-tus Simime and Mawazo Nyangwa Furthermore thanks aredue to Venancia Mlelwa from Sokoine University and MadsMadsen Krag from University of Copenhagen for doing thelaboratory work The authors also wish to thank GoodluckMoshi their driverMarcoNjana andNassoroHMagogo theTAFORI botanist for assisting with species identification andKlaus Dons for preparing a study site map Financial supportwas provided by Danida through the ENRECA Project

ldquoParticipatory forest management for rural livelihoods forestconservation and good governance in Tanzaniardquo (no 725)

References

[1] P G H Frost ldquoThe Ecology of Miombo Woodlandsrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 11ndash57 1996

[2] N Burgess J Hales E Underwood et al Terrestrial Ecoregionsof Africa and Madagascar A Conservation Assessment IslandPress World Wildlife Fund 2004

[3] J Clarke W Cavendish and C Coote ldquoRural householdsand miombo woodlands use value and managementrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 101ndash135 1996

[4] B M Campbell A Angelsen A Cunningham Y KaterereA Sitoe and S Wunder ldquoMiombo woodlandsmdashopportunitiesand barriers to sustainable forest managementrdquo httpsener-gypediainfoimages66dMiombo2007pdf

[5] S Syampungani P W Chirwa F K Akinnifesi G Sileshi andO C Ajayi ldquoTheMiombo woodlands at the cross roads poten-tial threats sustainable livelihoods policy gaps and challengesrdquoNatural Resources Forum vol 33 no 2 pp 150ndash159 2009

[6] J I O Abbot and K Homewood ldquoA history of change causesof miombo woodland decline in a protected area in MalawirdquoJournal of Applied Ecology vol 36 no 3 pp 422ndash433 1999

[7] E J Luoga E T F Witkowski and K Balkwill ldquoLand coverand use changes in relation to the institutional frameworkand tenure of land and resources in eastern Tanzania Miombowoodlandsrdquo Environment Development and Sustainability vol7 no 1 pp 71ndash93 2005

[8] FAO The State of Food and Agriculture 2010-2011 Forest andAgriculture Organization Rome Italy 2010

[9] A H Gentry ldquoTropical forest biodiversity distributional pat-terns and their conservational significancerdquo Oikos vol 63 no1 pp 19ndash28 1992

[10] O E Sala F S Chapin III J J Armesto et al ldquoGlobalbiodiversity scenarios for the year 2100rdquo Science vol 287 no5459 pp 1770ndash1774 2000

[11] H J Geist and E F Lambin ldquoProximate causes and underlyingdriving forces of tropical deforestationrdquo BioScience vol 52 no2 pp 143ndash150 2002

[12] R S DeFries ldquoTropical forests deforestation and ecosystemsservices Contributions of remote sensingrdquo in GeoinformaticsFor Tropical Ecosystems P S Roy Ed pp 1ndash32 2003

[13] B M Campbell P Frost and N Bryon ldquoMiombo woodlandsand their use overview and key issuesrdquo in The Miombo inTransition Woodlands and Welfare in Africa B Campbell Edpp 1ndash10 2006

[14] H J Geist ldquoGlobal assessment of deforestation related totobacco farmingrdquo Tobacco Control vol 8 no 1 pp 18ndash28 1999

[15] J Sauer and J M Abdallah ldquoForest diversity tobacco produc-tion and resource management in Tanzaniardquo Forest Policy andEconomics vol 9 no 5 pp 421ndash439 2007

[16] E N Chidumayo and K J Mbata ldquoShifting cultivation ediblecaterpillars and livelihoods in the Kopa area of northernZambiardquo Forests Trees and Livelihoods vol 12 no 3 pp 175ndash1932002

[17] E N Chidumayo and L Kwibisa ldquoEffects of deforestation ongrass biomass and soil nutrient status in miombo woodlandZambiardquo Agriculture Ecosystems and Environment vol 96 no1ndash3 pp 97ndash105 2003

ISRN Biodiversity 15

[18] J F Lund and T Treue ldquoAre we getting there Evidence ofdecentralized forest management from the Tanzanian miombowoodlandsrdquoWorld Development vol 36 no 12 pp 2780ndash28002008

[19] T Blomley and S Iddi Participatory Forest Management inTanzania 1993ndash2009mdashLessons Learned and Experiences toDate Ministry of Natural Resources and Tourism Forestry andBeekeeping Division Dar es Salaam Tanzania 2009

[20] T Treue Y M Ngaga H Meilby et al ldquoDoes participatoryforest management promote sustainable forest utilisation inTanzaniardquo International Forestry Review vol 16 no 1 pp 1ndash162014

[21] Ministry ofNatural Resources andTourismParticipatory ForestManagement in Tanzania Facts and Figures Forestry andBeekeeping Division Dar es Salaam Tanzania 2008

[22] E N Chidumayo ldquoSpecies structure in Zambian miombowoodlandrdquo Journal of Tropical Ecology vol 3 no 2 pp 109ndash1181987

[23] J D Lowore ldquoCoppice regeneration in some miombo wood-lands of Malawirdquo FRIM Report 99001 Forestry ResearchInstitute of Malawi 1999

[24] E J Luoga E T F Witkowski and K Balkwill ldquoHarvestedand standing wood stocks in protected and communal miombowoodlands of eastern Tanzaniardquo Forest Ecology and Manage-ment vol 164 no 1ndash3 pp 15ndash30 2002

[25] M Williams C M Ryan R M Rees E Sambane J Fernandoand J Grace ldquoCarbon sequestration and biodiversity of re-growing miombo woodlands in Mozambiquerdquo Forest Ecologyand Management vol 254 no 2 pp 145ndash155 2008

[26] T Banda NMwangulango BMeyer et al ldquoThewoodland veg-etation of the Katavi-Rukwa ecosystem in western TanzaniardquoForest Ecology andManagement vol 255 no 8-9 pp 3382ndash33952008

[27] R A Giliba E K Boon C J Kayombo E B Musamba AM Kashindye and P F Shayo ldquoSpecies composition richnessand diversity in Miombo Woodland of Bereku Forest ReserveTanzaniardquo Journal of Biodiversity vol 2 no 1 pp 1ndash7 2011

[28] D D Shirima P K T Munishi S L Lewis et al ldquoCarbonstorage structure and composition of miombo woodlands inTanzaniarsquos Eastern Arc Mountainsrdquo African Journal of Ecologyvol 49 no 3 pp 332ndash342 2011

[29] P K T Munishi R A P C Temu and G Soka ldquoPlant com-munities and tree species associations in a Miombo ecosystemin the Lake Rukwa basin Southern Tanzania implications forconservationrdquo Journal of Ecology and Natural Environment vol3 no 2 pp 63ndash71 2011

[30] J Dewis and F Freitas ldquoPhysical analysis of soilsrdquo in Physicaland Chemical Methods of Soil andWater Analysis FAO Bulletinno 10 pp 51ndash57 2nd edition 1970

[31] S R Olsen and L E Sommers ldquoPhosphorusrdquo inMethods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 403ndash430 American Societyof Agronomy Madson Wis USA 1982

[32] J D Rhoades ldquoCation exchange capacityrdquo in Methods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 149ndash157 American Society ofAgronomy Madson Wis USA 1982

[33] IMatejovic ldquoDetermination of carbon hydrogen and nitrogenin soils by automated elemental analysis (dry combustionmethod)rdquo Communications in Soil Science and Plant Analysisvol 24 no 17-18 pp 2213ndash2222 1993

[34] J P Moslashberg Soil Analysis Manual Revised Edition Laboratoryof Soil Sciences Department of Soil Science SokoineUniversityof Agriculture Morogoro Tanzania 2001

[35] N C BradyThe Nature and Properties of Soils Macmillan 8thedition 1974

[36] C J Krebs Ecological Methodology Hamper Collins PublishersNew York NY USA 2nd edition 1999

[37] B Husch T W Beers and J A Kershaw Forest MensurationJohn Wiley amp Sons Hoboken NJ USA 4th edition 2003

[38] E E Mwakalukwa H Meilby and T Treue ldquoVolume andaboveground biomass models for dry Miombo Woodland inTanzaniardquo In press

[39] M Kent Vegetation Description and Analysis A PracticalApproach Wiley-Blackwell John Wiley amp Sons Hoboken NJUSA 2nd edition 2012

[40] B McCune and M J Mefford PC-ORD Multivariate Analysisof Ecological Data Version 6 MjM Software Gleneden BeachOre USA 2011

[41] MDufrene andP Legendre ldquoSpecies assemblages and indicatorspecies the need for a flexible asymmetrical approachrdquo EcologyMonography vol 67 pp 777ndash795 1997

[42] J E PeckMultivariate Analysis for Community Ecologists Step-by-Step using PC-ORD MjM Software Design Gleneden BeachOre USA 2010

[43] M A Njana Arborescent species diversity and stocking inMiombo Woodland of Urumwa forest reserve and their contri-bution to Livelihoods Tabora Tanzania [MS thesis] SokoineUniversity of Agriculture Morogoro Tanzania 2008

[44] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal no 200 pp 59ndash70 2004

[45] J Isango ldquoStand structure and tree species composition ofTanzania miombo woodlands a case study from miombowoodlands of community based forest management in Iringadistrictrdquo in MITMIOMBOmdashManagement of Indigenous TreeSpecies For EcosystemRestoration andWood Production in Semi-Arid Miombo Woodlands in Eastern Africa Proceedings ofthe 1st MITMIOMBO Project Workshop held in MorogoroTanzania 6th-12th February 2007 Working Papers of theFinnish Forest Research Institute no 50 pp 43ndash56 2007

[46] J R Landon Booker Tropical Soil Manual A Handbook ForSoil Survey and Agricultural Land Evaluation in the Tropics andSubtropics Longman Scientific amp Technical and John Wiley ampSons 1991

[47] R F Fisher and D Binkley Ecology and Management of ForestSoils John Wiley amp Sons 3rd edition 2000

[48] W A Rees ldquoPreliminary studies into bush utilization by Cattlein Zambiardquo Journal of Applied Ecology vol 11 pp 207ndash214 1974

[49] S M Philip Measuring Trees and Forests CAB InternationalWallingford UK 2nd edition 1994

[50] J D Lowore P G Abbot and M Werren ldquoStackwood volumeestimations formiombowoodlands inMalawirdquoCommonwealthForestry Review vol 73 no 3 pp 193ndash197 1994

[51] D Kubota T Masunaga Hermansah et al ldquoSoil environmentand tree species diversity in tropical rain forest West SumatraIndonesiardquo in Soils of Tropical Forest Ecosystems CharacteristicsEcology and Management A Schulte and D Ruhiyat Eds pp159ndash167 1998

[52] P K T Munishi T H Shear T Wentworth and R A PC Temu ldquoCompositional gradients of plant communities insubmontane rainforests of EasternTanzaniardquo Journal of TropicalForest Science vol 19 no 1 pp 35ndash45 2007

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

EcosystemsJournal of

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MeteorologyAdvances in

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Marine BiologyJournal of

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Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental Chemistry

Atmospheric SciencesInternational Journal of

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Waste ManagementJournal of

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International Journal of

Geophysics

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BiodiversityInternational Journal of

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OceanographyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

Page 3: Research Article Floristic Composition, Structure, and

ISRN Biodiversity 3

the ward of Kiwele The forest vegetation has been describedas dry Miombo woodland similar to the dry woodlandtype described from other countries such as Zimbabwe andMozambique [1] The forest is located in a relatively flat areaat an elevation of 850ndash1300 metres above sea level Theregion is characterised by distinct wet and dry seasons withalmost no rain in the four months of June-September andabout 80 of the annual precipitation falling in DecemberndashMarch Average rainfall data covering the last 50 years (1960ndash2010) were obtained from the meteorological station at Nduliairport which is located about 30 km from the forest andindicate that the area receives an average annual precipitation(mean plusmn standard error) of 617plusmn17mm (448ndash1085mm)Themean annual temperature is 198∘C and the average relativehumidities at 0600 and 1200GMT are 539 and 514respectively

The GVLFR is a production forest which is managedby the Mfyome village under a community-based forestmanagement (CBFM) arrangement established in 2002 com-pare above The primary economic activity in Mfyome issmallholder agriculture and the main economic uses of theforest are production of timber charcoal and firewood [20]The woodland is also used for grazing and is an importantsource of subsistence products such as firewood constructionmaterials fruit mushrooms wild vegetables and medicinalplants [18]

22 Vegetation Survey The field survey was conducted inJuly and August 2009 and involved establishment of a totalof 35 permanent nested circular sample plots distributedacross the entire forest Plots were established along transectlines and the distance between plots was approximately2 km (Figure 1) The radii of the nested circular plots were5m (00079 ha) 15m (00707 ha) and 20m (01257 ha) Thefollowing parameters were recorded within each of the 35plots within the 5m radius all small trees and shrubs(lt150 cm tall or ge150 cm but lt1 cm Dbh) were counted andtheir species were identified and medium-size trees andshrubs (ge1 cm Dbh but lt5 cm Dbh) were identified andmeasured with respect to diameter Within 15m radius thespecies were identified and the diameter was measured for alllarge trees and shrubs with Dbh ge5 cm Within 20m radiusall stumps of trees and shrubs were identified to specieslevel and measured for diameter 20 cm above ground Initialidentification of species for both standing treesshrubs andstumps relied on the knowledge of local botanists (usinglocal vernacular species names and features such as colorof the bark smell and leaves) and was later confirmed bybotanists from Tanzania Forest Research Institute (TAFORI)based at Lushoto Silviculture Research Station For speciesthat were difficult to identify in the field samples weretaken to the herbarium at Lushoto for reidentification Othermeasurements taken within the plots were geographicallocation (UTMcoordinates) and elevation (m) usingGPS andslope () using a Suunto clinometer

23 Soil Sampling Soil samples were collected from fivepoints which were located at the centre of the plot and 10mfrom the centre in the four cardinal directions (North East

South and West) At each point two samples were taken 0ndash15 cm and 15ndash30 cm below the surfaceThe five samples takenfrom each depth range were mixed in the field to obtain onecomposite sample per depth range and plot Thus 70 soilsamples (35 from each depth range) were collected from the35 plots In addition a soil core device with an inner diameterof 5 cm and a length of 5 cm was used for extracting soilbulk density samples from the centre of each plot and at eachdepth Hence a total of 70 samples were collected for bulkdensity determination

24 Laboratory Analyses In the laboratory all soil sam-ples were ground and passed through a 2mm sieve toremove stones and gravel Fine and coarse roots were alsoremoved Subsequently soil samples collected at 0ndash15 cmdepth were analysed for soil pH soil texture cation-exchangecapacity (CEC cmol(+)kg) available phosphorus (ppm)and exchangeable bases (Ca2+ Mg2+ and K+ cmol(+)kg)Samples from both depth ranges (0ndash15 and 15ndash30 cm) wereanalysed for percentages of organic carbon and total nitrogenStandard methods for soil analysis were used in order toobtain estimates for each of the mentioned variables that canbe compared with results reported in the literature [30ndash34]Soil pH was determined electrometrically using 10 g of soilsample diluted in 25mL distilled water that is using a 1 25ratio of soil to water Soil texture was determined by thehydrometer method and the textural classification was doneby the use of the soil texture triangle [35]

The Bray 1 method was used for the determination ofextractable P for acidic soils with pH less than 7 while theOlsen method was used for soils with pH above 7 (alkalinesoils) The ammonium acetate method at pH 7 was used indetermination ofCEC and by the use of an atomic absorptionspectrophotometer in a UNICAM 919 AA Spectrometer allexchangeable cations (Ca2+ Mg2+ and K+) were determinedSubsamples were finely ground into powder form (lt1mm) inan agate mortar and analyzed for total percentages of organicC and N by dry combustion (Dumas method) in a Leco CNS2000 analyzer [33] Samples for bulk density estimation wereoven-dried at 105∘C to constant weight and the weight wasrecorded (accuracy 001 g) The volume was calculated fromlength and cross-sectional area of the soil core and bulk den-sity was determined as dry weight (g) per unit volume (cm3)Most analyses were conducted at the Laboratory of ForestBiology Sokoine University of Agriculture (SUA) but C andN analyses were conducted at the Soil Science Laboratory attheDepartment of Forest andLandscape (nowDepartment ofGeosciences and Natural Resource Management) Universityof Copenhagen Denmark

25 Data Analysis Based on the data collected the followingmeasures were analysed species composition was expressedthrough species richness and diversity measures forest struc-ture was expressed through stem density basal area andvolume for plant communities species groups and diameterclasses Total species richness was computed as the totalnumber of species across all 35 plots Species diversity wascomputed using Shannonrsquos and Simpsonrsquos Diversity Indices

4 ISRN Biodiversity

[36]The volume of stumpswas calculated as cylinder volumewhile total volume for standing trees was calculated usinga regression equation developed for GVLFR by the authors[37 38] ln(V)= minus84554 + 23236 times ln(Dbh) (R2 = 0983RMSE = 0248 Dbh range 14ndash62 cm 119899 = 104) where V isvolume (m3tree) Dbh is diameter at breast height (ge1 cm)RMSE is the residual standard error R2 is the coefficientof determination n is the total sample size and ln is thenatural logarithmThe ImportanceValue Index (IVI) for eachspecies in each plot was calculated as the sum of relativedensity and dominance (basal area) and expressed in percent[39] Percentage base saturation (BS) was determined asthe ratio of total base cation concentration to CEC whilethe C N ratio was determined using the estimated elementalpercentages of carbon and nitrogen [35]

Using IVI for each species plots were classified byagglomerative hierarchical cluster analysis using Soslashrensenrsquosdistance measure and a group linkage method with flexible120573 of minus050 The 35 plots were ordinated by nonmetricmultidimensional scaling (NMS) using the PC ORDsoftwareversion 60 [40] Topographic variables (elevation and slope)and edaphic variables (pH bulk density texture extractableP CEC exchangeable base cations BS C N ratio Cand N) were correlated with the NMS ordination axesIndicatordominant species in each cluster were determinedusing percentage indicator values (IV) where values of 0correspond to no indication and 100 is perfect indication [4142] The first three to five names of these Indicatordominantspecies with the highest percentage indicator values (IV)constancy and significant indicator values (119875 lt 005) wereused to assign names to the clustersplant community types[29 41 42] The Steinhaus (SoslashrensenCzekanowski) coeffi-cient was used to assess the similaritydissimilarity of thespecies compositions of the plant communities [39]

3 Results

31 Species Richness Including all size categories a totalof 88 species (29 plant families) of standing trees andshrubssmall trees were identified in the GVLFR (Table 1)Trees contributed 60 (21 plant families) and shrubs 40(15 plant families) of the species For stumps a total of 42species (20 plant families) of trees and shrubssmall treeswith basal diameter ranging from 2 to 50 cm were identifiedFor stumps trees contributed 76 (13 plant families) of thespecies while shrubs contributed 24 (10 plant families)All species represented by stumps were also represented bystanding treesshrubs In general tree and shrub speciesfrom the family Caesalpiniaceae contributed most (13) tothe total number of species (standing individuals) followedby those from the families Mimosaceae (10) Rubiaceae(10) Fabaceae (9) and Euphorbiaceae (9) (Table 1)Among standing trees the greatest number of species wasfound in the four plant families Caesalpiniaceae (17)Mimosaceae (15) Fabaceae (13) and Combretaceae (9)while shrubssmall trees included most species from thefamilies Rubiaceae (26) Euphorbiaceae (17) and Cap-paraceae (9) For stumps tree and shrub species from

0 5 10 15 20 25 30 35

0

20

40

60

80

Sites

Spec

ies r

ichn

ess

Figure 2 Species accumulation curve for large individuals (Dbhge5 cm) measured within circular plots with a radius of 15m in theGangalamtumba VLFR Vertical lines indicate standard deviations(range 0ndash49)

the family Mimosaceae contributed most (17) to the totalnumber of species followed by species from the familiesCaesalpiniaceae (14) Combretaceae (10) and Fabaceae(7) Among species categorised as trees the families Cae-salpiniaceae (19) and Mimosaceae (19) contributed equalnumbers of species followed by Combretaceae (13) andFabaceae (9) With respect to shrubs each of the familieswas represented by a single species (10 see Table 1)

When considering different size categories and includingboth trees and shrubs (small sizes Dbhlt 5 cm and large sizesDbh ge 5 cm) a total of 78 species (28 families) were foundamong large sizes with Caesalpiniaceae (13) Mimosaceae(12) and Fabaceae (10) being the most species-rich plantfamilies while among small sizes a total of 69 species (27families) were observed with Rubiaceae (13) Caesalpini-aceae (12) andMimosaceae (10) contributing the greatestnumber of species (Table 1) In general the average number ofspecies per plot was found to be 14 species (range 5ndash24 speciesper plot)

The species accumulation curve (Figure 2) shows thatthe 35 sitesplots used in this study were sufficient to covermuch (but not all) of the variation and species diversity ofthe study area At 35 plots the graph has not yet reached itsasymptotic level but is starting to converge implying that anyfurther increase of sample size would be expected to lead toinclusion of additional rare species However although thesample size was small (35 plots) and does not quite capturethe full woody plant biodiversity of the reserve the results arestill useful for characterizing the treeshrub species diversityand relationships between species and site

32 Species Diversity Shannon-Wiener diversity indices forlarge and small individuals were found to be 344 and 326respectively and the Simpson index for large individuals was

ISRN Biodiversity 5

Table1Ch

ecklist

oftre

eand

shrubspeciesrecordedin

Gangalamtumba

VLF

Rshow

ingfre

quency

()density

(meanplusmnSE

)basalarea(meanplusmnSE

)dispersio

nindex(D

I)and

Impo

rtance

ValueInd

ex(IVI)bothforthe

currentp

opulationof

largeind

ividuals(plotsize=

15m

radiusm

inim

umDbh

=5c

m)a

ndforstumps

(plotsize=

20m

radiusm

inim

umbasald

iameter

=2c

m)SH

shrub

ST

smalltreeandT

tree

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

1Mgiha

Dalbergia

arbutifolia

Fabaceae

subfam

ilyPapilio

noideae

ST60

247plusmn69136plusmn037

224

4765

1468plusmn41006plusmn005

170

2Mtono

Commiphora

afric

ana

Burseraceae

T77

110plusmn23159plusmn037

175

1142

1414plusmn06001plusmn001

111

3Mlama

Combretum

molleG

Don

Com

bretaceae

T74

116plusmn27069plusmn015

132

1523

3468plusmn19005plusmn002

307

4Mku

ngugu

Acacia

sp

Mim

osaceae

T23

40plusmn22102plusmn054

111

2873

920plusmn14001plusmn001

65

5Mkw

eeBrachyste

gia

spiciform

isBe

nth

Caesalpiniaceae

T37

58plusmn20118plusmn034

110

1731

2661plusmn24020plusmn009

308

6Mkalala

Albiziapetersiana

(Belle)O

liv

Mim

osaceae

T40

80plusmn30055plusmn020

85

2711

636plusmn29005plusmn004

94

7Mlyasenga

Combretum

zeyheri

Soun

dCom

bretaceae

T43

60plusmn20030plusmn011

741597

2020plusmn08001plusmn001

47

8Mkombivawo

Bauh

iniapetersiana

Caesalpiniaceae

SH34

54plusmn21029plusmn010

64

2000

9Muguvani

Markham

iaobtusifolia

Bign

oniaceae

T60

65plusmn13038plusmn010

64

647

605plusmn03

00

23

10Mdeke

Hym

enodictyon

parvifoliu

mOliv

Rubiaceae

ST31

50plusmn24048plusmn024

58

2749

302plusmn02

00

17

11Mub

wegele

Sclerocarryabirrea

sbspbirr

eaAnacardiaceae

T34

21plusmn6061plusmn023

58

441

605plusmn03001plusmn001

28

12Mmem

enam

ene

Margaritaria

discoidea(Bail)

Euph

orbiaceae

SH51

68plusmn24032plusmn013

57

2073

307plusmn07

00

06

13Mkambala

Acaciamellifera

(Vahl)Be

nth

Mim

osaceae

T29

14plusmn5049plusmn019

50

359

302plusmn02

00

08

14Mugegere

Dich

rosta

chys

cinerea

(L)Wight

ampArn

Mim

osaceae

ST31

53plusmn26017plusmn009

47

3086

2959plusmn19003plusmn002

178

15Mbata

AcaciaseyalD

elvar

seyal

Mim

osaceae

T34

30plusmn10019plusmn006

45

887

311plusmn11001plusmn001

46

16Mgulumo

Lann

easchw

einfurthiiAnacardiaceae

T43

24plusmn7032plusmn009

39

544

907plusmn04002plusmn001

22

17Muyom

boBrachyste

giaboehmii

Caesalpiniaceae

T11

11plusmn7019plusmn015

38

1309

607plusmn05001plusmn001

22

18Mmulim

uli

Cassiaabbreviata

Caesalpiniaceae

T34

31plusmn13017plusmn007

36

1353

916plusmn12001plusmn001

49

19Mdavi

Cordiasin

ensis

Lam

Boraginaceae

ST6

23plusmn23011plusmn010

34

5498

302plusmn02

00

06

6 ISRN Biodiversity

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

20Mdw

endw

eTerm

inaliabrow

nii

Com

bretaceae

T17

14plusmn8019plusmn009

32

1129

305plusmn05

00

12

21Mfilafila

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T31

25plusmn8015plusmn005

30

646

605plusmn03

00

35

22Mkw

ata

Codyladensiflora

Caesalpiniaceae

T9

4plusmn2033plusmn019

28

282

334plusmn34004plusmn004

83

23Mgung

aAc

aciaabyssin

ica(H

ochst)

Mim

osaceae

T17

12plusmn7014plusmn007

24

1140

614plusmn12001plusmn001

39

24Mkole

Grew

iabicolor

Tiliaceae

ST26

21plusmn10008plusmn003

21

1078

605plusmn03

00

15

25Mparapand

eStrychnosp

otatorum

Lf

Loganiaceae

T23

23plusmn11014plusmn009

20

1331

607plusmn05

00

17

26Kitim

bwi

Orm

ocarpum

kirkii

Fabaceae

SH29

18plusmn6007plusmn003

19492

27Mtabagila

Lonchocarpus

capassa

Fabaceae

T26

11plusmn5014plusmn006

17550

302plusmn02

00

04

28Muw

otapon

ziOzoroainsig

nsssp

retic

ulata

Anacardiaceae

T14

10plusmn5010plusmn005

16564

1411plusmn05001plusmn000

31

29Msanzi

Gardeniaresin

iflua

Hiern

Rubiaceae

ST9

13plusmn8008plusmn005

161229

30Mkoga

Vitexpayos

Verbenaceae

ST17

12plusmn5011plusmn004

15605

302plusmn02

00

02

31Mpelem

eleGr

ewiaforbesiiHaw

Ex

Mast

Tiliaceae

ST14

16plusmn9005plusmn002

147

1246

32Mny

wenyw

eeDalbergiaboehmii

Fabaceae

T14

11plusmn7009plusmn007

151221

33Mulagavega

Albiziaam

ara(Roxb)

Boiv

Mim

osaceae

T14

9plusmn5004plusmn003

14712

34Mkola

Afzelia

quan

zensis

Caesalpiniaceae

T11

6plusmn3015plusmn009

14532

35Mugusi

Brachyste

giamanga

Caesalpiniaceae

T20

11plusmn6010plusmn007

13824

618plusmn13002plusmn002

25

36Mwaham

aShrebera

trichoclada

Oleaceae

T17

11plusmn6005plusmn002

12697

309plusmn09001plusmn001

15

37Mpingo

Dalbergia

mela

noxylon

Fabaceae

T11

11plusmn9004plusmn003

121655

314plusmn14001plusmn001

26

38Mub

aya

Strychnosinn

ocua

Loganiaceae

T17

8plusmn4011plusmn008

12375

302plusmn02001plusmn001

06

39Msisina

AlbiziaharveyiF

ournMim

osaceae

T14

5plusmn3008plusmn005

11359

305plusmn05002plusmn002

15

40Mlim

boEu

phorbiacuneata

Valh

Euph

orbiaceae

ST14

12plusmn6004plusmn002

11699

41Mwam

biElaeodendron

buchan

annii

Cela

steraceae

T3

8plusmn8003plusmn003

102000

42Mvembadand

aXe

roderris

stuhlmannii

Fabaceae

T14

4plusmn2011plusmn005

09

191

43Mtelela

Brachyste

giabu

ssei

Harms

Caesalpiniaceae

T6

2plusmn1012plusmn010

09

253

ISRN Biodiversity 7

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

44Mteresi

Prem

naholstiiGurke

Verbenaceae

ST9

8plusmn5003plusmn002

09

899

45Mkongolo

Commiphora

ugogensis

Burseraceae

T6

1plusmn1008plusmn006

08

097

302plusmn02001plusmn001

09

46Muw

isaBo

sciaangustifolia

A

Rich

varangustifo

liaCa

pparaceae

T17

8plusmn4004plusmn002

08

426

47Mnyalup

uko

Canthium

pseudoverticillatum

Hien

Rubiaceae

ST20

8plusmn4004plusmn002

07

414

48Mnyaluh

anga

Brideliascleu

roneura

MuellArg

Euph

orbiaceae

ST14

6plusmn3004plusmn002

07

341

49Mdide

Manilkaramochisia

(Bak)Dub

ard

Sapo

taceae

T9

5plusmn4002plusmn001

07

793

50Muh

emi

Erythrinaabyssin

icaFabaceae

T6

1plusmn1007plusmn006

07

163

51Msambarawe

Vangueria

infausta

BurchSspRo

tund

ataRu

biaceae

ST6

8plusmn5002plusmn002

06

925

52Mhehefu

Allophylu

sferrugineus

Taub

Sapind

aceae

SH9

5plusmn3002plusmn001

05

540

314plusmn14001plusmn001

14

53Mnyengrsquoenyengrsquoe

Excoecariabu

ssei

(Pax)

Euph

orbiaceae

ST11

4plusmn2001plusmn001

05

321

54Muganga

Berchemiadiscolor

Rham

naceae

T6

4plusmn3004plusmn003

04

717

55Mning

aPterocarpu

sangolensis

Fabaceae

T6

2plusmn1005plusmn004

04

253

309plusmn09006plusmn006

25

56Mtanang

we

Zizip

husm

ucronata

Rham

naceae

T3

4plusmn4003plusmn003

04

900

57Muh

ekele

Eucle

adivinorum

Hiern

Ebenaceae

ST3

3plusmn3001plusmn001

04

800

302plusmn02

00

49

58Mub

umila

Cassipourea

mollis

(REfr)Alstom

Rhizop

horaceae

T9

4plusmn3002plusmn001

04

526

302plusmn02

00

04

59Mkw

ambe

Flueggea

virosa

Willd

Euph

orbiaceae

SH6

3plusmn2003plusmn003

03

406

60Kivang

aZa

nhaafric

ana

(Radlk)Ex

ell

Sapind

aceae

T9

2plusmn1001plusmn001

02

212

302plusmn02

00

02

61Mning

amaji

Pterocarpu

stinctorius

Fabaceae

T3

0002plusmn002

02

100

62Mtosi

MaeruatriphyllaA

Rich

Capp

araceae

ST3

2plusmn2001plusmn001

02

600

63Mugosa

Ehretia

amoena

Boraginaceae

ST9

1plusmn1

00

01

094

64Mnyon

gamem

beStegan

otaenia

araliacea

Apiaceae

T6

1plusmn1

001

01

163

65Mvelevele

Vernoniaam

ygdalin

aAs

teraceae

SH3

2plusmn2001plusmn001

01

400

66Mpo

ngolo

Catunaregam

spinosa

(Thun

b)

Rubiaceae

ST3

1plusmn1001plusmn001

01

200

8 ISRN Biodiversity

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

67Mbo

liboli

Acaciadrepanolobium

(Harms)

Mim

osaceae

T3

000

01

100

68Mwim

akigulu

Maeruaangolen

sisCa

pparaceae

SH3

1plusmn1

00

01

300

69Mnyali

Tamarindu

sind

icaCa

esalpiniaceae

T6

1plusmn1001plusmn001

01

097

70Mgombw

ani

Combretum

aculeatum

Com

bretaceae

T6

1plusmn1

00

01

097

302plusmn02

00

04

71Msang

ala

Burkea

afric

anaHoo

kCa

esalpiniaceae

T3

0001plusmn001

01

100

302plusmn02

00

04

72Mkokonza

Opilia

amentacea

Roxb

Opiliaceae

SH3

000

00

100

311plusmn11

00

42

73Mfumbi

Kigelia

afric

ana

Bign

oniaceae

T3

000

00

100

74Mlang

ali

Euphorbia

cand

elabrum

Euph

orbiaceae

T3

000

00

100

75Mpu

lulu

Term

inaliaseric

eaCom

bretaceae

T3

000

00

100

76Mdaha

Diospyros

usam

barensisFWhite

Ebenaceae

T3

000

00

100

305plusmn05001plusmn001

15

77Mtund

wa

XimeniacaffraSond

Olacaceae

ST3

000

00

100

78Mwim

aperu

Tarenn

agla

veolens(S

Moo

re)B

rem

Rubiaceae

ST+

79Mwesa

Boscia

mossambicensisKl

Capp

araceae

ST+

80Musasam

ulo

Psychotria

schu

mmaniana

Rubiaceae

ST+

81Muh

anza

Senn

asin

gueana

Caesalpiniaceae

ST+

82Mtund

wahavi

Ximeniaam

erica

naOlacaceae

ST+

83Mtin

giligiti

Phyllanthu

sengler

iPax

Euph

orbiaceae

T+

84Msada

Vangueria

madagascarie

nsis

Gmel

Rubiaceae

ST+

85Mku

nung

uZa

nthoxylum

chalybeum

Rutaceae

T+

86Lu

kali

Croton

scheffleriP

axEu

phorbiaceae

SH+

87Kilim

andembw

eGardeniaternifolia

KSchu

mamp

Thon

nRu

biaceae

ST+

88MpelaM

buyu

Adan

soniadigitata

Bombacaceae

T++

Total(allspecies)

13511521plusmn5941355plusmn552

200

294

60plusmn30072plusmn049

200

+indicatesspecies

identifi

edam

ongsm

allerind

ividualswith

in5m

radius

plots(Dbhlt5c

m)and++

indicatesthata

largeind

ividualw

asidentifi

edwith

ina1

5-radius

plot

butw

asno

tincludedin

thea

nalyseso

fste

mdensitybasalareaand

volumea

sitw

asconsidered

anou

tlier

duetoits

tremendo

ussiz

e(Dbh

=340c

m)

ISRN Biodiversity 9

005 and that of small individuals was 006 The followingspecies were observed to have the greatest contributionsto the Shannon-Wiener diversity index of large individualsDalbergia arbutifolia (contributing 030) Combretum molle(020) Commiphora africana (019) Albizia petersiana (016)and Margaritaria discoidea (014) while for smaller ones thegreatest contributions were found for Brachystegia spiciformis(026) Dalbergia arbutifolia (024) Grewia forbesii (023)Margaritaria discoidea (020) and Dichrostachys cinerea(016) In terms of frequency of occurrence for standingindividuals (large sizes) Commiphora africana was the mostfrequent species (77 of plots) followed by Combretummolle (74) and Dalbergia arbutifolia (60) while for smallsizes Margaritaria discoidea (66) Markhamia obtusifolia(63) and Dalbergia arbutifolia (57) were the most fre-quent species The Importance Value Index (IVI) for largeindividuals (Dbh ge 5 cm) shows that Dalbergia arbutifolia(224) Commiphora africana (175) and Combretum molle(132) were the most important species among standingindividuals while Brachystegia spiciformis (308)Combretummolle (307) and Dichrostachys cinerea (178) appeared to bethe most important among harvested individuals (stumps)These species were also found to have higher frequencies thanany other harvested species observed in the GVLFR (Table 1)

33 Stem Density The total mean stem density for large indi-viduals with Dbh ge5 cm was 1521 plusmn 594 stemsha (Table 1)and that of small individuals with Dbh lt5 cm (includingindividuals with Dbh lt1 cm) was 14318 plusmn 6956 stemshaAmong large individuals the most abundant species wereDalbergia arbutifolia (162 of 1521 stemsha) Combretummolle (8) Commiphora africana (72) and Albizia peter-siana (53) Among small individuals the most abundantspecies were Brachystegia spiciformis (13 of 14318 stemsha)followed by Dalbergia arbutifolia (11) and Grewia forbesii(10) For stumps the overall mean density was 60 plusmn38 stemsha with Combretum molle (12) Dalbergia arbuti-folia (12) Brachystegia spiciformis (10) and Dichrostachyscinerea (10) contributing the most (Table 1) Generally thedistribution of standing trees to size classes showed the usualreverse J shape which was also approximately observed forstumps (Figure 3) However for stumps the density of stemsin the 1ndash10 cm diameter class was slightly lower than whatwould be expected if tree felling had been a random event

34 Basal Area For the GVLFR as a whole the meanbasal areas for large (ge5 cm Dbh) and small individuals(lt5 cm Dbh) were 1355 plusmn 552m2ha (Table 1 Figure 4)and 305 plusmn 002m2ha respectively The species contributingmost to the basal area of large individuals were Commiphoraafricana (12) Dalbergia arbutifolia (10) and Brachystegiaspiciformis (9) while those contributing most to the basalarea of smaller individuals were Dalbergia arbutifolia (16)Grewia forbesii (15) and Dichrostachys cinerea (13) Themean basal area for stumps was 072m2ha with Brachystegiaspiciformis contributing the greatest individual proportion(28) 41 species made up the rest (Figure 4)

60542

3335

530

113

28 24

346166

34

11

02

01

10

100

1000

10000

100000

Diameter classes (cm)

Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Stem

s (ha

minus1)

Figure 3 Density of standing trees ge1 cmDbh and stumps ge1 cm bydiameter class in Gangalamtumba VLFR (119899 = 35) NB logarithmicscale on vertical axis

744477

241

103041 055

014025 018

010004

001

01

1

10

Diameter classes (cm)Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Mea

n ba

sal a

rea (

m2

haminus1)

Figure 4 Distribution of basal area per hectare for standingtrees ge1 cm Dbh and stumps ge1 cm by diameter classes in theGangalamtumba VLFR (119899 = 35) NB logarithmic scale on verticalaxis

35 Volume The mean volumes for large (ge5 cm Dbh) andsmall individuals (lt5 cm Dbh) were 9217 plusmn 390m3ha and1257 plusmn 635m3ha respectively (not shown in tables) Thespecies contributing most to the volume of large individualswere Commiphora africana (12) Brachystegia spiciformis(10) Acacia sp (9) and Dalbergia arbutifolia (9) Forsmaller individuals the species that contributed most tovolume were Dalbergia arbutifolia (16) Grewia forbesii(14) and Dichrostachys cinerea (13) The mean remainingvolume of stumps was found to be 015 plusmn 01m3ha withBrachystegia spiciformis contributing the greatest individualpercentage (28) 41 species made up the rest

10 ISRN Biodiversity

36 Spatial Distribution Dispersion indices (DI) are pre-sented for individual species in Table 1 The dispersion indexvalues range from 094 indicating almost complete spatialrandomness or slight underdispersion to 5498 indicatingconsiderable overdispersion that is a patchy or clustereddistributionOut of 77 species excluding the single very largeAdansonia digitata that was considered an outlier 64 species(83) 9 species (12) and 4 species (5) were found tohave DI gt 1 DI = 1 and DI lt 1 respectively so the majorityof species are characterised by a patchy distribution acrossthe forest The species with the lowest estimated DI wasEhretia amoena (094) while the highest DI was estimated forCordia sinensis (5498)Themost abundant species includingDalbergia arbutifolia (DI = 4765) Combretum molle (DI =1523) and Commiphora africana (DI = 1142) are stronglyoverdispersed

37 Plant Communities and Species Association Four plantcommunities were identified through cluster analysis basedon the statistical significance (5) of the observed maximumindicator values (Table 2) Only two of these plant commu-nities were dominated by species from the family Caesalpini-aceae (Communities 1 and 24) The other two showed greatvariationoverlap between species of different plant families(Communities 3 and 5) The estimated Steinhaus similarityindices between pairs of plant communities varied from 32for Communities 1 and 3 and Communities 5 and 24 to 37for Communities 3 and 5 (not shown in tables)

The ordination diagram (Figure 5) shows that one topo-graphic and six edaphic variables appear to be associatedwiththe four plant communities and the species distribution inthe study area The strongest correlation with communitycomposition was observed for elevation followed by soilpH at 0ndash15 cm depth base cation Ca2+ at 0ndash15 cm depthpercent base saturation (BS) at 0ndash15 cm depth percent clayat 0ndash15 cm depth C N ratio at 15ndash30 cm depth and percentsand at 0ndash15 cm depth The base cations magnesium (Mg2+)and potassium (K+) were not directly correlated with thecommunity composition but since they are included in thebase saturation percentage they are indirectly related Plantcommunities were ordered along the second ordination axiswhich was positively correlated with pH15 (119903 = 071) Ca15(119903 = 069) BS (119903 = 065) andClay15 (119903 = 052) and negativelycorrelated with Sand15 (119903 = minus046) Axis 1 of the ordinationwas positively correlated with Elev (119903 = 085) and CNrat30(119903 = 051) As shown in Table 3 and indicated graphically inFigure 5 correlations between many of the edaphic variablesare strong particularly between pH15 Sand15 Clay15 Ca15and BS whereas correlation between topographic and mostedaphic variables is small and nonsignificant However thereis a significant negative correlation (119903 = minus042) between Elevand Sand15 indicating that sandy soils are mostly found atlower elevations

4 Discussion

41 Species Composition The results reported in this studyshow that the composition of the vegetation types found in

Elev

pH15Ca15

Sand15

Clay15

CNrat30

BS

Axis 1

Axis 2

Community 1Community 3

Community 5Community 24

Figure 5 Compositional gradients and plant communities in NMSordination of 35 vegetation plots for trees ge5 cm in GangalamtumbaVLFR Four plant communities are recognized (cf Table 2) Com-munity 1 = Brachystegia spiciformis Diplorynchus condylocarponand Lannea schweinfurthii woodland Community 3 = Dalbergiaarbutifolia Commiphora africana and Albizia petersianawoodlandCommunity 5 = Acacia sp Acacia abyssinica and Albizia amarawoodland and Community 24 = Bauhinia petersiana and Shreberatrichoclada woodland Elev elevation (m) CNrat30 C N ratio at15ndash30 cm depth Sand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm Ca15 = Ca2+ (cmol(+)kg) at 0ndash15 cm pH15 = soil pH at 0ndash15 cm BS base saturation at 0ndash15 cm

the GVLFR especially the dominance of species from thefamily Caesalpiniaceae agreed well with previous descrip-tions and classifications of plant communities commonlyfound in miombo woodlands [1] However the observeddominance based on IVI of the genera Dalbergia Com-miphora and Combretum contrasts with patterns usuallyconsidered common for miombo woodlands The frequencyof species in these genera was also high compared to otherspecies observed in the GVLFR (Table 1) Similar deviationsexist between the results obtained by Banda et al [26]in the Katavi-Rukwa ecosystem where they observed thatTerminalia and Combretum were the dominant genera andthe findings of Giliba et al [27] and Njana [43] whoboth noted the dominance of the two common miombogenera Brachystegia and Julbernardia However Combretumalso occurred in their study areas The results suggest thaton a larger spatial scale the species diversity of miombowoodlands is very high and that the three common generaBrachystegia Julbernadia and Isoberlinia are not alwaysdominant at the local scale

The species richness observed in the GVLFR compareswell with miombo community studies in other areas of drymiombo in Tanzania and elsewhere which receive an average

ISRN Biodiversity 11

Table2Plantcom

mun

itiesandspeciesa

ssociatio

nsin

thed

ryMiombo

woo

dlands

ofGangalamtumba

VLF

RCom

mun

itynu

mbers135and24

representthe

different

plantassociatio

ns

119899speciesnu

mbero

fspecies

(77in

total)with

Dbhge5c

mIV+

speciesind

icator

valuemeanplusmnstd

errorand

BAisbasalarea

Com

mun

ityAs

sociated

species

Family

Habit

IV+

()

Con

stancy

()119875value

Stem

sha

BA m2 ha

MeanDbh

Brachyste

giaspiciform

ismdashDiplorhynchus

cond

ylocarponmdashLa

nnea

schw

einfurthiiw

oodland

1(n s

pecies

=47

nplots=9)

Sitevariables(meanplusmnSE

)Elev

=1200plusmn20pH15

=644plusmn013C

a15=604plusmn128

Sand

15=721plusmn431C

lay15=137plusmn188Silt15

=142plusmn335C

Nrat30=135plusmn05andBS

=526plusmn65

Brachyste

gia

spiciform

isCa

esalpiniaceae

T820

100

000

02164plusmn59356plusmn077138plusmn07

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T759

89000

0866plusmn18044plusmn01382plusmn05

Lann

easchw

einfurthii

Anacardiaceae

T719

100

000

0449plusmn14072plusmn022126plusmn09

Bosciaangustifolia

Capp

araceae

T536

5600056

27plusmn12014plusmn00776plusmn06

Euphorbiacuneata

Euph

orbiaceae

ST428

4400200

42plusmn19012plusmn00665plusmn06

Other

species

mdashmdash

mdashmdash

mdash1075plusmn5741007plusmn647102plusmn03

Subtotal

1423plusmn174

1505plusmn178

109plusmn03

DalbergiaarbutifoliamdashCo

mmiphora

afric

anamdash

Albizia

petersiana

woo

dland

3(n

species=55n

plots=

16)Site

variables(meanplusmnSE

)Elev

=986plusmn19pH15

=648plusmn009C

a15=856plusmn109

Sand

15=767plusmn156C

lay15=135plusmn155Silt15

=97plusmn096C

Nrat30=106plusmn03andBS

=744plusmn44

Dalbergiaarbutifolia

Fabaceae

subfam

ilyPapilio

noideae

ST793

100

000

02500plusmn123263plusmn06477plusmn02

Commiphora

afric

ana

Burseraceae

T542

9400026

187plusmn40272plusmn064119plusmn06

Albiziapetersiana

Mim

osacea

T536

7500200

157plusmn57103plusmn04084plusmn02

Sclerocarryabirrea

Anacardiaceae

T504

6300186

40plusmn11128plusmn045168plusmn17

Other

species

mdashmdash

mdashmdash

mdash852plusmn449669plusmn37788plusmn03

Subtotal

1735plusmn166

1435plusmn071

92plusmn02

Acaciaspmdash

Acaciaabyssin

icamdash

Albiziaam

arawoo

dland

5(n

species=33n

plots=5)

Sitevariables(m

eanplusmnSE

)Elev

=986plusmn52pH15

=734plusmn023C

a15=139plusmn33

Sand

15=745plusmn678C

lay15=148plusmn47Silt15

=107plusmn26C

Nrat30=106plusmn07andBS

=963plusmn89

Acaciasp

Mim

osaceae

T981

100

000

02269plusmn111662plusmn286172plusmn14

Acaciaabyssin

icaMim

osaceae

T594

8000030

31plusmn9060plusmn03299plusmn08

Albiziaam

ara

Mim

osaceae

T552

60000

6654plusmn30023plusmn01671plusmn08

Grew

iabicolor

Tiliaceae

ST533

6000106

113plusmn52040plusmn01770plusmn04

Acaciaseyal

Mim

osaceae

T433

6000526

62plusmn34034plusmn01790plusmn05

Other

species

mdashmdash

mdashmdash

mdash665plusmn533552plusmn49872plusmn04

Subtotal

1194plusmn169

1367plusmn347

101plusmn05

Bauh

iniapetersiana

mdashShrebera

trichoclada

woo

dland

24(n

species=35n

plots=5)

Sitevariables(meanplusmnSE

)Elev

=1175plusmn25pH15

=73plusmn04C

a15=254plusmn69

Sand

15=522plusmn68C

lay15=331plusmn28

Silt15=147plusmn44C

Nrat30=961plusmn13andBS

=1041plusmn204

Bauh

iniapetersiana

Caesalpiniaceae

SH551

8000118192plusmn121111plusmn05075plusmn03

Shrebera

trichoclada

Oleaceae

T505

6000110

57plusmn32022plusmn01380plusmn05

Manilkaramochisia

Sapo

taceae

T376

4000332

34plusmn27014plusmn00969plusmn10

Dalbergia

mela

noxylon

Fabaceae

T370

4000380

68plusmn58026plusmn02266plusmn03

Ehretia

amoena

Boraginaceae

ST347

4000344

6plusmn4

002plusmn00170plusmn04

Other

species

mdashmdash

mdashmdash

mdash982plusmn759643plusmn47999plusmn05

Subtotal

1338plusmn137

817plusmn087

91plusmn04

Total

1521plusmn5941355plusmn55298plusmn01

Elevelevatio

n(m

)CN

rat30CN

ratio

at15ndash30c

mdepthSand

15sand(

)at0

ndash15c

mC

lay15clay

()at0

ndash15c

mSilt15silt

()at0

ndash15c

mC

a15Ca2+(cmol(+)kg)at0

ndash15c

mpH15soilp

Hat0ndash

15cm

BS

base

saturatio

nat0ndash

15cm

12 ISRN Biodiversity

Table 3 Pearson-correlation matrix for two topographic and eight edaphic variablesdagger associated with the classified plant communities in theGangalamtumba VLFR (119899 = 35) Applied significance levels lowast5 lowastlowast1 and lowastlowastlowast01 +not significant

Elev Slope pH15 Ca15 K15 N15 Sand15 Clay15 CNrat30Slope 019+

pH15 minus013+ minus033lowast

Ca15 002+ minus020+ 083lowastlowastlowast

K15 minus029+ 000+ 010+ 012+

N15 006+ 036lowast 010+ 041lowastlowast 033lowast

Sand15 minus042lowastlowast 003+ minus053lowastlowastlowast minus074lowastlowastlowast 006+ minus046lowastlowast

Clay15 031+ minus012+ 051lowastlowast 076lowastlowastlowast minus001+ 047lowastlowast minus086lowastlowastlowast

CNrat30 036lowast 010+ minus039lowast minus051lowastlowast minus015+ minus019+ 040lowast minus048lowastlowast

BS minus024+ minus017+ 084lowastlowastlowast 091lowastlowastlowast 015+ 037lowast minus058lowastlowastlowast 060lowastlowastlowast minus051lowastlowastdaggerElev elevation (m) pH15 soil pH at 0ndash15 cm Ca15 Ca2+ (cmol(+)kg) at 0ndash15 cm K15 K+ (cmol(+)kg) at 0ndash15 cm N15 N concentration at 0ndash15 cmSand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm CNrat30 C N ratio at 15ndash30 cm depth BS base saturation at 0ndash15 cm 119905-value was calculated as119905 = 119903radic(119899 minus 2)(1 minus 119903

2) where 119903 is the Pearson-correlation coefficient and 119899 is the total sample size

Table 4 Species richness observed in other studies from drymiombo woodlands

Plot size(ha)

Totalnumberof plots

Total samplearea(ha)

Total numberof species References

0071 70 495 82 [43]0071 80 565 110 [27]0071 133 940 229 [26]0071 247 1746 102 [44]004 40 160 81 [45]025 14 350 69 [25]01 2 020 40 [28]01 152 1520 92 genera [22]0071 35 247 88 This study

annual rainfall of 565ndash1500mm (Table 4) Using plot sizes of004ndash025 ha and sample sizes of 2ndash247 plots a total numberof species ranging from40 (Dbhge 10 cm) to 229 (Dbhge 2 cm)have been reported fromMiombowoodlands [22 25ndash28 43ndash45]

The high number of species reported by Banda et al [26]Chidumayo [22] Isango [45] and Chamshama et al [44] islikely to be a consequence of the spatial scale and coverage ofthese studies as they all cover large areas include more thanone site and operate with large sample sizes For exampleChidumayo [22] included species from both wet and dryMiombo areas in Zambia The study by Sauer and Abdallah[15] who reported a total of 131 species occurring in thetobacco growing zone of Iringa rural district included twoforest reserves and three family-managed forests Thereforeconsidering the climatic conditions in the GVLFR (617mmof rainfall per year) and the sample size (35 plots) thespecies richness reported in this study can be ranked atleast as high or higher than those found in the studiesmentioned The selective sampling approach focusing onvarious microhabitat types adopted by Banda et al [26] mayhave contributed to the large number of species observed

in their study area Similarly the higher number of speciesfound by Giliba et al [27] was probably due to the presenceof riverine forest offering site conditions favourable formanyspecies

The values of the Shannon-Wiener (1198671015840 = 344) andSimpson indices (119863 = 005) reported for large individ-uals in this study are within the range observed for mostcommunities of particular life forms [36] For example 1198671015840usually does not exceed 5 although this maximum valuevaries depending on the type of the biological communitysampled and the sampling approach applied (eg minimumdiameter and size of sample units) A threshold value of 2 for1198671015840 has been mentioned as a minimum value above which

an ecosystem can be regarded as medium to highly diverse[27] Chamshama et al [44] reported three 1198671015840 values of31 32 and 33 from Kitulangalo Miombo forest in EasternTanzania while Njana [43] reported a 1198671015840 value of 340from dry Miombo forest in Western Tanzania The studiesby Sauer and Abdallah [15] and Giliba et al [27] reportedparticularly high values of 346 and 427 respectively Thiscould be attributed to the very large sample sizes used inboth studies and the presence of riverine forest where thechance of encountering many rare species is likely to be highThe forests examined in the mentioned studies receive anaverage annual rainfall of 700ndash1000mm compared to whichthe rainfall in the GVLFR is low (617mm on average per yearcf above)The relatively high diversity found inGVLFRmusttherefore be attributed to other factors than climate The soilanalyses indicate that the soil fertility level in the GVLFRis relatively high with considerable proportions of all 2 1lattice clay minerals (114) (ie illite montmorillonite andvermiculite) plus a good amount of organic matter whichmay suggest that the soil has large reserves of important plantnutrients for example K Mg and Fe The base saturationpercentage (BS) which is normally used to indicate the soilfertility status (Landon 1991) was also high 76 on averageand with 86 of the samples (30 samples) with BS valuesgt50 (fertile soil) and only 14 of the samples (5 samples)with BS below 50 (less fertile soil) As another indicationof high soil fertility status the mean C N ratio was 12 plusmn 043

ISRN Biodiversity 13

(range 7ndash19) for top soil (0ndash15 cm) and 11 plusmn 036 (range 5ndash16) for subsoil (15ndash30 cm) In general the values for both soilstrata fall within the expected range of 8ndash17 Soil pH values(mean 67 plusmn 01 range 567ndash852)were alsowithin the optimalrangewhere all the nutrients that aremost important for plantgrowth (Ca Mg K and P) are available and accessible toplants [46] In this study 97 of the soil samples had pHbelow 8 (one sample had a pH of 852) Fisher and Binkley[47] noted that high pH is almost never a problem in forestsas most trees do well across the full range of common pHvaluesTherefore considering the low average annual rainfallcompared to other forests the relatively high fertility of theGVLFR may be the main factor creating an environmentfavourable to many species thus leading to a quite highspecies diversity observed in this forest

Based on the Importance Value Index Brachystegia spi-ciformis and Combretum molle appeared to be the mostimportant species among harvested trees (stumps) in thestudy area This result agreed very well with the large valuesof basal area and volume and the information obtained fromlocal scouts and members of the village environmental com-mittee who said that the most frequently harvested speciesfor charcoal making include all Brachystegia species found inthe forest (ie Brachystegia spiciformis Brachystegia mangaBrachystegia boehmii and Brachystegia bussei) Among theCombretum species the most important one (based on IVI)Combretum molle is mostly used for house construction andfirewood rather than for charcoal making Apart from theBrachystegia species the only other species mentioned asimportant for charcoal making was Acacia mellifera Otherspecies are only used in case they happen to fall when fellingthe preferred species during the preparation of charcoal kilnsWith respect to stumps Brachystegia spiciformis Brachystegiamanga and Combretum molle are among the ten mostabundant species in terms of density basal area and volumeper hectare Stumps of the other species mentioned are notcommonly found a factwhichmay be due to the small samplesize being unable to capture sites where these species areharvested but may also be related to their limited distributionin the forest as indicated by the estimated dispersion indices(see Table 1)

42 Forest Structure Species densities reported from otherMiombo woodland areas in Tanzania are typically 348ndash1495stemsha for trees with Dbh gt4 cm [24 43 45] Comparedwith this the GVLFR is highly stocked as the estimateddensity is 2296 stemsha for trees with Dbh gt4 cmThemeanstem density of 1521 plusmn 594ha for trees with Dbh ge5 cmis also more than twice as large as values found in otherstudies [25ndash27 44 45 48] A similar pattern is seen whencomparing the density of regeneration between the studiesThe diameter distribution is characterised by a very cleartrend of decreasing stem density with increasing diameterThe shape of the distribution is thus an inverted ldquoJrdquo (Figure 3)which is a common feature of natural forests with activeregeneration and recruitment [49] However not many largetrees were captured by the sample whereas a considerablenumber of relatively large stumps were observed suggestingthat anthropogenic activities such as charcoal making may

have affected the structure and ecological balance of the forest(see Figure 3) Since the woodlands are often hit by fire whichtends to kill the seedlings (especially the late fires) and thusonly few seedlings can be expected to reach larger diameterclasses lack of mature trees and the resulting lack of seedsmay eventually threaten the biodiversity of the forest

The mean basal area of 1355 plusmn 552m2ha observedin this study is slightly above the range of values typicallyreported from the miombo region 75ndash126m2ha [26 28 4344 50] However the basal areas reported by Isango [45] werea bit higher (1504ndash1563m2ha) than observed in this study

Themean total volume inGVLFRwas estimated at 9217plusmn390m3ha for trees with Dbh ge5 cm Other studies in dryMiombo woodlands have reported mean volumes of 167ndash7603m3ha [24 44 45 50] The current standing volume ofGVLFR is thus slightly higher than values typically reportedfor forests in the Miombo ecoregion A plausible reason forthis may be that compared to other forests the GVLFR isstill well stocked despite ongoing human activities such ascharcoalmakingThebasal area observed for stumpswas only072m2ha so there is no indication of intensive extractionover many years This corresponds well with the findings ofTreue et al [20] who conclude that the estimated 04m3haannual extraction of woody biomass from GVLFR is consid-erably below its estimated annual increment of 15m3ha andthat the local forest managers seem capable of regulating theharvesting activities which in addition to village membersrsquocollection for subsistence uses also included commercialcharcoal production by external companies that pay a fee perbag of charcoal extracted to the village government

43 Plant Communities and Species Associations Except forBrachystegia spiciformis the majority of the Brachystegia andJulbernardia species that are common to miombo wood-lands elsewhere are not among the species most commonlyobserved in this study A similar pattern was observed byBanda et al [26] in the Katavi-Rukwa ecosystem wherethe genera that are most common in miombo woodlandsBrachystegia Julbernardia and Isoberlinia were not commonin their study sites Furthermore the four plant communi-ties distinguished in this study are comparable with thosereported by other studies in Tanzania including the work byMunishi et al [29] in theMiombowoodlands of Rukwa basinChunya district Tanzania and the study by Banda et al [26]in the Katavi-Rukwa ecosystem

Elevation was noted by Munishi et al [29] to be themost important factor shaping the species communities intheir study area This study found a similar pattern with thehighest coefficient of correlation observed for elevation sug-gesting that topographical variation is among the strongestdeterminants of community composition in dry Miombowoodlands hence influencing the spatial distribution ofspecies strongly However in our study area edaphic factorsalso influenced the species distribution directly Two plantcommunities occurredmainly on clayey soils with high pH atintermediate elevations one on sandy soils with lowpHat lowelevations and one on sandy-clayey soils at higher elevationsand with neutral soil pH (Figure 5) Specifically it appeared

14 ISRN Biodiversity

that the Acacia woodland category (Community 5) grows atlow elevations around temporary streams (or at least wherethe ground water table is relatively high) and the Bauhiniawoodland category (Community 24) appearsmostly in placeswith a relatively high percentage of clay (and therefore highvalues of pH Ca and BS) By contrast it appeared that theDalbergia woodland category (Community 3) is located atmore sandy sites (with low values of pH Ca and BS) andthe Brachystegia woodland category (Community 1) seemedto be located mostly at higher elevations where the CN-ratio is quite high Correlations between elevation and thebasic soil variables pH Ca and percentages of sand andclay were low (cf Figure 5) Thus the results indicate thatthe plant communities of the dry miombo woodlands inGVLFR are not only shaped by the topographic variation(elevation) and the groundwater level but also by basic soilcharacteristics The results thus confirm findings from otherstudies detecting effects of elevation and soil characteristicson species composition [51 52]

5 Conclusion

Considering that the sample size used in this study wassmaller than samples used in other studies in dry miombowoodlands the results show that the species diversity inGVLFR is relatively high compared to other forest reservesThe vegetation of GVLFR is characterised by high densitybasal area and volume and despite the scarcity of largediameter trees this indicates that the forest is in a goodcondition The effect of anthropogenic activities is neverthe-less evident and stresses the need for proper managementespecially for economically important species preferred forcharcoalmaking (egBrachystegia spiciformis) if the currentspecies diversity is to be maintained or enhanced A repeatedfuture study would be needed to assess whether the currentcommunity-based management regime yields this intendedoutcome but the available information and analyses allow forsome optimism in this respect

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors wish to thank people from Mfyome villagefor their invaluable assistance during field work Mzee IddiKaheya Damian Chotamasege AugustinoMkwama Libera-tus Simime and Mawazo Nyangwa Furthermore thanks aredue to Venancia Mlelwa from Sokoine University and MadsMadsen Krag from University of Copenhagen for doing thelaboratory work The authors also wish to thank GoodluckMoshi their driverMarcoNjana andNassoroHMagogo theTAFORI botanist for assisting with species identification andKlaus Dons for preparing a study site map Financial supportwas provided by Danida through the ENRECA Project

ldquoParticipatory forest management for rural livelihoods forestconservation and good governance in Tanzaniardquo (no 725)

References

[1] P G H Frost ldquoThe Ecology of Miombo Woodlandsrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 11ndash57 1996

[2] N Burgess J Hales E Underwood et al Terrestrial Ecoregionsof Africa and Madagascar A Conservation Assessment IslandPress World Wildlife Fund 2004

[3] J Clarke W Cavendish and C Coote ldquoRural householdsand miombo woodlands use value and managementrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 101ndash135 1996

[4] B M Campbell A Angelsen A Cunningham Y KaterereA Sitoe and S Wunder ldquoMiombo woodlandsmdashopportunitiesand barriers to sustainable forest managementrdquo httpsener-gypediainfoimages66dMiombo2007pdf

[5] S Syampungani P W Chirwa F K Akinnifesi G Sileshi andO C Ajayi ldquoTheMiombo woodlands at the cross roads poten-tial threats sustainable livelihoods policy gaps and challengesrdquoNatural Resources Forum vol 33 no 2 pp 150ndash159 2009

[6] J I O Abbot and K Homewood ldquoA history of change causesof miombo woodland decline in a protected area in MalawirdquoJournal of Applied Ecology vol 36 no 3 pp 422ndash433 1999

[7] E J Luoga E T F Witkowski and K Balkwill ldquoLand coverand use changes in relation to the institutional frameworkand tenure of land and resources in eastern Tanzania Miombowoodlandsrdquo Environment Development and Sustainability vol7 no 1 pp 71ndash93 2005

[8] FAO The State of Food and Agriculture 2010-2011 Forest andAgriculture Organization Rome Italy 2010

[9] A H Gentry ldquoTropical forest biodiversity distributional pat-terns and their conservational significancerdquo Oikos vol 63 no1 pp 19ndash28 1992

[10] O E Sala F S Chapin III J J Armesto et al ldquoGlobalbiodiversity scenarios for the year 2100rdquo Science vol 287 no5459 pp 1770ndash1774 2000

[11] H J Geist and E F Lambin ldquoProximate causes and underlyingdriving forces of tropical deforestationrdquo BioScience vol 52 no2 pp 143ndash150 2002

[12] R S DeFries ldquoTropical forests deforestation and ecosystemsservices Contributions of remote sensingrdquo in GeoinformaticsFor Tropical Ecosystems P S Roy Ed pp 1ndash32 2003

[13] B M Campbell P Frost and N Bryon ldquoMiombo woodlandsand their use overview and key issuesrdquo in The Miombo inTransition Woodlands and Welfare in Africa B Campbell Edpp 1ndash10 2006

[14] H J Geist ldquoGlobal assessment of deforestation related totobacco farmingrdquo Tobacco Control vol 8 no 1 pp 18ndash28 1999

[15] J Sauer and J M Abdallah ldquoForest diversity tobacco produc-tion and resource management in Tanzaniardquo Forest Policy andEconomics vol 9 no 5 pp 421ndash439 2007

[16] E N Chidumayo and K J Mbata ldquoShifting cultivation ediblecaterpillars and livelihoods in the Kopa area of northernZambiardquo Forests Trees and Livelihoods vol 12 no 3 pp 175ndash1932002

[17] E N Chidumayo and L Kwibisa ldquoEffects of deforestation ongrass biomass and soil nutrient status in miombo woodlandZambiardquo Agriculture Ecosystems and Environment vol 96 no1ndash3 pp 97ndash105 2003

ISRN Biodiversity 15

[18] J F Lund and T Treue ldquoAre we getting there Evidence ofdecentralized forest management from the Tanzanian miombowoodlandsrdquoWorld Development vol 36 no 12 pp 2780ndash28002008

[19] T Blomley and S Iddi Participatory Forest Management inTanzania 1993ndash2009mdashLessons Learned and Experiences toDate Ministry of Natural Resources and Tourism Forestry andBeekeeping Division Dar es Salaam Tanzania 2009

[20] T Treue Y M Ngaga H Meilby et al ldquoDoes participatoryforest management promote sustainable forest utilisation inTanzaniardquo International Forestry Review vol 16 no 1 pp 1ndash162014

[21] Ministry ofNatural Resources andTourismParticipatory ForestManagement in Tanzania Facts and Figures Forestry andBeekeeping Division Dar es Salaam Tanzania 2008

[22] E N Chidumayo ldquoSpecies structure in Zambian miombowoodlandrdquo Journal of Tropical Ecology vol 3 no 2 pp 109ndash1181987

[23] J D Lowore ldquoCoppice regeneration in some miombo wood-lands of Malawirdquo FRIM Report 99001 Forestry ResearchInstitute of Malawi 1999

[24] E J Luoga E T F Witkowski and K Balkwill ldquoHarvestedand standing wood stocks in protected and communal miombowoodlands of eastern Tanzaniardquo Forest Ecology and Manage-ment vol 164 no 1ndash3 pp 15ndash30 2002

[25] M Williams C M Ryan R M Rees E Sambane J Fernandoand J Grace ldquoCarbon sequestration and biodiversity of re-growing miombo woodlands in Mozambiquerdquo Forest Ecologyand Management vol 254 no 2 pp 145ndash155 2008

[26] T Banda NMwangulango BMeyer et al ldquoThewoodland veg-etation of the Katavi-Rukwa ecosystem in western TanzaniardquoForest Ecology andManagement vol 255 no 8-9 pp 3382ndash33952008

[27] R A Giliba E K Boon C J Kayombo E B Musamba AM Kashindye and P F Shayo ldquoSpecies composition richnessand diversity in Miombo Woodland of Bereku Forest ReserveTanzaniardquo Journal of Biodiversity vol 2 no 1 pp 1ndash7 2011

[28] D D Shirima P K T Munishi S L Lewis et al ldquoCarbonstorage structure and composition of miombo woodlands inTanzaniarsquos Eastern Arc Mountainsrdquo African Journal of Ecologyvol 49 no 3 pp 332ndash342 2011

[29] P K T Munishi R A P C Temu and G Soka ldquoPlant com-munities and tree species associations in a Miombo ecosystemin the Lake Rukwa basin Southern Tanzania implications forconservationrdquo Journal of Ecology and Natural Environment vol3 no 2 pp 63ndash71 2011

[30] J Dewis and F Freitas ldquoPhysical analysis of soilsrdquo in Physicaland Chemical Methods of Soil andWater Analysis FAO Bulletinno 10 pp 51ndash57 2nd edition 1970

[31] S R Olsen and L E Sommers ldquoPhosphorusrdquo inMethods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 403ndash430 American Societyof Agronomy Madson Wis USA 1982

[32] J D Rhoades ldquoCation exchange capacityrdquo in Methods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 149ndash157 American Society ofAgronomy Madson Wis USA 1982

[33] IMatejovic ldquoDetermination of carbon hydrogen and nitrogenin soils by automated elemental analysis (dry combustionmethod)rdquo Communications in Soil Science and Plant Analysisvol 24 no 17-18 pp 2213ndash2222 1993

[34] J P Moslashberg Soil Analysis Manual Revised Edition Laboratoryof Soil Sciences Department of Soil Science SokoineUniversityof Agriculture Morogoro Tanzania 2001

[35] N C BradyThe Nature and Properties of Soils Macmillan 8thedition 1974

[36] C J Krebs Ecological Methodology Hamper Collins PublishersNew York NY USA 2nd edition 1999

[37] B Husch T W Beers and J A Kershaw Forest MensurationJohn Wiley amp Sons Hoboken NJ USA 4th edition 2003

[38] E E Mwakalukwa H Meilby and T Treue ldquoVolume andaboveground biomass models for dry Miombo Woodland inTanzaniardquo In press

[39] M Kent Vegetation Description and Analysis A PracticalApproach Wiley-Blackwell John Wiley amp Sons Hoboken NJUSA 2nd edition 2012

[40] B McCune and M J Mefford PC-ORD Multivariate Analysisof Ecological Data Version 6 MjM Software Gleneden BeachOre USA 2011

[41] MDufrene andP Legendre ldquoSpecies assemblages and indicatorspecies the need for a flexible asymmetrical approachrdquo EcologyMonography vol 67 pp 777ndash795 1997

[42] J E PeckMultivariate Analysis for Community Ecologists Step-by-Step using PC-ORD MjM Software Design Gleneden BeachOre USA 2010

[43] M A Njana Arborescent species diversity and stocking inMiombo Woodland of Urumwa forest reserve and their contri-bution to Livelihoods Tabora Tanzania [MS thesis] SokoineUniversity of Agriculture Morogoro Tanzania 2008

[44] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal no 200 pp 59ndash70 2004

[45] J Isango ldquoStand structure and tree species composition ofTanzania miombo woodlands a case study from miombowoodlands of community based forest management in Iringadistrictrdquo in MITMIOMBOmdashManagement of Indigenous TreeSpecies For EcosystemRestoration andWood Production in Semi-Arid Miombo Woodlands in Eastern Africa Proceedings ofthe 1st MITMIOMBO Project Workshop held in MorogoroTanzania 6th-12th February 2007 Working Papers of theFinnish Forest Research Institute no 50 pp 43ndash56 2007

[46] J R Landon Booker Tropical Soil Manual A Handbook ForSoil Survey and Agricultural Land Evaluation in the Tropics andSubtropics Longman Scientific amp Technical and John Wiley ampSons 1991

[47] R F Fisher and D Binkley Ecology and Management of ForestSoils John Wiley amp Sons 3rd edition 2000

[48] W A Rees ldquoPreliminary studies into bush utilization by Cattlein Zambiardquo Journal of Applied Ecology vol 11 pp 207ndash214 1974

[49] S M Philip Measuring Trees and Forests CAB InternationalWallingford UK 2nd edition 1994

[50] J D Lowore P G Abbot and M Werren ldquoStackwood volumeestimations formiombowoodlands inMalawirdquoCommonwealthForestry Review vol 73 no 3 pp 193ndash197 1994

[51] D Kubota T Masunaga Hermansah et al ldquoSoil environmentand tree species diversity in tropical rain forest West SumatraIndonesiardquo in Soils of Tropical Forest Ecosystems CharacteristicsEcology and Management A Schulte and D Ruhiyat Eds pp159ndash167 1998

[52] P K T Munishi T H Shear T Wentworth and R A PC Temu ldquoCompositional gradients of plant communities insubmontane rainforests of EasternTanzaniardquo Journal of TropicalForest Science vol 19 no 1 pp 35ndash45 2007

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

EcosystemsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MeteorologyAdvances in

EcologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Marine BiologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental Chemistry

Atmospheric SciencesInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Geological ResearchJournal of

EarthquakesJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BiodiversityInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

Page 4: Research Article Floristic Composition, Structure, and

4 ISRN Biodiversity

[36]The volume of stumpswas calculated as cylinder volumewhile total volume for standing trees was calculated usinga regression equation developed for GVLFR by the authors[37 38] ln(V)= minus84554 + 23236 times ln(Dbh) (R2 = 0983RMSE = 0248 Dbh range 14ndash62 cm 119899 = 104) where V isvolume (m3tree) Dbh is diameter at breast height (ge1 cm)RMSE is the residual standard error R2 is the coefficientof determination n is the total sample size and ln is thenatural logarithmThe ImportanceValue Index (IVI) for eachspecies in each plot was calculated as the sum of relativedensity and dominance (basal area) and expressed in percent[39] Percentage base saturation (BS) was determined asthe ratio of total base cation concentration to CEC whilethe C N ratio was determined using the estimated elementalpercentages of carbon and nitrogen [35]

Using IVI for each species plots were classified byagglomerative hierarchical cluster analysis using Soslashrensenrsquosdistance measure and a group linkage method with flexible120573 of minus050 The 35 plots were ordinated by nonmetricmultidimensional scaling (NMS) using the PC ORDsoftwareversion 60 [40] Topographic variables (elevation and slope)and edaphic variables (pH bulk density texture extractableP CEC exchangeable base cations BS C N ratio Cand N) were correlated with the NMS ordination axesIndicatordominant species in each cluster were determinedusing percentage indicator values (IV) where values of 0correspond to no indication and 100 is perfect indication [4142] The first three to five names of these Indicatordominantspecies with the highest percentage indicator values (IV)constancy and significant indicator values (119875 lt 005) wereused to assign names to the clustersplant community types[29 41 42] The Steinhaus (SoslashrensenCzekanowski) coeffi-cient was used to assess the similaritydissimilarity of thespecies compositions of the plant communities [39]

3 Results

31 Species Richness Including all size categories a totalof 88 species (29 plant families) of standing trees andshrubssmall trees were identified in the GVLFR (Table 1)Trees contributed 60 (21 plant families) and shrubs 40(15 plant families) of the species For stumps a total of 42species (20 plant families) of trees and shrubssmall treeswith basal diameter ranging from 2 to 50 cm were identifiedFor stumps trees contributed 76 (13 plant families) of thespecies while shrubs contributed 24 (10 plant families)All species represented by stumps were also represented bystanding treesshrubs In general tree and shrub speciesfrom the family Caesalpiniaceae contributed most (13) tothe total number of species (standing individuals) followedby those from the families Mimosaceae (10) Rubiaceae(10) Fabaceae (9) and Euphorbiaceae (9) (Table 1)Among standing trees the greatest number of species wasfound in the four plant families Caesalpiniaceae (17)Mimosaceae (15) Fabaceae (13) and Combretaceae (9)while shrubssmall trees included most species from thefamilies Rubiaceae (26) Euphorbiaceae (17) and Cap-paraceae (9) For stumps tree and shrub species from

0 5 10 15 20 25 30 35

0

20

40

60

80

Sites

Spec

ies r

ichn

ess

Figure 2 Species accumulation curve for large individuals (Dbhge5 cm) measured within circular plots with a radius of 15m in theGangalamtumba VLFR Vertical lines indicate standard deviations(range 0ndash49)

the family Mimosaceae contributed most (17) to the totalnumber of species followed by species from the familiesCaesalpiniaceae (14) Combretaceae (10) and Fabaceae(7) Among species categorised as trees the families Cae-salpiniaceae (19) and Mimosaceae (19) contributed equalnumbers of species followed by Combretaceae (13) andFabaceae (9) With respect to shrubs each of the familieswas represented by a single species (10 see Table 1)

When considering different size categories and includingboth trees and shrubs (small sizes Dbhlt 5 cm and large sizesDbh ge 5 cm) a total of 78 species (28 families) were foundamong large sizes with Caesalpiniaceae (13) Mimosaceae(12) and Fabaceae (10) being the most species-rich plantfamilies while among small sizes a total of 69 species (27families) were observed with Rubiaceae (13) Caesalpini-aceae (12) andMimosaceae (10) contributing the greatestnumber of species (Table 1) In general the average number ofspecies per plot was found to be 14 species (range 5ndash24 speciesper plot)

The species accumulation curve (Figure 2) shows thatthe 35 sitesplots used in this study were sufficient to covermuch (but not all) of the variation and species diversity ofthe study area At 35 plots the graph has not yet reached itsasymptotic level but is starting to converge implying that anyfurther increase of sample size would be expected to lead toinclusion of additional rare species However although thesample size was small (35 plots) and does not quite capturethe full woody plant biodiversity of the reserve the results arestill useful for characterizing the treeshrub species diversityand relationships between species and site

32 Species Diversity Shannon-Wiener diversity indices forlarge and small individuals were found to be 344 and 326respectively and the Simpson index for large individuals was

ISRN Biodiversity 5

Table1Ch

ecklist

oftre

eand

shrubspeciesrecordedin

Gangalamtumba

VLF

Rshow

ingfre

quency

()density

(meanplusmnSE

)basalarea(meanplusmnSE

)dispersio

nindex(D

I)and

Impo

rtance

ValueInd

ex(IVI)bothforthe

currentp

opulationof

largeind

ividuals(plotsize=

15m

radiusm

inim

umDbh

=5c

m)a

ndforstumps

(plotsize=

20m

radiusm

inim

umbasald

iameter

=2c

m)SH

shrub

ST

smalltreeandT

tree

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

1Mgiha

Dalbergia

arbutifolia

Fabaceae

subfam

ilyPapilio

noideae

ST60

247plusmn69136plusmn037

224

4765

1468plusmn41006plusmn005

170

2Mtono

Commiphora

afric

ana

Burseraceae

T77

110plusmn23159plusmn037

175

1142

1414plusmn06001plusmn001

111

3Mlama

Combretum

molleG

Don

Com

bretaceae

T74

116plusmn27069plusmn015

132

1523

3468plusmn19005plusmn002

307

4Mku

ngugu

Acacia

sp

Mim

osaceae

T23

40plusmn22102plusmn054

111

2873

920plusmn14001plusmn001

65

5Mkw

eeBrachyste

gia

spiciform

isBe

nth

Caesalpiniaceae

T37

58plusmn20118plusmn034

110

1731

2661plusmn24020plusmn009

308

6Mkalala

Albiziapetersiana

(Belle)O

liv

Mim

osaceae

T40

80plusmn30055plusmn020

85

2711

636plusmn29005plusmn004

94

7Mlyasenga

Combretum

zeyheri

Soun

dCom

bretaceae

T43

60plusmn20030plusmn011

741597

2020plusmn08001plusmn001

47

8Mkombivawo

Bauh

iniapetersiana

Caesalpiniaceae

SH34

54plusmn21029plusmn010

64

2000

9Muguvani

Markham

iaobtusifolia

Bign

oniaceae

T60

65plusmn13038plusmn010

64

647

605plusmn03

00

23

10Mdeke

Hym

enodictyon

parvifoliu

mOliv

Rubiaceae

ST31

50plusmn24048plusmn024

58

2749

302plusmn02

00

17

11Mub

wegele

Sclerocarryabirrea

sbspbirr

eaAnacardiaceae

T34

21plusmn6061plusmn023

58

441

605plusmn03001plusmn001

28

12Mmem

enam

ene

Margaritaria

discoidea(Bail)

Euph

orbiaceae

SH51

68plusmn24032plusmn013

57

2073

307plusmn07

00

06

13Mkambala

Acaciamellifera

(Vahl)Be

nth

Mim

osaceae

T29

14plusmn5049plusmn019

50

359

302plusmn02

00

08

14Mugegere

Dich

rosta

chys

cinerea

(L)Wight

ampArn

Mim

osaceae

ST31

53plusmn26017plusmn009

47

3086

2959plusmn19003plusmn002

178

15Mbata

AcaciaseyalD

elvar

seyal

Mim

osaceae

T34

30plusmn10019plusmn006

45

887

311plusmn11001plusmn001

46

16Mgulumo

Lann

easchw

einfurthiiAnacardiaceae

T43

24plusmn7032plusmn009

39

544

907plusmn04002plusmn001

22

17Muyom

boBrachyste

giaboehmii

Caesalpiniaceae

T11

11plusmn7019plusmn015

38

1309

607plusmn05001plusmn001

22

18Mmulim

uli

Cassiaabbreviata

Caesalpiniaceae

T34

31plusmn13017plusmn007

36

1353

916plusmn12001plusmn001

49

19Mdavi

Cordiasin

ensis

Lam

Boraginaceae

ST6

23plusmn23011plusmn010

34

5498

302plusmn02

00

06

6 ISRN Biodiversity

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

20Mdw

endw

eTerm

inaliabrow

nii

Com

bretaceae

T17

14plusmn8019plusmn009

32

1129

305plusmn05

00

12

21Mfilafila

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T31

25plusmn8015plusmn005

30

646

605plusmn03

00

35

22Mkw

ata

Codyladensiflora

Caesalpiniaceae

T9

4plusmn2033plusmn019

28

282

334plusmn34004plusmn004

83

23Mgung

aAc

aciaabyssin

ica(H

ochst)

Mim

osaceae

T17

12plusmn7014plusmn007

24

1140

614plusmn12001plusmn001

39

24Mkole

Grew

iabicolor

Tiliaceae

ST26

21plusmn10008plusmn003

21

1078

605plusmn03

00

15

25Mparapand

eStrychnosp

otatorum

Lf

Loganiaceae

T23

23plusmn11014plusmn009

20

1331

607plusmn05

00

17

26Kitim

bwi

Orm

ocarpum

kirkii

Fabaceae

SH29

18plusmn6007plusmn003

19492

27Mtabagila

Lonchocarpus

capassa

Fabaceae

T26

11plusmn5014plusmn006

17550

302plusmn02

00

04

28Muw

otapon

ziOzoroainsig

nsssp

retic

ulata

Anacardiaceae

T14

10plusmn5010plusmn005

16564

1411plusmn05001plusmn000

31

29Msanzi

Gardeniaresin

iflua

Hiern

Rubiaceae

ST9

13plusmn8008plusmn005

161229

30Mkoga

Vitexpayos

Verbenaceae

ST17

12plusmn5011plusmn004

15605

302plusmn02

00

02

31Mpelem

eleGr

ewiaforbesiiHaw

Ex

Mast

Tiliaceae

ST14

16plusmn9005plusmn002

147

1246

32Mny

wenyw

eeDalbergiaboehmii

Fabaceae

T14

11plusmn7009plusmn007

151221

33Mulagavega

Albiziaam

ara(Roxb)

Boiv

Mim

osaceae

T14

9plusmn5004plusmn003

14712

34Mkola

Afzelia

quan

zensis

Caesalpiniaceae

T11

6plusmn3015plusmn009

14532

35Mugusi

Brachyste

giamanga

Caesalpiniaceae

T20

11plusmn6010plusmn007

13824

618plusmn13002plusmn002

25

36Mwaham

aShrebera

trichoclada

Oleaceae

T17

11plusmn6005plusmn002

12697

309plusmn09001plusmn001

15

37Mpingo

Dalbergia

mela

noxylon

Fabaceae

T11

11plusmn9004plusmn003

121655

314plusmn14001plusmn001

26

38Mub

aya

Strychnosinn

ocua

Loganiaceae

T17

8plusmn4011plusmn008

12375

302plusmn02001plusmn001

06

39Msisina

AlbiziaharveyiF

ournMim

osaceae

T14

5plusmn3008plusmn005

11359

305plusmn05002plusmn002

15

40Mlim

boEu

phorbiacuneata

Valh

Euph

orbiaceae

ST14

12plusmn6004plusmn002

11699

41Mwam

biElaeodendron

buchan

annii

Cela

steraceae

T3

8plusmn8003plusmn003

102000

42Mvembadand

aXe

roderris

stuhlmannii

Fabaceae

T14

4plusmn2011plusmn005

09

191

43Mtelela

Brachyste

giabu

ssei

Harms

Caesalpiniaceae

T6

2plusmn1012plusmn010

09

253

ISRN Biodiversity 7

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

44Mteresi

Prem

naholstiiGurke

Verbenaceae

ST9

8plusmn5003plusmn002

09

899

45Mkongolo

Commiphora

ugogensis

Burseraceae

T6

1plusmn1008plusmn006

08

097

302plusmn02001plusmn001

09

46Muw

isaBo

sciaangustifolia

A

Rich

varangustifo

liaCa

pparaceae

T17

8plusmn4004plusmn002

08

426

47Mnyalup

uko

Canthium

pseudoverticillatum

Hien

Rubiaceae

ST20

8plusmn4004plusmn002

07

414

48Mnyaluh

anga

Brideliascleu

roneura

MuellArg

Euph

orbiaceae

ST14

6plusmn3004plusmn002

07

341

49Mdide

Manilkaramochisia

(Bak)Dub

ard

Sapo

taceae

T9

5plusmn4002plusmn001

07

793

50Muh

emi

Erythrinaabyssin

icaFabaceae

T6

1plusmn1007plusmn006

07

163

51Msambarawe

Vangueria

infausta

BurchSspRo

tund

ataRu

biaceae

ST6

8plusmn5002plusmn002

06

925

52Mhehefu

Allophylu

sferrugineus

Taub

Sapind

aceae

SH9

5plusmn3002plusmn001

05

540

314plusmn14001plusmn001

14

53Mnyengrsquoenyengrsquoe

Excoecariabu

ssei

(Pax)

Euph

orbiaceae

ST11

4plusmn2001plusmn001

05

321

54Muganga

Berchemiadiscolor

Rham

naceae

T6

4plusmn3004plusmn003

04

717

55Mning

aPterocarpu

sangolensis

Fabaceae

T6

2plusmn1005plusmn004

04

253

309plusmn09006plusmn006

25

56Mtanang

we

Zizip

husm

ucronata

Rham

naceae

T3

4plusmn4003plusmn003

04

900

57Muh

ekele

Eucle

adivinorum

Hiern

Ebenaceae

ST3

3plusmn3001plusmn001

04

800

302plusmn02

00

49

58Mub

umila

Cassipourea

mollis

(REfr)Alstom

Rhizop

horaceae

T9

4plusmn3002plusmn001

04

526

302plusmn02

00

04

59Mkw

ambe

Flueggea

virosa

Willd

Euph

orbiaceae

SH6

3plusmn2003plusmn003

03

406

60Kivang

aZa

nhaafric

ana

(Radlk)Ex

ell

Sapind

aceae

T9

2plusmn1001plusmn001

02

212

302plusmn02

00

02

61Mning

amaji

Pterocarpu

stinctorius

Fabaceae

T3

0002plusmn002

02

100

62Mtosi

MaeruatriphyllaA

Rich

Capp

araceae

ST3

2plusmn2001plusmn001

02

600

63Mugosa

Ehretia

amoena

Boraginaceae

ST9

1plusmn1

00

01

094

64Mnyon

gamem

beStegan

otaenia

araliacea

Apiaceae

T6

1plusmn1

001

01

163

65Mvelevele

Vernoniaam

ygdalin

aAs

teraceae

SH3

2plusmn2001plusmn001

01

400

66Mpo

ngolo

Catunaregam

spinosa

(Thun

b)

Rubiaceae

ST3

1plusmn1001plusmn001

01

200

8 ISRN Biodiversity

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

67Mbo

liboli

Acaciadrepanolobium

(Harms)

Mim

osaceae

T3

000

01

100

68Mwim

akigulu

Maeruaangolen

sisCa

pparaceae

SH3

1plusmn1

00

01

300

69Mnyali

Tamarindu

sind

icaCa

esalpiniaceae

T6

1plusmn1001plusmn001

01

097

70Mgombw

ani

Combretum

aculeatum

Com

bretaceae

T6

1plusmn1

00

01

097

302plusmn02

00

04

71Msang

ala

Burkea

afric

anaHoo

kCa

esalpiniaceae

T3

0001plusmn001

01

100

302plusmn02

00

04

72Mkokonza

Opilia

amentacea

Roxb

Opiliaceae

SH3

000

00

100

311plusmn11

00

42

73Mfumbi

Kigelia

afric

ana

Bign

oniaceae

T3

000

00

100

74Mlang

ali

Euphorbia

cand

elabrum

Euph

orbiaceae

T3

000

00

100

75Mpu

lulu

Term

inaliaseric

eaCom

bretaceae

T3

000

00

100

76Mdaha

Diospyros

usam

barensisFWhite

Ebenaceae

T3

000

00

100

305plusmn05001plusmn001

15

77Mtund

wa

XimeniacaffraSond

Olacaceae

ST3

000

00

100

78Mwim

aperu

Tarenn

agla

veolens(S

Moo

re)B

rem

Rubiaceae

ST+

79Mwesa

Boscia

mossambicensisKl

Capp

araceae

ST+

80Musasam

ulo

Psychotria

schu

mmaniana

Rubiaceae

ST+

81Muh

anza

Senn

asin

gueana

Caesalpiniaceae

ST+

82Mtund

wahavi

Ximeniaam

erica

naOlacaceae

ST+

83Mtin

giligiti

Phyllanthu

sengler

iPax

Euph

orbiaceae

T+

84Msada

Vangueria

madagascarie

nsis

Gmel

Rubiaceae

ST+

85Mku

nung

uZa

nthoxylum

chalybeum

Rutaceae

T+

86Lu

kali

Croton

scheffleriP

axEu

phorbiaceae

SH+

87Kilim

andembw

eGardeniaternifolia

KSchu

mamp

Thon

nRu

biaceae

ST+

88MpelaM

buyu

Adan

soniadigitata

Bombacaceae

T++

Total(allspecies)

13511521plusmn5941355plusmn552

200

294

60plusmn30072plusmn049

200

+indicatesspecies

identifi

edam

ongsm

allerind

ividualswith

in5m

radius

plots(Dbhlt5c

m)and++

indicatesthata

largeind

ividualw

asidentifi

edwith

ina1

5-radius

plot

butw

asno

tincludedin

thea

nalyseso

fste

mdensitybasalareaand

volumea

sitw

asconsidered

anou

tlier

duetoits

tremendo

ussiz

e(Dbh

=340c

m)

ISRN Biodiversity 9

005 and that of small individuals was 006 The followingspecies were observed to have the greatest contributionsto the Shannon-Wiener diversity index of large individualsDalbergia arbutifolia (contributing 030) Combretum molle(020) Commiphora africana (019) Albizia petersiana (016)and Margaritaria discoidea (014) while for smaller ones thegreatest contributions were found for Brachystegia spiciformis(026) Dalbergia arbutifolia (024) Grewia forbesii (023)Margaritaria discoidea (020) and Dichrostachys cinerea(016) In terms of frequency of occurrence for standingindividuals (large sizes) Commiphora africana was the mostfrequent species (77 of plots) followed by Combretummolle (74) and Dalbergia arbutifolia (60) while for smallsizes Margaritaria discoidea (66) Markhamia obtusifolia(63) and Dalbergia arbutifolia (57) were the most fre-quent species The Importance Value Index (IVI) for largeindividuals (Dbh ge 5 cm) shows that Dalbergia arbutifolia(224) Commiphora africana (175) and Combretum molle(132) were the most important species among standingindividuals while Brachystegia spiciformis (308)Combretummolle (307) and Dichrostachys cinerea (178) appeared to bethe most important among harvested individuals (stumps)These species were also found to have higher frequencies thanany other harvested species observed in the GVLFR (Table 1)

33 Stem Density The total mean stem density for large indi-viduals with Dbh ge5 cm was 1521 plusmn 594 stemsha (Table 1)and that of small individuals with Dbh lt5 cm (includingindividuals with Dbh lt1 cm) was 14318 plusmn 6956 stemshaAmong large individuals the most abundant species wereDalbergia arbutifolia (162 of 1521 stemsha) Combretummolle (8) Commiphora africana (72) and Albizia peter-siana (53) Among small individuals the most abundantspecies were Brachystegia spiciformis (13 of 14318 stemsha)followed by Dalbergia arbutifolia (11) and Grewia forbesii(10) For stumps the overall mean density was 60 plusmn38 stemsha with Combretum molle (12) Dalbergia arbuti-folia (12) Brachystegia spiciformis (10) and Dichrostachyscinerea (10) contributing the most (Table 1) Generally thedistribution of standing trees to size classes showed the usualreverse J shape which was also approximately observed forstumps (Figure 3) However for stumps the density of stemsin the 1ndash10 cm diameter class was slightly lower than whatwould be expected if tree felling had been a random event

34 Basal Area For the GVLFR as a whole the meanbasal areas for large (ge5 cm Dbh) and small individuals(lt5 cm Dbh) were 1355 plusmn 552m2ha (Table 1 Figure 4)and 305 plusmn 002m2ha respectively The species contributingmost to the basal area of large individuals were Commiphoraafricana (12) Dalbergia arbutifolia (10) and Brachystegiaspiciformis (9) while those contributing most to the basalarea of smaller individuals were Dalbergia arbutifolia (16)Grewia forbesii (15) and Dichrostachys cinerea (13) Themean basal area for stumps was 072m2ha with Brachystegiaspiciformis contributing the greatest individual proportion(28) 41 species made up the rest (Figure 4)

60542

3335

530

113

28 24

346166

34

11

02

01

10

100

1000

10000

100000

Diameter classes (cm)

Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Stem

s (ha

minus1)

Figure 3 Density of standing trees ge1 cmDbh and stumps ge1 cm bydiameter class in Gangalamtumba VLFR (119899 = 35) NB logarithmicscale on vertical axis

744477

241

103041 055

014025 018

010004

001

01

1

10

Diameter classes (cm)Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Mea

n ba

sal a

rea (

m2

haminus1)

Figure 4 Distribution of basal area per hectare for standingtrees ge1 cm Dbh and stumps ge1 cm by diameter classes in theGangalamtumba VLFR (119899 = 35) NB logarithmic scale on verticalaxis

35 Volume The mean volumes for large (ge5 cm Dbh) andsmall individuals (lt5 cm Dbh) were 9217 plusmn 390m3ha and1257 plusmn 635m3ha respectively (not shown in tables) Thespecies contributing most to the volume of large individualswere Commiphora africana (12) Brachystegia spiciformis(10) Acacia sp (9) and Dalbergia arbutifolia (9) Forsmaller individuals the species that contributed most tovolume were Dalbergia arbutifolia (16) Grewia forbesii(14) and Dichrostachys cinerea (13) The mean remainingvolume of stumps was found to be 015 plusmn 01m3ha withBrachystegia spiciformis contributing the greatest individualpercentage (28) 41 species made up the rest

10 ISRN Biodiversity

36 Spatial Distribution Dispersion indices (DI) are pre-sented for individual species in Table 1 The dispersion indexvalues range from 094 indicating almost complete spatialrandomness or slight underdispersion to 5498 indicatingconsiderable overdispersion that is a patchy or clustereddistributionOut of 77 species excluding the single very largeAdansonia digitata that was considered an outlier 64 species(83) 9 species (12) and 4 species (5) were found tohave DI gt 1 DI = 1 and DI lt 1 respectively so the majorityof species are characterised by a patchy distribution acrossthe forest The species with the lowest estimated DI wasEhretia amoena (094) while the highest DI was estimated forCordia sinensis (5498)Themost abundant species includingDalbergia arbutifolia (DI = 4765) Combretum molle (DI =1523) and Commiphora africana (DI = 1142) are stronglyoverdispersed

37 Plant Communities and Species Association Four plantcommunities were identified through cluster analysis basedon the statistical significance (5) of the observed maximumindicator values (Table 2) Only two of these plant commu-nities were dominated by species from the family Caesalpini-aceae (Communities 1 and 24) The other two showed greatvariationoverlap between species of different plant families(Communities 3 and 5) The estimated Steinhaus similarityindices between pairs of plant communities varied from 32for Communities 1 and 3 and Communities 5 and 24 to 37for Communities 3 and 5 (not shown in tables)

The ordination diagram (Figure 5) shows that one topo-graphic and six edaphic variables appear to be associatedwiththe four plant communities and the species distribution inthe study area The strongest correlation with communitycomposition was observed for elevation followed by soilpH at 0ndash15 cm depth base cation Ca2+ at 0ndash15 cm depthpercent base saturation (BS) at 0ndash15 cm depth percent clayat 0ndash15 cm depth C N ratio at 15ndash30 cm depth and percentsand at 0ndash15 cm depth The base cations magnesium (Mg2+)and potassium (K+) were not directly correlated with thecommunity composition but since they are included in thebase saturation percentage they are indirectly related Plantcommunities were ordered along the second ordination axiswhich was positively correlated with pH15 (119903 = 071) Ca15(119903 = 069) BS (119903 = 065) andClay15 (119903 = 052) and negativelycorrelated with Sand15 (119903 = minus046) Axis 1 of the ordinationwas positively correlated with Elev (119903 = 085) and CNrat30(119903 = 051) As shown in Table 3 and indicated graphically inFigure 5 correlations between many of the edaphic variablesare strong particularly between pH15 Sand15 Clay15 Ca15and BS whereas correlation between topographic and mostedaphic variables is small and nonsignificant However thereis a significant negative correlation (119903 = minus042) between Elevand Sand15 indicating that sandy soils are mostly found atlower elevations

4 Discussion

41 Species Composition The results reported in this studyshow that the composition of the vegetation types found in

Elev

pH15Ca15

Sand15

Clay15

CNrat30

BS

Axis 1

Axis 2

Community 1Community 3

Community 5Community 24

Figure 5 Compositional gradients and plant communities in NMSordination of 35 vegetation plots for trees ge5 cm in GangalamtumbaVLFR Four plant communities are recognized (cf Table 2) Com-munity 1 = Brachystegia spiciformis Diplorynchus condylocarponand Lannea schweinfurthii woodland Community 3 = Dalbergiaarbutifolia Commiphora africana and Albizia petersianawoodlandCommunity 5 = Acacia sp Acacia abyssinica and Albizia amarawoodland and Community 24 = Bauhinia petersiana and Shreberatrichoclada woodland Elev elevation (m) CNrat30 C N ratio at15ndash30 cm depth Sand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm Ca15 = Ca2+ (cmol(+)kg) at 0ndash15 cm pH15 = soil pH at 0ndash15 cm BS base saturation at 0ndash15 cm

the GVLFR especially the dominance of species from thefamily Caesalpiniaceae agreed well with previous descrip-tions and classifications of plant communities commonlyfound in miombo woodlands [1] However the observeddominance based on IVI of the genera Dalbergia Com-miphora and Combretum contrasts with patterns usuallyconsidered common for miombo woodlands The frequencyof species in these genera was also high compared to otherspecies observed in the GVLFR (Table 1) Similar deviationsexist between the results obtained by Banda et al [26]in the Katavi-Rukwa ecosystem where they observed thatTerminalia and Combretum were the dominant genera andthe findings of Giliba et al [27] and Njana [43] whoboth noted the dominance of the two common miombogenera Brachystegia and Julbernardia However Combretumalso occurred in their study areas The results suggest thaton a larger spatial scale the species diversity of miombowoodlands is very high and that the three common generaBrachystegia Julbernadia and Isoberlinia are not alwaysdominant at the local scale

The species richness observed in the GVLFR compareswell with miombo community studies in other areas of drymiombo in Tanzania and elsewhere which receive an average

ISRN Biodiversity 11

Table2Plantcom

mun

itiesandspeciesa

ssociatio

nsin

thed

ryMiombo

woo

dlands

ofGangalamtumba

VLF

RCom

mun

itynu

mbers135and24

representthe

different

plantassociatio

ns

119899speciesnu

mbero

fspecies

(77in

total)with

Dbhge5c

mIV+

speciesind

icator

valuemeanplusmnstd

errorand

BAisbasalarea

Com

mun

ityAs

sociated

species

Family

Habit

IV+

()

Con

stancy

()119875value

Stem

sha

BA m2 ha

MeanDbh

Brachyste

giaspiciform

ismdashDiplorhynchus

cond

ylocarponmdashLa

nnea

schw

einfurthiiw

oodland

1(n s

pecies

=47

nplots=9)

Sitevariables(meanplusmnSE

)Elev

=1200plusmn20pH15

=644plusmn013C

a15=604plusmn128

Sand

15=721plusmn431C

lay15=137plusmn188Silt15

=142plusmn335C

Nrat30=135plusmn05andBS

=526plusmn65

Brachyste

gia

spiciform

isCa

esalpiniaceae

T820

100

000

02164plusmn59356plusmn077138plusmn07

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T759

89000

0866plusmn18044plusmn01382plusmn05

Lann

easchw

einfurthii

Anacardiaceae

T719

100

000

0449plusmn14072plusmn022126plusmn09

Bosciaangustifolia

Capp

araceae

T536

5600056

27plusmn12014plusmn00776plusmn06

Euphorbiacuneata

Euph

orbiaceae

ST428

4400200

42plusmn19012plusmn00665plusmn06

Other

species

mdashmdash

mdashmdash

mdash1075plusmn5741007plusmn647102plusmn03

Subtotal

1423plusmn174

1505plusmn178

109plusmn03

DalbergiaarbutifoliamdashCo

mmiphora

afric

anamdash

Albizia

petersiana

woo

dland

3(n

species=55n

plots=

16)Site

variables(meanplusmnSE

)Elev

=986plusmn19pH15

=648plusmn009C

a15=856plusmn109

Sand

15=767plusmn156C

lay15=135plusmn155Silt15

=97plusmn096C

Nrat30=106plusmn03andBS

=744plusmn44

Dalbergiaarbutifolia

Fabaceae

subfam

ilyPapilio

noideae

ST793

100

000

02500plusmn123263plusmn06477plusmn02

Commiphora

afric

ana

Burseraceae

T542

9400026

187plusmn40272plusmn064119plusmn06

Albiziapetersiana

Mim

osacea

T536

7500200

157plusmn57103plusmn04084plusmn02

Sclerocarryabirrea

Anacardiaceae

T504

6300186

40plusmn11128plusmn045168plusmn17

Other

species

mdashmdash

mdashmdash

mdash852plusmn449669plusmn37788plusmn03

Subtotal

1735plusmn166

1435plusmn071

92plusmn02

Acaciaspmdash

Acaciaabyssin

icamdash

Albiziaam

arawoo

dland

5(n

species=33n

plots=5)

Sitevariables(m

eanplusmnSE

)Elev

=986plusmn52pH15

=734plusmn023C

a15=139plusmn33

Sand

15=745plusmn678C

lay15=148plusmn47Silt15

=107plusmn26C

Nrat30=106plusmn07andBS

=963plusmn89

Acaciasp

Mim

osaceae

T981

100

000

02269plusmn111662plusmn286172plusmn14

Acaciaabyssin

icaMim

osaceae

T594

8000030

31plusmn9060plusmn03299plusmn08

Albiziaam

ara

Mim

osaceae

T552

60000

6654plusmn30023plusmn01671plusmn08

Grew

iabicolor

Tiliaceae

ST533

6000106

113plusmn52040plusmn01770plusmn04

Acaciaseyal

Mim

osaceae

T433

6000526

62plusmn34034plusmn01790plusmn05

Other

species

mdashmdash

mdashmdash

mdash665plusmn533552plusmn49872plusmn04

Subtotal

1194plusmn169

1367plusmn347

101plusmn05

Bauh

iniapetersiana

mdashShrebera

trichoclada

woo

dland

24(n

species=35n

plots=5)

Sitevariables(meanplusmnSE

)Elev

=1175plusmn25pH15

=73plusmn04C

a15=254plusmn69

Sand

15=522plusmn68C

lay15=331plusmn28

Silt15=147plusmn44C

Nrat30=961plusmn13andBS

=1041plusmn204

Bauh

iniapetersiana

Caesalpiniaceae

SH551

8000118192plusmn121111plusmn05075plusmn03

Shrebera

trichoclada

Oleaceae

T505

6000110

57plusmn32022plusmn01380plusmn05

Manilkaramochisia

Sapo

taceae

T376

4000332

34plusmn27014plusmn00969plusmn10

Dalbergia

mela

noxylon

Fabaceae

T370

4000380

68plusmn58026plusmn02266plusmn03

Ehretia

amoena

Boraginaceae

ST347

4000344

6plusmn4

002plusmn00170plusmn04

Other

species

mdashmdash

mdashmdash

mdash982plusmn759643plusmn47999plusmn05

Subtotal

1338plusmn137

817plusmn087

91plusmn04

Total

1521plusmn5941355plusmn55298plusmn01

Elevelevatio

n(m

)CN

rat30CN

ratio

at15ndash30c

mdepthSand

15sand(

)at0

ndash15c

mC

lay15clay

()at0

ndash15c

mSilt15silt

()at0

ndash15c

mC

a15Ca2+(cmol(+)kg)at0

ndash15c

mpH15soilp

Hat0ndash

15cm

BS

base

saturatio

nat0ndash

15cm

12 ISRN Biodiversity

Table 3 Pearson-correlation matrix for two topographic and eight edaphic variablesdagger associated with the classified plant communities in theGangalamtumba VLFR (119899 = 35) Applied significance levels lowast5 lowastlowast1 and lowastlowastlowast01 +not significant

Elev Slope pH15 Ca15 K15 N15 Sand15 Clay15 CNrat30Slope 019+

pH15 minus013+ minus033lowast

Ca15 002+ minus020+ 083lowastlowastlowast

K15 minus029+ 000+ 010+ 012+

N15 006+ 036lowast 010+ 041lowastlowast 033lowast

Sand15 minus042lowastlowast 003+ minus053lowastlowastlowast minus074lowastlowastlowast 006+ minus046lowastlowast

Clay15 031+ minus012+ 051lowastlowast 076lowastlowastlowast minus001+ 047lowastlowast minus086lowastlowastlowast

CNrat30 036lowast 010+ minus039lowast minus051lowastlowast minus015+ minus019+ 040lowast minus048lowastlowast

BS minus024+ minus017+ 084lowastlowastlowast 091lowastlowastlowast 015+ 037lowast minus058lowastlowastlowast 060lowastlowastlowast minus051lowastlowastdaggerElev elevation (m) pH15 soil pH at 0ndash15 cm Ca15 Ca2+ (cmol(+)kg) at 0ndash15 cm K15 K+ (cmol(+)kg) at 0ndash15 cm N15 N concentration at 0ndash15 cmSand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm CNrat30 C N ratio at 15ndash30 cm depth BS base saturation at 0ndash15 cm 119905-value was calculated as119905 = 119903radic(119899 minus 2)(1 minus 119903

2) where 119903 is the Pearson-correlation coefficient and 119899 is the total sample size

Table 4 Species richness observed in other studies from drymiombo woodlands

Plot size(ha)

Totalnumberof plots

Total samplearea(ha)

Total numberof species References

0071 70 495 82 [43]0071 80 565 110 [27]0071 133 940 229 [26]0071 247 1746 102 [44]004 40 160 81 [45]025 14 350 69 [25]01 2 020 40 [28]01 152 1520 92 genera [22]0071 35 247 88 This study

annual rainfall of 565ndash1500mm (Table 4) Using plot sizes of004ndash025 ha and sample sizes of 2ndash247 plots a total numberof species ranging from40 (Dbhge 10 cm) to 229 (Dbhge 2 cm)have been reported fromMiombowoodlands [22 25ndash28 43ndash45]

The high number of species reported by Banda et al [26]Chidumayo [22] Isango [45] and Chamshama et al [44] islikely to be a consequence of the spatial scale and coverage ofthese studies as they all cover large areas include more thanone site and operate with large sample sizes For exampleChidumayo [22] included species from both wet and dryMiombo areas in Zambia The study by Sauer and Abdallah[15] who reported a total of 131 species occurring in thetobacco growing zone of Iringa rural district included twoforest reserves and three family-managed forests Thereforeconsidering the climatic conditions in the GVLFR (617mmof rainfall per year) and the sample size (35 plots) thespecies richness reported in this study can be ranked atleast as high or higher than those found in the studiesmentioned The selective sampling approach focusing onvarious microhabitat types adopted by Banda et al [26] mayhave contributed to the large number of species observed

in their study area Similarly the higher number of speciesfound by Giliba et al [27] was probably due to the presenceof riverine forest offering site conditions favourable formanyspecies

The values of the Shannon-Wiener (1198671015840 = 344) andSimpson indices (119863 = 005) reported for large individ-uals in this study are within the range observed for mostcommunities of particular life forms [36] For example 1198671015840usually does not exceed 5 although this maximum valuevaries depending on the type of the biological communitysampled and the sampling approach applied (eg minimumdiameter and size of sample units) A threshold value of 2 for1198671015840 has been mentioned as a minimum value above which

an ecosystem can be regarded as medium to highly diverse[27] Chamshama et al [44] reported three 1198671015840 values of31 32 and 33 from Kitulangalo Miombo forest in EasternTanzania while Njana [43] reported a 1198671015840 value of 340from dry Miombo forest in Western Tanzania The studiesby Sauer and Abdallah [15] and Giliba et al [27] reportedparticularly high values of 346 and 427 respectively Thiscould be attributed to the very large sample sizes used inboth studies and the presence of riverine forest where thechance of encountering many rare species is likely to be highThe forests examined in the mentioned studies receive anaverage annual rainfall of 700ndash1000mm compared to whichthe rainfall in the GVLFR is low (617mm on average per yearcf above)The relatively high diversity found inGVLFRmusttherefore be attributed to other factors than climate The soilanalyses indicate that the soil fertility level in the GVLFRis relatively high with considerable proportions of all 2 1lattice clay minerals (114) (ie illite montmorillonite andvermiculite) plus a good amount of organic matter whichmay suggest that the soil has large reserves of important plantnutrients for example K Mg and Fe The base saturationpercentage (BS) which is normally used to indicate the soilfertility status (Landon 1991) was also high 76 on averageand with 86 of the samples (30 samples) with BS valuesgt50 (fertile soil) and only 14 of the samples (5 samples)with BS below 50 (less fertile soil) As another indicationof high soil fertility status the mean C N ratio was 12 plusmn 043

ISRN Biodiversity 13

(range 7ndash19) for top soil (0ndash15 cm) and 11 plusmn 036 (range 5ndash16) for subsoil (15ndash30 cm) In general the values for both soilstrata fall within the expected range of 8ndash17 Soil pH values(mean 67 plusmn 01 range 567ndash852)were alsowithin the optimalrangewhere all the nutrients that aremost important for plantgrowth (Ca Mg K and P) are available and accessible toplants [46] In this study 97 of the soil samples had pHbelow 8 (one sample had a pH of 852) Fisher and Binkley[47] noted that high pH is almost never a problem in forestsas most trees do well across the full range of common pHvaluesTherefore considering the low average annual rainfallcompared to other forests the relatively high fertility of theGVLFR may be the main factor creating an environmentfavourable to many species thus leading to a quite highspecies diversity observed in this forest

Based on the Importance Value Index Brachystegia spi-ciformis and Combretum molle appeared to be the mostimportant species among harvested trees (stumps) in thestudy area This result agreed very well with the large valuesof basal area and volume and the information obtained fromlocal scouts and members of the village environmental com-mittee who said that the most frequently harvested speciesfor charcoal making include all Brachystegia species found inthe forest (ie Brachystegia spiciformis Brachystegia mangaBrachystegia boehmii and Brachystegia bussei) Among theCombretum species the most important one (based on IVI)Combretum molle is mostly used for house construction andfirewood rather than for charcoal making Apart from theBrachystegia species the only other species mentioned asimportant for charcoal making was Acacia mellifera Otherspecies are only used in case they happen to fall when fellingthe preferred species during the preparation of charcoal kilnsWith respect to stumps Brachystegia spiciformis Brachystegiamanga and Combretum molle are among the ten mostabundant species in terms of density basal area and volumeper hectare Stumps of the other species mentioned are notcommonly found a factwhichmay be due to the small samplesize being unable to capture sites where these species areharvested but may also be related to their limited distributionin the forest as indicated by the estimated dispersion indices(see Table 1)

42 Forest Structure Species densities reported from otherMiombo woodland areas in Tanzania are typically 348ndash1495stemsha for trees with Dbh gt4 cm [24 43 45] Comparedwith this the GVLFR is highly stocked as the estimateddensity is 2296 stemsha for trees with Dbh gt4 cmThemeanstem density of 1521 plusmn 594ha for trees with Dbh ge5 cmis also more than twice as large as values found in otherstudies [25ndash27 44 45 48] A similar pattern is seen whencomparing the density of regeneration between the studiesThe diameter distribution is characterised by a very cleartrend of decreasing stem density with increasing diameterThe shape of the distribution is thus an inverted ldquoJrdquo (Figure 3)which is a common feature of natural forests with activeregeneration and recruitment [49] However not many largetrees were captured by the sample whereas a considerablenumber of relatively large stumps were observed suggestingthat anthropogenic activities such as charcoal making may

have affected the structure and ecological balance of the forest(see Figure 3) Since the woodlands are often hit by fire whichtends to kill the seedlings (especially the late fires) and thusonly few seedlings can be expected to reach larger diameterclasses lack of mature trees and the resulting lack of seedsmay eventually threaten the biodiversity of the forest

The mean basal area of 1355 plusmn 552m2ha observedin this study is slightly above the range of values typicallyreported from the miombo region 75ndash126m2ha [26 28 4344 50] However the basal areas reported by Isango [45] werea bit higher (1504ndash1563m2ha) than observed in this study

Themean total volume inGVLFRwas estimated at 9217plusmn390m3ha for trees with Dbh ge5 cm Other studies in dryMiombo woodlands have reported mean volumes of 167ndash7603m3ha [24 44 45 50] The current standing volume ofGVLFR is thus slightly higher than values typically reportedfor forests in the Miombo ecoregion A plausible reason forthis may be that compared to other forests the GVLFR isstill well stocked despite ongoing human activities such ascharcoalmakingThebasal area observed for stumpswas only072m2ha so there is no indication of intensive extractionover many years This corresponds well with the findings ofTreue et al [20] who conclude that the estimated 04m3haannual extraction of woody biomass from GVLFR is consid-erably below its estimated annual increment of 15m3ha andthat the local forest managers seem capable of regulating theharvesting activities which in addition to village membersrsquocollection for subsistence uses also included commercialcharcoal production by external companies that pay a fee perbag of charcoal extracted to the village government

43 Plant Communities and Species Associations Except forBrachystegia spiciformis the majority of the Brachystegia andJulbernardia species that are common to miombo wood-lands elsewhere are not among the species most commonlyobserved in this study A similar pattern was observed byBanda et al [26] in the Katavi-Rukwa ecosystem wherethe genera that are most common in miombo woodlandsBrachystegia Julbernardia and Isoberlinia were not commonin their study sites Furthermore the four plant communi-ties distinguished in this study are comparable with thosereported by other studies in Tanzania including the work byMunishi et al [29] in theMiombowoodlands of Rukwa basinChunya district Tanzania and the study by Banda et al [26]in the Katavi-Rukwa ecosystem

Elevation was noted by Munishi et al [29] to be themost important factor shaping the species communities intheir study area This study found a similar pattern with thehighest coefficient of correlation observed for elevation sug-gesting that topographical variation is among the strongestdeterminants of community composition in dry Miombowoodlands hence influencing the spatial distribution ofspecies strongly However in our study area edaphic factorsalso influenced the species distribution directly Two plantcommunities occurredmainly on clayey soils with high pH atintermediate elevations one on sandy soils with lowpHat lowelevations and one on sandy-clayey soils at higher elevationsand with neutral soil pH (Figure 5) Specifically it appeared

14 ISRN Biodiversity

that the Acacia woodland category (Community 5) grows atlow elevations around temporary streams (or at least wherethe ground water table is relatively high) and the Bauhiniawoodland category (Community 24) appearsmostly in placeswith a relatively high percentage of clay (and therefore highvalues of pH Ca and BS) By contrast it appeared that theDalbergia woodland category (Community 3) is located atmore sandy sites (with low values of pH Ca and BS) andthe Brachystegia woodland category (Community 1) seemedto be located mostly at higher elevations where the CN-ratio is quite high Correlations between elevation and thebasic soil variables pH Ca and percentages of sand andclay were low (cf Figure 5) Thus the results indicate thatthe plant communities of the dry miombo woodlands inGVLFR are not only shaped by the topographic variation(elevation) and the groundwater level but also by basic soilcharacteristics The results thus confirm findings from otherstudies detecting effects of elevation and soil characteristicson species composition [51 52]

5 Conclusion

Considering that the sample size used in this study wassmaller than samples used in other studies in dry miombowoodlands the results show that the species diversity inGVLFR is relatively high compared to other forest reservesThe vegetation of GVLFR is characterised by high densitybasal area and volume and despite the scarcity of largediameter trees this indicates that the forest is in a goodcondition The effect of anthropogenic activities is neverthe-less evident and stresses the need for proper managementespecially for economically important species preferred forcharcoalmaking (egBrachystegia spiciformis) if the currentspecies diversity is to be maintained or enhanced A repeatedfuture study would be needed to assess whether the currentcommunity-based management regime yields this intendedoutcome but the available information and analyses allow forsome optimism in this respect

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors wish to thank people from Mfyome villagefor their invaluable assistance during field work Mzee IddiKaheya Damian Chotamasege AugustinoMkwama Libera-tus Simime and Mawazo Nyangwa Furthermore thanks aredue to Venancia Mlelwa from Sokoine University and MadsMadsen Krag from University of Copenhagen for doing thelaboratory work The authors also wish to thank GoodluckMoshi their driverMarcoNjana andNassoroHMagogo theTAFORI botanist for assisting with species identification andKlaus Dons for preparing a study site map Financial supportwas provided by Danida through the ENRECA Project

ldquoParticipatory forest management for rural livelihoods forestconservation and good governance in Tanzaniardquo (no 725)

References

[1] P G H Frost ldquoThe Ecology of Miombo Woodlandsrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 11ndash57 1996

[2] N Burgess J Hales E Underwood et al Terrestrial Ecoregionsof Africa and Madagascar A Conservation Assessment IslandPress World Wildlife Fund 2004

[3] J Clarke W Cavendish and C Coote ldquoRural householdsand miombo woodlands use value and managementrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 101ndash135 1996

[4] B M Campbell A Angelsen A Cunningham Y KaterereA Sitoe and S Wunder ldquoMiombo woodlandsmdashopportunitiesand barriers to sustainable forest managementrdquo httpsener-gypediainfoimages66dMiombo2007pdf

[5] S Syampungani P W Chirwa F K Akinnifesi G Sileshi andO C Ajayi ldquoTheMiombo woodlands at the cross roads poten-tial threats sustainable livelihoods policy gaps and challengesrdquoNatural Resources Forum vol 33 no 2 pp 150ndash159 2009

[6] J I O Abbot and K Homewood ldquoA history of change causesof miombo woodland decline in a protected area in MalawirdquoJournal of Applied Ecology vol 36 no 3 pp 422ndash433 1999

[7] E J Luoga E T F Witkowski and K Balkwill ldquoLand coverand use changes in relation to the institutional frameworkand tenure of land and resources in eastern Tanzania Miombowoodlandsrdquo Environment Development and Sustainability vol7 no 1 pp 71ndash93 2005

[8] FAO The State of Food and Agriculture 2010-2011 Forest andAgriculture Organization Rome Italy 2010

[9] A H Gentry ldquoTropical forest biodiversity distributional pat-terns and their conservational significancerdquo Oikos vol 63 no1 pp 19ndash28 1992

[10] O E Sala F S Chapin III J J Armesto et al ldquoGlobalbiodiversity scenarios for the year 2100rdquo Science vol 287 no5459 pp 1770ndash1774 2000

[11] H J Geist and E F Lambin ldquoProximate causes and underlyingdriving forces of tropical deforestationrdquo BioScience vol 52 no2 pp 143ndash150 2002

[12] R S DeFries ldquoTropical forests deforestation and ecosystemsservices Contributions of remote sensingrdquo in GeoinformaticsFor Tropical Ecosystems P S Roy Ed pp 1ndash32 2003

[13] B M Campbell P Frost and N Bryon ldquoMiombo woodlandsand their use overview and key issuesrdquo in The Miombo inTransition Woodlands and Welfare in Africa B Campbell Edpp 1ndash10 2006

[14] H J Geist ldquoGlobal assessment of deforestation related totobacco farmingrdquo Tobacco Control vol 8 no 1 pp 18ndash28 1999

[15] J Sauer and J M Abdallah ldquoForest diversity tobacco produc-tion and resource management in Tanzaniardquo Forest Policy andEconomics vol 9 no 5 pp 421ndash439 2007

[16] E N Chidumayo and K J Mbata ldquoShifting cultivation ediblecaterpillars and livelihoods in the Kopa area of northernZambiardquo Forests Trees and Livelihoods vol 12 no 3 pp 175ndash1932002

[17] E N Chidumayo and L Kwibisa ldquoEffects of deforestation ongrass biomass and soil nutrient status in miombo woodlandZambiardquo Agriculture Ecosystems and Environment vol 96 no1ndash3 pp 97ndash105 2003

ISRN Biodiversity 15

[18] J F Lund and T Treue ldquoAre we getting there Evidence ofdecentralized forest management from the Tanzanian miombowoodlandsrdquoWorld Development vol 36 no 12 pp 2780ndash28002008

[19] T Blomley and S Iddi Participatory Forest Management inTanzania 1993ndash2009mdashLessons Learned and Experiences toDate Ministry of Natural Resources and Tourism Forestry andBeekeeping Division Dar es Salaam Tanzania 2009

[20] T Treue Y M Ngaga H Meilby et al ldquoDoes participatoryforest management promote sustainable forest utilisation inTanzaniardquo International Forestry Review vol 16 no 1 pp 1ndash162014

[21] Ministry ofNatural Resources andTourismParticipatory ForestManagement in Tanzania Facts and Figures Forestry andBeekeeping Division Dar es Salaam Tanzania 2008

[22] E N Chidumayo ldquoSpecies structure in Zambian miombowoodlandrdquo Journal of Tropical Ecology vol 3 no 2 pp 109ndash1181987

[23] J D Lowore ldquoCoppice regeneration in some miombo wood-lands of Malawirdquo FRIM Report 99001 Forestry ResearchInstitute of Malawi 1999

[24] E J Luoga E T F Witkowski and K Balkwill ldquoHarvestedand standing wood stocks in protected and communal miombowoodlands of eastern Tanzaniardquo Forest Ecology and Manage-ment vol 164 no 1ndash3 pp 15ndash30 2002

[25] M Williams C M Ryan R M Rees E Sambane J Fernandoand J Grace ldquoCarbon sequestration and biodiversity of re-growing miombo woodlands in Mozambiquerdquo Forest Ecologyand Management vol 254 no 2 pp 145ndash155 2008

[26] T Banda NMwangulango BMeyer et al ldquoThewoodland veg-etation of the Katavi-Rukwa ecosystem in western TanzaniardquoForest Ecology andManagement vol 255 no 8-9 pp 3382ndash33952008

[27] R A Giliba E K Boon C J Kayombo E B Musamba AM Kashindye and P F Shayo ldquoSpecies composition richnessand diversity in Miombo Woodland of Bereku Forest ReserveTanzaniardquo Journal of Biodiversity vol 2 no 1 pp 1ndash7 2011

[28] D D Shirima P K T Munishi S L Lewis et al ldquoCarbonstorage structure and composition of miombo woodlands inTanzaniarsquos Eastern Arc Mountainsrdquo African Journal of Ecologyvol 49 no 3 pp 332ndash342 2011

[29] P K T Munishi R A P C Temu and G Soka ldquoPlant com-munities and tree species associations in a Miombo ecosystemin the Lake Rukwa basin Southern Tanzania implications forconservationrdquo Journal of Ecology and Natural Environment vol3 no 2 pp 63ndash71 2011

[30] J Dewis and F Freitas ldquoPhysical analysis of soilsrdquo in Physicaland Chemical Methods of Soil andWater Analysis FAO Bulletinno 10 pp 51ndash57 2nd edition 1970

[31] S R Olsen and L E Sommers ldquoPhosphorusrdquo inMethods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 403ndash430 American Societyof Agronomy Madson Wis USA 1982

[32] J D Rhoades ldquoCation exchange capacityrdquo in Methods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 149ndash157 American Society ofAgronomy Madson Wis USA 1982

[33] IMatejovic ldquoDetermination of carbon hydrogen and nitrogenin soils by automated elemental analysis (dry combustionmethod)rdquo Communications in Soil Science and Plant Analysisvol 24 no 17-18 pp 2213ndash2222 1993

[34] J P Moslashberg Soil Analysis Manual Revised Edition Laboratoryof Soil Sciences Department of Soil Science SokoineUniversityof Agriculture Morogoro Tanzania 2001

[35] N C BradyThe Nature and Properties of Soils Macmillan 8thedition 1974

[36] C J Krebs Ecological Methodology Hamper Collins PublishersNew York NY USA 2nd edition 1999

[37] B Husch T W Beers and J A Kershaw Forest MensurationJohn Wiley amp Sons Hoboken NJ USA 4th edition 2003

[38] E E Mwakalukwa H Meilby and T Treue ldquoVolume andaboveground biomass models for dry Miombo Woodland inTanzaniardquo In press

[39] M Kent Vegetation Description and Analysis A PracticalApproach Wiley-Blackwell John Wiley amp Sons Hoboken NJUSA 2nd edition 2012

[40] B McCune and M J Mefford PC-ORD Multivariate Analysisof Ecological Data Version 6 MjM Software Gleneden BeachOre USA 2011

[41] MDufrene andP Legendre ldquoSpecies assemblages and indicatorspecies the need for a flexible asymmetrical approachrdquo EcologyMonography vol 67 pp 777ndash795 1997

[42] J E PeckMultivariate Analysis for Community Ecologists Step-by-Step using PC-ORD MjM Software Design Gleneden BeachOre USA 2010

[43] M A Njana Arborescent species diversity and stocking inMiombo Woodland of Urumwa forest reserve and their contri-bution to Livelihoods Tabora Tanzania [MS thesis] SokoineUniversity of Agriculture Morogoro Tanzania 2008

[44] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal no 200 pp 59ndash70 2004

[45] J Isango ldquoStand structure and tree species composition ofTanzania miombo woodlands a case study from miombowoodlands of community based forest management in Iringadistrictrdquo in MITMIOMBOmdashManagement of Indigenous TreeSpecies For EcosystemRestoration andWood Production in Semi-Arid Miombo Woodlands in Eastern Africa Proceedings ofthe 1st MITMIOMBO Project Workshop held in MorogoroTanzania 6th-12th February 2007 Working Papers of theFinnish Forest Research Institute no 50 pp 43ndash56 2007

[46] J R Landon Booker Tropical Soil Manual A Handbook ForSoil Survey and Agricultural Land Evaluation in the Tropics andSubtropics Longman Scientific amp Technical and John Wiley ampSons 1991

[47] R F Fisher and D Binkley Ecology and Management of ForestSoils John Wiley amp Sons 3rd edition 2000

[48] W A Rees ldquoPreliminary studies into bush utilization by Cattlein Zambiardquo Journal of Applied Ecology vol 11 pp 207ndash214 1974

[49] S M Philip Measuring Trees and Forests CAB InternationalWallingford UK 2nd edition 1994

[50] J D Lowore P G Abbot and M Werren ldquoStackwood volumeestimations formiombowoodlands inMalawirdquoCommonwealthForestry Review vol 73 no 3 pp 193ndash197 1994

[51] D Kubota T Masunaga Hermansah et al ldquoSoil environmentand tree species diversity in tropical rain forest West SumatraIndonesiardquo in Soils of Tropical Forest Ecosystems CharacteristicsEcology and Management A Schulte and D Ruhiyat Eds pp159ndash167 1998

[52] P K T Munishi T H Shear T Wentworth and R A PC Temu ldquoCompositional gradients of plant communities insubmontane rainforests of EasternTanzaniardquo Journal of TropicalForest Science vol 19 no 1 pp 35ndash45 2007

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

EcosystemsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MeteorologyAdvances in

EcologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Marine BiologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental Chemistry

Atmospheric SciencesInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Geological ResearchJournal of

EarthquakesJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BiodiversityInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

Page 5: Research Article Floristic Composition, Structure, and

ISRN Biodiversity 5

Table1Ch

ecklist

oftre

eand

shrubspeciesrecordedin

Gangalamtumba

VLF

Rshow

ingfre

quency

()density

(meanplusmnSE

)basalarea(meanplusmnSE

)dispersio

nindex(D

I)and

Impo

rtance

ValueInd

ex(IVI)bothforthe

currentp

opulationof

largeind

ividuals(plotsize=

15m

radiusm

inim

umDbh

=5c

m)a

ndforstumps

(plotsize=

20m

radiusm

inim

umbasald

iameter

=2c

m)SH

shrub

ST

smalltreeandT

tree

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

1Mgiha

Dalbergia

arbutifolia

Fabaceae

subfam

ilyPapilio

noideae

ST60

247plusmn69136plusmn037

224

4765

1468plusmn41006plusmn005

170

2Mtono

Commiphora

afric

ana

Burseraceae

T77

110plusmn23159plusmn037

175

1142

1414plusmn06001plusmn001

111

3Mlama

Combretum

molleG

Don

Com

bretaceae

T74

116plusmn27069plusmn015

132

1523

3468plusmn19005plusmn002

307

4Mku

ngugu

Acacia

sp

Mim

osaceae

T23

40plusmn22102plusmn054

111

2873

920plusmn14001plusmn001

65

5Mkw

eeBrachyste

gia

spiciform

isBe

nth

Caesalpiniaceae

T37

58plusmn20118plusmn034

110

1731

2661plusmn24020plusmn009

308

6Mkalala

Albiziapetersiana

(Belle)O

liv

Mim

osaceae

T40

80plusmn30055plusmn020

85

2711

636plusmn29005plusmn004

94

7Mlyasenga

Combretum

zeyheri

Soun

dCom

bretaceae

T43

60plusmn20030plusmn011

741597

2020plusmn08001plusmn001

47

8Mkombivawo

Bauh

iniapetersiana

Caesalpiniaceae

SH34

54plusmn21029plusmn010

64

2000

9Muguvani

Markham

iaobtusifolia

Bign

oniaceae

T60

65plusmn13038plusmn010

64

647

605plusmn03

00

23

10Mdeke

Hym

enodictyon

parvifoliu

mOliv

Rubiaceae

ST31

50plusmn24048plusmn024

58

2749

302plusmn02

00

17

11Mub

wegele

Sclerocarryabirrea

sbspbirr

eaAnacardiaceae

T34

21plusmn6061plusmn023

58

441

605plusmn03001plusmn001

28

12Mmem

enam

ene

Margaritaria

discoidea(Bail)

Euph

orbiaceae

SH51

68plusmn24032plusmn013

57

2073

307plusmn07

00

06

13Mkambala

Acaciamellifera

(Vahl)Be

nth

Mim

osaceae

T29

14plusmn5049plusmn019

50

359

302plusmn02

00

08

14Mugegere

Dich

rosta

chys

cinerea

(L)Wight

ampArn

Mim

osaceae

ST31

53plusmn26017plusmn009

47

3086

2959plusmn19003plusmn002

178

15Mbata

AcaciaseyalD

elvar

seyal

Mim

osaceae

T34

30plusmn10019plusmn006

45

887

311plusmn11001plusmn001

46

16Mgulumo

Lann

easchw

einfurthiiAnacardiaceae

T43

24plusmn7032plusmn009

39

544

907plusmn04002plusmn001

22

17Muyom

boBrachyste

giaboehmii

Caesalpiniaceae

T11

11plusmn7019plusmn015

38

1309

607plusmn05001plusmn001

22

18Mmulim

uli

Cassiaabbreviata

Caesalpiniaceae

T34

31plusmn13017plusmn007

36

1353

916plusmn12001plusmn001

49

19Mdavi

Cordiasin

ensis

Lam

Boraginaceae

ST6

23plusmn23011plusmn010

34

5498

302plusmn02

00

06

6 ISRN Biodiversity

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

20Mdw

endw

eTerm

inaliabrow

nii

Com

bretaceae

T17

14plusmn8019plusmn009

32

1129

305plusmn05

00

12

21Mfilafila

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T31

25plusmn8015plusmn005

30

646

605plusmn03

00

35

22Mkw

ata

Codyladensiflora

Caesalpiniaceae

T9

4plusmn2033plusmn019

28

282

334plusmn34004plusmn004

83

23Mgung

aAc

aciaabyssin

ica(H

ochst)

Mim

osaceae

T17

12plusmn7014plusmn007

24

1140

614plusmn12001plusmn001

39

24Mkole

Grew

iabicolor

Tiliaceae

ST26

21plusmn10008plusmn003

21

1078

605plusmn03

00

15

25Mparapand

eStrychnosp

otatorum

Lf

Loganiaceae

T23

23plusmn11014plusmn009

20

1331

607plusmn05

00

17

26Kitim

bwi

Orm

ocarpum

kirkii

Fabaceae

SH29

18plusmn6007plusmn003

19492

27Mtabagila

Lonchocarpus

capassa

Fabaceae

T26

11plusmn5014plusmn006

17550

302plusmn02

00

04

28Muw

otapon

ziOzoroainsig

nsssp

retic

ulata

Anacardiaceae

T14

10plusmn5010plusmn005

16564

1411plusmn05001plusmn000

31

29Msanzi

Gardeniaresin

iflua

Hiern

Rubiaceae

ST9

13plusmn8008plusmn005

161229

30Mkoga

Vitexpayos

Verbenaceae

ST17

12plusmn5011plusmn004

15605

302plusmn02

00

02

31Mpelem

eleGr

ewiaforbesiiHaw

Ex

Mast

Tiliaceae

ST14

16plusmn9005plusmn002

147

1246

32Mny

wenyw

eeDalbergiaboehmii

Fabaceae

T14

11plusmn7009plusmn007

151221

33Mulagavega

Albiziaam

ara(Roxb)

Boiv

Mim

osaceae

T14

9plusmn5004plusmn003

14712

34Mkola

Afzelia

quan

zensis

Caesalpiniaceae

T11

6plusmn3015plusmn009

14532

35Mugusi

Brachyste

giamanga

Caesalpiniaceae

T20

11plusmn6010plusmn007

13824

618plusmn13002plusmn002

25

36Mwaham

aShrebera

trichoclada

Oleaceae

T17

11plusmn6005plusmn002

12697

309plusmn09001plusmn001

15

37Mpingo

Dalbergia

mela

noxylon

Fabaceae

T11

11plusmn9004plusmn003

121655

314plusmn14001plusmn001

26

38Mub

aya

Strychnosinn

ocua

Loganiaceae

T17

8plusmn4011plusmn008

12375

302plusmn02001plusmn001

06

39Msisina

AlbiziaharveyiF

ournMim

osaceae

T14

5plusmn3008plusmn005

11359

305plusmn05002plusmn002

15

40Mlim

boEu

phorbiacuneata

Valh

Euph

orbiaceae

ST14

12plusmn6004plusmn002

11699

41Mwam

biElaeodendron

buchan

annii

Cela

steraceae

T3

8plusmn8003plusmn003

102000

42Mvembadand

aXe

roderris

stuhlmannii

Fabaceae

T14

4plusmn2011plusmn005

09

191

43Mtelela

Brachyste

giabu

ssei

Harms

Caesalpiniaceae

T6

2plusmn1012plusmn010

09

253

ISRN Biodiversity 7

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

44Mteresi

Prem

naholstiiGurke

Verbenaceae

ST9

8plusmn5003plusmn002

09

899

45Mkongolo

Commiphora

ugogensis

Burseraceae

T6

1plusmn1008plusmn006

08

097

302plusmn02001plusmn001

09

46Muw

isaBo

sciaangustifolia

A

Rich

varangustifo

liaCa

pparaceae

T17

8plusmn4004plusmn002

08

426

47Mnyalup

uko

Canthium

pseudoverticillatum

Hien

Rubiaceae

ST20

8plusmn4004plusmn002

07

414

48Mnyaluh

anga

Brideliascleu

roneura

MuellArg

Euph

orbiaceae

ST14

6plusmn3004plusmn002

07

341

49Mdide

Manilkaramochisia

(Bak)Dub

ard

Sapo

taceae

T9

5plusmn4002plusmn001

07

793

50Muh

emi

Erythrinaabyssin

icaFabaceae

T6

1plusmn1007plusmn006

07

163

51Msambarawe

Vangueria

infausta

BurchSspRo

tund

ataRu

biaceae

ST6

8plusmn5002plusmn002

06

925

52Mhehefu

Allophylu

sferrugineus

Taub

Sapind

aceae

SH9

5plusmn3002plusmn001

05

540

314plusmn14001plusmn001

14

53Mnyengrsquoenyengrsquoe

Excoecariabu

ssei

(Pax)

Euph

orbiaceae

ST11

4plusmn2001plusmn001

05

321

54Muganga

Berchemiadiscolor

Rham

naceae

T6

4plusmn3004plusmn003

04

717

55Mning

aPterocarpu

sangolensis

Fabaceae

T6

2plusmn1005plusmn004

04

253

309plusmn09006plusmn006

25

56Mtanang

we

Zizip

husm

ucronata

Rham

naceae

T3

4plusmn4003plusmn003

04

900

57Muh

ekele

Eucle

adivinorum

Hiern

Ebenaceae

ST3

3plusmn3001plusmn001

04

800

302plusmn02

00

49

58Mub

umila

Cassipourea

mollis

(REfr)Alstom

Rhizop

horaceae

T9

4plusmn3002plusmn001

04

526

302plusmn02

00

04

59Mkw

ambe

Flueggea

virosa

Willd

Euph

orbiaceae

SH6

3plusmn2003plusmn003

03

406

60Kivang

aZa

nhaafric

ana

(Radlk)Ex

ell

Sapind

aceae

T9

2plusmn1001plusmn001

02

212

302plusmn02

00

02

61Mning

amaji

Pterocarpu

stinctorius

Fabaceae

T3

0002plusmn002

02

100

62Mtosi

MaeruatriphyllaA

Rich

Capp

araceae

ST3

2plusmn2001plusmn001

02

600

63Mugosa

Ehretia

amoena

Boraginaceae

ST9

1plusmn1

00

01

094

64Mnyon

gamem

beStegan

otaenia

araliacea

Apiaceae

T6

1plusmn1

001

01

163

65Mvelevele

Vernoniaam

ygdalin

aAs

teraceae

SH3

2plusmn2001plusmn001

01

400

66Mpo

ngolo

Catunaregam

spinosa

(Thun

b)

Rubiaceae

ST3

1plusmn1001plusmn001

01

200

8 ISRN Biodiversity

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

67Mbo

liboli

Acaciadrepanolobium

(Harms)

Mim

osaceae

T3

000

01

100

68Mwim

akigulu

Maeruaangolen

sisCa

pparaceae

SH3

1plusmn1

00

01

300

69Mnyali

Tamarindu

sind

icaCa

esalpiniaceae

T6

1plusmn1001plusmn001

01

097

70Mgombw

ani

Combretum

aculeatum

Com

bretaceae

T6

1plusmn1

00

01

097

302plusmn02

00

04

71Msang

ala

Burkea

afric

anaHoo

kCa

esalpiniaceae

T3

0001plusmn001

01

100

302plusmn02

00

04

72Mkokonza

Opilia

amentacea

Roxb

Opiliaceae

SH3

000

00

100

311plusmn11

00

42

73Mfumbi

Kigelia

afric

ana

Bign

oniaceae

T3

000

00

100

74Mlang

ali

Euphorbia

cand

elabrum

Euph

orbiaceae

T3

000

00

100

75Mpu

lulu

Term

inaliaseric

eaCom

bretaceae

T3

000

00

100

76Mdaha

Diospyros

usam

barensisFWhite

Ebenaceae

T3

000

00

100

305plusmn05001plusmn001

15

77Mtund

wa

XimeniacaffraSond

Olacaceae

ST3

000

00

100

78Mwim

aperu

Tarenn

agla

veolens(S

Moo

re)B

rem

Rubiaceae

ST+

79Mwesa

Boscia

mossambicensisKl

Capp

araceae

ST+

80Musasam

ulo

Psychotria

schu

mmaniana

Rubiaceae

ST+

81Muh

anza

Senn

asin

gueana

Caesalpiniaceae

ST+

82Mtund

wahavi

Ximeniaam

erica

naOlacaceae

ST+

83Mtin

giligiti

Phyllanthu

sengler

iPax

Euph

orbiaceae

T+

84Msada

Vangueria

madagascarie

nsis

Gmel

Rubiaceae

ST+

85Mku

nung

uZa

nthoxylum

chalybeum

Rutaceae

T+

86Lu

kali

Croton

scheffleriP

axEu

phorbiaceae

SH+

87Kilim

andembw

eGardeniaternifolia

KSchu

mamp

Thon

nRu

biaceae

ST+

88MpelaM

buyu

Adan

soniadigitata

Bombacaceae

T++

Total(allspecies)

13511521plusmn5941355plusmn552

200

294

60plusmn30072plusmn049

200

+indicatesspecies

identifi

edam

ongsm

allerind

ividualswith

in5m

radius

plots(Dbhlt5c

m)and++

indicatesthata

largeind

ividualw

asidentifi

edwith

ina1

5-radius

plot

butw

asno

tincludedin

thea

nalyseso

fste

mdensitybasalareaand

volumea

sitw

asconsidered

anou

tlier

duetoits

tremendo

ussiz

e(Dbh

=340c

m)

ISRN Biodiversity 9

005 and that of small individuals was 006 The followingspecies were observed to have the greatest contributionsto the Shannon-Wiener diversity index of large individualsDalbergia arbutifolia (contributing 030) Combretum molle(020) Commiphora africana (019) Albizia petersiana (016)and Margaritaria discoidea (014) while for smaller ones thegreatest contributions were found for Brachystegia spiciformis(026) Dalbergia arbutifolia (024) Grewia forbesii (023)Margaritaria discoidea (020) and Dichrostachys cinerea(016) In terms of frequency of occurrence for standingindividuals (large sizes) Commiphora africana was the mostfrequent species (77 of plots) followed by Combretummolle (74) and Dalbergia arbutifolia (60) while for smallsizes Margaritaria discoidea (66) Markhamia obtusifolia(63) and Dalbergia arbutifolia (57) were the most fre-quent species The Importance Value Index (IVI) for largeindividuals (Dbh ge 5 cm) shows that Dalbergia arbutifolia(224) Commiphora africana (175) and Combretum molle(132) were the most important species among standingindividuals while Brachystegia spiciformis (308)Combretummolle (307) and Dichrostachys cinerea (178) appeared to bethe most important among harvested individuals (stumps)These species were also found to have higher frequencies thanany other harvested species observed in the GVLFR (Table 1)

33 Stem Density The total mean stem density for large indi-viduals with Dbh ge5 cm was 1521 plusmn 594 stemsha (Table 1)and that of small individuals with Dbh lt5 cm (includingindividuals with Dbh lt1 cm) was 14318 plusmn 6956 stemshaAmong large individuals the most abundant species wereDalbergia arbutifolia (162 of 1521 stemsha) Combretummolle (8) Commiphora africana (72) and Albizia peter-siana (53) Among small individuals the most abundantspecies were Brachystegia spiciformis (13 of 14318 stemsha)followed by Dalbergia arbutifolia (11) and Grewia forbesii(10) For stumps the overall mean density was 60 plusmn38 stemsha with Combretum molle (12) Dalbergia arbuti-folia (12) Brachystegia spiciformis (10) and Dichrostachyscinerea (10) contributing the most (Table 1) Generally thedistribution of standing trees to size classes showed the usualreverse J shape which was also approximately observed forstumps (Figure 3) However for stumps the density of stemsin the 1ndash10 cm diameter class was slightly lower than whatwould be expected if tree felling had been a random event

34 Basal Area For the GVLFR as a whole the meanbasal areas for large (ge5 cm Dbh) and small individuals(lt5 cm Dbh) were 1355 plusmn 552m2ha (Table 1 Figure 4)and 305 plusmn 002m2ha respectively The species contributingmost to the basal area of large individuals were Commiphoraafricana (12) Dalbergia arbutifolia (10) and Brachystegiaspiciformis (9) while those contributing most to the basalarea of smaller individuals were Dalbergia arbutifolia (16)Grewia forbesii (15) and Dichrostachys cinerea (13) Themean basal area for stumps was 072m2ha with Brachystegiaspiciformis contributing the greatest individual proportion(28) 41 species made up the rest (Figure 4)

60542

3335

530

113

28 24

346166

34

11

02

01

10

100

1000

10000

100000

Diameter classes (cm)

Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Stem

s (ha

minus1)

Figure 3 Density of standing trees ge1 cmDbh and stumps ge1 cm bydiameter class in Gangalamtumba VLFR (119899 = 35) NB logarithmicscale on vertical axis

744477

241

103041 055

014025 018

010004

001

01

1

10

Diameter classes (cm)Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Mea

n ba

sal a

rea (

m2

haminus1)

Figure 4 Distribution of basal area per hectare for standingtrees ge1 cm Dbh and stumps ge1 cm by diameter classes in theGangalamtumba VLFR (119899 = 35) NB logarithmic scale on verticalaxis

35 Volume The mean volumes for large (ge5 cm Dbh) andsmall individuals (lt5 cm Dbh) were 9217 plusmn 390m3ha and1257 plusmn 635m3ha respectively (not shown in tables) Thespecies contributing most to the volume of large individualswere Commiphora africana (12) Brachystegia spiciformis(10) Acacia sp (9) and Dalbergia arbutifolia (9) Forsmaller individuals the species that contributed most tovolume were Dalbergia arbutifolia (16) Grewia forbesii(14) and Dichrostachys cinerea (13) The mean remainingvolume of stumps was found to be 015 plusmn 01m3ha withBrachystegia spiciformis contributing the greatest individualpercentage (28) 41 species made up the rest

10 ISRN Biodiversity

36 Spatial Distribution Dispersion indices (DI) are pre-sented for individual species in Table 1 The dispersion indexvalues range from 094 indicating almost complete spatialrandomness or slight underdispersion to 5498 indicatingconsiderable overdispersion that is a patchy or clustereddistributionOut of 77 species excluding the single very largeAdansonia digitata that was considered an outlier 64 species(83) 9 species (12) and 4 species (5) were found tohave DI gt 1 DI = 1 and DI lt 1 respectively so the majorityof species are characterised by a patchy distribution acrossthe forest The species with the lowest estimated DI wasEhretia amoena (094) while the highest DI was estimated forCordia sinensis (5498)Themost abundant species includingDalbergia arbutifolia (DI = 4765) Combretum molle (DI =1523) and Commiphora africana (DI = 1142) are stronglyoverdispersed

37 Plant Communities and Species Association Four plantcommunities were identified through cluster analysis basedon the statistical significance (5) of the observed maximumindicator values (Table 2) Only two of these plant commu-nities were dominated by species from the family Caesalpini-aceae (Communities 1 and 24) The other two showed greatvariationoverlap between species of different plant families(Communities 3 and 5) The estimated Steinhaus similarityindices between pairs of plant communities varied from 32for Communities 1 and 3 and Communities 5 and 24 to 37for Communities 3 and 5 (not shown in tables)

The ordination diagram (Figure 5) shows that one topo-graphic and six edaphic variables appear to be associatedwiththe four plant communities and the species distribution inthe study area The strongest correlation with communitycomposition was observed for elevation followed by soilpH at 0ndash15 cm depth base cation Ca2+ at 0ndash15 cm depthpercent base saturation (BS) at 0ndash15 cm depth percent clayat 0ndash15 cm depth C N ratio at 15ndash30 cm depth and percentsand at 0ndash15 cm depth The base cations magnesium (Mg2+)and potassium (K+) were not directly correlated with thecommunity composition but since they are included in thebase saturation percentage they are indirectly related Plantcommunities were ordered along the second ordination axiswhich was positively correlated with pH15 (119903 = 071) Ca15(119903 = 069) BS (119903 = 065) andClay15 (119903 = 052) and negativelycorrelated with Sand15 (119903 = minus046) Axis 1 of the ordinationwas positively correlated with Elev (119903 = 085) and CNrat30(119903 = 051) As shown in Table 3 and indicated graphically inFigure 5 correlations between many of the edaphic variablesare strong particularly between pH15 Sand15 Clay15 Ca15and BS whereas correlation between topographic and mostedaphic variables is small and nonsignificant However thereis a significant negative correlation (119903 = minus042) between Elevand Sand15 indicating that sandy soils are mostly found atlower elevations

4 Discussion

41 Species Composition The results reported in this studyshow that the composition of the vegetation types found in

Elev

pH15Ca15

Sand15

Clay15

CNrat30

BS

Axis 1

Axis 2

Community 1Community 3

Community 5Community 24

Figure 5 Compositional gradients and plant communities in NMSordination of 35 vegetation plots for trees ge5 cm in GangalamtumbaVLFR Four plant communities are recognized (cf Table 2) Com-munity 1 = Brachystegia spiciformis Diplorynchus condylocarponand Lannea schweinfurthii woodland Community 3 = Dalbergiaarbutifolia Commiphora africana and Albizia petersianawoodlandCommunity 5 = Acacia sp Acacia abyssinica and Albizia amarawoodland and Community 24 = Bauhinia petersiana and Shreberatrichoclada woodland Elev elevation (m) CNrat30 C N ratio at15ndash30 cm depth Sand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm Ca15 = Ca2+ (cmol(+)kg) at 0ndash15 cm pH15 = soil pH at 0ndash15 cm BS base saturation at 0ndash15 cm

the GVLFR especially the dominance of species from thefamily Caesalpiniaceae agreed well with previous descrip-tions and classifications of plant communities commonlyfound in miombo woodlands [1] However the observeddominance based on IVI of the genera Dalbergia Com-miphora and Combretum contrasts with patterns usuallyconsidered common for miombo woodlands The frequencyof species in these genera was also high compared to otherspecies observed in the GVLFR (Table 1) Similar deviationsexist between the results obtained by Banda et al [26]in the Katavi-Rukwa ecosystem where they observed thatTerminalia and Combretum were the dominant genera andthe findings of Giliba et al [27] and Njana [43] whoboth noted the dominance of the two common miombogenera Brachystegia and Julbernardia However Combretumalso occurred in their study areas The results suggest thaton a larger spatial scale the species diversity of miombowoodlands is very high and that the three common generaBrachystegia Julbernadia and Isoberlinia are not alwaysdominant at the local scale

The species richness observed in the GVLFR compareswell with miombo community studies in other areas of drymiombo in Tanzania and elsewhere which receive an average

ISRN Biodiversity 11

Table2Plantcom

mun

itiesandspeciesa

ssociatio

nsin

thed

ryMiombo

woo

dlands

ofGangalamtumba

VLF

RCom

mun

itynu

mbers135and24

representthe

different

plantassociatio

ns

119899speciesnu

mbero

fspecies

(77in

total)with

Dbhge5c

mIV+

speciesind

icator

valuemeanplusmnstd

errorand

BAisbasalarea

Com

mun

ityAs

sociated

species

Family

Habit

IV+

()

Con

stancy

()119875value

Stem

sha

BA m2 ha

MeanDbh

Brachyste

giaspiciform

ismdashDiplorhynchus

cond

ylocarponmdashLa

nnea

schw

einfurthiiw

oodland

1(n s

pecies

=47

nplots=9)

Sitevariables(meanplusmnSE

)Elev

=1200plusmn20pH15

=644plusmn013C

a15=604plusmn128

Sand

15=721plusmn431C

lay15=137plusmn188Silt15

=142plusmn335C

Nrat30=135plusmn05andBS

=526plusmn65

Brachyste

gia

spiciform

isCa

esalpiniaceae

T820

100

000

02164plusmn59356plusmn077138plusmn07

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T759

89000

0866plusmn18044plusmn01382plusmn05

Lann

easchw

einfurthii

Anacardiaceae

T719

100

000

0449plusmn14072plusmn022126plusmn09

Bosciaangustifolia

Capp

araceae

T536

5600056

27plusmn12014plusmn00776plusmn06

Euphorbiacuneata

Euph

orbiaceae

ST428

4400200

42plusmn19012plusmn00665plusmn06

Other

species

mdashmdash

mdashmdash

mdash1075plusmn5741007plusmn647102plusmn03

Subtotal

1423plusmn174

1505plusmn178

109plusmn03

DalbergiaarbutifoliamdashCo

mmiphora

afric

anamdash

Albizia

petersiana

woo

dland

3(n

species=55n

plots=

16)Site

variables(meanplusmnSE

)Elev

=986plusmn19pH15

=648plusmn009C

a15=856plusmn109

Sand

15=767plusmn156C

lay15=135plusmn155Silt15

=97plusmn096C

Nrat30=106plusmn03andBS

=744plusmn44

Dalbergiaarbutifolia

Fabaceae

subfam

ilyPapilio

noideae

ST793

100

000

02500plusmn123263plusmn06477plusmn02

Commiphora

afric

ana

Burseraceae

T542

9400026

187plusmn40272plusmn064119plusmn06

Albiziapetersiana

Mim

osacea

T536

7500200

157plusmn57103plusmn04084plusmn02

Sclerocarryabirrea

Anacardiaceae

T504

6300186

40plusmn11128plusmn045168plusmn17

Other

species

mdashmdash

mdashmdash

mdash852plusmn449669plusmn37788plusmn03

Subtotal

1735plusmn166

1435plusmn071

92plusmn02

Acaciaspmdash

Acaciaabyssin

icamdash

Albiziaam

arawoo

dland

5(n

species=33n

plots=5)

Sitevariables(m

eanplusmnSE

)Elev

=986plusmn52pH15

=734plusmn023C

a15=139plusmn33

Sand

15=745plusmn678C

lay15=148plusmn47Silt15

=107plusmn26C

Nrat30=106plusmn07andBS

=963plusmn89

Acaciasp

Mim

osaceae

T981

100

000

02269plusmn111662plusmn286172plusmn14

Acaciaabyssin

icaMim

osaceae

T594

8000030

31plusmn9060plusmn03299plusmn08

Albiziaam

ara

Mim

osaceae

T552

60000

6654plusmn30023plusmn01671plusmn08

Grew

iabicolor

Tiliaceae

ST533

6000106

113plusmn52040plusmn01770plusmn04

Acaciaseyal

Mim

osaceae

T433

6000526

62plusmn34034plusmn01790plusmn05

Other

species

mdashmdash

mdashmdash

mdash665plusmn533552plusmn49872plusmn04

Subtotal

1194plusmn169

1367plusmn347

101plusmn05

Bauh

iniapetersiana

mdashShrebera

trichoclada

woo

dland

24(n

species=35n

plots=5)

Sitevariables(meanplusmnSE

)Elev

=1175plusmn25pH15

=73plusmn04C

a15=254plusmn69

Sand

15=522plusmn68C

lay15=331plusmn28

Silt15=147plusmn44C

Nrat30=961plusmn13andBS

=1041plusmn204

Bauh

iniapetersiana

Caesalpiniaceae

SH551

8000118192plusmn121111plusmn05075plusmn03

Shrebera

trichoclada

Oleaceae

T505

6000110

57plusmn32022plusmn01380plusmn05

Manilkaramochisia

Sapo

taceae

T376

4000332

34plusmn27014plusmn00969plusmn10

Dalbergia

mela

noxylon

Fabaceae

T370

4000380

68plusmn58026plusmn02266plusmn03

Ehretia

amoena

Boraginaceae

ST347

4000344

6plusmn4

002plusmn00170plusmn04

Other

species

mdashmdash

mdashmdash

mdash982plusmn759643plusmn47999plusmn05

Subtotal

1338plusmn137

817plusmn087

91plusmn04

Total

1521plusmn5941355plusmn55298plusmn01

Elevelevatio

n(m

)CN

rat30CN

ratio

at15ndash30c

mdepthSand

15sand(

)at0

ndash15c

mC

lay15clay

()at0

ndash15c

mSilt15silt

()at0

ndash15c

mC

a15Ca2+(cmol(+)kg)at0

ndash15c

mpH15soilp

Hat0ndash

15cm

BS

base

saturatio

nat0ndash

15cm

12 ISRN Biodiversity

Table 3 Pearson-correlation matrix for two topographic and eight edaphic variablesdagger associated with the classified plant communities in theGangalamtumba VLFR (119899 = 35) Applied significance levels lowast5 lowastlowast1 and lowastlowastlowast01 +not significant

Elev Slope pH15 Ca15 K15 N15 Sand15 Clay15 CNrat30Slope 019+

pH15 minus013+ minus033lowast

Ca15 002+ minus020+ 083lowastlowastlowast

K15 minus029+ 000+ 010+ 012+

N15 006+ 036lowast 010+ 041lowastlowast 033lowast

Sand15 minus042lowastlowast 003+ minus053lowastlowastlowast minus074lowastlowastlowast 006+ minus046lowastlowast

Clay15 031+ minus012+ 051lowastlowast 076lowastlowastlowast minus001+ 047lowastlowast minus086lowastlowastlowast

CNrat30 036lowast 010+ minus039lowast minus051lowastlowast minus015+ minus019+ 040lowast minus048lowastlowast

BS minus024+ minus017+ 084lowastlowastlowast 091lowastlowastlowast 015+ 037lowast minus058lowastlowastlowast 060lowastlowastlowast minus051lowastlowastdaggerElev elevation (m) pH15 soil pH at 0ndash15 cm Ca15 Ca2+ (cmol(+)kg) at 0ndash15 cm K15 K+ (cmol(+)kg) at 0ndash15 cm N15 N concentration at 0ndash15 cmSand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm CNrat30 C N ratio at 15ndash30 cm depth BS base saturation at 0ndash15 cm 119905-value was calculated as119905 = 119903radic(119899 minus 2)(1 minus 119903

2) where 119903 is the Pearson-correlation coefficient and 119899 is the total sample size

Table 4 Species richness observed in other studies from drymiombo woodlands

Plot size(ha)

Totalnumberof plots

Total samplearea(ha)

Total numberof species References

0071 70 495 82 [43]0071 80 565 110 [27]0071 133 940 229 [26]0071 247 1746 102 [44]004 40 160 81 [45]025 14 350 69 [25]01 2 020 40 [28]01 152 1520 92 genera [22]0071 35 247 88 This study

annual rainfall of 565ndash1500mm (Table 4) Using plot sizes of004ndash025 ha and sample sizes of 2ndash247 plots a total numberof species ranging from40 (Dbhge 10 cm) to 229 (Dbhge 2 cm)have been reported fromMiombowoodlands [22 25ndash28 43ndash45]

The high number of species reported by Banda et al [26]Chidumayo [22] Isango [45] and Chamshama et al [44] islikely to be a consequence of the spatial scale and coverage ofthese studies as they all cover large areas include more thanone site and operate with large sample sizes For exampleChidumayo [22] included species from both wet and dryMiombo areas in Zambia The study by Sauer and Abdallah[15] who reported a total of 131 species occurring in thetobacco growing zone of Iringa rural district included twoforest reserves and three family-managed forests Thereforeconsidering the climatic conditions in the GVLFR (617mmof rainfall per year) and the sample size (35 plots) thespecies richness reported in this study can be ranked atleast as high or higher than those found in the studiesmentioned The selective sampling approach focusing onvarious microhabitat types adopted by Banda et al [26] mayhave contributed to the large number of species observed

in their study area Similarly the higher number of speciesfound by Giliba et al [27] was probably due to the presenceof riverine forest offering site conditions favourable formanyspecies

The values of the Shannon-Wiener (1198671015840 = 344) andSimpson indices (119863 = 005) reported for large individ-uals in this study are within the range observed for mostcommunities of particular life forms [36] For example 1198671015840usually does not exceed 5 although this maximum valuevaries depending on the type of the biological communitysampled and the sampling approach applied (eg minimumdiameter and size of sample units) A threshold value of 2 for1198671015840 has been mentioned as a minimum value above which

an ecosystem can be regarded as medium to highly diverse[27] Chamshama et al [44] reported three 1198671015840 values of31 32 and 33 from Kitulangalo Miombo forest in EasternTanzania while Njana [43] reported a 1198671015840 value of 340from dry Miombo forest in Western Tanzania The studiesby Sauer and Abdallah [15] and Giliba et al [27] reportedparticularly high values of 346 and 427 respectively Thiscould be attributed to the very large sample sizes used inboth studies and the presence of riverine forest where thechance of encountering many rare species is likely to be highThe forests examined in the mentioned studies receive anaverage annual rainfall of 700ndash1000mm compared to whichthe rainfall in the GVLFR is low (617mm on average per yearcf above)The relatively high diversity found inGVLFRmusttherefore be attributed to other factors than climate The soilanalyses indicate that the soil fertility level in the GVLFRis relatively high with considerable proportions of all 2 1lattice clay minerals (114) (ie illite montmorillonite andvermiculite) plus a good amount of organic matter whichmay suggest that the soil has large reserves of important plantnutrients for example K Mg and Fe The base saturationpercentage (BS) which is normally used to indicate the soilfertility status (Landon 1991) was also high 76 on averageand with 86 of the samples (30 samples) with BS valuesgt50 (fertile soil) and only 14 of the samples (5 samples)with BS below 50 (less fertile soil) As another indicationof high soil fertility status the mean C N ratio was 12 plusmn 043

ISRN Biodiversity 13

(range 7ndash19) for top soil (0ndash15 cm) and 11 plusmn 036 (range 5ndash16) for subsoil (15ndash30 cm) In general the values for both soilstrata fall within the expected range of 8ndash17 Soil pH values(mean 67 plusmn 01 range 567ndash852)were alsowithin the optimalrangewhere all the nutrients that aremost important for plantgrowth (Ca Mg K and P) are available and accessible toplants [46] In this study 97 of the soil samples had pHbelow 8 (one sample had a pH of 852) Fisher and Binkley[47] noted that high pH is almost never a problem in forestsas most trees do well across the full range of common pHvaluesTherefore considering the low average annual rainfallcompared to other forests the relatively high fertility of theGVLFR may be the main factor creating an environmentfavourable to many species thus leading to a quite highspecies diversity observed in this forest

Based on the Importance Value Index Brachystegia spi-ciformis and Combretum molle appeared to be the mostimportant species among harvested trees (stumps) in thestudy area This result agreed very well with the large valuesof basal area and volume and the information obtained fromlocal scouts and members of the village environmental com-mittee who said that the most frequently harvested speciesfor charcoal making include all Brachystegia species found inthe forest (ie Brachystegia spiciformis Brachystegia mangaBrachystegia boehmii and Brachystegia bussei) Among theCombretum species the most important one (based on IVI)Combretum molle is mostly used for house construction andfirewood rather than for charcoal making Apart from theBrachystegia species the only other species mentioned asimportant for charcoal making was Acacia mellifera Otherspecies are only used in case they happen to fall when fellingthe preferred species during the preparation of charcoal kilnsWith respect to stumps Brachystegia spiciformis Brachystegiamanga and Combretum molle are among the ten mostabundant species in terms of density basal area and volumeper hectare Stumps of the other species mentioned are notcommonly found a factwhichmay be due to the small samplesize being unable to capture sites where these species areharvested but may also be related to their limited distributionin the forest as indicated by the estimated dispersion indices(see Table 1)

42 Forest Structure Species densities reported from otherMiombo woodland areas in Tanzania are typically 348ndash1495stemsha for trees with Dbh gt4 cm [24 43 45] Comparedwith this the GVLFR is highly stocked as the estimateddensity is 2296 stemsha for trees with Dbh gt4 cmThemeanstem density of 1521 plusmn 594ha for trees with Dbh ge5 cmis also more than twice as large as values found in otherstudies [25ndash27 44 45 48] A similar pattern is seen whencomparing the density of regeneration between the studiesThe diameter distribution is characterised by a very cleartrend of decreasing stem density with increasing diameterThe shape of the distribution is thus an inverted ldquoJrdquo (Figure 3)which is a common feature of natural forests with activeregeneration and recruitment [49] However not many largetrees were captured by the sample whereas a considerablenumber of relatively large stumps were observed suggestingthat anthropogenic activities such as charcoal making may

have affected the structure and ecological balance of the forest(see Figure 3) Since the woodlands are often hit by fire whichtends to kill the seedlings (especially the late fires) and thusonly few seedlings can be expected to reach larger diameterclasses lack of mature trees and the resulting lack of seedsmay eventually threaten the biodiversity of the forest

The mean basal area of 1355 plusmn 552m2ha observedin this study is slightly above the range of values typicallyreported from the miombo region 75ndash126m2ha [26 28 4344 50] However the basal areas reported by Isango [45] werea bit higher (1504ndash1563m2ha) than observed in this study

Themean total volume inGVLFRwas estimated at 9217plusmn390m3ha for trees with Dbh ge5 cm Other studies in dryMiombo woodlands have reported mean volumes of 167ndash7603m3ha [24 44 45 50] The current standing volume ofGVLFR is thus slightly higher than values typically reportedfor forests in the Miombo ecoregion A plausible reason forthis may be that compared to other forests the GVLFR isstill well stocked despite ongoing human activities such ascharcoalmakingThebasal area observed for stumpswas only072m2ha so there is no indication of intensive extractionover many years This corresponds well with the findings ofTreue et al [20] who conclude that the estimated 04m3haannual extraction of woody biomass from GVLFR is consid-erably below its estimated annual increment of 15m3ha andthat the local forest managers seem capable of regulating theharvesting activities which in addition to village membersrsquocollection for subsistence uses also included commercialcharcoal production by external companies that pay a fee perbag of charcoal extracted to the village government

43 Plant Communities and Species Associations Except forBrachystegia spiciformis the majority of the Brachystegia andJulbernardia species that are common to miombo wood-lands elsewhere are not among the species most commonlyobserved in this study A similar pattern was observed byBanda et al [26] in the Katavi-Rukwa ecosystem wherethe genera that are most common in miombo woodlandsBrachystegia Julbernardia and Isoberlinia were not commonin their study sites Furthermore the four plant communi-ties distinguished in this study are comparable with thosereported by other studies in Tanzania including the work byMunishi et al [29] in theMiombowoodlands of Rukwa basinChunya district Tanzania and the study by Banda et al [26]in the Katavi-Rukwa ecosystem

Elevation was noted by Munishi et al [29] to be themost important factor shaping the species communities intheir study area This study found a similar pattern with thehighest coefficient of correlation observed for elevation sug-gesting that topographical variation is among the strongestdeterminants of community composition in dry Miombowoodlands hence influencing the spatial distribution ofspecies strongly However in our study area edaphic factorsalso influenced the species distribution directly Two plantcommunities occurredmainly on clayey soils with high pH atintermediate elevations one on sandy soils with lowpHat lowelevations and one on sandy-clayey soils at higher elevationsand with neutral soil pH (Figure 5) Specifically it appeared

14 ISRN Biodiversity

that the Acacia woodland category (Community 5) grows atlow elevations around temporary streams (or at least wherethe ground water table is relatively high) and the Bauhiniawoodland category (Community 24) appearsmostly in placeswith a relatively high percentage of clay (and therefore highvalues of pH Ca and BS) By contrast it appeared that theDalbergia woodland category (Community 3) is located atmore sandy sites (with low values of pH Ca and BS) andthe Brachystegia woodland category (Community 1) seemedto be located mostly at higher elevations where the CN-ratio is quite high Correlations between elevation and thebasic soil variables pH Ca and percentages of sand andclay were low (cf Figure 5) Thus the results indicate thatthe plant communities of the dry miombo woodlands inGVLFR are not only shaped by the topographic variation(elevation) and the groundwater level but also by basic soilcharacteristics The results thus confirm findings from otherstudies detecting effects of elevation and soil characteristicson species composition [51 52]

5 Conclusion

Considering that the sample size used in this study wassmaller than samples used in other studies in dry miombowoodlands the results show that the species diversity inGVLFR is relatively high compared to other forest reservesThe vegetation of GVLFR is characterised by high densitybasal area and volume and despite the scarcity of largediameter trees this indicates that the forest is in a goodcondition The effect of anthropogenic activities is neverthe-less evident and stresses the need for proper managementespecially for economically important species preferred forcharcoalmaking (egBrachystegia spiciformis) if the currentspecies diversity is to be maintained or enhanced A repeatedfuture study would be needed to assess whether the currentcommunity-based management regime yields this intendedoutcome but the available information and analyses allow forsome optimism in this respect

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors wish to thank people from Mfyome villagefor their invaluable assistance during field work Mzee IddiKaheya Damian Chotamasege AugustinoMkwama Libera-tus Simime and Mawazo Nyangwa Furthermore thanks aredue to Venancia Mlelwa from Sokoine University and MadsMadsen Krag from University of Copenhagen for doing thelaboratory work The authors also wish to thank GoodluckMoshi their driverMarcoNjana andNassoroHMagogo theTAFORI botanist for assisting with species identification andKlaus Dons for preparing a study site map Financial supportwas provided by Danida through the ENRECA Project

ldquoParticipatory forest management for rural livelihoods forestconservation and good governance in Tanzaniardquo (no 725)

References

[1] P G H Frost ldquoThe Ecology of Miombo Woodlandsrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 11ndash57 1996

[2] N Burgess J Hales E Underwood et al Terrestrial Ecoregionsof Africa and Madagascar A Conservation Assessment IslandPress World Wildlife Fund 2004

[3] J Clarke W Cavendish and C Coote ldquoRural householdsand miombo woodlands use value and managementrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 101ndash135 1996

[4] B M Campbell A Angelsen A Cunningham Y KaterereA Sitoe and S Wunder ldquoMiombo woodlandsmdashopportunitiesand barriers to sustainable forest managementrdquo httpsener-gypediainfoimages66dMiombo2007pdf

[5] S Syampungani P W Chirwa F K Akinnifesi G Sileshi andO C Ajayi ldquoTheMiombo woodlands at the cross roads poten-tial threats sustainable livelihoods policy gaps and challengesrdquoNatural Resources Forum vol 33 no 2 pp 150ndash159 2009

[6] J I O Abbot and K Homewood ldquoA history of change causesof miombo woodland decline in a protected area in MalawirdquoJournal of Applied Ecology vol 36 no 3 pp 422ndash433 1999

[7] E J Luoga E T F Witkowski and K Balkwill ldquoLand coverand use changes in relation to the institutional frameworkand tenure of land and resources in eastern Tanzania Miombowoodlandsrdquo Environment Development and Sustainability vol7 no 1 pp 71ndash93 2005

[8] FAO The State of Food and Agriculture 2010-2011 Forest andAgriculture Organization Rome Italy 2010

[9] A H Gentry ldquoTropical forest biodiversity distributional pat-terns and their conservational significancerdquo Oikos vol 63 no1 pp 19ndash28 1992

[10] O E Sala F S Chapin III J J Armesto et al ldquoGlobalbiodiversity scenarios for the year 2100rdquo Science vol 287 no5459 pp 1770ndash1774 2000

[11] H J Geist and E F Lambin ldquoProximate causes and underlyingdriving forces of tropical deforestationrdquo BioScience vol 52 no2 pp 143ndash150 2002

[12] R S DeFries ldquoTropical forests deforestation and ecosystemsservices Contributions of remote sensingrdquo in GeoinformaticsFor Tropical Ecosystems P S Roy Ed pp 1ndash32 2003

[13] B M Campbell P Frost and N Bryon ldquoMiombo woodlandsand their use overview and key issuesrdquo in The Miombo inTransition Woodlands and Welfare in Africa B Campbell Edpp 1ndash10 2006

[14] H J Geist ldquoGlobal assessment of deforestation related totobacco farmingrdquo Tobacco Control vol 8 no 1 pp 18ndash28 1999

[15] J Sauer and J M Abdallah ldquoForest diversity tobacco produc-tion and resource management in Tanzaniardquo Forest Policy andEconomics vol 9 no 5 pp 421ndash439 2007

[16] E N Chidumayo and K J Mbata ldquoShifting cultivation ediblecaterpillars and livelihoods in the Kopa area of northernZambiardquo Forests Trees and Livelihoods vol 12 no 3 pp 175ndash1932002

[17] E N Chidumayo and L Kwibisa ldquoEffects of deforestation ongrass biomass and soil nutrient status in miombo woodlandZambiardquo Agriculture Ecosystems and Environment vol 96 no1ndash3 pp 97ndash105 2003

ISRN Biodiversity 15

[18] J F Lund and T Treue ldquoAre we getting there Evidence ofdecentralized forest management from the Tanzanian miombowoodlandsrdquoWorld Development vol 36 no 12 pp 2780ndash28002008

[19] T Blomley and S Iddi Participatory Forest Management inTanzania 1993ndash2009mdashLessons Learned and Experiences toDate Ministry of Natural Resources and Tourism Forestry andBeekeeping Division Dar es Salaam Tanzania 2009

[20] T Treue Y M Ngaga H Meilby et al ldquoDoes participatoryforest management promote sustainable forest utilisation inTanzaniardquo International Forestry Review vol 16 no 1 pp 1ndash162014

[21] Ministry ofNatural Resources andTourismParticipatory ForestManagement in Tanzania Facts and Figures Forestry andBeekeeping Division Dar es Salaam Tanzania 2008

[22] E N Chidumayo ldquoSpecies structure in Zambian miombowoodlandrdquo Journal of Tropical Ecology vol 3 no 2 pp 109ndash1181987

[23] J D Lowore ldquoCoppice regeneration in some miombo wood-lands of Malawirdquo FRIM Report 99001 Forestry ResearchInstitute of Malawi 1999

[24] E J Luoga E T F Witkowski and K Balkwill ldquoHarvestedand standing wood stocks in protected and communal miombowoodlands of eastern Tanzaniardquo Forest Ecology and Manage-ment vol 164 no 1ndash3 pp 15ndash30 2002

[25] M Williams C M Ryan R M Rees E Sambane J Fernandoand J Grace ldquoCarbon sequestration and biodiversity of re-growing miombo woodlands in Mozambiquerdquo Forest Ecologyand Management vol 254 no 2 pp 145ndash155 2008

[26] T Banda NMwangulango BMeyer et al ldquoThewoodland veg-etation of the Katavi-Rukwa ecosystem in western TanzaniardquoForest Ecology andManagement vol 255 no 8-9 pp 3382ndash33952008

[27] R A Giliba E K Boon C J Kayombo E B Musamba AM Kashindye and P F Shayo ldquoSpecies composition richnessand diversity in Miombo Woodland of Bereku Forest ReserveTanzaniardquo Journal of Biodiversity vol 2 no 1 pp 1ndash7 2011

[28] D D Shirima P K T Munishi S L Lewis et al ldquoCarbonstorage structure and composition of miombo woodlands inTanzaniarsquos Eastern Arc Mountainsrdquo African Journal of Ecologyvol 49 no 3 pp 332ndash342 2011

[29] P K T Munishi R A P C Temu and G Soka ldquoPlant com-munities and tree species associations in a Miombo ecosystemin the Lake Rukwa basin Southern Tanzania implications forconservationrdquo Journal of Ecology and Natural Environment vol3 no 2 pp 63ndash71 2011

[30] J Dewis and F Freitas ldquoPhysical analysis of soilsrdquo in Physicaland Chemical Methods of Soil andWater Analysis FAO Bulletinno 10 pp 51ndash57 2nd edition 1970

[31] S R Olsen and L E Sommers ldquoPhosphorusrdquo inMethods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 403ndash430 American Societyof Agronomy Madson Wis USA 1982

[32] J D Rhoades ldquoCation exchange capacityrdquo in Methods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 149ndash157 American Society ofAgronomy Madson Wis USA 1982

[33] IMatejovic ldquoDetermination of carbon hydrogen and nitrogenin soils by automated elemental analysis (dry combustionmethod)rdquo Communications in Soil Science and Plant Analysisvol 24 no 17-18 pp 2213ndash2222 1993

[34] J P Moslashberg Soil Analysis Manual Revised Edition Laboratoryof Soil Sciences Department of Soil Science SokoineUniversityof Agriculture Morogoro Tanzania 2001

[35] N C BradyThe Nature and Properties of Soils Macmillan 8thedition 1974

[36] C J Krebs Ecological Methodology Hamper Collins PublishersNew York NY USA 2nd edition 1999

[37] B Husch T W Beers and J A Kershaw Forest MensurationJohn Wiley amp Sons Hoboken NJ USA 4th edition 2003

[38] E E Mwakalukwa H Meilby and T Treue ldquoVolume andaboveground biomass models for dry Miombo Woodland inTanzaniardquo In press

[39] M Kent Vegetation Description and Analysis A PracticalApproach Wiley-Blackwell John Wiley amp Sons Hoboken NJUSA 2nd edition 2012

[40] B McCune and M J Mefford PC-ORD Multivariate Analysisof Ecological Data Version 6 MjM Software Gleneden BeachOre USA 2011

[41] MDufrene andP Legendre ldquoSpecies assemblages and indicatorspecies the need for a flexible asymmetrical approachrdquo EcologyMonography vol 67 pp 777ndash795 1997

[42] J E PeckMultivariate Analysis for Community Ecologists Step-by-Step using PC-ORD MjM Software Design Gleneden BeachOre USA 2010

[43] M A Njana Arborescent species diversity and stocking inMiombo Woodland of Urumwa forest reserve and their contri-bution to Livelihoods Tabora Tanzania [MS thesis] SokoineUniversity of Agriculture Morogoro Tanzania 2008

[44] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal no 200 pp 59ndash70 2004

[45] J Isango ldquoStand structure and tree species composition ofTanzania miombo woodlands a case study from miombowoodlands of community based forest management in Iringadistrictrdquo in MITMIOMBOmdashManagement of Indigenous TreeSpecies For EcosystemRestoration andWood Production in Semi-Arid Miombo Woodlands in Eastern Africa Proceedings ofthe 1st MITMIOMBO Project Workshop held in MorogoroTanzania 6th-12th February 2007 Working Papers of theFinnish Forest Research Institute no 50 pp 43ndash56 2007

[46] J R Landon Booker Tropical Soil Manual A Handbook ForSoil Survey and Agricultural Land Evaluation in the Tropics andSubtropics Longman Scientific amp Technical and John Wiley ampSons 1991

[47] R F Fisher and D Binkley Ecology and Management of ForestSoils John Wiley amp Sons 3rd edition 2000

[48] W A Rees ldquoPreliminary studies into bush utilization by Cattlein Zambiardquo Journal of Applied Ecology vol 11 pp 207ndash214 1974

[49] S M Philip Measuring Trees and Forests CAB InternationalWallingford UK 2nd edition 1994

[50] J D Lowore P G Abbot and M Werren ldquoStackwood volumeestimations formiombowoodlands inMalawirdquoCommonwealthForestry Review vol 73 no 3 pp 193ndash197 1994

[51] D Kubota T Masunaga Hermansah et al ldquoSoil environmentand tree species diversity in tropical rain forest West SumatraIndonesiardquo in Soils of Tropical Forest Ecosystems CharacteristicsEcology and Management A Schulte and D Ruhiyat Eds pp159ndash167 1998

[52] P K T Munishi T H Shear T Wentworth and R A PC Temu ldquoCompositional gradients of plant communities insubmontane rainforests of EasternTanzaniardquo Journal of TropicalForest Science vol 19 no 1 pp 35ndash45 2007

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

EcosystemsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MeteorologyAdvances in

EcologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Marine BiologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental Chemistry

Atmospheric SciencesInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Geological ResearchJournal of

EarthquakesJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BiodiversityInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

Page 6: Research Article Floristic Composition, Structure, and

6 ISRN Biodiversity

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

20Mdw

endw

eTerm

inaliabrow

nii

Com

bretaceae

T17

14plusmn8019plusmn009

32

1129

305plusmn05

00

12

21Mfilafila

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T31

25plusmn8015plusmn005

30

646

605plusmn03

00

35

22Mkw

ata

Codyladensiflora

Caesalpiniaceae

T9

4plusmn2033plusmn019

28

282

334plusmn34004plusmn004

83

23Mgung

aAc

aciaabyssin

ica(H

ochst)

Mim

osaceae

T17

12plusmn7014plusmn007

24

1140

614plusmn12001plusmn001

39

24Mkole

Grew

iabicolor

Tiliaceae

ST26

21plusmn10008plusmn003

21

1078

605plusmn03

00

15

25Mparapand

eStrychnosp

otatorum

Lf

Loganiaceae

T23

23plusmn11014plusmn009

20

1331

607plusmn05

00

17

26Kitim

bwi

Orm

ocarpum

kirkii

Fabaceae

SH29

18plusmn6007plusmn003

19492

27Mtabagila

Lonchocarpus

capassa

Fabaceae

T26

11plusmn5014plusmn006

17550

302plusmn02

00

04

28Muw

otapon

ziOzoroainsig

nsssp

retic

ulata

Anacardiaceae

T14

10plusmn5010plusmn005

16564

1411plusmn05001plusmn000

31

29Msanzi

Gardeniaresin

iflua

Hiern

Rubiaceae

ST9

13plusmn8008plusmn005

161229

30Mkoga

Vitexpayos

Verbenaceae

ST17

12plusmn5011plusmn004

15605

302plusmn02

00

02

31Mpelem

eleGr

ewiaforbesiiHaw

Ex

Mast

Tiliaceae

ST14

16plusmn9005plusmn002

147

1246

32Mny

wenyw

eeDalbergiaboehmii

Fabaceae

T14

11plusmn7009plusmn007

151221

33Mulagavega

Albiziaam

ara(Roxb)

Boiv

Mim

osaceae

T14

9plusmn5004plusmn003

14712

34Mkola

Afzelia

quan

zensis

Caesalpiniaceae

T11

6plusmn3015plusmn009

14532

35Mugusi

Brachyste

giamanga

Caesalpiniaceae

T20

11plusmn6010plusmn007

13824

618plusmn13002plusmn002

25

36Mwaham

aShrebera

trichoclada

Oleaceae

T17

11plusmn6005plusmn002

12697

309plusmn09001plusmn001

15

37Mpingo

Dalbergia

mela

noxylon

Fabaceae

T11

11plusmn9004plusmn003

121655

314plusmn14001plusmn001

26

38Mub

aya

Strychnosinn

ocua

Loganiaceae

T17

8plusmn4011plusmn008

12375

302plusmn02001plusmn001

06

39Msisina

AlbiziaharveyiF

ournMim

osaceae

T14

5plusmn3008plusmn005

11359

305plusmn05002plusmn002

15

40Mlim

boEu

phorbiacuneata

Valh

Euph

orbiaceae

ST14

12plusmn6004plusmn002

11699

41Mwam

biElaeodendron

buchan

annii

Cela

steraceae

T3

8plusmn8003plusmn003

102000

42Mvembadand

aXe

roderris

stuhlmannii

Fabaceae

T14

4plusmn2011plusmn005

09

191

43Mtelela

Brachyste

giabu

ssei

Harms

Caesalpiniaceae

T6

2plusmn1012plusmn010

09

253

ISRN Biodiversity 7

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

44Mteresi

Prem

naholstiiGurke

Verbenaceae

ST9

8plusmn5003plusmn002

09

899

45Mkongolo

Commiphora

ugogensis

Burseraceae

T6

1plusmn1008plusmn006

08

097

302plusmn02001plusmn001

09

46Muw

isaBo

sciaangustifolia

A

Rich

varangustifo

liaCa

pparaceae

T17

8plusmn4004plusmn002

08

426

47Mnyalup

uko

Canthium

pseudoverticillatum

Hien

Rubiaceae

ST20

8plusmn4004plusmn002

07

414

48Mnyaluh

anga

Brideliascleu

roneura

MuellArg

Euph

orbiaceae

ST14

6plusmn3004plusmn002

07

341

49Mdide

Manilkaramochisia

(Bak)Dub

ard

Sapo

taceae

T9

5plusmn4002plusmn001

07

793

50Muh

emi

Erythrinaabyssin

icaFabaceae

T6

1plusmn1007plusmn006

07

163

51Msambarawe

Vangueria

infausta

BurchSspRo

tund

ataRu

biaceae

ST6

8plusmn5002plusmn002

06

925

52Mhehefu

Allophylu

sferrugineus

Taub

Sapind

aceae

SH9

5plusmn3002plusmn001

05

540

314plusmn14001plusmn001

14

53Mnyengrsquoenyengrsquoe

Excoecariabu

ssei

(Pax)

Euph

orbiaceae

ST11

4plusmn2001plusmn001

05

321

54Muganga

Berchemiadiscolor

Rham

naceae

T6

4plusmn3004plusmn003

04

717

55Mning

aPterocarpu

sangolensis

Fabaceae

T6

2plusmn1005plusmn004

04

253

309plusmn09006plusmn006

25

56Mtanang

we

Zizip

husm

ucronata

Rham

naceae

T3

4plusmn4003plusmn003

04

900

57Muh

ekele

Eucle

adivinorum

Hiern

Ebenaceae

ST3

3plusmn3001plusmn001

04

800

302plusmn02

00

49

58Mub

umila

Cassipourea

mollis

(REfr)Alstom

Rhizop

horaceae

T9

4plusmn3002plusmn001

04

526

302plusmn02

00

04

59Mkw

ambe

Flueggea

virosa

Willd

Euph

orbiaceae

SH6

3plusmn2003plusmn003

03

406

60Kivang

aZa

nhaafric

ana

(Radlk)Ex

ell

Sapind

aceae

T9

2plusmn1001plusmn001

02

212

302plusmn02

00

02

61Mning

amaji

Pterocarpu

stinctorius

Fabaceae

T3

0002plusmn002

02

100

62Mtosi

MaeruatriphyllaA

Rich

Capp

araceae

ST3

2plusmn2001plusmn001

02

600

63Mugosa

Ehretia

amoena

Boraginaceae

ST9

1plusmn1

00

01

094

64Mnyon

gamem

beStegan

otaenia

araliacea

Apiaceae

T6

1plusmn1

001

01

163

65Mvelevele

Vernoniaam

ygdalin

aAs

teraceae

SH3

2plusmn2001plusmn001

01

400

66Mpo

ngolo

Catunaregam

spinosa

(Thun

b)

Rubiaceae

ST3

1plusmn1001plusmn001

01

200

8 ISRN Biodiversity

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

67Mbo

liboli

Acaciadrepanolobium

(Harms)

Mim

osaceae

T3

000

01

100

68Mwim

akigulu

Maeruaangolen

sisCa

pparaceae

SH3

1plusmn1

00

01

300

69Mnyali

Tamarindu

sind

icaCa

esalpiniaceae

T6

1plusmn1001plusmn001

01

097

70Mgombw

ani

Combretum

aculeatum

Com

bretaceae

T6

1plusmn1

00

01

097

302plusmn02

00

04

71Msang

ala

Burkea

afric

anaHoo

kCa

esalpiniaceae

T3

0001plusmn001

01

100

302plusmn02

00

04

72Mkokonza

Opilia

amentacea

Roxb

Opiliaceae

SH3

000

00

100

311plusmn11

00

42

73Mfumbi

Kigelia

afric

ana

Bign

oniaceae

T3

000

00

100

74Mlang

ali

Euphorbia

cand

elabrum

Euph

orbiaceae

T3

000

00

100

75Mpu

lulu

Term

inaliaseric

eaCom

bretaceae

T3

000

00

100

76Mdaha

Diospyros

usam

barensisFWhite

Ebenaceae

T3

000

00

100

305plusmn05001plusmn001

15

77Mtund

wa

XimeniacaffraSond

Olacaceae

ST3

000

00

100

78Mwim

aperu

Tarenn

agla

veolens(S

Moo

re)B

rem

Rubiaceae

ST+

79Mwesa

Boscia

mossambicensisKl

Capp

araceae

ST+

80Musasam

ulo

Psychotria

schu

mmaniana

Rubiaceae

ST+

81Muh

anza

Senn

asin

gueana

Caesalpiniaceae

ST+

82Mtund

wahavi

Ximeniaam

erica

naOlacaceae

ST+

83Mtin

giligiti

Phyllanthu

sengler

iPax

Euph

orbiaceae

T+

84Msada

Vangueria

madagascarie

nsis

Gmel

Rubiaceae

ST+

85Mku

nung

uZa

nthoxylum

chalybeum

Rutaceae

T+

86Lu

kali

Croton

scheffleriP

axEu

phorbiaceae

SH+

87Kilim

andembw

eGardeniaternifolia

KSchu

mamp

Thon

nRu

biaceae

ST+

88MpelaM

buyu

Adan

soniadigitata

Bombacaceae

T++

Total(allspecies)

13511521plusmn5941355plusmn552

200

294

60plusmn30072plusmn049

200

+indicatesspecies

identifi

edam

ongsm

allerind

ividualswith

in5m

radius

plots(Dbhlt5c

m)and++

indicatesthata

largeind

ividualw

asidentifi

edwith

ina1

5-radius

plot

butw

asno

tincludedin

thea

nalyseso

fste

mdensitybasalareaand

volumea

sitw

asconsidered

anou

tlier

duetoits

tremendo

ussiz

e(Dbh

=340c

m)

ISRN Biodiversity 9

005 and that of small individuals was 006 The followingspecies were observed to have the greatest contributionsto the Shannon-Wiener diversity index of large individualsDalbergia arbutifolia (contributing 030) Combretum molle(020) Commiphora africana (019) Albizia petersiana (016)and Margaritaria discoidea (014) while for smaller ones thegreatest contributions were found for Brachystegia spiciformis(026) Dalbergia arbutifolia (024) Grewia forbesii (023)Margaritaria discoidea (020) and Dichrostachys cinerea(016) In terms of frequency of occurrence for standingindividuals (large sizes) Commiphora africana was the mostfrequent species (77 of plots) followed by Combretummolle (74) and Dalbergia arbutifolia (60) while for smallsizes Margaritaria discoidea (66) Markhamia obtusifolia(63) and Dalbergia arbutifolia (57) were the most fre-quent species The Importance Value Index (IVI) for largeindividuals (Dbh ge 5 cm) shows that Dalbergia arbutifolia(224) Commiphora africana (175) and Combretum molle(132) were the most important species among standingindividuals while Brachystegia spiciformis (308)Combretummolle (307) and Dichrostachys cinerea (178) appeared to bethe most important among harvested individuals (stumps)These species were also found to have higher frequencies thanany other harvested species observed in the GVLFR (Table 1)

33 Stem Density The total mean stem density for large indi-viduals with Dbh ge5 cm was 1521 plusmn 594 stemsha (Table 1)and that of small individuals with Dbh lt5 cm (includingindividuals with Dbh lt1 cm) was 14318 plusmn 6956 stemshaAmong large individuals the most abundant species wereDalbergia arbutifolia (162 of 1521 stemsha) Combretummolle (8) Commiphora africana (72) and Albizia peter-siana (53) Among small individuals the most abundantspecies were Brachystegia spiciformis (13 of 14318 stemsha)followed by Dalbergia arbutifolia (11) and Grewia forbesii(10) For stumps the overall mean density was 60 plusmn38 stemsha with Combretum molle (12) Dalbergia arbuti-folia (12) Brachystegia spiciformis (10) and Dichrostachyscinerea (10) contributing the most (Table 1) Generally thedistribution of standing trees to size classes showed the usualreverse J shape which was also approximately observed forstumps (Figure 3) However for stumps the density of stemsin the 1ndash10 cm diameter class was slightly lower than whatwould be expected if tree felling had been a random event

34 Basal Area For the GVLFR as a whole the meanbasal areas for large (ge5 cm Dbh) and small individuals(lt5 cm Dbh) were 1355 plusmn 552m2ha (Table 1 Figure 4)and 305 plusmn 002m2ha respectively The species contributingmost to the basal area of large individuals were Commiphoraafricana (12) Dalbergia arbutifolia (10) and Brachystegiaspiciformis (9) while those contributing most to the basalarea of smaller individuals were Dalbergia arbutifolia (16)Grewia forbesii (15) and Dichrostachys cinerea (13) Themean basal area for stumps was 072m2ha with Brachystegiaspiciformis contributing the greatest individual proportion(28) 41 species made up the rest (Figure 4)

60542

3335

530

113

28 24

346166

34

11

02

01

10

100

1000

10000

100000

Diameter classes (cm)

Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Stem

s (ha

minus1)

Figure 3 Density of standing trees ge1 cmDbh and stumps ge1 cm bydiameter class in Gangalamtumba VLFR (119899 = 35) NB logarithmicscale on vertical axis

744477

241

103041 055

014025 018

010004

001

01

1

10

Diameter classes (cm)Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Mea

n ba

sal a

rea (

m2

haminus1)

Figure 4 Distribution of basal area per hectare for standingtrees ge1 cm Dbh and stumps ge1 cm by diameter classes in theGangalamtumba VLFR (119899 = 35) NB logarithmic scale on verticalaxis

35 Volume The mean volumes for large (ge5 cm Dbh) andsmall individuals (lt5 cm Dbh) were 9217 plusmn 390m3ha and1257 plusmn 635m3ha respectively (not shown in tables) Thespecies contributing most to the volume of large individualswere Commiphora africana (12) Brachystegia spiciformis(10) Acacia sp (9) and Dalbergia arbutifolia (9) Forsmaller individuals the species that contributed most tovolume were Dalbergia arbutifolia (16) Grewia forbesii(14) and Dichrostachys cinerea (13) The mean remainingvolume of stumps was found to be 015 plusmn 01m3ha withBrachystegia spiciformis contributing the greatest individualpercentage (28) 41 species made up the rest

10 ISRN Biodiversity

36 Spatial Distribution Dispersion indices (DI) are pre-sented for individual species in Table 1 The dispersion indexvalues range from 094 indicating almost complete spatialrandomness or slight underdispersion to 5498 indicatingconsiderable overdispersion that is a patchy or clustereddistributionOut of 77 species excluding the single very largeAdansonia digitata that was considered an outlier 64 species(83) 9 species (12) and 4 species (5) were found tohave DI gt 1 DI = 1 and DI lt 1 respectively so the majorityof species are characterised by a patchy distribution acrossthe forest The species with the lowest estimated DI wasEhretia amoena (094) while the highest DI was estimated forCordia sinensis (5498)Themost abundant species includingDalbergia arbutifolia (DI = 4765) Combretum molle (DI =1523) and Commiphora africana (DI = 1142) are stronglyoverdispersed

37 Plant Communities and Species Association Four plantcommunities were identified through cluster analysis basedon the statistical significance (5) of the observed maximumindicator values (Table 2) Only two of these plant commu-nities were dominated by species from the family Caesalpini-aceae (Communities 1 and 24) The other two showed greatvariationoverlap between species of different plant families(Communities 3 and 5) The estimated Steinhaus similarityindices between pairs of plant communities varied from 32for Communities 1 and 3 and Communities 5 and 24 to 37for Communities 3 and 5 (not shown in tables)

The ordination diagram (Figure 5) shows that one topo-graphic and six edaphic variables appear to be associatedwiththe four plant communities and the species distribution inthe study area The strongest correlation with communitycomposition was observed for elevation followed by soilpH at 0ndash15 cm depth base cation Ca2+ at 0ndash15 cm depthpercent base saturation (BS) at 0ndash15 cm depth percent clayat 0ndash15 cm depth C N ratio at 15ndash30 cm depth and percentsand at 0ndash15 cm depth The base cations magnesium (Mg2+)and potassium (K+) were not directly correlated with thecommunity composition but since they are included in thebase saturation percentage they are indirectly related Plantcommunities were ordered along the second ordination axiswhich was positively correlated with pH15 (119903 = 071) Ca15(119903 = 069) BS (119903 = 065) andClay15 (119903 = 052) and negativelycorrelated with Sand15 (119903 = minus046) Axis 1 of the ordinationwas positively correlated with Elev (119903 = 085) and CNrat30(119903 = 051) As shown in Table 3 and indicated graphically inFigure 5 correlations between many of the edaphic variablesare strong particularly between pH15 Sand15 Clay15 Ca15and BS whereas correlation between topographic and mostedaphic variables is small and nonsignificant However thereis a significant negative correlation (119903 = minus042) between Elevand Sand15 indicating that sandy soils are mostly found atlower elevations

4 Discussion

41 Species Composition The results reported in this studyshow that the composition of the vegetation types found in

Elev

pH15Ca15

Sand15

Clay15

CNrat30

BS

Axis 1

Axis 2

Community 1Community 3

Community 5Community 24

Figure 5 Compositional gradients and plant communities in NMSordination of 35 vegetation plots for trees ge5 cm in GangalamtumbaVLFR Four plant communities are recognized (cf Table 2) Com-munity 1 = Brachystegia spiciformis Diplorynchus condylocarponand Lannea schweinfurthii woodland Community 3 = Dalbergiaarbutifolia Commiphora africana and Albizia petersianawoodlandCommunity 5 = Acacia sp Acacia abyssinica and Albizia amarawoodland and Community 24 = Bauhinia petersiana and Shreberatrichoclada woodland Elev elevation (m) CNrat30 C N ratio at15ndash30 cm depth Sand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm Ca15 = Ca2+ (cmol(+)kg) at 0ndash15 cm pH15 = soil pH at 0ndash15 cm BS base saturation at 0ndash15 cm

the GVLFR especially the dominance of species from thefamily Caesalpiniaceae agreed well with previous descrip-tions and classifications of plant communities commonlyfound in miombo woodlands [1] However the observeddominance based on IVI of the genera Dalbergia Com-miphora and Combretum contrasts with patterns usuallyconsidered common for miombo woodlands The frequencyof species in these genera was also high compared to otherspecies observed in the GVLFR (Table 1) Similar deviationsexist between the results obtained by Banda et al [26]in the Katavi-Rukwa ecosystem where they observed thatTerminalia and Combretum were the dominant genera andthe findings of Giliba et al [27] and Njana [43] whoboth noted the dominance of the two common miombogenera Brachystegia and Julbernardia However Combretumalso occurred in their study areas The results suggest thaton a larger spatial scale the species diversity of miombowoodlands is very high and that the three common generaBrachystegia Julbernadia and Isoberlinia are not alwaysdominant at the local scale

The species richness observed in the GVLFR compareswell with miombo community studies in other areas of drymiombo in Tanzania and elsewhere which receive an average

ISRN Biodiversity 11

Table2Plantcom

mun

itiesandspeciesa

ssociatio

nsin

thed

ryMiombo

woo

dlands

ofGangalamtumba

VLF

RCom

mun

itynu

mbers135and24

representthe

different

plantassociatio

ns

119899speciesnu

mbero

fspecies

(77in

total)with

Dbhge5c

mIV+

speciesind

icator

valuemeanplusmnstd

errorand

BAisbasalarea

Com

mun

ityAs

sociated

species

Family

Habit

IV+

()

Con

stancy

()119875value

Stem

sha

BA m2 ha

MeanDbh

Brachyste

giaspiciform

ismdashDiplorhynchus

cond

ylocarponmdashLa

nnea

schw

einfurthiiw

oodland

1(n s

pecies

=47

nplots=9)

Sitevariables(meanplusmnSE

)Elev

=1200plusmn20pH15

=644plusmn013C

a15=604plusmn128

Sand

15=721plusmn431C

lay15=137plusmn188Silt15

=142plusmn335C

Nrat30=135plusmn05andBS

=526plusmn65

Brachyste

gia

spiciform

isCa

esalpiniaceae

T820

100

000

02164plusmn59356plusmn077138plusmn07

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T759

89000

0866plusmn18044plusmn01382plusmn05

Lann

easchw

einfurthii

Anacardiaceae

T719

100

000

0449plusmn14072plusmn022126plusmn09

Bosciaangustifolia

Capp

araceae

T536

5600056

27plusmn12014plusmn00776plusmn06

Euphorbiacuneata

Euph

orbiaceae

ST428

4400200

42plusmn19012plusmn00665plusmn06

Other

species

mdashmdash

mdashmdash

mdash1075plusmn5741007plusmn647102plusmn03

Subtotal

1423plusmn174

1505plusmn178

109plusmn03

DalbergiaarbutifoliamdashCo

mmiphora

afric

anamdash

Albizia

petersiana

woo

dland

3(n

species=55n

plots=

16)Site

variables(meanplusmnSE

)Elev

=986plusmn19pH15

=648plusmn009C

a15=856plusmn109

Sand

15=767plusmn156C

lay15=135plusmn155Silt15

=97plusmn096C

Nrat30=106plusmn03andBS

=744plusmn44

Dalbergiaarbutifolia

Fabaceae

subfam

ilyPapilio

noideae

ST793

100

000

02500plusmn123263plusmn06477plusmn02

Commiphora

afric

ana

Burseraceae

T542

9400026

187plusmn40272plusmn064119plusmn06

Albiziapetersiana

Mim

osacea

T536

7500200

157plusmn57103plusmn04084plusmn02

Sclerocarryabirrea

Anacardiaceae

T504

6300186

40plusmn11128plusmn045168plusmn17

Other

species

mdashmdash

mdashmdash

mdash852plusmn449669plusmn37788plusmn03

Subtotal

1735plusmn166

1435plusmn071

92plusmn02

Acaciaspmdash

Acaciaabyssin

icamdash

Albiziaam

arawoo

dland

5(n

species=33n

plots=5)

Sitevariables(m

eanplusmnSE

)Elev

=986plusmn52pH15

=734plusmn023C

a15=139plusmn33

Sand

15=745plusmn678C

lay15=148plusmn47Silt15

=107plusmn26C

Nrat30=106plusmn07andBS

=963plusmn89

Acaciasp

Mim

osaceae

T981

100

000

02269plusmn111662plusmn286172plusmn14

Acaciaabyssin

icaMim

osaceae

T594

8000030

31plusmn9060plusmn03299plusmn08

Albiziaam

ara

Mim

osaceae

T552

60000

6654plusmn30023plusmn01671plusmn08

Grew

iabicolor

Tiliaceae

ST533

6000106

113plusmn52040plusmn01770plusmn04

Acaciaseyal

Mim

osaceae

T433

6000526

62plusmn34034plusmn01790plusmn05

Other

species

mdashmdash

mdashmdash

mdash665plusmn533552plusmn49872plusmn04

Subtotal

1194plusmn169

1367plusmn347

101plusmn05

Bauh

iniapetersiana

mdashShrebera

trichoclada

woo

dland

24(n

species=35n

plots=5)

Sitevariables(meanplusmnSE

)Elev

=1175plusmn25pH15

=73plusmn04C

a15=254plusmn69

Sand

15=522plusmn68C

lay15=331plusmn28

Silt15=147plusmn44C

Nrat30=961plusmn13andBS

=1041plusmn204

Bauh

iniapetersiana

Caesalpiniaceae

SH551

8000118192plusmn121111plusmn05075plusmn03

Shrebera

trichoclada

Oleaceae

T505

6000110

57plusmn32022plusmn01380plusmn05

Manilkaramochisia

Sapo

taceae

T376

4000332

34plusmn27014plusmn00969plusmn10

Dalbergia

mela

noxylon

Fabaceae

T370

4000380

68plusmn58026plusmn02266plusmn03

Ehretia

amoena

Boraginaceae

ST347

4000344

6plusmn4

002plusmn00170plusmn04

Other

species

mdashmdash

mdashmdash

mdash982plusmn759643plusmn47999plusmn05

Subtotal

1338plusmn137

817plusmn087

91plusmn04

Total

1521plusmn5941355plusmn55298plusmn01

Elevelevatio

n(m

)CN

rat30CN

ratio

at15ndash30c

mdepthSand

15sand(

)at0

ndash15c

mC

lay15clay

()at0

ndash15c

mSilt15silt

()at0

ndash15c

mC

a15Ca2+(cmol(+)kg)at0

ndash15c

mpH15soilp

Hat0ndash

15cm

BS

base

saturatio

nat0ndash

15cm

12 ISRN Biodiversity

Table 3 Pearson-correlation matrix for two topographic and eight edaphic variablesdagger associated with the classified plant communities in theGangalamtumba VLFR (119899 = 35) Applied significance levels lowast5 lowastlowast1 and lowastlowastlowast01 +not significant

Elev Slope pH15 Ca15 K15 N15 Sand15 Clay15 CNrat30Slope 019+

pH15 minus013+ minus033lowast

Ca15 002+ minus020+ 083lowastlowastlowast

K15 minus029+ 000+ 010+ 012+

N15 006+ 036lowast 010+ 041lowastlowast 033lowast

Sand15 minus042lowastlowast 003+ minus053lowastlowastlowast minus074lowastlowastlowast 006+ minus046lowastlowast

Clay15 031+ minus012+ 051lowastlowast 076lowastlowastlowast minus001+ 047lowastlowast minus086lowastlowastlowast

CNrat30 036lowast 010+ minus039lowast minus051lowastlowast minus015+ minus019+ 040lowast minus048lowastlowast

BS minus024+ minus017+ 084lowastlowastlowast 091lowastlowastlowast 015+ 037lowast minus058lowastlowastlowast 060lowastlowastlowast minus051lowastlowastdaggerElev elevation (m) pH15 soil pH at 0ndash15 cm Ca15 Ca2+ (cmol(+)kg) at 0ndash15 cm K15 K+ (cmol(+)kg) at 0ndash15 cm N15 N concentration at 0ndash15 cmSand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm CNrat30 C N ratio at 15ndash30 cm depth BS base saturation at 0ndash15 cm 119905-value was calculated as119905 = 119903radic(119899 minus 2)(1 minus 119903

2) where 119903 is the Pearson-correlation coefficient and 119899 is the total sample size

Table 4 Species richness observed in other studies from drymiombo woodlands

Plot size(ha)

Totalnumberof plots

Total samplearea(ha)

Total numberof species References

0071 70 495 82 [43]0071 80 565 110 [27]0071 133 940 229 [26]0071 247 1746 102 [44]004 40 160 81 [45]025 14 350 69 [25]01 2 020 40 [28]01 152 1520 92 genera [22]0071 35 247 88 This study

annual rainfall of 565ndash1500mm (Table 4) Using plot sizes of004ndash025 ha and sample sizes of 2ndash247 plots a total numberof species ranging from40 (Dbhge 10 cm) to 229 (Dbhge 2 cm)have been reported fromMiombowoodlands [22 25ndash28 43ndash45]

The high number of species reported by Banda et al [26]Chidumayo [22] Isango [45] and Chamshama et al [44] islikely to be a consequence of the spatial scale and coverage ofthese studies as they all cover large areas include more thanone site and operate with large sample sizes For exampleChidumayo [22] included species from both wet and dryMiombo areas in Zambia The study by Sauer and Abdallah[15] who reported a total of 131 species occurring in thetobacco growing zone of Iringa rural district included twoforest reserves and three family-managed forests Thereforeconsidering the climatic conditions in the GVLFR (617mmof rainfall per year) and the sample size (35 plots) thespecies richness reported in this study can be ranked atleast as high or higher than those found in the studiesmentioned The selective sampling approach focusing onvarious microhabitat types adopted by Banda et al [26] mayhave contributed to the large number of species observed

in their study area Similarly the higher number of speciesfound by Giliba et al [27] was probably due to the presenceof riverine forest offering site conditions favourable formanyspecies

The values of the Shannon-Wiener (1198671015840 = 344) andSimpson indices (119863 = 005) reported for large individ-uals in this study are within the range observed for mostcommunities of particular life forms [36] For example 1198671015840usually does not exceed 5 although this maximum valuevaries depending on the type of the biological communitysampled and the sampling approach applied (eg minimumdiameter and size of sample units) A threshold value of 2 for1198671015840 has been mentioned as a minimum value above which

an ecosystem can be regarded as medium to highly diverse[27] Chamshama et al [44] reported three 1198671015840 values of31 32 and 33 from Kitulangalo Miombo forest in EasternTanzania while Njana [43] reported a 1198671015840 value of 340from dry Miombo forest in Western Tanzania The studiesby Sauer and Abdallah [15] and Giliba et al [27] reportedparticularly high values of 346 and 427 respectively Thiscould be attributed to the very large sample sizes used inboth studies and the presence of riverine forest where thechance of encountering many rare species is likely to be highThe forests examined in the mentioned studies receive anaverage annual rainfall of 700ndash1000mm compared to whichthe rainfall in the GVLFR is low (617mm on average per yearcf above)The relatively high diversity found inGVLFRmusttherefore be attributed to other factors than climate The soilanalyses indicate that the soil fertility level in the GVLFRis relatively high with considerable proportions of all 2 1lattice clay minerals (114) (ie illite montmorillonite andvermiculite) plus a good amount of organic matter whichmay suggest that the soil has large reserves of important plantnutrients for example K Mg and Fe The base saturationpercentage (BS) which is normally used to indicate the soilfertility status (Landon 1991) was also high 76 on averageand with 86 of the samples (30 samples) with BS valuesgt50 (fertile soil) and only 14 of the samples (5 samples)with BS below 50 (less fertile soil) As another indicationof high soil fertility status the mean C N ratio was 12 plusmn 043

ISRN Biodiversity 13

(range 7ndash19) for top soil (0ndash15 cm) and 11 plusmn 036 (range 5ndash16) for subsoil (15ndash30 cm) In general the values for both soilstrata fall within the expected range of 8ndash17 Soil pH values(mean 67 plusmn 01 range 567ndash852)were alsowithin the optimalrangewhere all the nutrients that aremost important for plantgrowth (Ca Mg K and P) are available and accessible toplants [46] In this study 97 of the soil samples had pHbelow 8 (one sample had a pH of 852) Fisher and Binkley[47] noted that high pH is almost never a problem in forestsas most trees do well across the full range of common pHvaluesTherefore considering the low average annual rainfallcompared to other forests the relatively high fertility of theGVLFR may be the main factor creating an environmentfavourable to many species thus leading to a quite highspecies diversity observed in this forest

Based on the Importance Value Index Brachystegia spi-ciformis and Combretum molle appeared to be the mostimportant species among harvested trees (stumps) in thestudy area This result agreed very well with the large valuesof basal area and volume and the information obtained fromlocal scouts and members of the village environmental com-mittee who said that the most frequently harvested speciesfor charcoal making include all Brachystegia species found inthe forest (ie Brachystegia spiciformis Brachystegia mangaBrachystegia boehmii and Brachystegia bussei) Among theCombretum species the most important one (based on IVI)Combretum molle is mostly used for house construction andfirewood rather than for charcoal making Apart from theBrachystegia species the only other species mentioned asimportant for charcoal making was Acacia mellifera Otherspecies are only used in case they happen to fall when fellingthe preferred species during the preparation of charcoal kilnsWith respect to stumps Brachystegia spiciformis Brachystegiamanga and Combretum molle are among the ten mostabundant species in terms of density basal area and volumeper hectare Stumps of the other species mentioned are notcommonly found a factwhichmay be due to the small samplesize being unable to capture sites where these species areharvested but may also be related to their limited distributionin the forest as indicated by the estimated dispersion indices(see Table 1)

42 Forest Structure Species densities reported from otherMiombo woodland areas in Tanzania are typically 348ndash1495stemsha for trees with Dbh gt4 cm [24 43 45] Comparedwith this the GVLFR is highly stocked as the estimateddensity is 2296 stemsha for trees with Dbh gt4 cmThemeanstem density of 1521 plusmn 594ha for trees with Dbh ge5 cmis also more than twice as large as values found in otherstudies [25ndash27 44 45 48] A similar pattern is seen whencomparing the density of regeneration between the studiesThe diameter distribution is characterised by a very cleartrend of decreasing stem density with increasing diameterThe shape of the distribution is thus an inverted ldquoJrdquo (Figure 3)which is a common feature of natural forests with activeregeneration and recruitment [49] However not many largetrees were captured by the sample whereas a considerablenumber of relatively large stumps were observed suggestingthat anthropogenic activities such as charcoal making may

have affected the structure and ecological balance of the forest(see Figure 3) Since the woodlands are often hit by fire whichtends to kill the seedlings (especially the late fires) and thusonly few seedlings can be expected to reach larger diameterclasses lack of mature trees and the resulting lack of seedsmay eventually threaten the biodiversity of the forest

The mean basal area of 1355 plusmn 552m2ha observedin this study is slightly above the range of values typicallyreported from the miombo region 75ndash126m2ha [26 28 4344 50] However the basal areas reported by Isango [45] werea bit higher (1504ndash1563m2ha) than observed in this study

Themean total volume inGVLFRwas estimated at 9217plusmn390m3ha for trees with Dbh ge5 cm Other studies in dryMiombo woodlands have reported mean volumes of 167ndash7603m3ha [24 44 45 50] The current standing volume ofGVLFR is thus slightly higher than values typically reportedfor forests in the Miombo ecoregion A plausible reason forthis may be that compared to other forests the GVLFR isstill well stocked despite ongoing human activities such ascharcoalmakingThebasal area observed for stumpswas only072m2ha so there is no indication of intensive extractionover many years This corresponds well with the findings ofTreue et al [20] who conclude that the estimated 04m3haannual extraction of woody biomass from GVLFR is consid-erably below its estimated annual increment of 15m3ha andthat the local forest managers seem capable of regulating theharvesting activities which in addition to village membersrsquocollection for subsistence uses also included commercialcharcoal production by external companies that pay a fee perbag of charcoal extracted to the village government

43 Plant Communities and Species Associations Except forBrachystegia spiciformis the majority of the Brachystegia andJulbernardia species that are common to miombo wood-lands elsewhere are not among the species most commonlyobserved in this study A similar pattern was observed byBanda et al [26] in the Katavi-Rukwa ecosystem wherethe genera that are most common in miombo woodlandsBrachystegia Julbernardia and Isoberlinia were not commonin their study sites Furthermore the four plant communi-ties distinguished in this study are comparable with thosereported by other studies in Tanzania including the work byMunishi et al [29] in theMiombowoodlands of Rukwa basinChunya district Tanzania and the study by Banda et al [26]in the Katavi-Rukwa ecosystem

Elevation was noted by Munishi et al [29] to be themost important factor shaping the species communities intheir study area This study found a similar pattern with thehighest coefficient of correlation observed for elevation sug-gesting that topographical variation is among the strongestdeterminants of community composition in dry Miombowoodlands hence influencing the spatial distribution ofspecies strongly However in our study area edaphic factorsalso influenced the species distribution directly Two plantcommunities occurredmainly on clayey soils with high pH atintermediate elevations one on sandy soils with lowpHat lowelevations and one on sandy-clayey soils at higher elevationsand with neutral soil pH (Figure 5) Specifically it appeared

14 ISRN Biodiversity

that the Acacia woodland category (Community 5) grows atlow elevations around temporary streams (or at least wherethe ground water table is relatively high) and the Bauhiniawoodland category (Community 24) appearsmostly in placeswith a relatively high percentage of clay (and therefore highvalues of pH Ca and BS) By contrast it appeared that theDalbergia woodland category (Community 3) is located atmore sandy sites (with low values of pH Ca and BS) andthe Brachystegia woodland category (Community 1) seemedto be located mostly at higher elevations where the CN-ratio is quite high Correlations between elevation and thebasic soil variables pH Ca and percentages of sand andclay were low (cf Figure 5) Thus the results indicate thatthe plant communities of the dry miombo woodlands inGVLFR are not only shaped by the topographic variation(elevation) and the groundwater level but also by basic soilcharacteristics The results thus confirm findings from otherstudies detecting effects of elevation and soil characteristicson species composition [51 52]

5 Conclusion

Considering that the sample size used in this study wassmaller than samples used in other studies in dry miombowoodlands the results show that the species diversity inGVLFR is relatively high compared to other forest reservesThe vegetation of GVLFR is characterised by high densitybasal area and volume and despite the scarcity of largediameter trees this indicates that the forest is in a goodcondition The effect of anthropogenic activities is neverthe-less evident and stresses the need for proper managementespecially for economically important species preferred forcharcoalmaking (egBrachystegia spiciformis) if the currentspecies diversity is to be maintained or enhanced A repeatedfuture study would be needed to assess whether the currentcommunity-based management regime yields this intendedoutcome but the available information and analyses allow forsome optimism in this respect

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors wish to thank people from Mfyome villagefor their invaluable assistance during field work Mzee IddiKaheya Damian Chotamasege AugustinoMkwama Libera-tus Simime and Mawazo Nyangwa Furthermore thanks aredue to Venancia Mlelwa from Sokoine University and MadsMadsen Krag from University of Copenhagen for doing thelaboratory work The authors also wish to thank GoodluckMoshi their driverMarcoNjana andNassoroHMagogo theTAFORI botanist for assisting with species identification andKlaus Dons for preparing a study site map Financial supportwas provided by Danida through the ENRECA Project

ldquoParticipatory forest management for rural livelihoods forestconservation and good governance in Tanzaniardquo (no 725)

References

[1] P G H Frost ldquoThe Ecology of Miombo Woodlandsrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 11ndash57 1996

[2] N Burgess J Hales E Underwood et al Terrestrial Ecoregionsof Africa and Madagascar A Conservation Assessment IslandPress World Wildlife Fund 2004

[3] J Clarke W Cavendish and C Coote ldquoRural householdsand miombo woodlands use value and managementrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 101ndash135 1996

[4] B M Campbell A Angelsen A Cunningham Y KaterereA Sitoe and S Wunder ldquoMiombo woodlandsmdashopportunitiesand barriers to sustainable forest managementrdquo httpsener-gypediainfoimages66dMiombo2007pdf

[5] S Syampungani P W Chirwa F K Akinnifesi G Sileshi andO C Ajayi ldquoTheMiombo woodlands at the cross roads poten-tial threats sustainable livelihoods policy gaps and challengesrdquoNatural Resources Forum vol 33 no 2 pp 150ndash159 2009

[6] J I O Abbot and K Homewood ldquoA history of change causesof miombo woodland decline in a protected area in MalawirdquoJournal of Applied Ecology vol 36 no 3 pp 422ndash433 1999

[7] E J Luoga E T F Witkowski and K Balkwill ldquoLand coverand use changes in relation to the institutional frameworkand tenure of land and resources in eastern Tanzania Miombowoodlandsrdquo Environment Development and Sustainability vol7 no 1 pp 71ndash93 2005

[8] FAO The State of Food and Agriculture 2010-2011 Forest andAgriculture Organization Rome Italy 2010

[9] A H Gentry ldquoTropical forest biodiversity distributional pat-terns and their conservational significancerdquo Oikos vol 63 no1 pp 19ndash28 1992

[10] O E Sala F S Chapin III J J Armesto et al ldquoGlobalbiodiversity scenarios for the year 2100rdquo Science vol 287 no5459 pp 1770ndash1774 2000

[11] H J Geist and E F Lambin ldquoProximate causes and underlyingdriving forces of tropical deforestationrdquo BioScience vol 52 no2 pp 143ndash150 2002

[12] R S DeFries ldquoTropical forests deforestation and ecosystemsservices Contributions of remote sensingrdquo in GeoinformaticsFor Tropical Ecosystems P S Roy Ed pp 1ndash32 2003

[13] B M Campbell P Frost and N Bryon ldquoMiombo woodlandsand their use overview and key issuesrdquo in The Miombo inTransition Woodlands and Welfare in Africa B Campbell Edpp 1ndash10 2006

[14] H J Geist ldquoGlobal assessment of deforestation related totobacco farmingrdquo Tobacco Control vol 8 no 1 pp 18ndash28 1999

[15] J Sauer and J M Abdallah ldquoForest diversity tobacco produc-tion and resource management in Tanzaniardquo Forest Policy andEconomics vol 9 no 5 pp 421ndash439 2007

[16] E N Chidumayo and K J Mbata ldquoShifting cultivation ediblecaterpillars and livelihoods in the Kopa area of northernZambiardquo Forests Trees and Livelihoods vol 12 no 3 pp 175ndash1932002

[17] E N Chidumayo and L Kwibisa ldquoEffects of deforestation ongrass biomass and soil nutrient status in miombo woodlandZambiardquo Agriculture Ecosystems and Environment vol 96 no1ndash3 pp 97ndash105 2003

ISRN Biodiversity 15

[18] J F Lund and T Treue ldquoAre we getting there Evidence ofdecentralized forest management from the Tanzanian miombowoodlandsrdquoWorld Development vol 36 no 12 pp 2780ndash28002008

[19] T Blomley and S Iddi Participatory Forest Management inTanzania 1993ndash2009mdashLessons Learned and Experiences toDate Ministry of Natural Resources and Tourism Forestry andBeekeeping Division Dar es Salaam Tanzania 2009

[20] T Treue Y M Ngaga H Meilby et al ldquoDoes participatoryforest management promote sustainable forest utilisation inTanzaniardquo International Forestry Review vol 16 no 1 pp 1ndash162014

[21] Ministry ofNatural Resources andTourismParticipatory ForestManagement in Tanzania Facts and Figures Forestry andBeekeeping Division Dar es Salaam Tanzania 2008

[22] E N Chidumayo ldquoSpecies structure in Zambian miombowoodlandrdquo Journal of Tropical Ecology vol 3 no 2 pp 109ndash1181987

[23] J D Lowore ldquoCoppice regeneration in some miombo wood-lands of Malawirdquo FRIM Report 99001 Forestry ResearchInstitute of Malawi 1999

[24] E J Luoga E T F Witkowski and K Balkwill ldquoHarvestedand standing wood stocks in protected and communal miombowoodlands of eastern Tanzaniardquo Forest Ecology and Manage-ment vol 164 no 1ndash3 pp 15ndash30 2002

[25] M Williams C M Ryan R M Rees E Sambane J Fernandoand J Grace ldquoCarbon sequestration and biodiversity of re-growing miombo woodlands in Mozambiquerdquo Forest Ecologyand Management vol 254 no 2 pp 145ndash155 2008

[26] T Banda NMwangulango BMeyer et al ldquoThewoodland veg-etation of the Katavi-Rukwa ecosystem in western TanzaniardquoForest Ecology andManagement vol 255 no 8-9 pp 3382ndash33952008

[27] R A Giliba E K Boon C J Kayombo E B Musamba AM Kashindye and P F Shayo ldquoSpecies composition richnessand diversity in Miombo Woodland of Bereku Forest ReserveTanzaniardquo Journal of Biodiversity vol 2 no 1 pp 1ndash7 2011

[28] D D Shirima P K T Munishi S L Lewis et al ldquoCarbonstorage structure and composition of miombo woodlands inTanzaniarsquos Eastern Arc Mountainsrdquo African Journal of Ecologyvol 49 no 3 pp 332ndash342 2011

[29] P K T Munishi R A P C Temu and G Soka ldquoPlant com-munities and tree species associations in a Miombo ecosystemin the Lake Rukwa basin Southern Tanzania implications forconservationrdquo Journal of Ecology and Natural Environment vol3 no 2 pp 63ndash71 2011

[30] J Dewis and F Freitas ldquoPhysical analysis of soilsrdquo in Physicaland Chemical Methods of Soil andWater Analysis FAO Bulletinno 10 pp 51ndash57 2nd edition 1970

[31] S R Olsen and L E Sommers ldquoPhosphorusrdquo inMethods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 403ndash430 American Societyof Agronomy Madson Wis USA 1982

[32] J D Rhoades ldquoCation exchange capacityrdquo in Methods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 149ndash157 American Society ofAgronomy Madson Wis USA 1982

[33] IMatejovic ldquoDetermination of carbon hydrogen and nitrogenin soils by automated elemental analysis (dry combustionmethod)rdquo Communications in Soil Science and Plant Analysisvol 24 no 17-18 pp 2213ndash2222 1993

[34] J P Moslashberg Soil Analysis Manual Revised Edition Laboratoryof Soil Sciences Department of Soil Science SokoineUniversityof Agriculture Morogoro Tanzania 2001

[35] N C BradyThe Nature and Properties of Soils Macmillan 8thedition 1974

[36] C J Krebs Ecological Methodology Hamper Collins PublishersNew York NY USA 2nd edition 1999

[37] B Husch T W Beers and J A Kershaw Forest MensurationJohn Wiley amp Sons Hoboken NJ USA 4th edition 2003

[38] E E Mwakalukwa H Meilby and T Treue ldquoVolume andaboveground biomass models for dry Miombo Woodland inTanzaniardquo In press

[39] M Kent Vegetation Description and Analysis A PracticalApproach Wiley-Blackwell John Wiley amp Sons Hoboken NJUSA 2nd edition 2012

[40] B McCune and M J Mefford PC-ORD Multivariate Analysisof Ecological Data Version 6 MjM Software Gleneden BeachOre USA 2011

[41] MDufrene andP Legendre ldquoSpecies assemblages and indicatorspecies the need for a flexible asymmetrical approachrdquo EcologyMonography vol 67 pp 777ndash795 1997

[42] J E PeckMultivariate Analysis for Community Ecologists Step-by-Step using PC-ORD MjM Software Design Gleneden BeachOre USA 2010

[43] M A Njana Arborescent species diversity and stocking inMiombo Woodland of Urumwa forest reserve and their contri-bution to Livelihoods Tabora Tanzania [MS thesis] SokoineUniversity of Agriculture Morogoro Tanzania 2008

[44] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal no 200 pp 59ndash70 2004

[45] J Isango ldquoStand structure and tree species composition ofTanzania miombo woodlands a case study from miombowoodlands of community based forest management in Iringadistrictrdquo in MITMIOMBOmdashManagement of Indigenous TreeSpecies For EcosystemRestoration andWood Production in Semi-Arid Miombo Woodlands in Eastern Africa Proceedings ofthe 1st MITMIOMBO Project Workshop held in MorogoroTanzania 6th-12th February 2007 Working Papers of theFinnish Forest Research Institute no 50 pp 43ndash56 2007

[46] J R Landon Booker Tropical Soil Manual A Handbook ForSoil Survey and Agricultural Land Evaluation in the Tropics andSubtropics Longman Scientific amp Technical and John Wiley ampSons 1991

[47] R F Fisher and D Binkley Ecology and Management of ForestSoils John Wiley amp Sons 3rd edition 2000

[48] W A Rees ldquoPreliminary studies into bush utilization by Cattlein Zambiardquo Journal of Applied Ecology vol 11 pp 207ndash214 1974

[49] S M Philip Measuring Trees and Forests CAB InternationalWallingford UK 2nd edition 1994

[50] J D Lowore P G Abbot and M Werren ldquoStackwood volumeestimations formiombowoodlands inMalawirdquoCommonwealthForestry Review vol 73 no 3 pp 193ndash197 1994

[51] D Kubota T Masunaga Hermansah et al ldquoSoil environmentand tree species diversity in tropical rain forest West SumatraIndonesiardquo in Soils of Tropical Forest Ecosystems CharacteristicsEcology and Management A Schulte and D Ruhiyat Eds pp159ndash167 1998

[52] P K T Munishi T H Shear T Wentworth and R A PC Temu ldquoCompositional gradients of plant communities insubmontane rainforests of EasternTanzaniardquo Journal of TropicalForest Science vol 19 no 1 pp 35ndash45 2007

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

EcosystemsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MeteorologyAdvances in

EcologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Marine BiologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental Chemistry

Atmospheric SciencesInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Geological ResearchJournal of

EarthquakesJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BiodiversityInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

Page 7: Research Article Floristic Composition, Structure, and

ISRN Biodiversity 7

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

44Mteresi

Prem

naholstiiGurke

Verbenaceae

ST9

8plusmn5003plusmn002

09

899

45Mkongolo

Commiphora

ugogensis

Burseraceae

T6

1plusmn1008plusmn006

08

097

302plusmn02001plusmn001

09

46Muw

isaBo

sciaangustifolia

A

Rich

varangustifo

liaCa

pparaceae

T17

8plusmn4004plusmn002

08

426

47Mnyalup

uko

Canthium

pseudoverticillatum

Hien

Rubiaceae

ST20

8plusmn4004plusmn002

07

414

48Mnyaluh

anga

Brideliascleu

roneura

MuellArg

Euph

orbiaceae

ST14

6plusmn3004plusmn002

07

341

49Mdide

Manilkaramochisia

(Bak)Dub

ard

Sapo

taceae

T9

5plusmn4002plusmn001

07

793

50Muh

emi

Erythrinaabyssin

icaFabaceae

T6

1plusmn1007plusmn006

07

163

51Msambarawe

Vangueria

infausta

BurchSspRo

tund

ataRu

biaceae

ST6

8plusmn5002plusmn002

06

925

52Mhehefu

Allophylu

sferrugineus

Taub

Sapind

aceae

SH9

5plusmn3002plusmn001

05

540

314plusmn14001plusmn001

14

53Mnyengrsquoenyengrsquoe

Excoecariabu

ssei

(Pax)

Euph

orbiaceae

ST11

4plusmn2001plusmn001

05

321

54Muganga

Berchemiadiscolor

Rham

naceae

T6

4plusmn3004plusmn003

04

717

55Mning

aPterocarpu

sangolensis

Fabaceae

T6

2plusmn1005plusmn004

04

253

309plusmn09006plusmn006

25

56Mtanang

we

Zizip

husm

ucronata

Rham

naceae

T3

4plusmn4003plusmn003

04

900

57Muh

ekele

Eucle

adivinorum

Hiern

Ebenaceae

ST3

3plusmn3001plusmn001

04

800

302plusmn02

00

49

58Mub

umila

Cassipourea

mollis

(REfr)Alstom

Rhizop

horaceae

T9

4plusmn3002plusmn001

04

526

302plusmn02

00

04

59Mkw

ambe

Flueggea

virosa

Willd

Euph

orbiaceae

SH6

3plusmn2003plusmn003

03

406

60Kivang

aZa

nhaafric

ana

(Radlk)Ex

ell

Sapind

aceae

T9

2plusmn1001plusmn001

02

212

302plusmn02

00

02

61Mning

amaji

Pterocarpu

stinctorius

Fabaceae

T3

0002plusmn002

02

100

62Mtosi

MaeruatriphyllaA

Rich

Capp

araceae

ST3

2plusmn2001plusmn001

02

600

63Mugosa

Ehretia

amoena

Boraginaceae

ST9

1plusmn1

00

01

094

64Mnyon

gamem

beStegan

otaenia

araliacea

Apiaceae

T6

1plusmn1

001

01

163

65Mvelevele

Vernoniaam

ygdalin

aAs

teraceae

SH3

2plusmn2001plusmn001

01

400

66Mpo

ngolo

Catunaregam

spinosa

(Thun

b)

Rubiaceae

ST3

1plusmn1001plusmn001

01

200

8 ISRN Biodiversity

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

67Mbo

liboli

Acaciadrepanolobium

(Harms)

Mim

osaceae

T3

000

01

100

68Mwim

akigulu

Maeruaangolen

sisCa

pparaceae

SH3

1plusmn1

00

01

300

69Mnyali

Tamarindu

sind

icaCa

esalpiniaceae

T6

1plusmn1001plusmn001

01

097

70Mgombw

ani

Combretum

aculeatum

Com

bretaceae

T6

1plusmn1

00

01

097

302plusmn02

00

04

71Msang

ala

Burkea

afric

anaHoo

kCa

esalpiniaceae

T3

0001plusmn001

01

100

302plusmn02

00

04

72Mkokonza

Opilia

amentacea

Roxb

Opiliaceae

SH3

000

00

100

311plusmn11

00

42

73Mfumbi

Kigelia

afric

ana

Bign

oniaceae

T3

000

00

100

74Mlang

ali

Euphorbia

cand

elabrum

Euph

orbiaceae

T3

000

00

100

75Mpu

lulu

Term

inaliaseric

eaCom

bretaceae

T3

000

00

100

76Mdaha

Diospyros

usam

barensisFWhite

Ebenaceae

T3

000

00

100

305plusmn05001plusmn001

15

77Mtund

wa

XimeniacaffraSond

Olacaceae

ST3

000

00

100

78Mwim

aperu

Tarenn

agla

veolens(S

Moo

re)B

rem

Rubiaceae

ST+

79Mwesa

Boscia

mossambicensisKl

Capp

araceae

ST+

80Musasam

ulo

Psychotria

schu

mmaniana

Rubiaceae

ST+

81Muh

anza

Senn

asin

gueana

Caesalpiniaceae

ST+

82Mtund

wahavi

Ximeniaam

erica

naOlacaceae

ST+

83Mtin

giligiti

Phyllanthu

sengler

iPax

Euph

orbiaceae

T+

84Msada

Vangueria

madagascarie

nsis

Gmel

Rubiaceae

ST+

85Mku

nung

uZa

nthoxylum

chalybeum

Rutaceae

T+

86Lu

kali

Croton

scheffleriP

axEu

phorbiaceae

SH+

87Kilim

andembw

eGardeniaternifolia

KSchu

mamp

Thon

nRu

biaceae

ST+

88MpelaM

buyu

Adan

soniadigitata

Bombacaceae

T++

Total(allspecies)

13511521plusmn5941355plusmn552

200

294

60plusmn30072plusmn049

200

+indicatesspecies

identifi

edam

ongsm

allerind

ividualswith

in5m

radius

plots(Dbhlt5c

m)and++

indicatesthata

largeind

ividualw

asidentifi

edwith

ina1

5-radius

plot

butw

asno

tincludedin

thea

nalyseso

fste

mdensitybasalareaand

volumea

sitw

asconsidered

anou

tlier

duetoits

tremendo

ussiz

e(Dbh

=340c

m)

ISRN Biodiversity 9

005 and that of small individuals was 006 The followingspecies were observed to have the greatest contributionsto the Shannon-Wiener diversity index of large individualsDalbergia arbutifolia (contributing 030) Combretum molle(020) Commiphora africana (019) Albizia petersiana (016)and Margaritaria discoidea (014) while for smaller ones thegreatest contributions were found for Brachystegia spiciformis(026) Dalbergia arbutifolia (024) Grewia forbesii (023)Margaritaria discoidea (020) and Dichrostachys cinerea(016) In terms of frequency of occurrence for standingindividuals (large sizes) Commiphora africana was the mostfrequent species (77 of plots) followed by Combretummolle (74) and Dalbergia arbutifolia (60) while for smallsizes Margaritaria discoidea (66) Markhamia obtusifolia(63) and Dalbergia arbutifolia (57) were the most fre-quent species The Importance Value Index (IVI) for largeindividuals (Dbh ge 5 cm) shows that Dalbergia arbutifolia(224) Commiphora africana (175) and Combretum molle(132) were the most important species among standingindividuals while Brachystegia spiciformis (308)Combretummolle (307) and Dichrostachys cinerea (178) appeared to bethe most important among harvested individuals (stumps)These species were also found to have higher frequencies thanany other harvested species observed in the GVLFR (Table 1)

33 Stem Density The total mean stem density for large indi-viduals with Dbh ge5 cm was 1521 plusmn 594 stemsha (Table 1)and that of small individuals with Dbh lt5 cm (includingindividuals with Dbh lt1 cm) was 14318 plusmn 6956 stemshaAmong large individuals the most abundant species wereDalbergia arbutifolia (162 of 1521 stemsha) Combretummolle (8) Commiphora africana (72) and Albizia peter-siana (53) Among small individuals the most abundantspecies were Brachystegia spiciformis (13 of 14318 stemsha)followed by Dalbergia arbutifolia (11) and Grewia forbesii(10) For stumps the overall mean density was 60 plusmn38 stemsha with Combretum molle (12) Dalbergia arbuti-folia (12) Brachystegia spiciformis (10) and Dichrostachyscinerea (10) contributing the most (Table 1) Generally thedistribution of standing trees to size classes showed the usualreverse J shape which was also approximately observed forstumps (Figure 3) However for stumps the density of stemsin the 1ndash10 cm diameter class was slightly lower than whatwould be expected if tree felling had been a random event

34 Basal Area For the GVLFR as a whole the meanbasal areas for large (ge5 cm Dbh) and small individuals(lt5 cm Dbh) were 1355 plusmn 552m2ha (Table 1 Figure 4)and 305 plusmn 002m2ha respectively The species contributingmost to the basal area of large individuals were Commiphoraafricana (12) Dalbergia arbutifolia (10) and Brachystegiaspiciformis (9) while those contributing most to the basalarea of smaller individuals were Dalbergia arbutifolia (16)Grewia forbesii (15) and Dichrostachys cinerea (13) Themean basal area for stumps was 072m2ha with Brachystegiaspiciformis contributing the greatest individual proportion(28) 41 species made up the rest (Figure 4)

60542

3335

530

113

28 24

346166

34

11

02

01

10

100

1000

10000

100000

Diameter classes (cm)

Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Stem

s (ha

minus1)

Figure 3 Density of standing trees ge1 cmDbh and stumps ge1 cm bydiameter class in Gangalamtumba VLFR (119899 = 35) NB logarithmicscale on vertical axis

744477

241

103041 055

014025 018

010004

001

01

1

10

Diameter classes (cm)Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Mea

n ba

sal a

rea (

m2

haminus1)

Figure 4 Distribution of basal area per hectare for standingtrees ge1 cm Dbh and stumps ge1 cm by diameter classes in theGangalamtumba VLFR (119899 = 35) NB logarithmic scale on verticalaxis

35 Volume The mean volumes for large (ge5 cm Dbh) andsmall individuals (lt5 cm Dbh) were 9217 plusmn 390m3ha and1257 plusmn 635m3ha respectively (not shown in tables) Thespecies contributing most to the volume of large individualswere Commiphora africana (12) Brachystegia spiciformis(10) Acacia sp (9) and Dalbergia arbutifolia (9) Forsmaller individuals the species that contributed most tovolume were Dalbergia arbutifolia (16) Grewia forbesii(14) and Dichrostachys cinerea (13) The mean remainingvolume of stumps was found to be 015 plusmn 01m3ha withBrachystegia spiciformis contributing the greatest individualpercentage (28) 41 species made up the rest

10 ISRN Biodiversity

36 Spatial Distribution Dispersion indices (DI) are pre-sented for individual species in Table 1 The dispersion indexvalues range from 094 indicating almost complete spatialrandomness or slight underdispersion to 5498 indicatingconsiderable overdispersion that is a patchy or clustereddistributionOut of 77 species excluding the single very largeAdansonia digitata that was considered an outlier 64 species(83) 9 species (12) and 4 species (5) were found tohave DI gt 1 DI = 1 and DI lt 1 respectively so the majorityof species are characterised by a patchy distribution acrossthe forest The species with the lowest estimated DI wasEhretia amoena (094) while the highest DI was estimated forCordia sinensis (5498)Themost abundant species includingDalbergia arbutifolia (DI = 4765) Combretum molle (DI =1523) and Commiphora africana (DI = 1142) are stronglyoverdispersed

37 Plant Communities and Species Association Four plantcommunities were identified through cluster analysis basedon the statistical significance (5) of the observed maximumindicator values (Table 2) Only two of these plant commu-nities were dominated by species from the family Caesalpini-aceae (Communities 1 and 24) The other two showed greatvariationoverlap between species of different plant families(Communities 3 and 5) The estimated Steinhaus similarityindices between pairs of plant communities varied from 32for Communities 1 and 3 and Communities 5 and 24 to 37for Communities 3 and 5 (not shown in tables)

The ordination diagram (Figure 5) shows that one topo-graphic and six edaphic variables appear to be associatedwiththe four plant communities and the species distribution inthe study area The strongest correlation with communitycomposition was observed for elevation followed by soilpH at 0ndash15 cm depth base cation Ca2+ at 0ndash15 cm depthpercent base saturation (BS) at 0ndash15 cm depth percent clayat 0ndash15 cm depth C N ratio at 15ndash30 cm depth and percentsand at 0ndash15 cm depth The base cations magnesium (Mg2+)and potassium (K+) were not directly correlated with thecommunity composition but since they are included in thebase saturation percentage they are indirectly related Plantcommunities were ordered along the second ordination axiswhich was positively correlated with pH15 (119903 = 071) Ca15(119903 = 069) BS (119903 = 065) andClay15 (119903 = 052) and negativelycorrelated with Sand15 (119903 = minus046) Axis 1 of the ordinationwas positively correlated with Elev (119903 = 085) and CNrat30(119903 = 051) As shown in Table 3 and indicated graphically inFigure 5 correlations between many of the edaphic variablesare strong particularly between pH15 Sand15 Clay15 Ca15and BS whereas correlation between topographic and mostedaphic variables is small and nonsignificant However thereis a significant negative correlation (119903 = minus042) between Elevand Sand15 indicating that sandy soils are mostly found atlower elevations

4 Discussion

41 Species Composition The results reported in this studyshow that the composition of the vegetation types found in

Elev

pH15Ca15

Sand15

Clay15

CNrat30

BS

Axis 1

Axis 2

Community 1Community 3

Community 5Community 24

Figure 5 Compositional gradients and plant communities in NMSordination of 35 vegetation plots for trees ge5 cm in GangalamtumbaVLFR Four plant communities are recognized (cf Table 2) Com-munity 1 = Brachystegia spiciformis Diplorynchus condylocarponand Lannea schweinfurthii woodland Community 3 = Dalbergiaarbutifolia Commiphora africana and Albizia petersianawoodlandCommunity 5 = Acacia sp Acacia abyssinica and Albizia amarawoodland and Community 24 = Bauhinia petersiana and Shreberatrichoclada woodland Elev elevation (m) CNrat30 C N ratio at15ndash30 cm depth Sand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm Ca15 = Ca2+ (cmol(+)kg) at 0ndash15 cm pH15 = soil pH at 0ndash15 cm BS base saturation at 0ndash15 cm

the GVLFR especially the dominance of species from thefamily Caesalpiniaceae agreed well with previous descrip-tions and classifications of plant communities commonlyfound in miombo woodlands [1] However the observeddominance based on IVI of the genera Dalbergia Com-miphora and Combretum contrasts with patterns usuallyconsidered common for miombo woodlands The frequencyof species in these genera was also high compared to otherspecies observed in the GVLFR (Table 1) Similar deviationsexist between the results obtained by Banda et al [26]in the Katavi-Rukwa ecosystem where they observed thatTerminalia and Combretum were the dominant genera andthe findings of Giliba et al [27] and Njana [43] whoboth noted the dominance of the two common miombogenera Brachystegia and Julbernardia However Combretumalso occurred in their study areas The results suggest thaton a larger spatial scale the species diversity of miombowoodlands is very high and that the three common generaBrachystegia Julbernadia and Isoberlinia are not alwaysdominant at the local scale

The species richness observed in the GVLFR compareswell with miombo community studies in other areas of drymiombo in Tanzania and elsewhere which receive an average

ISRN Biodiversity 11

Table2Plantcom

mun

itiesandspeciesa

ssociatio

nsin

thed

ryMiombo

woo

dlands

ofGangalamtumba

VLF

RCom

mun

itynu

mbers135and24

representthe

different

plantassociatio

ns

119899speciesnu

mbero

fspecies

(77in

total)with

Dbhge5c

mIV+

speciesind

icator

valuemeanplusmnstd

errorand

BAisbasalarea

Com

mun

ityAs

sociated

species

Family

Habit

IV+

()

Con

stancy

()119875value

Stem

sha

BA m2 ha

MeanDbh

Brachyste

giaspiciform

ismdashDiplorhynchus

cond

ylocarponmdashLa

nnea

schw

einfurthiiw

oodland

1(n s

pecies

=47

nplots=9)

Sitevariables(meanplusmnSE

)Elev

=1200plusmn20pH15

=644plusmn013C

a15=604plusmn128

Sand

15=721plusmn431C

lay15=137plusmn188Silt15

=142plusmn335C

Nrat30=135plusmn05andBS

=526plusmn65

Brachyste

gia

spiciform

isCa

esalpiniaceae

T820

100

000

02164plusmn59356plusmn077138plusmn07

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T759

89000

0866plusmn18044plusmn01382plusmn05

Lann

easchw

einfurthii

Anacardiaceae

T719

100

000

0449plusmn14072plusmn022126plusmn09

Bosciaangustifolia

Capp

araceae

T536

5600056

27plusmn12014plusmn00776plusmn06

Euphorbiacuneata

Euph

orbiaceae

ST428

4400200

42plusmn19012plusmn00665plusmn06

Other

species

mdashmdash

mdashmdash

mdash1075plusmn5741007plusmn647102plusmn03

Subtotal

1423plusmn174

1505plusmn178

109plusmn03

DalbergiaarbutifoliamdashCo

mmiphora

afric

anamdash

Albizia

petersiana

woo

dland

3(n

species=55n

plots=

16)Site

variables(meanplusmnSE

)Elev

=986plusmn19pH15

=648plusmn009C

a15=856plusmn109

Sand

15=767plusmn156C

lay15=135plusmn155Silt15

=97plusmn096C

Nrat30=106plusmn03andBS

=744plusmn44

Dalbergiaarbutifolia

Fabaceae

subfam

ilyPapilio

noideae

ST793

100

000

02500plusmn123263plusmn06477plusmn02

Commiphora

afric

ana

Burseraceae

T542

9400026

187plusmn40272plusmn064119plusmn06

Albiziapetersiana

Mim

osacea

T536

7500200

157plusmn57103plusmn04084plusmn02

Sclerocarryabirrea

Anacardiaceae

T504

6300186

40plusmn11128plusmn045168plusmn17

Other

species

mdashmdash

mdashmdash

mdash852plusmn449669plusmn37788plusmn03

Subtotal

1735plusmn166

1435plusmn071

92plusmn02

Acaciaspmdash

Acaciaabyssin

icamdash

Albiziaam

arawoo

dland

5(n

species=33n

plots=5)

Sitevariables(m

eanplusmnSE

)Elev

=986plusmn52pH15

=734plusmn023C

a15=139plusmn33

Sand

15=745plusmn678C

lay15=148plusmn47Silt15

=107plusmn26C

Nrat30=106plusmn07andBS

=963plusmn89

Acaciasp

Mim

osaceae

T981

100

000

02269plusmn111662plusmn286172plusmn14

Acaciaabyssin

icaMim

osaceae

T594

8000030

31plusmn9060plusmn03299plusmn08

Albiziaam

ara

Mim

osaceae

T552

60000

6654plusmn30023plusmn01671plusmn08

Grew

iabicolor

Tiliaceae

ST533

6000106

113plusmn52040plusmn01770plusmn04

Acaciaseyal

Mim

osaceae

T433

6000526

62plusmn34034plusmn01790plusmn05

Other

species

mdashmdash

mdashmdash

mdash665plusmn533552plusmn49872plusmn04

Subtotal

1194plusmn169

1367plusmn347

101plusmn05

Bauh

iniapetersiana

mdashShrebera

trichoclada

woo

dland

24(n

species=35n

plots=5)

Sitevariables(meanplusmnSE

)Elev

=1175plusmn25pH15

=73plusmn04C

a15=254plusmn69

Sand

15=522plusmn68C

lay15=331plusmn28

Silt15=147plusmn44C

Nrat30=961plusmn13andBS

=1041plusmn204

Bauh

iniapetersiana

Caesalpiniaceae

SH551

8000118192plusmn121111plusmn05075plusmn03

Shrebera

trichoclada

Oleaceae

T505

6000110

57plusmn32022plusmn01380plusmn05

Manilkaramochisia

Sapo

taceae

T376

4000332

34plusmn27014plusmn00969plusmn10

Dalbergia

mela

noxylon

Fabaceae

T370

4000380

68plusmn58026plusmn02266plusmn03

Ehretia

amoena

Boraginaceae

ST347

4000344

6plusmn4

002plusmn00170plusmn04

Other

species

mdashmdash

mdashmdash

mdash982plusmn759643plusmn47999plusmn05

Subtotal

1338plusmn137

817plusmn087

91plusmn04

Total

1521plusmn5941355plusmn55298plusmn01

Elevelevatio

n(m

)CN

rat30CN

ratio

at15ndash30c

mdepthSand

15sand(

)at0

ndash15c

mC

lay15clay

()at0

ndash15c

mSilt15silt

()at0

ndash15c

mC

a15Ca2+(cmol(+)kg)at0

ndash15c

mpH15soilp

Hat0ndash

15cm

BS

base

saturatio

nat0ndash

15cm

12 ISRN Biodiversity

Table 3 Pearson-correlation matrix for two topographic and eight edaphic variablesdagger associated with the classified plant communities in theGangalamtumba VLFR (119899 = 35) Applied significance levels lowast5 lowastlowast1 and lowastlowastlowast01 +not significant

Elev Slope pH15 Ca15 K15 N15 Sand15 Clay15 CNrat30Slope 019+

pH15 minus013+ minus033lowast

Ca15 002+ minus020+ 083lowastlowastlowast

K15 minus029+ 000+ 010+ 012+

N15 006+ 036lowast 010+ 041lowastlowast 033lowast

Sand15 minus042lowastlowast 003+ minus053lowastlowastlowast minus074lowastlowastlowast 006+ minus046lowastlowast

Clay15 031+ minus012+ 051lowastlowast 076lowastlowastlowast minus001+ 047lowastlowast minus086lowastlowastlowast

CNrat30 036lowast 010+ minus039lowast minus051lowastlowast minus015+ minus019+ 040lowast minus048lowastlowast

BS minus024+ minus017+ 084lowastlowastlowast 091lowastlowastlowast 015+ 037lowast minus058lowastlowastlowast 060lowastlowastlowast minus051lowastlowastdaggerElev elevation (m) pH15 soil pH at 0ndash15 cm Ca15 Ca2+ (cmol(+)kg) at 0ndash15 cm K15 K+ (cmol(+)kg) at 0ndash15 cm N15 N concentration at 0ndash15 cmSand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm CNrat30 C N ratio at 15ndash30 cm depth BS base saturation at 0ndash15 cm 119905-value was calculated as119905 = 119903radic(119899 minus 2)(1 minus 119903

2) where 119903 is the Pearson-correlation coefficient and 119899 is the total sample size

Table 4 Species richness observed in other studies from drymiombo woodlands

Plot size(ha)

Totalnumberof plots

Total samplearea(ha)

Total numberof species References

0071 70 495 82 [43]0071 80 565 110 [27]0071 133 940 229 [26]0071 247 1746 102 [44]004 40 160 81 [45]025 14 350 69 [25]01 2 020 40 [28]01 152 1520 92 genera [22]0071 35 247 88 This study

annual rainfall of 565ndash1500mm (Table 4) Using plot sizes of004ndash025 ha and sample sizes of 2ndash247 plots a total numberof species ranging from40 (Dbhge 10 cm) to 229 (Dbhge 2 cm)have been reported fromMiombowoodlands [22 25ndash28 43ndash45]

The high number of species reported by Banda et al [26]Chidumayo [22] Isango [45] and Chamshama et al [44] islikely to be a consequence of the spatial scale and coverage ofthese studies as they all cover large areas include more thanone site and operate with large sample sizes For exampleChidumayo [22] included species from both wet and dryMiombo areas in Zambia The study by Sauer and Abdallah[15] who reported a total of 131 species occurring in thetobacco growing zone of Iringa rural district included twoforest reserves and three family-managed forests Thereforeconsidering the climatic conditions in the GVLFR (617mmof rainfall per year) and the sample size (35 plots) thespecies richness reported in this study can be ranked atleast as high or higher than those found in the studiesmentioned The selective sampling approach focusing onvarious microhabitat types adopted by Banda et al [26] mayhave contributed to the large number of species observed

in their study area Similarly the higher number of speciesfound by Giliba et al [27] was probably due to the presenceof riverine forest offering site conditions favourable formanyspecies

The values of the Shannon-Wiener (1198671015840 = 344) andSimpson indices (119863 = 005) reported for large individ-uals in this study are within the range observed for mostcommunities of particular life forms [36] For example 1198671015840usually does not exceed 5 although this maximum valuevaries depending on the type of the biological communitysampled and the sampling approach applied (eg minimumdiameter and size of sample units) A threshold value of 2 for1198671015840 has been mentioned as a minimum value above which

an ecosystem can be regarded as medium to highly diverse[27] Chamshama et al [44] reported three 1198671015840 values of31 32 and 33 from Kitulangalo Miombo forest in EasternTanzania while Njana [43] reported a 1198671015840 value of 340from dry Miombo forest in Western Tanzania The studiesby Sauer and Abdallah [15] and Giliba et al [27] reportedparticularly high values of 346 and 427 respectively Thiscould be attributed to the very large sample sizes used inboth studies and the presence of riverine forest where thechance of encountering many rare species is likely to be highThe forests examined in the mentioned studies receive anaverage annual rainfall of 700ndash1000mm compared to whichthe rainfall in the GVLFR is low (617mm on average per yearcf above)The relatively high diversity found inGVLFRmusttherefore be attributed to other factors than climate The soilanalyses indicate that the soil fertility level in the GVLFRis relatively high with considerable proportions of all 2 1lattice clay minerals (114) (ie illite montmorillonite andvermiculite) plus a good amount of organic matter whichmay suggest that the soil has large reserves of important plantnutrients for example K Mg and Fe The base saturationpercentage (BS) which is normally used to indicate the soilfertility status (Landon 1991) was also high 76 on averageand with 86 of the samples (30 samples) with BS valuesgt50 (fertile soil) and only 14 of the samples (5 samples)with BS below 50 (less fertile soil) As another indicationof high soil fertility status the mean C N ratio was 12 plusmn 043

ISRN Biodiversity 13

(range 7ndash19) for top soil (0ndash15 cm) and 11 plusmn 036 (range 5ndash16) for subsoil (15ndash30 cm) In general the values for both soilstrata fall within the expected range of 8ndash17 Soil pH values(mean 67 plusmn 01 range 567ndash852)were alsowithin the optimalrangewhere all the nutrients that aremost important for plantgrowth (Ca Mg K and P) are available and accessible toplants [46] In this study 97 of the soil samples had pHbelow 8 (one sample had a pH of 852) Fisher and Binkley[47] noted that high pH is almost never a problem in forestsas most trees do well across the full range of common pHvaluesTherefore considering the low average annual rainfallcompared to other forests the relatively high fertility of theGVLFR may be the main factor creating an environmentfavourable to many species thus leading to a quite highspecies diversity observed in this forest

Based on the Importance Value Index Brachystegia spi-ciformis and Combretum molle appeared to be the mostimportant species among harvested trees (stumps) in thestudy area This result agreed very well with the large valuesof basal area and volume and the information obtained fromlocal scouts and members of the village environmental com-mittee who said that the most frequently harvested speciesfor charcoal making include all Brachystegia species found inthe forest (ie Brachystegia spiciformis Brachystegia mangaBrachystegia boehmii and Brachystegia bussei) Among theCombretum species the most important one (based on IVI)Combretum molle is mostly used for house construction andfirewood rather than for charcoal making Apart from theBrachystegia species the only other species mentioned asimportant for charcoal making was Acacia mellifera Otherspecies are only used in case they happen to fall when fellingthe preferred species during the preparation of charcoal kilnsWith respect to stumps Brachystegia spiciformis Brachystegiamanga and Combretum molle are among the ten mostabundant species in terms of density basal area and volumeper hectare Stumps of the other species mentioned are notcommonly found a factwhichmay be due to the small samplesize being unable to capture sites where these species areharvested but may also be related to their limited distributionin the forest as indicated by the estimated dispersion indices(see Table 1)

42 Forest Structure Species densities reported from otherMiombo woodland areas in Tanzania are typically 348ndash1495stemsha for trees with Dbh gt4 cm [24 43 45] Comparedwith this the GVLFR is highly stocked as the estimateddensity is 2296 stemsha for trees with Dbh gt4 cmThemeanstem density of 1521 plusmn 594ha for trees with Dbh ge5 cmis also more than twice as large as values found in otherstudies [25ndash27 44 45 48] A similar pattern is seen whencomparing the density of regeneration between the studiesThe diameter distribution is characterised by a very cleartrend of decreasing stem density with increasing diameterThe shape of the distribution is thus an inverted ldquoJrdquo (Figure 3)which is a common feature of natural forests with activeregeneration and recruitment [49] However not many largetrees were captured by the sample whereas a considerablenumber of relatively large stumps were observed suggestingthat anthropogenic activities such as charcoal making may

have affected the structure and ecological balance of the forest(see Figure 3) Since the woodlands are often hit by fire whichtends to kill the seedlings (especially the late fires) and thusonly few seedlings can be expected to reach larger diameterclasses lack of mature trees and the resulting lack of seedsmay eventually threaten the biodiversity of the forest

The mean basal area of 1355 plusmn 552m2ha observedin this study is slightly above the range of values typicallyreported from the miombo region 75ndash126m2ha [26 28 4344 50] However the basal areas reported by Isango [45] werea bit higher (1504ndash1563m2ha) than observed in this study

Themean total volume inGVLFRwas estimated at 9217plusmn390m3ha for trees with Dbh ge5 cm Other studies in dryMiombo woodlands have reported mean volumes of 167ndash7603m3ha [24 44 45 50] The current standing volume ofGVLFR is thus slightly higher than values typically reportedfor forests in the Miombo ecoregion A plausible reason forthis may be that compared to other forests the GVLFR isstill well stocked despite ongoing human activities such ascharcoalmakingThebasal area observed for stumpswas only072m2ha so there is no indication of intensive extractionover many years This corresponds well with the findings ofTreue et al [20] who conclude that the estimated 04m3haannual extraction of woody biomass from GVLFR is consid-erably below its estimated annual increment of 15m3ha andthat the local forest managers seem capable of regulating theharvesting activities which in addition to village membersrsquocollection for subsistence uses also included commercialcharcoal production by external companies that pay a fee perbag of charcoal extracted to the village government

43 Plant Communities and Species Associations Except forBrachystegia spiciformis the majority of the Brachystegia andJulbernardia species that are common to miombo wood-lands elsewhere are not among the species most commonlyobserved in this study A similar pattern was observed byBanda et al [26] in the Katavi-Rukwa ecosystem wherethe genera that are most common in miombo woodlandsBrachystegia Julbernardia and Isoberlinia were not commonin their study sites Furthermore the four plant communi-ties distinguished in this study are comparable with thosereported by other studies in Tanzania including the work byMunishi et al [29] in theMiombowoodlands of Rukwa basinChunya district Tanzania and the study by Banda et al [26]in the Katavi-Rukwa ecosystem

Elevation was noted by Munishi et al [29] to be themost important factor shaping the species communities intheir study area This study found a similar pattern with thehighest coefficient of correlation observed for elevation sug-gesting that topographical variation is among the strongestdeterminants of community composition in dry Miombowoodlands hence influencing the spatial distribution ofspecies strongly However in our study area edaphic factorsalso influenced the species distribution directly Two plantcommunities occurredmainly on clayey soils with high pH atintermediate elevations one on sandy soils with lowpHat lowelevations and one on sandy-clayey soils at higher elevationsand with neutral soil pH (Figure 5) Specifically it appeared

14 ISRN Biodiversity

that the Acacia woodland category (Community 5) grows atlow elevations around temporary streams (or at least wherethe ground water table is relatively high) and the Bauhiniawoodland category (Community 24) appearsmostly in placeswith a relatively high percentage of clay (and therefore highvalues of pH Ca and BS) By contrast it appeared that theDalbergia woodland category (Community 3) is located atmore sandy sites (with low values of pH Ca and BS) andthe Brachystegia woodland category (Community 1) seemedto be located mostly at higher elevations where the CN-ratio is quite high Correlations between elevation and thebasic soil variables pH Ca and percentages of sand andclay were low (cf Figure 5) Thus the results indicate thatthe plant communities of the dry miombo woodlands inGVLFR are not only shaped by the topographic variation(elevation) and the groundwater level but also by basic soilcharacteristics The results thus confirm findings from otherstudies detecting effects of elevation and soil characteristicson species composition [51 52]

5 Conclusion

Considering that the sample size used in this study wassmaller than samples used in other studies in dry miombowoodlands the results show that the species diversity inGVLFR is relatively high compared to other forest reservesThe vegetation of GVLFR is characterised by high densitybasal area and volume and despite the scarcity of largediameter trees this indicates that the forest is in a goodcondition The effect of anthropogenic activities is neverthe-less evident and stresses the need for proper managementespecially for economically important species preferred forcharcoalmaking (egBrachystegia spiciformis) if the currentspecies diversity is to be maintained or enhanced A repeatedfuture study would be needed to assess whether the currentcommunity-based management regime yields this intendedoutcome but the available information and analyses allow forsome optimism in this respect

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors wish to thank people from Mfyome villagefor their invaluable assistance during field work Mzee IddiKaheya Damian Chotamasege AugustinoMkwama Libera-tus Simime and Mawazo Nyangwa Furthermore thanks aredue to Venancia Mlelwa from Sokoine University and MadsMadsen Krag from University of Copenhagen for doing thelaboratory work The authors also wish to thank GoodluckMoshi their driverMarcoNjana andNassoroHMagogo theTAFORI botanist for assisting with species identification andKlaus Dons for preparing a study site map Financial supportwas provided by Danida through the ENRECA Project

ldquoParticipatory forest management for rural livelihoods forestconservation and good governance in Tanzaniardquo (no 725)

References

[1] P G H Frost ldquoThe Ecology of Miombo Woodlandsrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 11ndash57 1996

[2] N Burgess J Hales E Underwood et al Terrestrial Ecoregionsof Africa and Madagascar A Conservation Assessment IslandPress World Wildlife Fund 2004

[3] J Clarke W Cavendish and C Coote ldquoRural householdsand miombo woodlands use value and managementrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 101ndash135 1996

[4] B M Campbell A Angelsen A Cunningham Y KaterereA Sitoe and S Wunder ldquoMiombo woodlandsmdashopportunitiesand barriers to sustainable forest managementrdquo httpsener-gypediainfoimages66dMiombo2007pdf

[5] S Syampungani P W Chirwa F K Akinnifesi G Sileshi andO C Ajayi ldquoTheMiombo woodlands at the cross roads poten-tial threats sustainable livelihoods policy gaps and challengesrdquoNatural Resources Forum vol 33 no 2 pp 150ndash159 2009

[6] J I O Abbot and K Homewood ldquoA history of change causesof miombo woodland decline in a protected area in MalawirdquoJournal of Applied Ecology vol 36 no 3 pp 422ndash433 1999

[7] E J Luoga E T F Witkowski and K Balkwill ldquoLand coverand use changes in relation to the institutional frameworkand tenure of land and resources in eastern Tanzania Miombowoodlandsrdquo Environment Development and Sustainability vol7 no 1 pp 71ndash93 2005

[8] FAO The State of Food and Agriculture 2010-2011 Forest andAgriculture Organization Rome Italy 2010

[9] A H Gentry ldquoTropical forest biodiversity distributional pat-terns and their conservational significancerdquo Oikos vol 63 no1 pp 19ndash28 1992

[10] O E Sala F S Chapin III J J Armesto et al ldquoGlobalbiodiversity scenarios for the year 2100rdquo Science vol 287 no5459 pp 1770ndash1774 2000

[11] H J Geist and E F Lambin ldquoProximate causes and underlyingdriving forces of tropical deforestationrdquo BioScience vol 52 no2 pp 143ndash150 2002

[12] R S DeFries ldquoTropical forests deforestation and ecosystemsservices Contributions of remote sensingrdquo in GeoinformaticsFor Tropical Ecosystems P S Roy Ed pp 1ndash32 2003

[13] B M Campbell P Frost and N Bryon ldquoMiombo woodlandsand their use overview and key issuesrdquo in The Miombo inTransition Woodlands and Welfare in Africa B Campbell Edpp 1ndash10 2006

[14] H J Geist ldquoGlobal assessment of deforestation related totobacco farmingrdquo Tobacco Control vol 8 no 1 pp 18ndash28 1999

[15] J Sauer and J M Abdallah ldquoForest diversity tobacco produc-tion and resource management in Tanzaniardquo Forest Policy andEconomics vol 9 no 5 pp 421ndash439 2007

[16] E N Chidumayo and K J Mbata ldquoShifting cultivation ediblecaterpillars and livelihoods in the Kopa area of northernZambiardquo Forests Trees and Livelihoods vol 12 no 3 pp 175ndash1932002

[17] E N Chidumayo and L Kwibisa ldquoEffects of deforestation ongrass biomass and soil nutrient status in miombo woodlandZambiardquo Agriculture Ecosystems and Environment vol 96 no1ndash3 pp 97ndash105 2003

ISRN Biodiversity 15

[18] J F Lund and T Treue ldquoAre we getting there Evidence ofdecentralized forest management from the Tanzanian miombowoodlandsrdquoWorld Development vol 36 no 12 pp 2780ndash28002008

[19] T Blomley and S Iddi Participatory Forest Management inTanzania 1993ndash2009mdashLessons Learned and Experiences toDate Ministry of Natural Resources and Tourism Forestry andBeekeeping Division Dar es Salaam Tanzania 2009

[20] T Treue Y M Ngaga H Meilby et al ldquoDoes participatoryforest management promote sustainable forest utilisation inTanzaniardquo International Forestry Review vol 16 no 1 pp 1ndash162014

[21] Ministry ofNatural Resources andTourismParticipatory ForestManagement in Tanzania Facts and Figures Forestry andBeekeeping Division Dar es Salaam Tanzania 2008

[22] E N Chidumayo ldquoSpecies structure in Zambian miombowoodlandrdquo Journal of Tropical Ecology vol 3 no 2 pp 109ndash1181987

[23] J D Lowore ldquoCoppice regeneration in some miombo wood-lands of Malawirdquo FRIM Report 99001 Forestry ResearchInstitute of Malawi 1999

[24] E J Luoga E T F Witkowski and K Balkwill ldquoHarvestedand standing wood stocks in protected and communal miombowoodlands of eastern Tanzaniardquo Forest Ecology and Manage-ment vol 164 no 1ndash3 pp 15ndash30 2002

[25] M Williams C M Ryan R M Rees E Sambane J Fernandoand J Grace ldquoCarbon sequestration and biodiversity of re-growing miombo woodlands in Mozambiquerdquo Forest Ecologyand Management vol 254 no 2 pp 145ndash155 2008

[26] T Banda NMwangulango BMeyer et al ldquoThewoodland veg-etation of the Katavi-Rukwa ecosystem in western TanzaniardquoForest Ecology andManagement vol 255 no 8-9 pp 3382ndash33952008

[27] R A Giliba E K Boon C J Kayombo E B Musamba AM Kashindye and P F Shayo ldquoSpecies composition richnessand diversity in Miombo Woodland of Bereku Forest ReserveTanzaniardquo Journal of Biodiversity vol 2 no 1 pp 1ndash7 2011

[28] D D Shirima P K T Munishi S L Lewis et al ldquoCarbonstorage structure and composition of miombo woodlands inTanzaniarsquos Eastern Arc Mountainsrdquo African Journal of Ecologyvol 49 no 3 pp 332ndash342 2011

[29] P K T Munishi R A P C Temu and G Soka ldquoPlant com-munities and tree species associations in a Miombo ecosystemin the Lake Rukwa basin Southern Tanzania implications forconservationrdquo Journal of Ecology and Natural Environment vol3 no 2 pp 63ndash71 2011

[30] J Dewis and F Freitas ldquoPhysical analysis of soilsrdquo in Physicaland Chemical Methods of Soil andWater Analysis FAO Bulletinno 10 pp 51ndash57 2nd edition 1970

[31] S R Olsen and L E Sommers ldquoPhosphorusrdquo inMethods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 403ndash430 American Societyof Agronomy Madson Wis USA 1982

[32] J D Rhoades ldquoCation exchange capacityrdquo in Methods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 149ndash157 American Society ofAgronomy Madson Wis USA 1982

[33] IMatejovic ldquoDetermination of carbon hydrogen and nitrogenin soils by automated elemental analysis (dry combustionmethod)rdquo Communications in Soil Science and Plant Analysisvol 24 no 17-18 pp 2213ndash2222 1993

[34] J P Moslashberg Soil Analysis Manual Revised Edition Laboratoryof Soil Sciences Department of Soil Science SokoineUniversityof Agriculture Morogoro Tanzania 2001

[35] N C BradyThe Nature and Properties of Soils Macmillan 8thedition 1974

[36] C J Krebs Ecological Methodology Hamper Collins PublishersNew York NY USA 2nd edition 1999

[37] B Husch T W Beers and J A Kershaw Forest MensurationJohn Wiley amp Sons Hoboken NJ USA 4th edition 2003

[38] E E Mwakalukwa H Meilby and T Treue ldquoVolume andaboveground biomass models for dry Miombo Woodland inTanzaniardquo In press

[39] M Kent Vegetation Description and Analysis A PracticalApproach Wiley-Blackwell John Wiley amp Sons Hoboken NJUSA 2nd edition 2012

[40] B McCune and M J Mefford PC-ORD Multivariate Analysisof Ecological Data Version 6 MjM Software Gleneden BeachOre USA 2011

[41] MDufrene andP Legendre ldquoSpecies assemblages and indicatorspecies the need for a flexible asymmetrical approachrdquo EcologyMonography vol 67 pp 777ndash795 1997

[42] J E PeckMultivariate Analysis for Community Ecologists Step-by-Step using PC-ORD MjM Software Design Gleneden BeachOre USA 2010

[43] M A Njana Arborescent species diversity and stocking inMiombo Woodland of Urumwa forest reserve and their contri-bution to Livelihoods Tabora Tanzania [MS thesis] SokoineUniversity of Agriculture Morogoro Tanzania 2008

[44] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal no 200 pp 59ndash70 2004

[45] J Isango ldquoStand structure and tree species composition ofTanzania miombo woodlands a case study from miombowoodlands of community based forest management in Iringadistrictrdquo in MITMIOMBOmdashManagement of Indigenous TreeSpecies For EcosystemRestoration andWood Production in Semi-Arid Miombo Woodlands in Eastern Africa Proceedings ofthe 1st MITMIOMBO Project Workshop held in MorogoroTanzania 6th-12th February 2007 Working Papers of theFinnish Forest Research Institute no 50 pp 43ndash56 2007

[46] J R Landon Booker Tropical Soil Manual A Handbook ForSoil Survey and Agricultural Land Evaluation in the Tropics andSubtropics Longman Scientific amp Technical and John Wiley ampSons 1991

[47] R F Fisher and D Binkley Ecology and Management of ForestSoils John Wiley amp Sons 3rd edition 2000

[48] W A Rees ldquoPreliminary studies into bush utilization by Cattlein Zambiardquo Journal of Applied Ecology vol 11 pp 207ndash214 1974

[49] S M Philip Measuring Trees and Forests CAB InternationalWallingford UK 2nd edition 1994

[50] J D Lowore P G Abbot and M Werren ldquoStackwood volumeestimations formiombowoodlands inMalawirdquoCommonwealthForestry Review vol 73 no 3 pp 193ndash197 1994

[51] D Kubota T Masunaga Hermansah et al ldquoSoil environmentand tree species diversity in tropical rain forest West SumatraIndonesiardquo in Soils of Tropical Forest Ecosystems CharacteristicsEcology and Management A Schulte and D Ruhiyat Eds pp159ndash167 1998

[52] P K T Munishi T H Shear T Wentworth and R A PC Temu ldquoCompositional gradients of plant communities insubmontane rainforests of EasternTanzaniardquo Journal of TropicalForest Science vol 19 no 1 pp 35ndash45 2007

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

EcosystemsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MeteorologyAdvances in

EcologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Marine BiologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental Chemistry

Atmospheric SciencesInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Geological ResearchJournal of

EarthquakesJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BiodiversityInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

Page 8: Research Article Floristic Composition, Structure, and

8 ISRN Biodiversity

Table1Con

tinued

Sno

Vernacularlocal

name

Speciesbo

tanical

name

Family

Habitlife

form

Currentp

opulation

Stum

psFrequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

DI

Frequency

()

Density

stemha

Basalarea

(m2 ha)

IVI

67Mbo

liboli

Acaciadrepanolobium

(Harms)

Mim

osaceae

T3

000

01

100

68Mwim

akigulu

Maeruaangolen

sisCa

pparaceae

SH3

1plusmn1

00

01

300

69Mnyali

Tamarindu

sind

icaCa

esalpiniaceae

T6

1plusmn1001plusmn001

01

097

70Mgombw

ani

Combretum

aculeatum

Com

bretaceae

T6

1plusmn1

00

01

097

302plusmn02

00

04

71Msang

ala

Burkea

afric

anaHoo

kCa

esalpiniaceae

T3

0001plusmn001

01

100

302plusmn02

00

04

72Mkokonza

Opilia

amentacea

Roxb

Opiliaceae

SH3

000

00

100

311plusmn11

00

42

73Mfumbi

Kigelia

afric

ana

Bign

oniaceae

T3

000

00

100

74Mlang

ali

Euphorbia

cand

elabrum

Euph

orbiaceae

T3

000

00

100

75Mpu

lulu

Term

inaliaseric

eaCom

bretaceae

T3

000

00

100

76Mdaha

Diospyros

usam

barensisFWhite

Ebenaceae

T3

000

00

100

305plusmn05001plusmn001

15

77Mtund

wa

XimeniacaffraSond

Olacaceae

ST3

000

00

100

78Mwim

aperu

Tarenn

agla

veolens(S

Moo

re)B

rem

Rubiaceae

ST+

79Mwesa

Boscia

mossambicensisKl

Capp

araceae

ST+

80Musasam

ulo

Psychotria

schu

mmaniana

Rubiaceae

ST+

81Muh

anza

Senn

asin

gueana

Caesalpiniaceae

ST+

82Mtund

wahavi

Ximeniaam

erica

naOlacaceae

ST+

83Mtin

giligiti

Phyllanthu

sengler

iPax

Euph

orbiaceae

T+

84Msada

Vangueria

madagascarie

nsis

Gmel

Rubiaceae

ST+

85Mku

nung

uZa

nthoxylum

chalybeum

Rutaceae

T+

86Lu

kali

Croton

scheffleriP

axEu

phorbiaceae

SH+

87Kilim

andembw

eGardeniaternifolia

KSchu

mamp

Thon

nRu

biaceae

ST+

88MpelaM

buyu

Adan

soniadigitata

Bombacaceae

T++

Total(allspecies)

13511521plusmn5941355plusmn552

200

294

60plusmn30072plusmn049

200

+indicatesspecies

identifi

edam

ongsm

allerind

ividualswith

in5m

radius

plots(Dbhlt5c

m)and++

indicatesthata

largeind

ividualw

asidentifi

edwith

ina1

5-radius

plot

butw

asno

tincludedin

thea

nalyseso

fste

mdensitybasalareaand

volumea

sitw

asconsidered

anou

tlier

duetoits

tremendo

ussiz

e(Dbh

=340c

m)

ISRN Biodiversity 9

005 and that of small individuals was 006 The followingspecies were observed to have the greatest contributionsto the Shannon-Wiener diversity index of large individualsDalbergia arbutifolia (contributing 030) Combretum molle(020) Commiphora africana (019) Albizia petersiana (016)and Margaritaria discoidea (014) while for smaller ones thegreatest contributions were found for Brachystegia spiciformis(026) Dalbergia arbutifolia (024) Grewia forbesii (023)Margaritaria discoidea (020) and Dichrostachys cinerea(016) In terms of frequency of occurrence for standingindividuals (large sizes) Commiphora africana was the mostfrequent species (77 of plots) followed by Combretummolle (74) and Dalbergia arbutifolia (60) while for smallsizes Margaritaria discoidea (66) Markhamia obtusifolia(63) and Dalbergia arbutifolia (57) were the most fre-quent species The Importance Value Index (IVI) for largeindividuals (Dbh ge 5 cm) shows that Dalbergia arbutifolia(224) Commiphora africana (175) and Combretum molle(132) were the most important species among standingindividuals while Brachystegia spiciformis (308)Combretummolle (307) and Dichrostachys cinerea (178) appeared to bethe most important among harvested individuals (stumps)These species were also found to have higher frequencies thanany other harvested species observed in the GVLFR (Table 1)

33 Stem Density The total mean stem density for large indi-viduals with Dbh ge5 cm was 1521 plusmn 594 stemsha (Table 1)and that of small individuals with Dbh lt5 cm (includingindividuals with Dbh lt1 cm) was 14318 plusmn 6956 stemshaAmong large individuals the most abundant species wereDalbergia arbutifolia (162 of 1521 stemsha) Combretummolle (8) Commiphora africana (72) and Albizia peter-siana (53) Among small individuals the most abundantspecies were Brachystegia spiciformis (13 of 14318 stemsha)followed by Dalbergia arbutifolia (11) and Grewia forbesii(10) For stumps the overall mean density was 60 plusmn38 stemsha with Combretum molle (12) Dalbergia arbuti-folia (12) Brachystegia spiciformis (10) and Dichrostachyscinerea (10) contributing the most (Table 1) Generally thedistribution of standing trees to size classes showed the usualreverse J shape which was also approximately observed forstumps (Figure 3) However for stumps the density of stemsin the 1ndash10 cm diameter class was slightly lower than whatwould be expected if tree felling had been a random event

34 Basal Area For the GVLFR as a whole the meanbasal areas for large (ge5 cm Dbh) and small individuals(lt5 cm Dbh) were 1355 plusmn 552m2ha (Table 1 Figure 4)and 305 plusmn 002m2ha respectively The species contributingmost to the basal area of large individuals were Commiphoraafricana (12) Dalbergia arbutifolia (10) and Brachystegiaspiciformis (9) while those contributing most to the basalarea of smaller individuals were Dalbergia arbutifolia (16)Grewia forbesii (15) and Dichrostachys cinerea (13) Themean basal area for stumps was 072m2ha with Brachystegiaspiciformis contributing the greatest individual proportion(28) 41 species made up the rest (Figure 4)

60542

3335

530

113

28 24

346166

34

11

02

01

10

100

1000

10000

100000

Diameter classes (cm)

Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Stem

s (ha

minus1)

Figure 3 Density of standing trees ge1 cmDbh and stumps ge1 cm bydiameter class in Gangalamtumba VLFR (119899 = 35) NB logarithmicscale on vertical axis

744477

241

103041 055

014025 018

010004

001

01

1

10

Diameter classes (cm)Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Mea

n ba

sal a

rea (

m2

haminus1)

Figure 4 Distribution of basal area per hectare for standingtrees ge1 cm Dbh and stumps ge1 cm by diameter classes in theGangalamtumba VLFR (119899 = 35) NB logarithmic scale on verticalaxis

35 Volume The mean volumes for large (ge5 cm Dbh) andsmall individuals (lt5 cm Dbh) were 9217 plusmn 390m3ha and1257 plusmn 635m3ha respectively (not shown in tables) Thespecies contributing most to the volume of large individualswere Commiphora africana (12) Brachystegia spiciformis(10) Acacia sp (9) and Dalbergia arbutifolia (9) Forsmaller individuals the species that contributed most tovolume were Dalbergia arbutifolia (16) Grewia forbesii(14) and Dichrostachys cinerea (13) The mean remainingvolume of stumps was found to be 015 plusmn 01m3ha withBrachystegia spiciformis contributing the greatest individualpercentage (28) 41 species made up the rest

10 ISRN Biodiversity

36 Spatial Distribution Dispersion indices (DI) are pre-sented for individual species in Table 1 The dispersion indexvalues range from 094 indicating almost complete spatialrandomness or slight underdispersion to 5498 indicatingconsiderable overdispersion that is a patchy or clustereddistributionOut of 77 species excluding the single very largeAdansonia digitata that was considered an outlier 64 species(83) 9 species (12) and 4 species (5) were found tohave DI gt 1 DI = 1 and DI lt 1 respectively so the majorityof species are characterised by a patchy distribution acrossthe forest The species with the lowest estimated DI wasEhretia amoena (094) while the highest DI was estimated forCordia sinensis (5498)Themost abundant species includingDalbergia arbutifolia (DI = 4765) Combretum molle (DI =1523) and Commiphora africana (DI = 1142) are stronglyoverdispersed

37 Plant Communities and Species Association Four plantcommunities were identified through cluster analysis basedon the statistical significance (5) of the observed maximumindicator values (Table 2) Only two of these plant commu-nities were dominated by species from the family Caesalpini-aceae (Communities 1 and 24) The other two showed greatvariationoverlap between species of different plant families(Communities 3 and 5) The estimated Steinhaus similarityindices between pairs of plant communities varied from 32for Communities 1 and 3 and Communities 5 and 24 to 37for Communities 3 and 5 (not shown in tables)

The ordination diagram (Figure 5) shows that one topo-graphic and six edaphic variables appear to be associatedwiththe four plant communities and the species distribution inthe study area The strongest correlation with communitycomposition was observed for elevation followed by soilpH at 0ndash15 cm depth base cation Ca2+ at 0ndash15 cm depthpercent base saturation (BS) at 0ndash15 cm depth percent clayat 0ndash15 cm depth C N ratio at 15ndash30 cm depth and percentsand at 0ndash15 cm depth The base cations magnesium (Mg2+)and potassium (K+) were not directly correlated with thecommunity composition but since they are included in thebase saturation percentage they are indirectly related Plantcommunities were ordered along the second ordination axiswhich was positively correlated with pH15 (119903 = 071) Ca15(119903 = 069) BS (119903 = 065) andClay15 (119903 = 052) and negativelycorrelated with Sand15 (119903 = minus046) Axis 1 of the ordinationwas positively correlated with Elev (119903 = 085) and CNrat30(119903 = 051) As shown in Table 3 and indicated graphically inFigure 5 correlations between many of the edaphic variablesare strong particularly between pH15 Sand15 Clay15 Ca15and BS whereas correlation between topographic and mostedaphic variables is small and nonsignificant However thereis a significant negative correlation (119903 = minus042) between Elevand Sand15 indicating that sandy soils are mostly found atlower elevations

4 Discussion

41 Species Composition The results reported in this studyshow that the composition of the vegetation types found in

Elev

pH15Ca15

Sand15

Clay15

CNrat30

BS

Axis 1

Axis 2

Community 1Community 3

Community 5Community 24

Figure 5 Compositional gradients and plant communities in NMSordination of 35 vegetation plots for trees ge5 cm in GangalamtumbaVLFR Four plant communities are recognized (cf Table 2) Com-munity 1 = Brachystegia spiciformis Diplorynchus condylocarponand Lannea schweinfurthii woodland Community 3 = Dalbergiaarbutifolia Commiphora africana and Albizia petersianawoodlandCommunity 5 = Acacia sp Acacia abyssinica and Albizia amarawoodland and Community 24 = Bauhinia petersiana and Shreberatrichoclada woodland Elev elevation (m) CNrat30 C N ratio at15ndash30 cm depth Sand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm Ca15 = Ca2+ (cmol(+)kg) at 0ndash15 cm pH15 = soil pH at 0ndash15 cm BS base saturation at 0ndash15 cm

the GVLFR especially the dominance of species from thefamily Caesalpiniaceae agreed well with previous descrip-tions and classifications of plant communities commonlyfound in miombo woodlands [1] However the observeddominance based on IVI of the genera Dalbergia Com-miphora and Combretum contrasts with patterns usuallyconsidered common for miombo woodlands The frequencyof species in these genera was also high compared to otherspecies observed in the GVLFR (Table 1) Similar deviationsexist between the results obtained by Banda et al [26]in the Katavi-Rukwa ecosystem where they observed thatTerminalia and Combretum were the dominant genera andthe findings of Giliba et al [27] and Njana [43] whoboth noted the dominance of the two common miombogenera Brachystegia and Julbernardia However Combretumalso occurred in their study areas The results suggest thaton a larger spatial scale the species diversity of miombowoodlands is very high and that the three common generaBrachystegia Julbernadia and Isoberlinia are not alwaysdominant at the local scale

The species richness observed in the GVLFR compareswell with miombo community studies in other areas of drymiombo in Tanzania and elsewhere which receive an average

ISRN Biodiversity 11

Table2Plantcom

mun

itiesandspeciesa

ssociatio

nsin

thed

ryMiombo

woo

dlands

ofGangalamtumba

VLF

RCom

mun

itynu

mbers135and24

representthe

different

plantassociatio

ns

119899speciesnu

mbero

fspecies

(77in

total)with

Dbhge5c

mIV+

speciesind

icator

valuemeanplusmnstd

errorand

BAisbasalarea

Com

mun

ityAs

sociated

species

Family

Habit

IV+

()

Con

stancy

()119875value

Stem

sha

BA m2 ha

MeanDbh

Brachyste

giaspiciform

ismdashDiplorhynchus

cond

ylocarponmdashLa

nnea

schw

einfurthiiw

oodland

1(n s

pecies

=47

nplots=9)

Sitevariables(meanplusmnSE

)Elev

=1200plusmn20pH15

=644plusmn013C

a15=604plusmn128

Sand

15=721plusmn431C

lay15=137plusmn188Silt15

=142plusmn335C

Nrat30=135plusmn05andBS

=526plusmn65

Brachyste

gia

spiciform

isCa

esalpiniaceae

T820

100

000

02164plusmn59356plusmn077138plusmn07

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T759

89000

0866plusmn18044plusmn01382plusmn05

Lann

easchw

einfurthii

Anacardiaceae

T719

100

000

0449plusmn14072plusmn022126plusmn09

Bosciaangustifolia

Capp

araceae

T536

5600056

27plusmn12014plusmn00776plusmn06

Euphorbiacuneata

Euph

orbiaceae

ST428

4400200

42plusmn19012plusmn00665plusmn06

Other

species

mdashmdash

mdashmdash

mdash1075plusmn5741007plusmn647102plusmn03

Subtotal

1423plusmn174

1505plusmn178

109plusmn03

DalbergiaarbutifoliamdashCo

mmiphora

afric

anamdash

Albizia

petersiana

woo

dland

3(n

species=55n

plots=

16)Site

variables(meanplusmnSE

)Elev

=986plusmn19pH15

=648plusmn009C

a15=856plusmn109

Sand

15=767plusmn156C

lay15=135plusmn155Silt15

=97plusmn096C

Nrat30=106plusmn03andBS

=744plusmn44

Dalbergiaarbutifolia

Fabaceae

subfam

ilyPapilio

noideae

ST793

100

000

02500plusmn123263plusmn06477plusmn02

Commiphora

afric

ana

Burseraceae

T542

9400026

187plusmn40272plusmn064119plusmn06

Albiziapetersiana

Mim

osacea

T536

7500200

157plusmn57103plusmn04084plusmn02

Sclerocarryabirrea

Anacardiaceae

T504

6300186

40plusmn11128plusmn045168plusmn17

Other

species

mdashmdash

mdashmdash

mdash852plusmn449669plusmn37788plusmn03

Subtotal

1735plusmn166

1435plusmn071

92plusmn02

Acaciaspmdash

Acaciaabyssin

icamdash

Albiziaam

arawoo

dland

5(n

species=33n

plots=5)

Sitevariables(m

eanplusmnSE

)Elev

=986plusmn52pH15

=734plusmn023C

a15=139plusmn33

Sand

15=745plusmn678C

lay15=148plusmn47Silt15

=107plusmn26C

Nrat30=106plusmn07andBS

=963plusmn89

Acaciasp

Mim

osaceae

T981

100

000

02269plusmn111662plusmn286172plusmn14

Acaciaabyssin

icaMim

osaceae

T594

8000030

31plusmn9060plusmn03299plusmn08

Albiziaam

ara

Mim

osaceae

T552

60000

6654plusmn30023plusmn01671plusmn08

Grew

iabicolor

Tiliaceae

ST533

6000106

113plusmn52040plusmn01770plusmn04

Acaciaseyal

Mim

osaceae

T433

6000526

62plusmn34034plusmn01790plusmn05

Other

species

mdashmdash

mdashmdash

mdash665plusmn533552plusmn49872plusmn04

Subtotal

1194plusmn169

1367plusmn347

101plusmn05

Bauh

iniapetersiana

mdashShrebera

trichoclada

woo

dland

24(n

species=35n

plots=5)

Sitevariables(meanplusmnSE

)Elev

=1175plusmn25pH15

=73plusmn04C

a15=254plusmn69

Sand

15=522plusmn68C

lay15=331plusmn28

Silt15=147plusmn44C

Nrat30=961plusmn13andBS

=1041plusmn204

Bauh

iniapetersiana

Caesalpiniaceae

SH551

8000118192plusmn121111plusmn05075plusmn03

Shrebera

trichoclada

Oleaceae

T505

6000110

57plusmn32022plusmn01380plusmn05

Manilkaramochisia

Sapo

taceae

T376

4000332

34plusmn27014plusmn00969plusmn10

Dalbergia

mela

noxylon

Fabaceae

T370

4000380

68plusmn58026plusmn02266plusmn03

Ehretia

amoena

Boraginaceae

ST347

4000344

6plusmn4

002plusmn00170plusmn04

Other

species

mdashmdash

mdashmdash

mdash982plusmn759643plusmn47999plusmn05

Subtotal

1338plusmn137

817plusmn087

91plusmn04

Total

1521plusmn5941355plusmn55298plusmn01

Elevelevatio

n(m

)CN

rat30CN

ratio

at15ndash30c

mdepthSand

15sand(

)at0

ndash15c

mC

lay15clay

()at0

ndash15c

mSilt15silt

()at0

ndash15c

mC

a15Ca2+(cmol(+)kg)at0

ndash15c

mpH15soilp

Hat0ndash

15cm

BS

base

saturatio

nat0ndash

15cm

12 ISRN Biodiversity

Table 3 Pearson-correlation matrix for two topographic and eight edaphic variablesdagger associated with the classified plant communities in theGangalamtumba VLFR (119899 = 35) Applied significance levels lowast5 lowastlowast1 and lowastlowastlowast01 +not significant

Elev Slope pH15 Ca15 K15 N15 Sand15 Clay15 CNrat30Slope 019+

pH15 minus013+ minus033lowast

Ca15 002+ minus020+ 083lowastlowastlowast

K15 minus029+ 000+ 010+ 012+

N15 006+ 036lowast 010+ 041lowastlowast 033lowast

Sand15 minus042lowastlowast 003+ minus053lowastlowastlowast minus074lowastlowastlowast 006+ minus046lowastlowast

Clay15 031+ minus012+ 051lowastlowast 076lowastlowastlowast minus001+ 047lowastlowast minus086lowastlowastlowast

CNrat30 036lowast 010+ minus039lowast minus051lowastlowast minus015+ minus019+ 040lowast minus048lowastlowast

BS minus024+ minus017+ 084lowastlowastlowast 091lowastlowastlowast 015+ 037lowast minus058lowastlowastlowast 060lowastlowastlowast minus051lowastlowastdaggerElev elevation (m) pH15 soil pH at 0ndash15 cm Ca15 Ca2+ (cmol(+)kg) at 0ndash15 cm K15 K+ (cmol(+)kg) at 0ndash15 cm N15 N concentration at 0ndash15 cmSand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm CNrat30 C N ratio at 15ndash30 cm depth BS base saturation at 0ndash15 cm 119905-value was calculated as119905 = 119903radic(119899 minus 2)(1 minus 119903

2) where 119903 is the Pearson-correlation coefficient and 119899 is the total sample size

Table 4 Species richness observed in other studies from drymiombo woodlands

Plot size(ha)

Totalnumberof plots

Total samplearea(ha)

Total numberof species References

0071 70 495 82 [43]0071 80 565 110 [27]0071 133 940 229 [26]0071 247 1746 102 [44]004 40 160 81 [45]025 14 350 69 [25]01 2 020 40 [28]01 152 1520 92 genera [22]0071 35 247 88 This study

annual rainfall of 565ndash1500mm (Table 4) Using plot sizes of004ndash025 ha and sample sizes of 2ndash247 plots a total numberof species ranging from40 (Dbhge 10 cm) to 229 (Dbhge 2 cm)have been reported fromMiombowoodlands [22 25ndash28 43ndash45]

The high number of species reported by Banda et al [26]Chidumayo [22] Isango [45] and Chamshama et al [44] islikely to be a consequence of the spatial scale and coverage ofthese studies as they all cover large areas include more thanone site and operate with large sample sizes For exampleChidumayo [22] included species from both wet and dryMiombo areas in Zambia The study by Sauer and Abdallah[15] who reported a total of 131 species occurring in thetobacco growing zone of Iringa rural district included twoforest reserves and three family-managed forests Thereforeconsidering the climatic conditions in the GVLFR (617mmof rainfall per year) and the sample size (35 plots) thespecies richness reported in this study can be ranked atleast as high or higher than those found in the studiesmentioned The selective sampling approach focusing onvarious microhabitat types adopted by Banda et al [26] mayhave contributed to the large number of species observed

in their study area Similarly the higher number of speciesfound by Giliba et al [27] was probably due to the presenceof riverine forest offering site conditions favourable formanyspecies

The values of the Shannon-Wiener (1198671015840 = 344) andSimpson indices (119863 = 005) reported for large individ-uals in this study are within the range observed for mostcommunities of particular life forms [36] For example 1198671015840usually does not exceed 5 although this maximum valuevaries depending on the type of the biological communitysampled and the sampling approach applied (eg minimumdiameter and size of sample units) A threshold value of 2 for1198671015840 has been mentioned as a minimum value above which

an ecosystem can be regarded as medium to highly diverse[27] Chamshama et al [44] reported three 1198671015840 values of31 32 and 33 from Kitulangalo Miombo forest in EasternTanzania while Njana [43] reported a 1198671015840 value of 340from dry Miombo forest in Western Tanzania The studiesby Sauer and Abdallah [15] and Giliba et al [27] reportedparticularly high values of 346 and 427 respectively Thiscould be attributed to the very large sample sizes used inboth studies and the presence of riverine forest where thechance of encountering many rare species is likely to be highThe forests examined in the mentioned studies receive anaverage annual rainfall of 700ndash1000mm compared to whichthe rainfall in the GVLFR is low (617mm on average per yearcf above)The relatively high diversity found inGVLFRmusttherefore be attributed to other factors than climate The soilanalyses indicate that the soil fertility level in the GVLFRis relatively high with considerable proportions of all 2 1lattice clay minerals (114) (ie illite montmorillonite andvermiculite) plus a good amount of organic matter whichmay suggest that the soil has large reserves of important plantnutrients for example K Mg and Fe The base saturationpercentage (BS) which is normally used to indicate the soilfertility status (Landon 1991) was also high 76 on averageand with 86 of the samples (30 samples) with BS valuesgt50 (fertile soil) and only 14 of the samples (5 samples)with BS below 50 (less fertile soil) As another indicationof high soil fertility status the mean C N ratio was 12 plusmn 043

ISRN Biodiversity 13

(range 7ndash19) for top soil (0ndash15 cm) and 11 plusmn 036 (range 5ndash16) for subsoil (15ndash30 cm) In general the values for both soilstrata fall within the expected range of 8ndash17 Soil pH values(mean 67 plusmn 01 range 567ndash852)were alsowithin the optimalrangewhere all the nutrients that aremost important for plantgrowth (Ca Mg K and P) are available and accessible toplants [46] In this study 97 of the soil samples had pHbelow 8 (one sample had a pH of 852) Fisher and Binkley[47] noted that high pH is almost never a problem in forestsas most trees do well across the full range of common pHvaluesTherefore considering the low average annual rainfallcompared to other forests the relatively high fertility of theGVLFR may be the main factor creating an environmentfavourable to many species thus leading to a quite highspecies diversity observed in this forest

Based on the Importance Value Index Brachystegia spi-ciformis and Combretum molle appeared to be the mostimportant species among harvested trees (stumps) in thestudy area This result agreed very well with the large valuesof basal area and volume and the information obtained fromlocal scouts and members of the village environmental com-mittee who said that the most frequently harvested speciesfor charcoal making include all Brachystegia species found inthe forest (ie Brachystegia spiciformis Brachystegia mangaBrachystegia boehmii and Brachystegia bussei) Among theCombretum species the most important one (based on IVI)Combretum molle is mostly used for house construction andfirewood rather than for charcoal making Apart from theBrachystegia species the only other species mentioned asimportant for charcoal making was Acacia mellifera Otherspecies are only used in case they happen to fall when fellingthe preferred species during the preparation of charcoal kilnsWith respect to stumps Brachystegia spiciformis Brachystegiamanga and Combretum molle are among the ten mostabundant species in terms of density basal area and volumeper hectare Stumps of the other species mentioned are notcommonly found a factwhichmay be due to the small samplesize being unable to capture sites where these species areharvested but may also be related to their limited distributionin the forest as indicated by the estimated dispersion indices(see Table 1)

42 Forest Structure Species densities reported from otherMiombo woodland areas in Tanzania are typically 348ndash1495stemsha for trees with Dbh gt4 cm [24 43 45] Comparedwith this the GVLFR is highly stocked as the estimateddensity is 2296 stemsha for trees with Dbh gt4 cmThemeanstem density of 1521 plusmn 594ha for trees with Dbh ge5 cmis also more than twice as large as values found in otherstudies [25ndash27 44 45 48] A similar pattern is seen whencomparing the density of regeneration between the studiesThe diameter distribution is characterised by a very cleartrend of decreasing stem density with increasing diameterThe shape of the distribution is thus an inverted ldquoJrdquo (Figure 3)which is a common feature of natural forests with activeregeneration and recruitment [49] However not many largetrees were captured by the sample whereas a considerablenumber of relatively large stumps were observed suggestingthat anthropogenic activities such as charcoal making may

have affected the structure and ecological balance of the forest(see Figure 3) Since the woodlands are often hit by fire whichtends to kill the seedlings (especially the late fires) and thusonly few seedlings can be expected to reach larger diameterclasses lack of mature trees and the resulting lack of seedsmay eventually threaten the biodiversity of the forest

The mean basal area of 1355 plusmn 552m2ha observedin this study is slightly above the range of values typicallyreported from the miombo region 75ndash126m2ha [26 28 4344 50] However the basal areas reported by Isango [45] werea bit higher (1504ndash1563m2ha) than observed in this study

Themean total volume inGVLFRwas estimated at 9217plusmn390m3ha for trees with Dbh ge5 cm Other studies in dryMiombo woodlands have reported mean volumes of 167ndash7603m3ha [24 44 45 50] The current standing volume ofGVLFR is thus slightly higher than values typically reportedfor forests in the Miombo ecoregion A plausible reason forthis may be that compared to other forests the GVLFR isstill well stocked despite ongoing human activities such ascharcoalmakingThebasal area observed for stumpswas only072m2ha so there is no indication of intensive extractionover many years This corresponds well with the findings ofTreue et al [20] who conclude that the estimated 04m3haannual extraction of woody biomass from GVLFR is consid-erably below its estimated annual increment of 15m3ha andthat the local forest managers seem capable of regulating theharvesting activities which in addition to village membersrsquocollection for subsistence uses also included commercialcharcoal production by external companies that pay a fee perbag of charcoal extracted to the village government

43 Plant Communities and Species Associations Except forBrachystegia spiciformis the majority of the Brachystegia andJulbernardia species that are common to miombo wood-lands elsewhere are not among the species most commonlyobserved in this study A similar pattern was observed byBanda et al [26] in the Katavi-Rukwa ecosystem wherethe genera that are most common in miombo woodlandsBrachystegia Julbernardia and Isoberlinia were not commonin their study sites Furthermore the four plant communi-ties distinguished in this study are comparable with thosereported by other studies in Tanzania including the work byMunishi et al [29] in theMiombowoodlands of Rukwa basinChunya district Tanzania and the study by Banda et al [26]in the Katavi-Rukwa ecosystem

Elevation was noted by Munishi et al [29] to be themost important factor shaping the species communities intheir study area This study found a similar pattern with thehighest coefficient of correlation observed for elevation sug-gesting that topographical variation is among the strongestdeterminants of community composition in dry Miombowoodlands hence influencing the spatial distribution ofspecies strongly However in our study area edaphic factorsalso influenced the species distribution directly Two plantcommunities occurredmainly on clayey soils with high pH atintermediate elevations one on sandy soils with lowpHat lowelevations and one on sandy-clayey soils at higher elevationsand with neutral soil pH (Figure 5) Specifically it appeared

14 ISRN Biodiversity

that the Acacia woodland category (Community 5) grows atlow elevations around temporary streams (or at least wherethe ground water table is relatively high) and the Bauhiniawoodland category (Community 24) appearsmostly in placeswith a relatively high percentage of clay (and therefore highvalues of pH Ca and BS) By contrast it appeared that theDalbergia woodland category (Community 3) is located atmore sandy sites (with low values of pH Ca and BS) andthe Brachystegia woodland category (Community 1) seemedto be located mostly at higher elevations where the CN-ratio is quite high Correlations between elevation and thebasic soil variables pH Ca and percentages of sand andclay were low (cf Figure 5) Thus the results indicate thatthe plant communities of the dry miombo woodlands inGVLFR are not only shaped by the topographic variation(elevation) and the groundwater level but also by basic soilcharacteristics The results thus confirm findings from otherstudies detecting effects of elevation and soil characteristicson species composition [51 52]

5 Conclusion

Considering that the sample size used in this study wassmaller than samples used in other studies in dry miombowoodlands the results show that the species diversity inGVLFR is relatively high compared to other forest reservesThe vegetation of GVLFR is characterised by high densitybasal area and volume and despite the scarcity of largediameter trees this indicates that the forest is in a goodcondition The effect of anthropogenic activities is neverthe-less evident and stresses the need for proper managementespecially for economically important species preferred forcharcoalmaking (egBrachystegia spiciformis) if the currentspecies diversity is to be maintained or enhanced A repeatedfuture study would be needed to assess whether the currentcommunity-based management regime yields this intendedoutcome but the available information and analyses allow forsome optimism in this respect

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors wish to thank people from Mfyome villagefor their invaluable assistance during field work Mzee IddiKaheya Damian Chotamasege AugustinoMkwama Libera-tus Simime and Mawazo Nyangwa Furthermore thanks aredue to Venancia Mlelwa from Sokoine University and MadsMadsen Krag from University of Copenhagen for doing thelaboratory work The authors also wish to thank GoodluckMoshi their driverMarcoNjana andNassoroHMagogo theTAFORI botanist for assisting with species identification andKlaus Dons for preparing a study site map Financial supportwas provided by Danida through the ENRECA Project

ldquoParticipatory forest management for rural livelihoods forestconservation and good governance in Tanzaniardquo (no 725)

References

[1] P G H Frost ldquoThe Ecology of Miombo Woodlandsrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 11ndash57 1996

[2] N Burgess J Hales E Underwood et al Terrestrial Ecoregionsof Africa and Madagascar A Conservation Assessment IslandPress World Wildlife Fund 2004

[3] J Clarke W Cavendish and C Coote ldquoRural householdsand miombo woodlands use value and managementrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 101ndash135 1996

[4] B M Campbell A Angelsen A Cunningham Y KaterereA Sitoe and S Wunder ldquoMiombo woodlandsmdashopportunitiesand barriers to sustainable forest managementrdquo httpsener-gypediainfoimages66dMiombo2007pdf

[5] S Syampungani P W Chirwa F K Akinnifesi G Sileshi andO C Ajayi ldquoTheMiombo woodlands at the cross roads poten-tial threats sustainable livelihoods policy gaps and challengesrdquoNatural Resources Forum vol 33 no 2 pp 150ndash159 2009

[6] J I O Abbot and K Homewood ldquoA history of change causesof miombo woodland decline in a protected area in MalawirdquoJournal of Applied Ecology vol 36 no 3 pp 422ndash433 1999

[7] E J Luoga E T F Witkowski and K Balkwill ldquoLand coverand use changes in relation to the institutional frameworkand tenure of land and resources in eastern Tanzania Miombowoodlandsrdquo Environment Development and Sustainability vol7 no 1 pp 71ndash93 2005

[8] FAO The State of Food and Agriculture 2010-2011 Forest andAgriculture Organization Rome Italy 2010

[9] A H Gentry ldquoTropical forest biodiversity distributional pat-terns and their conservational significancerdquo Oikos vol 63 no1 pp 19ndash28 1992

[10] O E Sala F S Chapin III J J Armesto et al ldquoGlobalbiodiversity scenarios for the year 2100rdquo Science vol 287 no5459 pp 1770ndash1774 2000

[11] H J Geist and E F Lambin ldquoProximate causes and underlyingdriving forces of tropical deforestationrdquo BioScience vol 52 no2 pp 143ndash150 2002

[12] R S DeFries ldquoTropical forests deforestation and ecosystemsservices Contributions of remote sensingrdquo in GeoinformaticsFor Tropical Ecosystems P S Roy Ed pp 1ndash32 2003

[13] B M Campbell P Frost and N Bryon ldquoMiombo woodlandsand their use overview and key issuesrdquo in The Miombo inTransition Woodlands and Welfare in Africa B Campbell Edpp 1ndash10 2006

[14] H J Geist ldquoGlobal assessment of deforestation related totobacco farmingrdquo Tobacco Control vol 8 no 1 pp 18ndash28 1999

[15] J Sauer and J M Abdallah ldquoForest diversity tobacco produc-tion and resource management in Tanzaniardquo Forest Policy andEconomics vol 9 no 5 pp 421ndash439 2007

[16] E N Chidumayo and K J Mbata ldquoShifting cultivation ediblecaterpillars and livelihoods in the Kopa area of northernZambiardquo Forests Trees and Livelihoods vol 12 no 3 pp 175ndash1932002

[17] E N Chidumayo and L Kwibisa ldquoEffects of deforestation ongrass biomass and soil nutrient status in miombo woodlandZambiardquo Agriculture Ecosystems and Environment vol 96 no1ndash3 pp 97ndash105 2003

ISRN Biodiversity 15

[18] J F Lund and T Treue ldquoAre we getting there Evidence ofdecentralized forest management from the Tanzanian miombowoodlandsrdquoWorld Development vol 36 no 12 pp 2780ndash28002008

[19] T Blomley and S Iddi Participatory Forest Management inTanzania 1993ndash2009mdashLessons Learned and Experiences toDate Ministry of Natural Resources and Tourism Forestry andBeekeeping Division Dar es Salaam Tanzania 2009

[20] T Treue Y M Ngaga H Meilby et al ldquoDoes participatoryforest management promote sustainable forest utilisation inTanzaniardquo International Forestry Review vol 16 no 1 pp 1ndash162014

[21] Ministry ofNatural Resources andTourismParticipatory ForestManagement in Tanzania Facts and Figures Forestry andBeekeeping Division Dar es Salaam Tanzania 2008

[22] E N Chidumayo ldquoSpecies structure in Zambian miombowoodlandrdquo Journal of Tropical Ecology vol 3 no 2 pp 109ndash1181987

[23] J D Lowore ldquoCoppice regeneration in some miombo wood-lands of Malawirdquo FRIM Report 99001 Forestry ResearchInstitute of Malawi 1999

[24] E J Luoga E T F Witkowski and K Balkwill ldquoHarvestedand standing wood stocks in protected and communal miombowoodlands of eastern Tanzaniardquo Forest Ecology and Manage-ment vol 164 no 1ndash3 pp 15ndash30 2002

[25] M Williams C M Ryan R M Rees E Sambane J Fernandoand J Grace ldquoCarbon sequestration and biodiversity of re-growing miombo woodlands in Mozambiquerdquo Forest Ecologyand Management vol 254 no 2 pp 145ndash155 2008

[26] T Banda NMwangulango BMeyer et al ldquoThewoodland veg-etation of the Katavi-Rukwa ecosystem in western TanzaniardquoForest Ecology andManagement vol 255 no 8-9 pp 3382ndash33952008

[27] R A Giliba E K Boon C J Kayombo E B Musamba AM Kashindye and P F Shayo ldquoSpecies composition richnessand diversity in Miombo Woodland of Bereku Forest ReserveTanzaniardquo Journal of Biodiversity vol 2 no 1 pp 1ndash7 2011

[28] D D Shirima P K T Munishi S L Lewis et al ldquoCarbonstorage structure and composition of miombo woodlands inTanzaniarsquos Eastern Arc Mountainsrdquo African Journal of Ecologyvol 49 no 3 pp 332ndash342 2011

[29] P K T Munishi R A P C Temu and G Soka ldquoPlant com-munities and tree species associations in a Miombo ecosystemin the Lake Rukwa basin Southern Tanzania implications forconservationrdquo Journal of Ecology and Natural Environment vol3 no 2 pp 63ndash71 2011

[30] J Dewis and F Freitas ldquoPhysical analysis of soilsrdquo in Physicaland Chemical Methods of Soil andWater Analysis FAO Bulletinno 10 pp 51ndash57 2nd edition 1970

[31] S R Olsen and L E Sommers ldquoPhosphorusrdquo inMethods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 403ndash430 American Societyof Agronomy Madson Wis USA 1982

[32] J D Rhoades ldquoCation exchange capacityrdquo in Methods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 149ndash157 American Society ofAgronomy Madson Wis USA 1982

[33] IMatejovic ldquoDetermination of carbon hydrogen and nitrogenin soils by automated elemental analysis (dry combustionmethod)rdquo Communications in Soil Science and Plant Analysisvol 24 no 17-18 pp 2213ndash2222 1993

[34] J P Moslashberg Soil Analysis Manual Revised Edition Laboratoryof Soil Sciences Department of Soil Science SokoineUniversityof Agriculture Morogoro Tanzania 2001

[35] N C BradyThe Nature and Properties of Soils Macmillan 8thedition 1974

[36] C J Krebs Ecological Methodology Hamper Collins PublishersNew York NY USA 2nd edition 1999

[37] B Husch T W Beers and J A Kershaw Forest MensurationJohn Wiley amp Sons Hoboken NJ USA 4th edition 2003

[38] E E Mwakalukwa H Meilby and T Treue ldquoVolume andaboveground biomass models for dry Miombo Woodland inTanzaniardquo In press

[39] M Kent Vegetation Description and Analysis A PracticalApproach Wiley-Blackwell John Wiley amp Sons Hoboken NJUSA 2nd edition 2012

[40] B McCune and M J Mefford PC-ORD Multivariate Analysisof Ecological Data Version 6 MjM Software Gleneden BeachOre USA 2011

[41] MDufrene andP Legendre ldquoSpecies assemblages and indicatorspecies the need for a flexible asymmetrical approachrdquo EcologyMonography vol 67 pp 777ndash795 1997

[42] J E PeckMultivariate Analysis for Community Ecologists Step-by-Step using PC-ORD MjM Software Design Gleneden BeachOre USA 2010

[43] M A Njana Arborescent species diversity and stocking inMiombo Woodland of Urumwa forest reserve and their contri-bution to Livelihoods Tabora Tanzania [MS thesis] SokoineUniversity of Agriculture Morogoro Tanzania 2008

[44] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal no 200 pp 59ndash70 2004

[45] J Isango ldquoStand structure and tree species composition ofTanzania miombo woodlands a case study from miombowoodlands of community based forest management in Iringadistrictrdquo in MITMIOMBOmdashManagement of Indigenous TreeSpecies For EcosystemRestoration andWood Production in Semi-Arid Miombo Woodlands in Eastern Africa Proceedings ofthe 1st MITMIOMBO Project Workshop held in MorogoroTanzania 6th-12th February 2007 Working Papers of theFinnish Forest Research Institute no 50 pp 43ndash56 2007

[46] J R Landon Booker Tropical Soil Manual A Handbook ForSoil Survey and Agricultural Land Evaluation in the Tropics andSubtropics Longman Scientific amp Technical and John Wiley ampSons 1991

[47] R F Fisher and D Binkley Ecology and Management of ForestSoils John Wiley amp Sons 3rd edition 2000

[48] W A Rees ldquoPreliminary studies into bush utilization by Cattlein Zambiardquo Journal of Applied Ecology vol 11 pp 207ndash214 1974

[49] S M Philip Measuring Trees and Forests CAB InternationalWallingford UK 2nd edition 1994

[50] J D Lowore P G Abbot and M Werren ldquoStackwood volumeestimations formiombowoodlands inMalawirdquoCommonwealthForestry Review vol 73 no 3 pp 193ndash197 1994

[51] D Kubota T Masunaga Hermansah et al ldquoSoil environmentand tree species diversity in tropical rain forest West SumatraIndonesiardquo in Soils of Tropical Forest Ecosystems CharacteristicsEcology and Management A Schulte and D Ruhiyat Eds pp159ndash167 1998

[52] P K T Munishi T H Shear T Wentworth and R A PC Temu ldquoCompositional gradients of plant communities insubmontane rainforests of EasternTanzaniardquo Journal of TropicalForest Science vol 19 no 1 pp 35ndash45 2007

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Journal of

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EcosystemsJournal of

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Marine BiologyJournal of

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Applied ampEnvironmentalSoil Science

Volume 2014

Advances in

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Environmental Chemistry

Atmospheric SciencesInternational Journal of

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Waste ManagementJournal of

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International Journal of

Geophysics

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

Page 9: Research Article Floristic Composition, Structure, and

ISRN Biodiversity 9

005 and that of small individuals was 006 The followingspecies were observed to have the greatest contributionsto the Shannon-Wiener diversity index of large individualsDalbergia arbutifolia (contributing 030) Combretum molle(020) Commiphora africana (019) Albizia petersiana (016)and Margaritaria discoidea (014) while for smaller ones thegreatest contributions were found for Brachystegia spiciformis(026) Dalbergia arbutifolia (024) Grewia forbesii (023)Margaritaria discoidea (020) and Dichrostachys cinerea(016) In terms of frequency of occurrence for standingindividuals (large sizes) Commiphora africana was the mostfrequent species (77 of plots) followed by Combretummolle (74) and Dalbergia arbutifolia (60) while for smallsizes Margaritaria discoidea (66) Markhamia obtusifolia(63) and Dalbergia arbutifolia (57) were the most fre-quent species The Importance Value Index (IVI) for largeindividuals (Dbh ge 5 cm) shows that Dalbergia arbutifolia(224) Commiphora africana (175) and Combretum molle(132) were the most important species among standingindividuals while Brachystegia spiciformis (308)Combretummolle (307) and Dichrostachys cinerea (178) appeared to bethe most important among harvested individuals (stumps)These species were also found to have higher frequencies thanany other harvested species observed in the GVLFR (Table 1)

33 Stem Density The total mean stem density for large indi-viduals with Dbh ge5 cm was 1521 plusmn 594 stemsha (Table 1)and that of small individuals with Dbh lt5 cm (includingindividuals with Dbh lt1 cm) was 14318 plusmn 6956 stemshaAmong large individuals the most abundant species wereDalbergia arbutifolia (162 of 1521 stemsha) Combretummolle (8) Commiphora africana (72) and Albizia peter-siana (53) Among small individuals the most abundantspecies were Brachystegia spiciformis (13 of 14318 stemsha)followed by Dalbergia arbutifolia (11) and Grewia forbesii(10) For stumps the overall mean density was 60 plusmn38 stemsha with Combretum molle (12) Dalbergia arbuti-folia (12) Brachystegia spiciformis (10) and Dichrostachyscinerea (10) contributing the most (Table 1) Generally thedistribution of standing trees to size classes showed the usualreverse J shape which was also approximately observed forstumps (Figure 3) However for stumps the density of stemsin the 1ndash10 cm diameter class was slightly lower than whatwould be expected if tree felling had been a random event

34 Basal Area For the GVLFR as a whole the meanbasal areas for large (ge5 cm Dbh) and small individuals(lt5 cm Dbh) were 1355 plusmn 552m2ha (Table 1 Figure 4)and 305 plusmn 002m2ha respectively The species contributingmost to the basal area of large individuals were Commiphoraafricana (12) Dalbergia arbutifolia (10) and Brachystegiaspiciformis (9) while those contributing most to the basalarea of smaller individuals were Dalbergia arbutifolia (16)Grewia forbesii (15) and Dichrostachys cinerea (13) Themean basal area for stumps was 072m2ha with Brachystegiaspiciformis contributing the greatest individual proportion(28) 41 species made up the rest (Figure 4)

60542

3335

530

113

28 24

346166

34

11

02

01

10

100

1000

10000

100000

Diameter classes (cm)

Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Stem

s (ha

minus1)

Figure 3 Density of standing trees ge1 cmDbh and stumps ge1 cm bydiameter class in Gangalamtumba VLFR (119899 = 35) NB logarithmicscale on vertical axis

744477

241

103041 055

014025 018

010004

001

01

1

10

Diameter classes (cm)Standing treesStumps

10

ndash100

101

ndash200

201

ndash300

301

ndash400

401

ndash500

501

ndash600

Mea

n ba

sal a

rea (

m2

haminus1)

Figure 4 Distribution of basal area per hectare for standingtrees ge1 cm Dbh and stumps ge1 cm by diameter classes in theGangalamtumba VLFR (119899 = 35) NB logarithmic scale on verticalaxis

35 Volume The mean volumes for large (ge5 cm Dbh) andsmall individuals (lt5 cm Dbh) were 9217 plusmn 390m3ha and1257 plusmn 635m3ha respectively (not shown in tables) Thespecies contributing most to the volume of large individualswere Commiphora africana (12) Brachystegia spiciformis(10) Acacia sp (9) and Dalbergia arbutifolia (9) Forsmaller individuals the species that contributed most tovolume were Dalbergia arbutifolia (16) Grewia forbesii(14) and Dichrostachys cinerea (13) The mean remainingvolume of stumps was found to be 015 plusmn 01m3ha withBrachystegia spiciformis contributing the greatest individualpercentage (28) 41 species made up the rest

10 ISRN Biodiversity

36 Spatial Distribution Dispersion indices (DI) are pre-sented for individual species in Table 1 The dispersion indexvalues range from 094 indicating almost complete spatialrandomness or slight underdispersion to 5498 indicatingconsiderable overdispersion that is a patchy or clustereddistributionOut of 77 species excluding the single very largeAdansonia digitata that was considered an outlier 64 species(83) 9 species (12) and 4 species (5) were found tohave DI gt 1 DI = 1 and DI lt 1 respectively so the majorityof species are characterised by a patchy distribution acrossthe forest The species with the lowest estimated DI wasEhretia amoena (094) while the highest DI was estimated forCordia sinensis (5498)Themost abundant species includingDalbergia arbutifolia (DI = 4765) Combretum molle (DI =1523) and Commiphora africana (DI = 1142) are stronglyoverdispersed

37 Plant Communities and Species Association Four plantcommunities were identified through cluster analysis basedon the statistical significance (5) of the observed maximumindicator values (Table 2) Only two of these plant commu-nities were dominated by species from the family Caesalpini-aceae (Communities 1 and 24) The other two showed greatvariationoverlap between species of different plant families(Communities 3 and 5) The estimated Steinhaus similarityindices between pairs of plant communities varied from 32for Communities 1 and 3 and Communities 5 and 24 to 37for Communities 3 and 5 (not shown in tables)

The ordination diagram (Figure 5) shows that one topo-graphic and six edaphic variables appear to be associatedwiththe four plant communities and the species distribution inthe study area The strongest correlation with communitycomposition was observed for elevation followed by soilpH at 0ndash15 cm depth base cation Ca2+ at 0ndash15 cm depthpercent base saturation (BS) at 0ndash15 cm depth percent clayat 0ndash15 cm depth C N ratio at 15ndash30 cm depth and percentsand at 0ndash15 cm depth The base cations magnesium (Mg2+)and potassium (K+) were not directly correlated with thecommunity composition but since they are included in thebase saturation percentage they are indirectly related Plantcommunities were ordered along the second ordination axiswhich was positively correlated with pH15 (119903 = 071) Ca15(119903 = 069) BS (119903 = 065) andClay15 (119903 = 052) and negativelycorrelated with Sand15 (119903 = minus046) Axis 1 of the ordinationwas positively correlated with Elev (119903 = 085) and CNrat30(119903 = 051) As shown in Table 3 and indicated graphically inFigure 5 correlations between many of the edaphic variablesare strong particularly between pH15 Sand15 Clay15 Ca15and BS whereas correlation between topographic and mostedaphic variables is small and nonsignificant However thereis a significant negative correlation (119903 = minus042) between Elevand Sand15 indicating that sandy soils are mostly found atlower elevations

4 Discussion

41 Species Composition The results reported in this studyshow that the composition of the vegetation types found in

Elev

pH15Ca15

Sand15

Clay15

CNrat30

BS

Axis 1

Axis 2

Community 1Community 3

Community 5Community 24

Figure 5 Compositional gradients and plant communities in NMSordination of 35 vegetation plots for trees ge5 cm in GangalamtumbaVLFR Four plant communities are recognized (cf Table 2) Com-munity 1 = Brachystegia spiciformis Diplorynchus condylocarponand Lannea schweinfurthii woodland Community 3 = Dalbergiaarbutifolia Commiphora africana and Albizia petersianawoodlandCommunity 5 = Acacia sp Acacia abyssinica and Albizia amarawoodland and Community 24 = Bauhinia petersiana and Shreberatrichoclada woodland Elev elevation (m) CNrat30 C N ratio at15ndash30 cm depth Sand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm Ca15 = Ca2+ (cmol(+)kg) at 0ndash15 cm pH15 = soil pH at 0ndash15 cm BS base saturation at 0ndash15 cm

the GVLFR especially the dominance of species from thefamily Caesalpiniaceae agreed well with previous descrip-tions and classifications of plant communities commonlyfound in miombo woodlands [1] However the observeddominance based on IVI of the genera Dalbergia Com-miphora and Combretum contrasts with patterns usuallyconsidered common for miombo woodlands The frequencyof species in these genera was also high compared to otherspecies observed in the GVLFR (Table 1) Similar deviationsexist between the results obtained by Banda et al [26]in the Katavi-Rukwa ecosystem where they observed thatTerminalia and Combretum were the dominant genera andthe findings of Giliba et al [27] and Njana [43] whoboth noted the dominance of the two common miombogenera Brachystegia and Julbernardia However Combretumalso occurred in their study areas The results suggest thaton a larger spatial scale the species diversity of miombowoodlands is very high and that the three common generaBrachystegia Julbernadia and Isoberlinia are not alwaysdominant at the local scale

The species richness observed in the GVLFR compareswell with miombo community studies in other areas of drymiombo in Tanzania and elsewhere which receive an average

ISRN Biodiversity 11

Table2Plantcom

mun

itiesandspeciesa

ssociatio

nsin

thed

ryMiombo

woo

dlands

ofGangalamtumba

VLF

RCom

mun

itynu

mbers135and24

representthe

different

plantassociatio

ns

119899speciesnu

mbero

fspecies

(77in

total)with

Dbhge5c

mIV+

speciesind

icator

valuemeanplusmnstd

errorand

BAisbasalarea

Com

mun

ityAs

sociated

species

Family

Habit

IV+

()

Con

stancy

()119875value

Stem

sha

BA m2 ha

MeanDbh

Brachyste

giaspiciform

ismdashDiplorhynchus

cond

ylocarponmdashLa

nnea

schw

einfurthiiw

oodland

1(n s

pecies

=47

nplots=9)

Sitevariables(meanplusmnSE

)Elev

=1200plusmn20pH15

=644plusmn013C

a15=604plusmn128

Sand

15=721plusmn431C

lay15=137plusmn188Silt15

=142plusmn335C

Nrat30=135plusmn05andBS

=526plusmn65

Brachyste

gia

spiciform

isCa

esalpiniaceae

T820

100

000

02164plusmn59356plusmn077138plusmn07

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T759

89000

0866plusmn18044plusmn01382plusmn05

Lann

easchw

einfurthii

Anacardiaceae

T719

100

000

0449plusmn14072plusmn022126plusmn09

Bosciaangustifolia

Capp

araceae

T536

5600056

27plusmn12014plusmn00776plusmn06

Euphorbiacuneata

Euph

orbiaceae

ST428

4400200

42plusmn19012plusmn00665plusmn06

Other

species

mdashmdash

mdashmdash

mdash1075plusmn5741007plusmn647102plusmn03

Subtotal

1423plusmn174

1505plusmn178

109plusmn03

DalbergiaarbutifoliamdashCo

mmiphora

afric

anamdash

Albizia

petersiana

woo

dland

3(n

species=55n

plots=

16)Site

variables(meanplusmnSE

)Elev

=986plusmn19pH15

=648plusmn009C

a15=856plusmn109

Sand

15=767plusmn156C

lay15=135plusmn155Silt15

=97plusmn096C

Nrat30=106plusmn03andBS

=744plusmn44

Dalbergiaarbutifolia

Fabaceae

subfam

ilyPapilio

noideae

ST793

100

000

02500plusmn123263plusmn06477plusmn02

Commiphora

afric

ana

Burseraceae

T542

9400026

187plusmn40272plusmn064119plusmn06

Albiziapetersiana

Mim

osacea

T536

7500200

157plusmn57103plusmn04084plusmn02

Sclerocarryabirrea

Anacardiaceae

T504

6300186

40plusmn11128plusmn045168plusmn17

Other

species

mdashmdash

mdashmdash

mdash852plusmn449669plusmn37788plusmn03

Subtotal

1735plusmn166

1435plusmn071

92plusmn02

Acaciaspmdash

Acaciaabyssin

icamdash

Albiziaam

arawoo

dland

5(n

species=33n

plots=5)

Sitevariables(m

eanplusmnSE

)Elev

=986plusmn52pH15

=734plusmn023C

a15=139plusmn33

Sand

15=745plusmn678C

lay15=148plusmn47Silt15

=107plusmn26C

Nrat30=106plusmn07andBS

=963plusmn89

Acaciasp

Mim

osaceae

T981

100

000

02269plusmn111662plusmn286172plusmn14

Acaciaabyssin

icaMim

osaceae

T594

8000030

31plusmn9060plusmn03299plusmn08

Albiziaam

ara

Mim

osaceae

T552

60000

6654plusmn30023plusmn01671plusmn08

Grew

iabicolor

Tiliaceae

ST533

6000106

113plusmn52040plusmn01770plusmn04

Acaciaseyal

Mim

osaceae

T433

6000526

62plusmn34034plusmn01790plusmn05

Other

species

mdashmdash

mdashmdash

mdash665plusmn533552plusmn49872plusmn04

Subtotal

1194plusmn169

1367plusmn347

101plusmn05

Bauh

iniapetersiana

mdashShrebera

trichoclada

woo

dland

24(n

species=35n

plots=5)

Sitevariables(meanplusmnSE

)Elev

=1175plusmn25pH15

=73plusmn04C

a15=254plusmn69

Sand

15=522plusmn68C

lay15=331plusmn28

Silt15=147plusmn44C

Nrat30=961plusmn13andBS

=1041plusmn204

Bauh

iniapetersiana

Caesalpiniaceae

SH551

8000118192plusmn121111plusmn05075plusmn03

Shrebera

trichoclada

Oleaceae

T505

6000110

57plusmn32022plusmn01380plusmn05

Manilkaramochisia

Sapo

taceae

T376

4000332

34plusmn27014plusmn00969plusmn10

Dalbergia

mela

noxylon

Fabaceae

T370

4000380

68plusmn58026plusmn02266plusmn03

Ehretia

amoena

Boraginaceae

ST347

4000344

6plusmn4

002plusmn00170plusmn04

Other

species

mdashmdash

mdashmdash

mdash982plusmn759643plusmn47999plusmn05

Subtotal

1338plusmn137

817plusmn087

91plusmn04

Total

1521plusmn5941355plusmn55298plusmn01

Elevelevatio

n(m

)CN

rat30CN

ratio

at15ndash30c

mdepthSand

15sand(

)at0

ndash15c

mC

lay15clay

()at0

ndash15c

mSilt15silt

()at0

ndash15c

mC

a15Ca2+(cmol(+)kg)at0

ndash15c

mpH15soilp

Hat0ndash

15cm

BS

base

saturatio

nat0ndash

15cm

12 ISRN Biodiversity

Table 3 Pearson-correlation matrix for two topographic and eight edaphic variablesdagger associated with the classified plant communities in theGangalamtumba VLFR (119899 = 35) Applied significance levels lowast5 lowastlowast1 and lowastlowastlowast01 +not significant

Elev Slope pH15 Ca15 K15 N15 Sand15 Clay15 CNrat30Slope 019+

pH15 minus013+ minus033lowast

Ca15 002+ minus020+ 083lowastlowastlowast

K15 minus029+ 000+ 010+ 012+

N15 006+ 036lowast 010+ 041lowastlowast 033lowast

Sand15 minus042lowastlowast 003+ minus053lowastlowastlowast minus074lowastlowastlowast 006+ minus046lowastlowast

Clay15 031+ minus012+ 051lowastlowast 076lowastlowastlowast minus001+ 047lowastlowast minus086lowastlowastlowast

CNrat30 036lowast 010+ minus039lowast minus051lowastlowast minus015+ minus019+ 040lowast minus048lowastlowast

BS minus024+ minus017+ 084lowastlowastlowast 091lowastlowastlowast 015+ 037lowast minus058lowastlowastlowast 060lowastlowastlowast minus051lowastlowastdaggerElev elevation (m) pH15 soil pH at 0ndash15 cm Ca15 Ca2+ (cmol(+)kg) at 0ndash15 cm K15 K+ (cmol(+)kg) at 0ndash15 cm N15 N concentration at 0ndash15 cmSand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm CNrat30 C N ratio at 15ndash30 cm depth BS base saturation at 0ndash15 cm 119905-value was calculated as119905 = 119903radic(119899 minus 2)(1 minus 119903

2) where 119903 is the Pearson-correlation coefficient and 119899 is the total sample size

Table 4 Species richness observed in other studies from drymiombo woodlands

Plot size(ha)

Totalnumberof plots

Total samplearea(ha)

Total numberof species References

0071 70 495 82 [43]0071 80 565 110 [27]0071 133 940 229 [26]0071 247 1746 102 [44]004 40 160 81 [45]025 14 350 69 [25]01 2 020 40 [28]01 152 1520 92 genera [22]0071 35 247 88 This study

annual rainfall of 565ndash1500mm (Table 4) Using plot sizes of004ndash025 ha and sample sizes of 2ndash247 plots a total numberof species ranging from40 (Dbhge 10 cm) to 229 (Dbhge 2 cm)have been reported fromMiombowoodlands [22 25ndash28 43ndash45]

The high number of species reported by Banda et al [26]Chidumayo [22] Isango [45] and Chamshama et al [44] islikely to be a consequence of the spatial scale and coverage ofthese studies as they all cover large areas include more thanone site and operate with large sample sizes For exampleChidumayo [22] included species from both wet and dryMiombo areas in Zambia The study by Sauer and Abdallah[15] who reported a total of 131 species occurring in thetobacco growing zone of Iringa rural district included twoforest reserves and three family-managed forests Thereforeconsidering the climatic conditions in the GVLFR (617mmof rainfall per year) and the sample size (35 plots) thespecies richness reported in this study can be ranked atleast as high or higher than those found in the studiesmentioned The selective sampling approach focusing onvarious microhabitat types adopted by Banda et al [26] mayhave contributed to the large number of species observed

in their study area Similarly the higher number of speciesfound by Giliba et al [27] was probably due to the presenceof riverine forest offering site conditions favourable formanyspecies

The values of the Shannon-Wiener (1198671015840 = 344) andSimpson indices (119863 = 005) reported for large individ-uals in this study are within the range observed for mostcommunities of particular life forms [36] For example 1198671015840usually does not exceed 5 although this maximum valuevaries depending on the type of the biological communitysampled and the sampling approach applied (eg minimumdiameter and size of sample units) A threshold value of 2 for1198671015840 has been mentioned as a minimum value above which

an ecosystem can be regarded as medium to highly diverse[27] Chamshama et al [44] reported three 1198671015840 values of31 32 and 33 from Kitulangalo Miombo forest in EasternTanzania while Njana [43] reported a 1198671015840 value of 340from dry Miombo forest in Western Tanzania The studiesby Sauer and Abdallah [15] and Giliba et al [27] reportedparticularly high values of 346 and 427 respectively Thiscould be attributed to the very large sample sizes used inboth studies and the presence of riverine forest where thechance of encountering many rare species is likely to be highThe forests examined in the mentioned studies receive anaverage annual rainfall of 700ndash1000mm compared to whichthe rainfall in the GVLFR is low (617mm on average per yearcf above)The relatively high diversity found inGVLFRmusttherefore be attributed to other factors than climate The soilanalyses indicate that the soil fertility level in the GVLFRis relatively high with considerable proportions of all 2 1lattice clay minerals (114) (ie illite montmorillonite andvermiculite) plus a good amount of organic matter whichmay suggest that the soil has large reserves of important plantnutrients for example K Mg and Fe The base saturationpercentage (BS) which is normally used to indicate the soilfertility status (Landon 1991) was also high 76 on averageand with 86 of the samples (30 samples) with BS valuesgt50 (fertile soil) and only 14 of the samples (5 samples)with BS below 50 (less fertile soil) As another indicationof high soil fertility status the mean C N ratio was 12 plusmn 043

ISRN Biodiversity 13

(range 7ndash19) for top soil (0ndash15 cm) and 11 plusmn 036 (range 5ndash16) for subsoil (15ndash30 cm) In general the values for both soilstrata fall within the expected range of 8ndash17 Soil pH values(mean 67 plusmn 01 range 567ndash852)were alsowithin the optimalrangewhere all the nutrients that aremost important for plantgrowth (Ca Mg K and P) are available and accessible toplants [46] In this study 97 of the soil samples had pHbelow 8 (one sample had a pH of 852) Fisher and Binkley[47] noted that high pH is almost never a problem in forestsas most trees do well across the full range of common pHvaluesTherefore considering the low average annual rainfallcompared to other forests the relatively high fertility of theGVLFR may be the main factor creating an environmentfavourable to many species thus leading to a quite highspecies diversity observed in this forest

Based on the Importance Value Index Brachystegia spi-ciformis and Combretum molle appeared to be the mostimportant species among harvested trees (stumps) in thestudy area This result agreed very well with the large valuesof basal area and volume and the information obtained fromlocal scouts and members of the village environmental com-mittee who said that the most frequently harvested speciesfor charcoal making include all Brachystegia species found inthe forest (ie Brachystegia spiciformis Brachystegia mangaBrachystegia boehmii and Brachystegia bussei) Among theCombretum species the most important one (based on IVI)Combretum molle is mostly used for house construction andfirewood rather than for charcoal making Apart from theBrachystegia species the only other species mentioned asimportant for charcoal making was Acacia mellifera Otherspecies are only used in case they happen to fall when fellingthe preferred species during the preparation of charcoal kilnsWith respect to stumps Brachystegia spiciformis Brachystegiamanga and Combretum molle are among the ten mostabundant species in terms of density basal area and volumeper hectare Stumps of the other species mentioned are notcommonly found a factwhichmay be due to the small samplesize being unable to capture sites where these species areharvested but may also be related to their limited distributionin the forest as indicated by the estimated dispersion indices(see Table 1)

42 Forest Structure Species densities reported from otherMiombo woodland areas in Tanzania are typically 348ndash1495stemsha for trees with Dbh gt4 cm [24 43 45] Comparedwith this the GVLFR is highly stocked as the estimateddensity is 2296 stemsha for trees with Dbh gt4 cmThemeanstem density of 1521 plusmn 594ha for trees with Dbh ge5 cmis also more than twice as large as values found in otherstudies [25ndash27 44 45 48] A similar pattern is seen whencomparing the density of regeneration between the studiesThe diameter distribution is characterised by a very cleartrend of decreasing stem density with increasing diameterThe shape of the distribution is thus an inverted ldquoJrdquo (Figure 3)which is a common feature of natural forests with activeregeneration and recruitment [49] However not many largetrees were captured by the sample whereas a considerablenumber of relatively large stumps were observed suggestingthat anthropogenic activities such as charcoal making may

have affected the structure and ecological balance of the forest(see Figure 3) Since the woodlands are often hit by fire whichtends to kill the seedlings (especially the late fires) and thusonly few seedlings can be expected to reach larger diameterclasses lack of mature trees and the resulting lack of seedsmay eventually threaten the biodiversity of the forest

The mean basal area of 1355 plusmn 552m2ha observedin this study is slightly above the range of values typicallyreported from the miombo region 75ndash126m2ha [26 28 4344 50] However the basal areas reported by Isango [45] werea bit higher (1504ndash1563m2ha) than observed in this study

Themean total volume inGVLFRwas estimated at 9217plusmn390m3ha for trees with Dbh ge5 cm Other studies in dryMiombo woodlands have reported mean volumes of 167ndash7603m3ha [24 44 45 50] The current standing volume ofGVLFR is thus slightly higher than values typically reportedfor forests in the Miombo ecoregion A plausible reason forthis may be that compared to other forests the GVLFR isstill well stocked despite ongoing human activities such ascharcoalmakingThebasal area observed for stumpswas only072m2ha so there is no indication of intensive extractionover many years This corresponds well with the findings ofTreue et al [20] who conclude that the estimated 04m3haannual extraction of woody biomass from GVLFR is consid-erably below its estimated annual increment of 15m3ha andthat the local forest managers seem capable of regulating theharvesting activities which in addition to village membersrsquocollection for subsistence uses also included commercialcharcoal production by external companies that pay a fee perbag of charcoal extracted to the village government

43 Plant Communities and Species Associations Except forBrachystegia spiciformis the majority of the Brachystegia andJulbernardia species that are common to miombo wood-lands elsewhere are not among the species most commonlyobserved in this study A similar pattern was observed byBanda et al [26] in the Katavi-Rukwa ecosystem wherethe genera that are most common in miombo woodlandsBrachystegia Julbernardia and Isoberlinia were not commonin their study sites Furthermore the four plant communi-ties distinguished in this study are comparable with thosereported by other studies in Tanzania including the work byMunishi et al [29] in theMiombowoodlands of Rukwa basinChunya district Tanzania and the study by Banda et al [26]in the Katavi-Rukwa ecosystem

Elevation was noted by Munishi et al [29] to be themost important factor shaping the species communities intheir study area This study found a similar pattern with thehighest coefficient of correlation observed for elevation sug-gesting that topographical variation is among the strongestdeterminants of community composition in dry Miombowoodlands hence influencing the spatial distribution ofspecies strongly However in our study area edaphic factorsalso influenced the species distribution directly Two plantcommunities occurredmainly on clayey soils with high pH atintermediate elevations one on sandy soils with lowpHat lowelevations and one on sandy-clayey soils at higher elevationsand with neutral soil pH (Figure 5) Specifically it appeared

14 ISRN Biodiversity

that the Acacia woodland category (Community 5) grows atlow elevations around temporary streams (or at least wherethe ground water table is relatively high) and the Bauhiniawoodland category (Community 24) appearsmostly in placeswith a relatively high percentage of clay (and therefore highvalues of pH Ca and BS) By contrast it appeared that theDalbergia woodland category (Community 3) is located atmore sandy sites (with low values of pH Ca and BS) andthe Brachystegia woodland category (Community 1) seemedto be located mostly at higher elevations where the CN-ratio is quite high Correlations between elevation and thebasic soil variables pH Ca and percentages of sand andclay were low (cf Figure 5) Thus the results indicate thatthe plant communities of the dry miombo woodlands inGVLFR are not only shaped by the topographic variation(elevation) and the groundwater level but also by basic soilcharacteristics The results thus confirm findings from otherstudies detecting effects of elevation and soil characteristicson species composition [51 52]

5 Conclusion

Considering that the sample size used in this study wassmaller than samples used in other studies in dry miombowoodlands the results show that the species diversity inGVLFR is relatively high compared to other forest reservesThe vegetation of GVLFR is characterised by high densitybasal area and volume and despite the scarcity of largediameter trees this indicates that the forest is in a goodcondition The effect of anthropogenic activities is neverthe-less evident and stresses the need for proper managementespecially for economically important species preferred forcharcoalmaking (egBrachystegia spiciformis) if the currentspecies diversity is to be maintained or enhanced A repeatedfuture study would be needed to assess whether the currentcommunity-based management regime yields this intendedoutcome but the available information and analyses allow forsome optimism in this respect

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors wish to thank people from Mfyome villagefor their invaluable assistance during field work Mzee IddiKaheya Damian Chotamasege AugustinoMkwama Libera-tus Simime and Mawazo Nyangwa Furthermore thanks aredue to Venancia Mlelwa from Sokoine University and MadsMadsen Krag from University of Copenhagen for doing thelaboratory work The authors also wish to thank GoodluckMoshi their driverMarcoNjana andNassoroHMagogo theTAFORI botanist for assisting with species identification andKlaus Dons for preparing a study site map Financial supportwas provided by Danida through the ENRECA Project

ldquoParticipatory forest management for rural livelihoods forestconservation and good governance in Tanzaniardquo (no 725)

References

[1] P G H Frost ldquoThe Ecology of Miombo Woodlandsrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 11ndash57 1996

[2] N Burgess J Hales E Underwood et al Terrestrial Ecoregionsof Africa and Madagascar A Conservation Assessment IslandPress World Wildlife Fund 2004

[3] J Clarke W Cavendish and C Coote ldquoRural householdsand miombo woodlands use value and managementrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 101ndash135 1996

[4] B M Campbell A Angelsen A Cunningham Y KaterereA Sitoe and S Wunder ldquoMiombo woodlandsmdashopportunitiesand barriers to sustainable forest managementrdquo httpsener-gypediainfoimages66dMiombo2007pdf

[5] S Syampungani P W Chirwa F K Akinnifesi G Sileshi andO C Ajayi ldquoTheMiombo woodlands at the cross roads poten-tial threats sustainable livelihoods policy gaps and challengesrdquoNatural Resources Forum vol 33 no 2 pp 150ndash159 2009

[6] J I O Abbot and K Homewood ldquoA history of change causesof miombo woodland decline in a protected area in MalawirdquoJournal of Applied Ecology vol 36 no 3 pp 422ndash433 1999

[7] E J Luoga E T F Witkowski and K Balkwill ldquoLand coverand use changes in relation to the institutional frameworkand tenure of land and resources in eastern Tanzania Miombowoodlandsrdquo Environment Development and Sustainability vol7 no 1 pp 71ndash93 2005

[8] FAO The State of Food and Agriculture 2010-2011 Forest andAgriculture Organization Rome Italy 2010

[9] A H Gentry ldquoTropical forest biodiversity distributional pat-terns and their conservational significancerdquo Oikos vol 63 no1 pp 19ndash28 1992

[10] O E Sala F S Chapin III J J Armesto et al ldquoGlobalbiodiversity scenarios for the year 2100rdquo Science vol 287 no5459 pp 1770ndash1774 2000

[11] H J Geist and E F Lambin ldquoProximate causes and underlyingdriving forces of tropical deforestationrdquo BioScience vol 52 no2 pp 143ndash150 2002

[12] R S DeFries ldquoTropical forests deforestation and ecosystemsservices Contributions of remote sensingrdquo in GeoinformaticsFor Tropical Ecosystems P S Roy Ed pp 1ndash32 2003

[13] B M Campbell P Frost and N Bryon ldquoMiombo woodlandsand their use overview and key issuesrdquo in The Miombo inTransition Woodlands and Welfare in Africa B Campbell Edpp 1ndash10 2006

[14] H J Geist ldquoGlobal assessment of deforestation related totobacco farmingrdquo Tobacco Control vol 8 no 1 pp 18ndash28 1999

[15] J Sauer and J M Abdallah ldquoForest diversity tobacco produc-tion and resource management in Tanzaniardquo Forest Policy andEconomics vol 9 no 5 pp 421ndash439 2007

[16] E N Chidumayo and K J Mbata ldquoShifting cultivation ediblecaterpillars and livelihoods in the Kopa area of northernZambiardquo Forests Trees and Livelihoods vol 12 no 3 pp 175ndash1932002

[17] E N Chidumayo and L Kwibisa ldquoEffects of deforestation ongrass biomass and soil nutrient status in miombo woodlandZambiardquo Agriculture Ecosystems and Environment vol 96 no1ndash3 pp 97ndash105 2003

ISRN Biodiversity 15

[18] J F Lund and T Treue ldquoAre we getting there Evidence ofdecentralized forest management from the Tanzanian miombowoodlandsrdquoWorld Development vol 36 no 12 pp 2780ndash28002008

[19] T Blomley and S Iddi Participatory Forest Management inTanzania 1993ndash2009mdashLessons Learned and Experiences toDate Ministry of Natural Resources and Tourism Forestry andBeekeeping Division Dar es Salaam Tanzania 2009

[20] T Treue Y M Ngaga H Meilby et al ldquoDoes participatoryforest management promote sustainable forest utilisation inTanzaniardquo International Forestry Review vol 16 no 1 pp 1ndash162014

[21] Ministry ofNatural Resources andTourismParticipatory ForestManagement in Tanzania Facts and Figures Forestry andBeekeeping Division Dar es Salaam Tanzania 2008

[22] E N Chidumayo ldquoSpecies structure in Zambian miombowoodlandrdquo Journal of Tropical Ecology vol 3 no 2 pp 109ndash1181987

[23] J D Lowore ldquoCoppice regeneration in some miombo wood-lands of Malawirdquo FRIM Report 99001 Forestry ResearchInstitute of Malawi 1999

[24] E J Luoga E T F Witkowski and K Balkwill ldquoHarvestedand standing wood stocks in protected and communal miombowoodlands of eastern Tanzaniardquo Forest Ecology and Manage-ment vol 164 no 1ndash3 pp 15ndash30 2002

[25] M Williams C M Ryan R M Rees E Sambane J Fernandoand J Grace ldquoCarbon sequestration and biodiversity of re-growing miombo woodlands in Mozambiquerdquo Forest Ecologyand Management vol 254 no 2 pp 145ndash155 2008

[26] T Banda NMwangulango BMeyer et al ldquoThewoodland veg-etation of the Katavi-Rukwa ecosystem in western TanzaniardquoForest Ecology andManagement vol 255 no 8-9 pp 3382ndash33952008

[27] R A Giliba E K Boon C J Kayombo E B Musamba AM Kashindye and P F Shayo ldquoSpecies composition richnessand diversity in Miombo Woodland of Bereku Forest ReserveTanzaniardquo Journal of Biodiversity vol 2 no 1 pp 1ndash7 2011

[28] D D Shirima P K T Munishi S L Lewis et al ldquoCarbonstorage structure and composition of miombo woodlands inTanzaniarsquos Eastern Arc Mountainsrdquo African Journal of Ecologyvol 49 no 3 pp 332ndash342 2011

[29] P K T Munishi R A P C Temu and G Soka ldquoPlant com-munities and tree species associations in a Miombo ecosystemin the Lake Rukwa basin Southern Tanzania implications forconservationrdquo Journal of Ecology and Natural Environment vol3 no 2 pp 63ndash71 2011

[30] J Dewis and F Freitas ldquoPhysical analysis of soilsrdquo in Physicaland Chemical Methods of Soil andWater Analysis FAO Bulletinno 10 pp 51ndash57 2nd edition 1970

[31] S R Olsen and L E Sommers ldquoPhosphorusrdquo inMethods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 403ndash430 American Societyof Agronomy Madson Wis USA 1982

[32] J D Rhoades ldquoCation exchange capacityrdquo in Methods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 149ndash157 American Society ofAgronomy Madson Wis USA 1982

[33] IMatejovic ldquoDetermination of carbon hydrogen and nitrogenin soils by automated elemental analysis (dry combustionmethod)rdquo Communications in Soil Science and Plant Analysisvol 24 no 17-18 pp 2213ndash2222 1993

[34] J P Moslashberg Soil Analysis Manual Revised Edition Laboratoryof Soil Sciences Department of Soil Science SokoineUniversityof Agriculture Morogoro Tanzania 2001

[35] N C BradyThe Nature and Properties of Soils Macmillan 8thedition 1974

[36] C J Krebs Ecological Methodology Hamper Collins PublishersNew York NY USA 2nd edition 1999

[37] B Husch T W Beers and J A Kershaw Forest MensurationJohn Wiley amp Sons Hoboken NJ USA 4th edition 2003

[38] E E Mwakalukwa H Meilby and T Treue ldquoVolume andaboveground biomass models for dry Miombo Woodland inTanzaniardquo In press

[39] M Kent Vegetation Description and Analysis A PracticalApproach Wiley-Blackwell John Wiley amp Sons Hoboken NJUSA 2nd edition 2012

[40] B McCune and M J Mefford PC-ORD Multivariate Analysisof Ecological Data Version 6 MjM Software Gleneden BeachOre USA 2011

[41] MDufrene andP Legendre ldquoSpecies assemblages and indicatorspecies the need for a flexible asymmetrical approachrdquo EcologyMonography vol 67 pp 777ndash795 1997

[42] J E PeckMultivariate Analysis for Community Ecologists Step-by-Step using PC-ORD MjM Software Design Gleneden BeachOre USA 2010

[43] M A Njana Arborescent species diversity and stocking inMiombo Woodland of Urumwa forest reserve and their contri-bution to Livelihoods Tabora Tanzania [MS thesis] SokoineUniversity of Agriculture Morogoro Tanzania 2008

[44] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal no 200 pp 59ndash70 2004

[45] J Isango ldquoStand structure and tree species composition ofTanzania miombo woodlands a case study from miombowoodlands of community based forest management in Iringadistrictrdquo in MITMIOMBOmdashManagement of Indigenous TreeSpecies For EcosystemRestoration andWood Production in Semi-Arid Miombo Woodlands in Eastern Africa Proceedings ofthe 1st MITMIOMBO Project Workshop held in MorogoroTanzania 6th-12th February 2007 Working Papers of theFinnish Forest Research Institute no 50 pp 43ndash56 2007

[46] J R Landon Booker Tropical Soil Manual A Handbook ForSoil Survey and Agricultural Land Evaluation in the Tropics andSubtropics Longman Scientific amp Technical and John Wiley ampSons 1991

[47] R F Fisher and D Binkley Ecology and Management of ForestSoils John Wiley amp Sons 3rd edition 2000

[48] W A Rees ldquoPreliminary studies into bush utilization by Cattlein Zambiardquo Journal of Applied Ecology vol 11 pp 207ndash214 1974

[49] S M Philip Measuring Trees and Forests CAB InternationalWallingford UK 2nd edition 1994

[50] J D Lowore P G Abbot and M Werren ldquoStackwood volumeestimations formiombowoodlands inMalawirdquoCommonwealthForestry Review vol 73 no 3 pp 193ndash197 1994

[51] D Kubota T Masunaga Hermansah et al ldquoSoil environmentand tree species diversity in tropical rain forest West SumatraIndonesiardquo in Soils of Tropical Forest Ecosystems CharacteristicsEcology and Management A Schulte and D Ruhiyat Eds pp159ndash167 1998

[52] P K T Munishi T H Shear T Wentworth and R A PC Temu ldquoCompositional gradients of plant communities insubmontane rainforests of EasternTanzaniardquo Journal of TropicalForest Science vol 19 no 1 pp 35ndash45 2007

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

EcosystemsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MeteorologyAdvances in

EcologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Marine BiologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental Chemistry

Atmospheric SciencesInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Geological ResearchJournal of

EarthquakesJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BiodiversityInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

Page 10: Research Article Floristic Composition, Structure, and

10 ISRN Biodiversity

36 Spatial Distribution Dispersion indices (DI) are pre-sented for individual species in Table 1 The dispersion indexvalues range from 094 indicating almost complete spatialrandomness or slight underdispersion to 5498 indicatingconsiderable overdispersion that is a patchy or clustereddistributionOut of 77 species excluding the single very largeAdansonia digitata that was considered an outlier 64 species(83) 9 species (12) and 4 species (5) were found tohave DI gt 1 DI = 1 and DI lt 1 respectively so the majorityof species are characterised by a patchy distribution acrossthe forest The species with the lowest estimated DI wasEhretia amoena (094) while the highest DI was estimated forCordia sinensis (5498)Themost abundant species includingDalbergia arbutifolia (DI = 4765) Combretum molle (DI =1523) and Commiphora africana (DI = 1142) are stronglyoverdispersed

37 Plant Communities and Species Association Four plantcommunities were identified through cluster analysis basedon the statistical significance (5) of the observed maximumindicator values (Table 2) Only two of these plant commu-nities were dominated by species from the family Caesalpini-aceae (Communities 1 and 24) The other two showed greatvariationoverlap between species of different plant families(Communities 3 and 5) The estimated Steinhaus similarityindices between pairs of plant communities varied from 32for Communities 1 and 3 and Communities 5 and 24 to 37for Communities 3 and 5 (not shown in tables)

The ordination diagram (Figure 5) shows that one topo-graphic and six edaphic variables appear to be associatedwiththe four plant communities and the species distribution inthe study area The strongest correlation with communitycomposition was observed for elevation followed by soilpH at 0ndash15 cm depth base cation Ca2+ at 0ndash15 cm depthpercent base saturation (BS) at 0ndash15 cm depth percent clayat 0ndash15 cm depth C N ratio at 15ndash30 cm depth and percentsand at 0ndash15 cm depth The base cations magnesium (Mg2+)and potassium (K+) were not directly correlated with thecommunity composition but since they are included in thebase saturation percentage they are indirectly related Plantcommunities were ordered along the second ordination axiswhich was positively correlated with pH15 (119903 = 071) Ca15(119903 = 069) BS (119903 = 065) andClay15 (119903 = 052) and negativelycorrelated with Sand15 (119903 = minus046) Axis 1 of the ordinationwas positively correlated with Elev (119903 = 085) and CNrat30(119903 = 051) As shown in Table 3 and indicated graphically inFigure 5 correlations between many of the edaphic variablesare strong particularly between pH15 Sand15 Clay15 Ca15and BS whereas correlation between topographic and mostedaphic variables is small and nonsignificant However thereis a significant negative correlation (119903 = minus042) between Elevand Sand15 indicating that sandy soils are mostly found atlower elevations

4 Discussion

41 Species Composition The results reported in this studyshow that the composition of the vegetation types found in

Elev

pH15Ca15

Sand15

Clay15

CNrat30

BS

Axis 1

Axis 2

Community 1Community 3

Community 5Community 24

Figure 5 Compositional gradients and plant communities in NMSordination of 35 vegetation plots for trees ge5 cm in GangalamtumbaVLFR Four plant communities are recognized (cf Table 2) Com-munity 1 = Brachystegia spiciformis Diplorynchus condylocarponand Lannea schweinfurthii woodland Community 3 = Dalbergiaarbutifolia Commiphora africana and Albizia petersianawoodlandCommunity 5 = Acacia sp Acacia abyssinica and Albizia amarawoodland and Community 24 = Bauhinia petersiana and Shreberatrichoclada woodland Elev elevation (m) CNrat30 C N ratio at15ndash30 cm depth Sand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm Ca15 = Ca2+ (cmol(+)kg) at 0ndash15 cm pH15 = soil pH at 0ndash15 cm BS base saturation at 0ndash15 cm

the GVLFR especially the dominance of species from thefamily Caesalpiniaceae agreed well with previous descrip-tions and classifications of plant communities commonlyfound in miombo woodlands [1] However the observeddominance based on IVI of the genera Dalbergia Com-miphora and Combretum contrasts with patterns usuallyconsidered common for miombo woodlands The frequencyof species in these genera was also high compared to otherspecies observed in the GVLFR (Table 1) Similar deviationsexist between the results obtained by Banda et al [26]in the Katavi-Rukwa ecosystem where they observed thatTerminalia and Combretum were the dominant genera andthe findings of Giliba et al [27] and Njana [43] whoboth noted the dominance of the two common miombogenera Brachystegia and Julbernardia However Combretumalso occurred in their study areas The results suggest thaton a larger spatial scale the species diversity of miombowoodlands is very high and that the three common generaBrachystegia Julbernadia and Isoberlinia are not alwaysdominant at the local scale

The species richness observed in the GVLFR compareswell with miombo community studies in other areas of drymiombo in Tanzania and elsewhere which receive an average

ISRN Biodiversity 11

Table2Plantcom

mun

itiesandspeciesa

ssociatio

nsin

thed

ryMiombo

woo

dlands

ofGangalamtumba

VLF

RCom

mun

itynu

mbers135and24

representthe

different

plantassociatio

ns

119899speciesnu

mbero

fspecies

(77in

total)with

Dbhge5c

mIV+

speciesind

icator

valuemeanplusmnstd

errorand

BAisbasalarea

Com

mun

ityAs

sociated

species

Family

Habit

IV+

()

Con

stancy

()119875value

Stem

sha

BA m2 ha

MeanDbh

Brachyste

giaspiciform

ismdashDiplorhynchus

cond

ylocarponmdashLa

nnea

schw

einfurthiiw

oodland

1(n s

pecies

=47

nplots=9)

Sitevariables(meanplusmnSE

)Elev

=1200plusmn20pH15

=644plusmn013C

a15=604plusmn128

Sand

15=721plusmn431C

lay15=137plusmn188Silt15

=142plusmn335C

Nrat30=135plusmn05andBS

=526plusmn65

Brachyste

gia

spiciform

isCa

esalpiniaceae

T820

100

000

02164plusmn59356plusmn077138plusmn07

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T759

89000

0866plusmn18044plusmn01382plusmn05

Lann

easchw

einfurthii

Anacardiaceae

T719

100

000

0449plusmn14072plusmn022126plusmn09

Bosciaangustifolia

Capp

araceae

T536

5600056

27plusmn12014plusmn00776plusmn06

Euphorbiacuneata

Euph

orbiaceae

ST428

4400200

42plusmn19012plusmn00665plusmn06

Other

species

mdashmdash

mdashmdash

mdash1075plusmn5741007plusmn647102plusmn03

Subtotal

1423plusmn174

1505plusmn178

109plusmn03

DalbergiaarbutifoliamdashCo

mmiphora

afric

anamdash

Albizia

petersiana

woo

dland

3(n

species=55n

plots=

16)Site

variables(meanplusmnSE

)Elev

=986plusmn19pH15

=648plusmn009C

a15=856plusmn109

Sand

15=767plusmn156C

lay15=135plusmn155Silt15

=97plusmn096C

Nrat30=106plusmn03andBS

=744plusmn44

Dalbergiaarbutifolia

Fabaceae

subfam

ilyPapilio

noideae

ST793

100

000

02500plusmn123263plusmn06477plusmn02

Commiphora

afric

ana

Burseraceae

T542

9400026

187plusmn40272plusmn064119plusmn06

Albiziapetersiana

Mim

osacea

T536

7500200

157plusmn57103plusmn04084plusmn02

Sclerocarryabirrea

Anacardiaceae

T504

6300186

40plusmn11128plusmn045168plusmn17

Other

species

mdashmdash

mdashmdash

mdash852plusmn449669plusmn37788plusmn03

Subtotal

1735plusmn166

1435plusmn071

92plusmn02

Acaciaspmdash

Acaciaabyssin

icamdash

Albiziaam

arawoo

dland

5(n

species=33n

plots=5)

Sitevariables(m

eanplusmnSE

)Elev

=986plusmn52pH15

=734plusmn023C

a15=139plusmn33

Sand

15=745plusmn678C

lay15=148plusmn47Silt15

=107plusmn26C

Nrat30=106plusmn07andBS

=963plusmn89

Acaciasp

Mim

osaceae

T981

100

000

02269plusmn111662plusmn286172plusmn14

Acaciaabyssin

icaMim

osaceae

T594

8000030

31plusmn9060plusmn03299plusmn08

Albiziaam

ara

Mim

osaceae

T552

60000

6654plusmn30023plusmn01671plusmn08

Grew

iabicolor

Tiliaceae

ST533

6000106

113plusmn52040plusmn01770plusmn04

Acaciaseyal

Mim

osaceae

T433

6000526

62plusmn34034plusmn01790plusmn05

Other

species

mdashmdash

mdashmdash

mdash665plusmn533552plusmn49872plusmn04

Subtotal

1194plusmn169

1367plusmn347

101plusmn05

Bauh

iniapetersiana

mdashShrebera

trichoclada

woo

dland

24(n

species=35n

plots=5)

Sitevariables(meanplusmnSE

)Elev

=1175plusmn25pH15

=73plusmn04C

a15=254plusmn69

Sand

15=522plusmn68C

lay15=331plusmn28

Silt15=147plusmn44C

Nrat30=961plusmn13andBS

=1041plusmn204

Bauh

iniapetersiana

Caesalpiniaceae

SH551

8000118192plusmn121111plusmn05075plusmn03

Shrebera

trichoclada

Oleaceae

T505

6000110

57plusmn32022plusmn01380plusmn05

Manilkaramochisia

Sapo

taceae

T376

4000332

34plusmn27014plusmn00969plusmn10

Dalbergia

mela

noxylon

Fabaceae

T370

4000380

68plusmn58026plusmn02266plusmn03

Ehretia

amoena

Boraginaceae

ST347

4000344

6plusmn4

002plusmn00170plusmn04

Other

species

mdashmdash

mdashmdash

mdash982plusmn759643plusmn47999plusmn05

Subtotal

1338plusmn137

817plusmn087

91plusmn04

Total

1521plusmn5941355plusmn55298plusmn01

Elevelevatio

n(m

)CN

rat30CN

ratio

at15ndash30c

mdepthSand

15sand(

)at0

ndash15c

mC

lay15clay

()at0

ndash15c

mSilt15silt

()at0

ndash15c

mC

a15Ca2+(cmol(+)kg)at0

ndash15c

mpH15soilp

Hat0ndash

15cm

BS

base

saturatio

nat0ndash

15cm

12 ISRN Biodiversity

Table 3 Pearson-correlation matrix for two topographic and eight edaphic variablesdagger associated with the classified plant communities in theGangalamtumba VLFR (119899 = 35) Applied significance levels lowast5 lowastlowast1 and lowastlowastlowast01 +not significant

Elev Slope pH15 Ca15 K15 N15 Sand15 Clay15 CNrat30Slope 019+

pH15 minus013+ minus033lowast

Ca15 002+ minus020+ 083lowastlowastlowast

K15 minus029+ 000+ 010+ 012+

N15 006+ 036lowast 010+ 041lowastlowast 033lowast

Sand15 minus042lowastlowast 003+ minus053lowastlowastlowast minus074lowastlowastlowast 006+ minus046lowastlowast

Clay15 031+ minus012+ 051lowastlowast 076lowastlowastlowast minus001+ 047lowastlowast minus086lowastlowastlowast

CNrat30 036lowast 010+ minus039lowast minus051lowastlowast minus015+ minus019+ 040lowast minus048lowastlowast

BS minus024+ minus017+ 084lowastlowastlowast 091lowastlowastlowast 015+ 037lowast minus058lowastlowastlowast 060lowastlowastlowast minus051lowastlowastdaggerElev elevation (m) pH15 soil pH at 0ndash15 cm Ca15 Ca2+ (cmol(+)kg) at 0ndash15 cm K15 K+ (cmol(+)kg) at 0ndash15 cm N15 N concentration at 0ndash15 cmSand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm CNrat30 C N ratio at 15ndash30 cm depth BS base saturation at 0ndash15 cm 119905-value was calculated as119905 = 119903radic(119899 minus 2)(1 minus 119903

2) where 119903 is the Pearson-correlation coefficient and 119899 is the total sample size

Table 4 Species richness observed in other studies from drymiombo woodlands

Plot size(ha)

Totalnumberof plots

Total samplearea(ha)

Total numberof species References

0071 70 495 82 [43]0071 80 565 110 [27]0071 133 940 229 [26]0071 247 1746 102 [44]004 40 160 81 [45]025 14 350 69 [25]01 2 020 40 [28]01 152 1520 92 genera [22]0071 35 247 88 This study

annual rainfall of 565ndash1500mm (Table 4) Using plot sizes of004ndash025 ha and sample sizes of 2ndash247 plots a total numberof species ranging from40 (Dbhge 10 cm) to 229 (Dbhge 2 cm)have been reported fromMiombowoodlands [22 25ndash28 43ndash45]

The high number of species reported by Banda et al [26]Chidumayo [22] Isango [45] and Chamshama et al [44] islikely to be a consequence of the spatial scale and coverage ofthese studies as they all cover large areas include more thanone site and operate with large sample sizes For exampleChidumayo [22] included species from both wet and dryMiombo areas in Zambia The study by Sauer and Abdallah[15] who reported a total of 131 species occurring in thetobacco growing zone of Iringa rural district included twoforest reserves and three family-managed forests Thereforeconsidering the climatic conditions in the GVLFR (617mmof rainfall per year) and the sample size (35 plots) thespecies richness reported in this study can be ranked atleast as high or higher than those found in the studiesmentioned The selective sampling approach focusing onvarious microhabitat types adopted by Banda et al [26] mayhave contributed to the large number of species observed

in their study area Similarly the higher number of speciesfound by Giliba et al [27] was probably due to the presenceof riverine forest offering site conditions favourable formanyspecies

The values of the Shannon-Wiener (1198671015840 = 344) andSimpson indices (119863 = 005) reported for large individ-uals in this study are within the range observed for mostcommunities of particular life forms [36] For example 1198671015840usually does not exceed 5 although this maximum valuevaries depending on the type of the biological communitysampled and the sampling approach applied (eg minimumdiameter and size of sample units) A threshold value of 2 for1198671015840 has been mentioned as a minimum value above which

an ecosystem can be regarded as medium to highly diverse[27] Chamshama et al [44] reported three 1198671015840 values of31 32 and 33 from Kitulangalo Miombo forest in EasternTanzania while Njana [43] reported a 1198671015840 value of 340from dry Miombo forest in Western Tanzania The studiesby Sauer and Abdallah [15] and Giliba et al [27] reportedparticularly high values of 346 and 427 respectively Thiscould be attributed to the very large sample sizes used inboth studies and the presence of riverine forest where thechance of encountering many rare species is likely to be highThe forests examined in the mentioned studies receive anaverage annual rainfall of 700ndash1000mm compared to whichthe rainfall in the GVLFR is low (617mm on average per yearcf above)The relatively high diversity found inGVLFRmusttherefore be attributed to other factors than climate The soilanalyses indicate that the soil fertility level in the GVLFRis relatively high with considerable proportions of all 2 1lattice clay minerals (114) (ie illite montmorillonite andvermiculite) plus a good amount of organic matter whichmay suggest that the soil has large reserves of important plantnutrients for example K Mg and Fe The base saturationpercentage (BS) which is normally used to indicate the soilfertility status (Landon 1991) was also high 76 on averageand with 86 of the samples (30 samples) with BS valuesgt50 (fertile soil) and only 14 of the samples (5 samples)with BS below 50 (less fertile soil) As another indicationof high soil fertility status the mean C N ratio was 12 plusmn 043

ISRN Biodiversity 13

(range 7ndash19) for top soil (0ndash15 cm) and 11 plusmn 036 (range 5ndash16) for subsoil (15ndash30 cm) In general the values for both soilstrata fall within the expected range of 8ndash17 Soil pH values(mean 67 plusmn 01 range 567ndash852)were alsowithin the optimalrangewhere all the nutrients that aremost important for plantgrowth (Ca Mg K and P) are available and accessible toplants [46] In this study 97 of the soil samples had pHbelow 8 (one sample had a pH of 852) Fisher and Binkley[47] noted that high pH is almost never a problem in forestsas most trees do well across the full range of common pHvaluesTherefore considering the low average annual rainfallcompared to other forests the relatively high fertility of theGVLFR may be the main factor creating an environmentfavourable to many species thus leading to a quite highspecies diversity observed in this forest

Based on the Importance Value Index Brachystegia spi-ciformis and Combretum molle appeared to be the mostimportant species among harvested trees (stumps) in thestudy area This result agreed very well with the large valuesof basal area and volume and the information obtained fromlocal scouts and members of the village environmental com-mittee who said that the most frequently harvested speciesfor charcoal making include all Brachystegia species found inthe forest (ie Brachystegia spiciformis Brachystegia mangaBrachystegia boehmii and Brachystegia bussei) Among theCombretum species the most important one (based on IVI)Combretum molle is mostly used for house construction andfirewood rather than for charcoal making Apart from theBrachystegia species the only other species mentioned asimportant for charcoal making was Acacia mellifera Otherspecies are only used in case they happen to fall when fellingthe preferred species during the preparation of charcoal kilnsWith respect to stumps Brachystegia spiciformis Brachystegiamanga and Combretum molle are among the ten mostabundant species in terms of density basal area and volumeper hectare Stumps of the other species mentioned are notcommonly found a factwhichmay be due to the small samplesize being unable to capture sites where these species areharvested but may also be related to their limited distributionin the forest as indicated by the estimated dispersion indices(see Table 1)

42 Forest Structure Species densities reported from otherMiombo woodland areas in Tanzania are typically 348ndash1495stemsha for trees with Dbh gt4 cm [24 43 45] Comparedwith this the GVLFR is highly stocked as the estimateddensity is 2296 stemsha for trees with Dbh gt4 cmThemeanstem density of 1521 plusmn 594ha for trees with Dbh ge5 cmis also more than twice as large as values found in otherstudies [25ndash27 44 45 48] A similar pattern is seen whencomparing the density of regeneration between the studiesThe diameter distribution is characterised by a very cleartrend of decreasing stem density with increasing diameterThe shape of the distribution is thus an inverted ldquoJrdquo (Figure 3)which is a common feature of natural forests with activeregeneration and recruitment [49] However not many largetrees were captured by the sample whereas a considerablenumber of relatively large stumps were observed suggestingthat anthropogenic activities such as charcoal making may

have affected the structure and ecological balance of the forest(see Figure 3) Since the woodlands are often hit by fire whichtends to kill the seedlings (especially the late fires) and thusonly few seedlings can be expected to reach larger diameterclasses lack of mature trees and the resulting lack of seedsmay eventually threaten the biodiversity of the forest

The mean basal area of 1355 plusmn 552m2ha observedin this study is slightly above the range of values typicallyreported from the miombo region 75ndash126m2ha [26 28 4344 50] However the basal areas reported by Isango [45] werea bit higher (1504ndash1563m2ha) than observed in this study

Themean total volume inGVLFRwas estimated at 9217plusmn390m3ha for trees with Dbh ge5 cm Other studies in dryMiombo woodlands have reported mean volumes of 167ndash7603m3ha [24 44 45 50] The current standing volume ofGVLFR is thus slightly higher than values typically reportedfor forests in the Miombo ecoregion A plausible reason forthis may be that compared to other forests the GVLFR isstill well stocked despite ongoing human activities such ascharcoalmakingThebasal area observed for stumpswas only072m2ha so there is no indication of intensive extractionover many years This corresponds well with the findings ofTreue et al [20] who conclude that the estimated 04m3haannual extraction of woody biomass from GVLFR is consid-erably below its estimated annual increment of 15m3ha andthat the local forest managers seem capable of regulating theharvesting activities which in addition to village membersrsquocollection for subsistence uses also included commercialcharcoal production by external companies that pay a fee perbag of charcoal extracted to the village government

43 Plant Communities and Species Associations Except forBrachystegia spiciformis the majority of the Brachystegia andJulbernardia species that are common to miombo wood-lands elsewhere are not among the species most commonlyobserved in this study A similar pattern was observed byBanda et al [26] in the Katavi-Rukwa ecosystem wherethe genera that are most common in miombo woodlandsBrachystegia Julbernardia and Isoberlinia were not commonin their study sites Furthermore the four plant communi-ties distinguished in this study are comparable with thosereported by other studies in Tanzania including the work byMunishi et al [29] in theMiombowoodlands of Rukwa basinChunya district Tanzania and the study by Banda et al [26]in the Katavi-Rukwa ecosystem

Elevation was noted by Munishi et al [29] to be themost important factor shaping the species communities intheir study area This study found a similar pattern with thehighest coefficient of correlation observed for elevation sug-gesting that topographical variation is among the strongestdeterminants of community composition in dry Miombowoodlands hence influencing the spatial distribution ofspecies strongly However in our study area edaphic factorsalso influenced the species distribution directly Two plantcommunities occurredmainly on clayey soils with high pH atintermediate elevations one on sandy soils with lowpHat lowelevations and one on sandy-clayey soils at higher elevationsand with neutral soil pH (Figure 5) Specifically it appeared

14 ISRN Biodiversity

that the Acacia woodland category (Community 5) grows atlow elevations around temporary streams (or at least wherethe ground water table is relatively high) and the Bauhiniawoodland category (Community 24) appearsmostly in placeswith a relatively high percentage of clay (and therefore highvalues of pH Ca and BS) By contrast it appeared that theDalbergia woodland category (Community 3) is located atmore sandy sites (with low values of pH Ca and BS) andthe Brachystegia woodland category (Community 1) seemedto be located mostly at higher elevations where the CN-ratio is quite high Correlations between elevation and thebasic soil variables pH Ca and percentages of sand andclay were low (cf Figure 5) Thus the results indicate thatthe plant communities of the dry miombo woodlands inGVLFR are not only shaped by the topographic variation(elevation) and the groundwater level but also by basic soilcharacteristics The results thus confirm findings from otherstudies detecting effects of elevation and soil characteristicson species composition [51 52]

5 Conclusion

Considering that the sample size used in this study wassmaller than samples used in other studies in dry miombowoodlands the results show that the species diversity inGVLFR is relatively high compared to other forest reservesThe vegetation of GVLFR is characterised by high densitybasal area and volume and despite the scarcity of largediameter trees this indicates that the forest is in a goodcondition The effect of anthropogenic activities is neverthe-less evident and stresses the need for proper managementespecially for economically important species preferred forcharcoalmaking (egBrachystegia spiciformis) if the currentspecies diversity is to be maintained or enhanced A repeatedfuture study would be needed to assess whether the currentcommunity-based management regime yields this intendedoutcome but the available information and analyses allow forsome optimism in this respect

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors wish to thank people from Mfyome villagefor their invaluable assistance during field work Mzee IddiKaheya Damian Chotamasege AugustinoMkwama Libera-tus Simime and Mawazo Nyangwa Furthermore thanks aredue to Venancia Mlelwa from Sokoine University and MadsMadsen Krag from University of Copenhagen for doing thelaboratory work The authors also wish to thank GoodluckMoshi their driverMarcoNjana andNassoroHMagogo theTAFORI botanist for assisting with species identification andKlaus Dons for preparing a study site map Financial supportwas provided by Danida through the ENRECA Project

ldquoParticipatory forest management for rural livelihoods forestconservation and good governance in Tanzaniardquo (no 725)

References

[1] P G H Frost ldquoThe Ecology of Miombo Woodlandsrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 11ndash57 1996

[2] N Burgess J Hales E Underwood et al Terrestrial Ecoregionsof Africa and Madagascar A Conservation Assessment IslandPress World Wildlife Fund 2004

[3] J Clarke W Cavendish and C Coote ldquoRural householdsand miombo woodlands use value and managementrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 101ndash135 1996

[4] B M Campbell A Angelsen A Cunningham Y KaterereA Sitoe and S Wunder ldquoMiombo woodlandsmdashopportunitiesand barriers to sustainable forest managementrdquo httpsener-gypediainfoimages66dMiombo2007pdf

[5] S Syampungani P W Chirwa F K Akinnifesi G Sileshi andO C Ajayi ldquoTheMiombo woodlands at the cross roads poten-tial threats sustainable livelihoods policy gaps and challengesrdquoNatural Resources Forum vol 33 no 2 pp 150ndash159 2009

[6] J I O Abbot and K Homewood ldquoA history of change causesof miombo woodland decline in a protected area in MalawirdquoJournal of Applied Ecology vol 36 no 3 pp 422ndash433 1999

[7] E J Luoga E T F Witkowski and K Balkwill ldquoLand coverand use changes in relation to the institutional frameworkand tenure of land and resources in eastern Tanzania Miombowoodlandsrdquo Environment Development and Sustainability vol7 no 1 pp 71ndash93 2005

[8] FAO The State of Food and Agriculture 2010-2011 Forest andAgriculture Organization Rome Italy 2010

[9] A H Gentry ldquoTropical forest biodiversity distributional pat-terns and their conservational significancerdquo Oikos vol 63 no1 pp 19ndash28 1992

[10] O E Sala F S Chapin III J J Armesto et al ldquoGlobalbiodiversity scenarios for the year 2100rdquo Science vol 287 no5459 pp 1770ndash1774 2000

[11] H J Geist and E F Lambin ldquoProximate causes and underlyingdriving forces of tropical deforestationrdquo BioScience vol 52 no2 pp 143ndash150 2002

[12] R S DeFries ldquoTropical forests deforestation and ecosystemsservices Contributions of remote sensingrdquo in GeoinformaticsFor Tropical Ecosystems P S Roy Ed pp 1ndash32 2003

[13] B M Campbell P Frost and N Bryon ldquoMiombo woodlandsand their use overview and key issuesrdquo in The Miombo inTransition Woodlands and Welfare in Africa B Campbell Edpp 1ndash10 2006

[14] H J Geist ldquoGlobal assessment of deforestation related totobacco farmingrdquo Tobacco Control vol 8 no 1 pp 18ndash28 1999

[15] J Sauer and J M Abdallah ldquoForest diversity tobacco produc-tion and resource management in Tanzaniardquo Forest Policy andEconomics vol 9 no 5 pp 421ndash439 2007

[16] E N Chidumayo and K J Mbata ldquoShifting cultivation ediblecaterpillars and livelihoods in the Kopa area of northernZambiardquo Forests Trees and Livelihoods vol 12 no 3 pp 175ndash1932002

[17] E N Chidumayo and L Kwibisa ldquoEffects of deforestation ongrass biomass and soil nutrient status in miombo woodlandZambiardquo Agriculture Ecosystems and Environment vol 96 no1ndash3 pp 97ndash105 2003

ISRN Biodiversity 15

[18] J F Lund and T Treue ldquoAre we getting there Evidence ofdecentralized forest management from the Tanzanian miombowoodlandsrdquoWorld Development vol 36 no 12 pp 2780ndash28002008

[19] T Blomley and S Iddi Participatory Forest Management inTanzania 1993ndash2009mdashLessons Learned and Experiences toDate Ministry of Natural Resources and Tourism Forestry andBeekeeping Division Dar es Salaam Tanzania 2009

[20] T Treue Y M Ngaga H Meilby et al ldquoDoes participatoryforest management promote sustainable forest utilisation inTanzaniardquo International Forestry Review vol 16 no 1 pp 1ndash162014

[21] Ministry ofNatural Resources andTourismParticipatory ForestManagement in Tanzania Facts and Figures Forestry andBeekeeping Division Dar es Salaam Tanzania 2008

[22] E N Chidumayo ldquoSpecies structure in Zambian miombowoodlandrdquo Journal of Tropical Ecology vol 3 no 2 pp 109ndash1181987

[23] J D Lowore ldquoCoppice regeneration in some miombo wood-lands of Malawirdquo FRIM Report 99001 Forestry ResearchInstitute of Malawi 1999

[24] E J Luoga E T F Witkowski and K Balkwill ldquoHarvestedand standing wood stocks in protected and communal miombowoodlands of eastern Tanzaniardquo Forest Ecology and Manage-ment vol 164 no 1ndash3 pp 15ndash30 2002

[25] M Williams C M Ryan R M Rees E Sambane J Fernandoand J Grace ldquoCarbon sequestration and biodiversity of re-growing miombo woodlands in Mozambiquerdquo Forest Ecologyand Management vol 254 no 2 pp 145ndash155 2008

[26] T Banda NMwangulango BMeyer et al ldquoThewoodland veg-etation of the Katavi-Rukwa ecosystem in western TanzaniardquoForest Ecology andManagement vol 255 no 8-9 pp 3382ndash33952008

[27] R A Giliba E K Boon C J Kayombo E B Musamba AM Kashindye and P F Shayo ldquoSpecies composition richnessand diversity in Miombo Woodland of Bereku Forest ReserveTanzaniardquo Journal of Biodiversity vol 2 no 1 pp 1ndash7 2011

[28] D D Shirima P K T Munishi S L Lewis et al ldquoCarbonstorage structure and composition of miombo woodlands inTanzaniarsquos Eastern Arc Mountainsrdquo African Journal of Ecologyvol 49 no 3 pp 332ndash342 2011

[29] P K T Munishi R A P C Temu and G Soka ldquoPlant com-munities and tree species associations in a Miombo ecosystemin the Lake Rukwa basin Southern Tanzania implications forconservationrdquo Journal of Ecology and Natural Environment vol3 no 2 pp 63ndash71 2011

[30] J Dewis and F Freitas ldquoPhysical analysis of soilsrdquo in Physicaland Chemical Methods of Soil andWater Analysis FAO Bulletinno 10 pp 51ndash57 2nd edition 1970

[31] S R Olsen and L E Sommers ldquoPhosphorusrdquo inMethods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 403ndash430 American Societyof Agronomy Madson Wis USA 1982

[32] J D Rhoades ldquoCation exchange capacityrdquo in Methods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 149ndash157 American Society ofAgronomy Madson Wis USA 1982

[33] IMatejovic ldquoDetermination of carbon hydrogen and nitrogenin soils by automated elemental analysis (dry combustionmethod)rdquo Communications in Soil Science and Plant Analysisvol 24 no 17-18 pp 2213ndash2222 1993

[34] J P Moslashberg Soil Analysis Manual Revised Edition Laboratoryof Soil Sciences Department of Soil Science SokoineUniversityof Agriculture Morogoro Tanzania 2001

[35] N C BradyThe Nature and Properties of Soils Macmillan 8thedition 1974

[36] C J Krebs Ecological Methodology Hamper Collins PublishersNew York NY USA 2nd edition 1999

[37] B Husch T W Beers and J A Kershaw Forest MensurationJohn Wiley amp Sons Hoboken NJ USA 4th edition 2003

[38] E E Mwakalukwa H Meilby and T Treue ldquoVolume andaboveground biomass models for dry Miombo Woodland inTanzaniardquo In press

[39] M Kent Vegetation Description and Analysis A PracticalApproach Wiley-Blackwell John Wiley amp Sons Hoboken NJUSA 2nd edition 2012

[40] B McCune and M J Mefford PC-ORD Multivariate Analysisof Ecological Data Version 6 MjM Software Gleneden BeachOre USA 2011

[41] MDufrene andP Legendre ldquoSpecies assemblages and indicatorspecies the need for a flexible asymmetrical approachrdquo EcologyMonography vol 67 pp 777ndash795 1997

[42] J E PeckMultivariate Analysis for Community Ecologists Step-by-Step using PC-ORD MjM Software Design Gleneden BeachOre USA 2010

[43] M A Njana Arborescent species diversity and stocking inMiombo Woodland of Urumwa forest reserve and their contri-bution to Livelihoods Tabora Tanzania [MS thesis] SokoineUniversity of Agriculture Morogoro Tanzania 2008

[44] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal no 200 pp 59ndash70 2004

[45] J Isango ldquoStand structure and tree species composition ofTanzania miombo woodlands a case study from miombowoodlands of community based forest management in Iringadistrictrdquo in MITMIOMBOmdashManagement of Indigenous TreeSpecies For EcosystemRestoration andWood Production in Semi-Arid Miombo Woodlands in Eastern Africa Proceedings ofthe 1st MITMIOMBO Project Workshop held in MorogoroTanzania 6th-12th February 2007 Working Papers of theFinnish Forest Research Institute no 50 pp 43ndash56 2007

[46] J R Landon Booker Tropical Soil Manual A Handbook ForSoil Survey and Agricultural Land Evaluation in the Tropics andSubtropics Longman Scientific amp Technical and John Wiley ampSons 1991

[47] R F Fisher and D Binkley Ecology and Management of ForestSoils John Wiley amp Sons 3rd edition 2000

[48] W A Rees ldquoPreliminary studies into bush utilization by Cattlein Zambiardquo Journal of Applied Ecology vol 11 pp 207ndash214 1974

[49] S M Philip Measuring Trees and Forests CAB InternationalWallingford UK 2nd edition 1994

[50] J D Lowore P G Abbot and M Werren ldquoStackwood volumeestimations formiombowoodlands inMalawirdquoCommonwealthForestry Review vol 73 no 3 pp 193ndash197 1994

[51] D Kubota T Masunaga Hermansah et al ldquoSoil environmentand tree species diversity in tropical rain forest West SumatraIndonesiardquo in Soils of Tropical Forest Ecosystems CharacteristicsEcology and Management A Schulte and D Ruhiyat Eds pp159ndash167 1998

[52] P K T Munishi T H Shear T Wentworth and R A PC Temu ldquoCompositional gradients of plant communities insubmontane rainforests of EasternTanzaniardquo Journal of TropicalForest Science vol 19 no 1 pp 35ndash45 2007

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

EcosystemsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MeteorologyAdvances in

EcologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Marine BiologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental Chemistry

Atmospheric SciencesInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Geological ResearchJournal of

EarthquakesJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BiodiversityInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

Page 11: Research Article Floristic Composition, Structure, and

ISRN Biodiversity 11

Table2Plantcom

mun

itiesandspeciesa

ssociatio

nsin

thed

ryMiombo

woo

dlands

ofGangalamtumba

VLF

RCom

mun

itynu

mbers135and24

representthe

different

plantassociatio

ns

119899speciesnu

mbero

fspecies

(77in

total)with

Dbhge5c

mIV+

speciesind

icator

valuemeanplusmnstd

errorand

BAisbasalarea

Com

mun

ityAs

sociated

species

Family

Habit

IV+

()

Con

stancy

()119875value

Stem

sha

BA m2 ha

MeanDbh

Brachyste

giaspiciform

ismdashDiplorhynchus

cond

ylocarponmdashLa

nnea

schw

einfurthiiw

oodland

1(n s

pecies

=47

nplots=9)

Sitevariables(meanplusmnSE

)Elev

=1200plusmn20pH15

=644plusmn013C

a15=604plusmn128

Sand

15=721plusmn431C

lay15=137plusmn188Silt15

=142plusmn335C

Nrat30=135plusmn05andBS

=526plusmn65

Brachyste

gia

spiciform

isCa

esalpiniaceae

T820

100

000

02164plusmn59356plusmn077138plusmn07

Diplorynchu

scond

ylocarpon

Apocyn

aceae

T759

89000

0866plusmn18044plusmn01382plusmn05

Lann

easchw

einfurthii

Anacardiaceae

T719

100

000

0449plusmn14072plusmn022126plusmn09

Bosciaangustifolia

Capp

araceae

T536

5600056

27plusmn12014plusmn00776plusmn06

Euphorbiacuneata

Euph

orbiaceae

ST428

4400200

42plusmn19012plusmn00665plusmn06

Other

species

mdashmdash

mdashmdash

mdash1075plusmn5741007plusmn647102plusmn03

Subtotal

1423plusmn174

1505plusmn178

109plusmn03

DalbergiaarbutifoliamdashCo

mmiphora

afric

anamdash

Albizia

petersiana

woo

dland

3(n

species=55n

plots=

16)Site

variables(meanplusmnSE

)Elev

=986plusmn19pH15

=648plusmn009C

a15=856plusmn109

Sand

15=767plusmn156C

lay15=135plusmn155Silt15

=97plusmn096C

Nrat30=106plusmn03andBS

=744plusmn44

Dalbergiaarbutifolia

Fabaceae

subfam

ilyPapilio

noideae

ST793

100

000

02500plusmn123263plusmn06477plusmn02

Commiphora

afric

ana

Burseraceae

T542

9400026

187plusmn40272plusmn064119plusmn06

Albiziapetersiana

Mim

osacea

T536

7500200

157plusmn57103plusmn04084plusmn02

Sclerocarryabirrea

Anacardiaceae

T504

6300186

40plusmn11128plusmn045168plusmn17

Other

species

mdashmdash

mdashmdash

mdash852plusmn449669plusmn37788plusmn03

Subtotal

1735plusmn166

1435plusmn071

92plusmn02

Acaciaspmdash

Acaciaabyssin

icamdash

Albiziaam

arawoo

dland

5(n

species=33n

plots=5)

Sitevariables(m

eanplusmnSE

)Elev

=986plusmn52pH15

=734plusmn023C

a15=139plusmn33

Sand

15=745plusmn678C

lay15=148plusmn47Silt15

=107plusmn26C

Nrat30=106plusmn07andBS

=963plusmn89

Acaciasp

Mim

osaceae

T981

100

000

02269plusmn111662plusmn286172plusmn14

Acaciaabyssin

icaMim

osaceae

T594

8000030

31plusmn9060plusmn03299plusmn08

Albiziaam

ara

Mim

osaceae

T552

60000

6654plusmn30023plusmn01671plusmn08

Grew

iabicolor

Tiliaceae

ST533

6000106

113plusmn52040plusmn01770plusmn04

Acaciaseyal

Mim

osaceae

T433

6000526

62plusmn34034plusmn01790plusmn05

Other

species

mdashmdash

mdashmdash

mdash665plusmn533552plusmn49872plusmn04

Subtotal

1194plusmn169

1367plusmn347

101plusmn05

Bauh

iniapetersiana

mdashShrebera

trichoclada

woo

dland

24(n

species=35n

plots=5)

Sitevariables(meanplusmnSE

)Elev

=1175plusmn25pH15

=73plusmn04C

a15=254plusmn69

Sand

15=522plusmn68C

lay15=331plusmn28

Silt15=147plusmn44C

Nrat30=961plusmn13andBS

=1041plusmn204

Bauh

iniapetersiana

Caesalpiniaceae

SH551

8000118192plusmn121111plusmn05075plusmn03

Shrebera

trichoclada

Oleaceae

T505

6000110

57plusmn32022plusmn01380plusmn05

Manilkaramochisia

Sapo

taceae

T376

4000332

34plusmn27014plusmn00969plusmn10

Dalbergia

mela

noxylon

Fabaceae

T370

4000380

68plusmn58026plusmn02266plusmn03

Ehretia

amoena

Boraginaceae

ST347

4000344

6plusmn4

002plusmn00170plusmn04

Other

species

mdashmdash

mdashmdash

mdash982plusmn759643plusmn47999plusmn05

Subtotal

1338plusmn137

817plusmn087

91plusmn04

Total

1521plusmn5941355plusmn55298plusmn01

Elevelevatio

n(m

)CN

rat30CN

ratio

at15ndash30c

mdepthSand

15sand(

)at0

ndash15c

mC

lay15clay

()at0

ndash15c

mSilt15silt

()at0

ndash15c

mC

a15Ca2+(cmol(+)kg)at0

ndash15c

mpH15soilp

Hat0ndash

15cm

BS

base

saturatio

nat0ndash

15cm

12 ISRN Biodiversity

Table 3 Pearson-correlation matrix for two topographic and eight edaphic variablesdagger associated with the classified plant communities in theGangalamtumba VLFR (119899 = 35) Applied significance levels lowast5 lowastlowast1 and lowastlowastlowast01 +not significant

Elev Slope pH15 Ca15 K15 N15 Sand15 Clay15 CNrat30Slope 019+

pH15 minus013+ minus033lowast

Ca15 002+ minus020+ 083lowastlowastlowast

K15 minus029+ 000+ 010+ 012+

N15 006+ 036lowast 010+ 041lowastlowast 033lowast

Sand15 minus042lowastlowast 003+ minus053lowastlowastlowast minus074lowastlowastlowast 006+ minus046lowastlowast

Clay15 031+ minus012+ 051lowastlowast 076lowastlowastlowast minus001+ 047lowastlowast minus086lowastlowastlowast

CNrat30 036lowast 010+ minus039lowast minus051lowastlowast minus015+ minus019+ 040lowast minus048lowastlowast

BS minus024+ minus017+ 084lowastlowastlowast 091lowastlowastlowast 015+ 037lowast minus058lowastlowastlowast 060lowastlowastlowast minus051lowastlowastdaggerElev elevation (m) pH15 soil pH at 0ndash15 cm Ca15 Ca2+ (cmol(+)kg) at 0ndash15 cm K15 K+ (cmol(+)kg) at 0ndash15 cm N15 N concentration at 0ndash15 cmSand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm CNrat30 C N ratio at 15ndash30 cm depth BS base saturation at 0ndash15 cm 119905-value was calculated as119905 = 119903radic(119899 minus 2)(1 minus 119903

2) where 119903 is the Pearson-correlation coefficient and 119899 is the total sample size

Table 4 Species richness observed in other studies from drymiombo woodlands

Plot size(ha)

Totalnumberof plots

Total samplearea(ha)

Total numberof species References

0071 70 495 82 [43]0071 80 565 110 [27]0071 133 940 229 [26]0071 247 1746 102 [44]004 40 160 81 [45]025 14 350 69 [25]01 2 020 40 [28]01 152 1520 92 genera [22]0071 35 247 88 This study

annual rainfall of 565ndash1500mm (Table 4) Using plot sizes of004ndash025 ha and sample sizes of 2ndash247 plots a total numberof species ranging from40 (Dbhge 10 cm) to 229 (Dbhge 2 cm)have been reported fromMiombowoodlands [22 25ndash28 43ndash45]

The high number of species reported by Banda et al [26]Chidumayo [22] Isango [45] and Chamshama et al [44] islikely to be a consequence of the spatial scale and coverage ofthese studies as they all cover large areas include more thanone site and operate with large sample sizes For exampleChidumayo [22] included species from both wet and dryMiombo areas in Zambia The study by Sauer and Abdallah[15] who reported a total of 131 species occurring in thetobacco growing zone of Iringa rural district included twoforest reserves and three family-managed forests Thereforeconsidering the climatic conditions in the GVLFR (617mmof rainfall per year) and the sample size (35 plots) thespecies richness reported in this study can be ranked atleast as high or higher than those found in the studiesmentioned The selective sampling approach focusing onvarious microhabitat types adopted by Banda et al [26] mayhave contributed to the large number of species observed

in their study area Similarly the higher number of speciesfound by Giliba et al [27] was probably due to the presenceof riverine forest offering site conditions favourable formanyspecies

The values of the Shannon-Wiener (1198671015840 = 344) andSimpson indices (119863 = 005) reported for large individ-uals in this study are within the range observed for mostcommunities of particular life forms [36] For example 1198671015840usually does not exceed 5 although this maximum valuevaries depending on the type of the biological communitysampled and the sampling approach applied (eg minimumdiameter and size of sample units) A threshold value of 2 for1198671015840 has been mentioned as a minimum value above which

an ecosystem can be regarded as medium to highly diverse[27] Chamshama et al [44] reported three 1198671015840 values of31 32 and 33 from Kitulangalo Miombo forest in EasternTanzania while Njana [43] reported a 1198671015840 value of 340from dry Miombo forest in Western Tanzania The studiesby Sauer and Abdallah [15] and Giliba et al [27] reportedparticularly high values of 346 and 427 respectively Thiscould be attributed to the very large sample sizes used inboth studies and the presence of riverine forest where thechance of encountering many rare species is likely to be highThe forests examined in the mentioned studies receive anaverage annual rainfall of 700ndash1000mm compared to whichthe rainfall in the GVLFR is low (617mm on average per yearcf above)The relatively high diversity found inGVLFRmusttherefore be attributed to other factors than climate The soilanalyses indicate that the soil fertility level in the GVLFRis relatively high with considerable proportions of all 2 1lattice clay minerals (114) (ie illite montmorillonite andvermiculite) plus a good amount of organic matter whichmay suggest that the soil has large reserves of important plantnutrients for example K Mg and Fe The base saturationpercentage (BS) which is normally used to indicate the soilfertility status (Landon 1991) was also high 76 on averageand with 86 of the samples (30 samples) with BS valuesgt50 (fertile soil) and only 14 of the samples (5 samples)with BS below 50 (less fertile soil) As another indicationof high soil fertility status the mean C N ratio was 12 plusmn 043

ISRN Biodiversity 13

(range 7ndash19) for top soil (0ndash15 cm) and 11 plusmn 036 (range 5ndash16) for subsoil (15ndash30 cm) In general the values for both soilstrata fall within the expected range of 8ndash17 Soil pH values(mean 67 plusmn 01 range 567ndash852)were alsowithin the optimalrangewhere all the nutrients that aremost important for plantgrowth (Ca Mg K and P) are available and accessible toplants [46] In this study 97 of the soil samples had pHbelow 8 (one sample had a pH of 852) Fisher and Binkley[47] noted that high pH is almost never a problem in forestsas most trees do well across the full range of common pHvaluesTherefore considering the low average annual rainfallcompared to other forests the relatively high fertility of theGVLFR may be the main factor creating an environmentfavourable to many species thus leading to a quite highspecies diversity observed in this forest

Based on the Importance Value Index Brachystegia spi-ciformis and Combretum molle appeared to be the mostimportant species among harvested trees (stumps) in thestudy area This result agreed very well with the large valuesof basal area and volume and the information obtained fromlocal scouts and members of the village environmental com-mittee who said that the most frequently harvested speciesfor charcoal making include all Brachystegia species found inthe forest (ie Brachystegia spiciformis Brachystegia mangaBrachystegia boehmii and Brachystegia bussei) Among theCombretum species the most important one (based on IVI)Combretum molle is mostly used for house construction andfirewood rather than for charcoal making Apart from theBrachystegia species the only other species mentioned asimportant for charcoal making was Acacia mellifera Otherspecies are only used in case they happen to fall when fellingthe preferred species during the preparation of charcoal kilnsWith respect to stumps Brachystegia spiciformis Brachystegiamanga and Combretum molle are among the ten mostabundant species in terms of density basal area and volumeper hectare Stumps of the other species mentioned are notcommonly found a factwhichmay be due to the small samplesize being unable to capture sites where these species areharvested but may also be related to their limited distributionin the forest as indicated by the estimated dispersion indices(see Table 1)

42 Forest Structure Species densities reported from otherMiombo woodland areas in Tanzania are typically 348ndash1495stemsha for trees with Dbh gt4 cm [24 43 45] Comparedwith this the GVLFR is highly stocked as the estimateddensity is 2296 stemsha for trees with Dbh gt4 cmThemeanstem density of 1521 plusmn 594ha for trees with Dbh ge5 cmis also more than twice as large as values found in otherstudies [25ndash27 44 45 48] A similar pattern is seen whencomparing the density of regeneration between the studiesThe diameter distribution is characterised by a very cleartrend of decreasing stem density with increasing diameterThe shape of the distribution is thus an inverted ldquoJrdquo (Figure 3)which is a common feature of natural forests with activeregeneration and recruitment [49] However not many largetrees were captured by the sample whereas a considerablenumber of relatively large stumps were observed suggestingthat anthropogenic activities such as charcoal making may

have affected the structure and ecological balance of the forest(see Figure 3) Since the woodlands are often hit by fire whichtends to kill the seedlings (especially the late fires) and thusonly few seedlings can be expected to reach larger diameterclasses lack of mature trees and the resulting lack of seedsmay eventually threaten the biodiversity of the forest

The mean basal area of 1355 plusmn 552m2ha observedin this study is slightly above the range of values typicallyreported from the miombo region 75ndash126m2ha [26 28 4344 50] However the basal areas reported by Isango [45] werea bit higher (1504ndash1563m2ha) than observed in this study

Themean total volume inGVLFRwas estimated at 9217plusmn390m3ha for trees with Dbh ge5 cm Other studies in dryMiombo woodlands have reported mean volumes of 167ndash7603m3ha [24 44 45 50] The current standing volume ofGVLFR is thus slightly higher than values typically reportedfor forests in the Miombo ecoregion A plausible reason forthis may be that compared to other forests the GVLFR isstill well stocked despite ongoing human activities such ascharcoalmakingThebasal area observed for stumpswas only072m2ha so there is no indication of intensive extractionover many years This corresponds well with the findings ofTreue et al [20] who conclude that the estimated 04m3haannual extraction of woody biomass from GVLFR is consid-erably below its estimated annual increment of 15m3ha andthat the local forest managers seem capable of regulating theharvesting activities which in addition to village membersrsquocollection for subsistence uses also included commercialcharcoal production by external companies that pay a fee perbag of charcoal extracted to the village government

43 Plant Communities and Species Associations Except forBrachystegia spiciformis the majority of the Brachystegia andJulbernardia species that are common to miombo wood-lands elsewhere are not among the species most commonlyobserved in this study A similar pattern was observed byBanda et al [26] in the Katavi-Rukwa ecosystem wherethe genera that are most common in miombo woodlandsBrachystegia Julbernardia and Isoberlinia were not commonin their study sites Furthermore the four plant communi-ties distinguished in this study are comparable with thosereported by other studies in Tanzania including the work byMunishi et al [29] in theMiombowoodlands of Rukwa basinChunya district Tanzania and the study by Banda et al [26]in the Katavi-Rukwa ecosystem

Elevation was noted by Munishi et al [29] to be themost important factor shaping the species communities intheir study area This study found a similar pattern with thehighest coefficient of correlation observed for elevation sug-gesting that topographical variation is among the strongestdeterminants of community composition in dry Miombowoodlands hence influencing the spatial distribution ofspecies strongly However in our study area edaphic factorsalso influenced the species distribution directly Two plantcommunities occurredmainly on clayey soils with high pH atintermediate elevations one on sandy soils with lowpHat lowelevations and one on sandy-clayey soils at higher elevationsand with neutral soil pH (Figure 5) Specifically it appeared

14 ISRN Biodiversity

that the Acacia woodland category (Community 5) grows atlow elevations around temporary streams (or at least wherethe ground water table is relatively high) and the Bauhiniawoodland category (Community 24) appearsmostly in placeswith a relatively high percentage of clay (and therefore highvalues of pH Ca and BS) By contrast it appeared that theDalbergia woodland category (Community 3) is located atmore sandy sites (with low values of pH Ca and BS) andthe Brachystegia woodland category (Community 1) seemedto be located mostly at higher elevations where the CN-ratio is quite high Correlations between elevation and thebasic soil variables pH Ca and percentages of sand andclay were low (cf Figure 5) Thus the results indicate thatthe plant communities of the dry miombo woodlands inGVLFR are not only shaped by the topographic variation(elevation) and the groundwater level but also by basic soilcharacteristics The results thus confirm findings from otherstudies detecting effects of elevation and soil characteristicson species composition [51 52]

5 Conclusion

Considering that the sample size used in this study wassmaller than samples used in other studies in dry miombowoodlands the results show that the species diversity inGVLFR is relatively high compared to other forest reservesThe vegetation of GVLFR is characterised by high densitybasal area and volume and despite the scarcity of largediameter trees this indicates that the forest is in a goodcondition The effect of anthropogenic activities is neverthe-less evident and stresses the need for proper managementespecially for economically important species preferred forcharcoalmaking (egBrachystegia spiciformis) if the currentspecies diversity is to be maintained or enhanced A repeatedfuture study would be needed to assess whether the currentcommunity-based management regime yields this intendedoutcome but the available information and analyses allow forsome optimism in this respect

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors wish to thank people from Mfyome villagefor their invaluable assistance during field work Mzee IddiKaheya Damian Chotamasege AugustinoMkwama Libera-tus Simime and Mawazo Nyangwa Furthermore thanks aredue to Venancia Mlelwa from Sokoine University and MadsMadsen Krag from University of Copenhagen for doing thelaboratory work The authors also wish to thank GoodluckMoshi their driverMarcoNjana andNassoroHMagogo theTAFORI botanist for assisting with species identification andKlaus Dons for preparing a study site map Financial supportwas provided by Danida through the ENRECA Project

ldquoParticipatory forest management for rural livelihoods forestconservation and good governance in Tanzaniardquo (no 725)

References

[1] P G H Frost ldquoThe Ecology of Miombo Woodlandsrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 11ndash57 1996

[2] N Burgess J Hales E Underwood et al Terrestrial Ecoregionsof Africa and Madagascar A Conservation Assessment IslandPress World Wildlife Fund 2004

[3] J Clarke W Cavendish and C Coote ldquoRural householdsand miombo woodlands use value and managementrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 101ndash135 1996

[4] B M Campbell A Angelsen A Cunningham Y KaterereA Sitoe and S Wunder ldquoMiombo woodlandsmdashopportunitiesand barriers to sustainable forest managementrdquo httpsener-gypediainfoimages66dMiombo2007pdf

[5] S Syampungani P W Chirwa F K Akinnifesi G Sileshi andO C Ajayi ldquoTheMiombo woodlands at the cross roads poten-tial threats sustainable livelihoods policy gaps and challengesrdquoNatural Resources Forum vol 33 no 2 pp 150ndash159 2009

[6] J I O Abbot and K Homewood ldquoA history of change causesof miombo woodland decline in a protected area in MalawirdquoJournal of Applied Ecology vol 36 no 3 pp 422ndash433 1999

[7] E J Luoga E T F Witkowski and K Balkwill ldquoLand coverand use changes in relation to the institutional frameworkand tenure of land and resources in eastern Tanzania Miombowoodlandsrdquo Environment Development and Sustainability vol7 no 1 pp 71ndash93 2005

[8] FAO The State of Food and Agriculture 2010-2011 Forest andAgriculture Organization Rome Italy 2010

[9] A H Gentry ldquoTropical forest biodiversity distributional pat-terns and their conservational significancerdquo Oikos vol 63 no1 pp 19ndash28 1992

[10] O E Sala F S Chapin III J J Armesto et al ldquoGlobalbiodiversity scenarios for the year 2100rdquo Science vol 287 no5459 pp 1770ndash1774 2000

[11] H J Geist and E F Lambin ldquoProximate causes and underlyingdriving forces of tropical deforestationrdquo BioScience vol 52 no2 pp 143ndash150 2002

[12] R S DeFries ldquoTropical forests deforestation and ecosystemsservices Contributions of remote sensingrdquo in GeoinformaticsFor Tropical Ecosystems P S Roy Ed pp 1ndash32 2003

[13] B M Campbell P Frost and N Bryon ldquoMiombo woodlandsand their use overview and key issuesrdquo in The Miombo inTransition Woodlands and Welfare in Africa B Campbell Edpp 1ndash10 2006

[14] H J Geist ldquoGlobal assessment of deforestation related totobacco farmingrdquo Tobacco Control vol 8 no 1 pp 18ndash28 1999

[15] J Sauer and J M Abdallah ldquoForest diversity tobacco produc-tion and resource management in Tanzaniardquo Forest Policy andEconomics vol 9 no 5 pp 421ndash439 2007

[16] E N Chidumayo and K J Mbata ldquoShifting cultivation ediblecaterpillars and livelihoods in the Kopa area of northernZambiardquo Forests Trees and Livelihoods vol 12 no 3 pp 175ndash1932002

[17] E N Chidumayo and L Kwibisa ldquoEffects of deforestation ongrass biomass and soil nutrient status in miombo woodlandZambiardquo Agriculture Ecosystems and Environment vol 96 no1ndash3 pp 97ndash105 2003

ISRN Biodiversity 15

[18] J F Lund and T Treue ldquoAre we getting there Evidence ofdecentralized forest management from the Tanzanian miombowoodlandsrdquoWorld Development vol 36 no 12 pp 2780ndash28002008

[19] T Blomley and S Iddi Participatory Forest Management inTanzania 1993ndash2009mdashLessons Learned and Experiences toDate Ministry of Natural Resources and Tourism Forestry andBeekeeping Division Dar es Salaam Tanzania 2009

[20] T Treue Y M Ngaga H Meilby et al ldquoDoes participatoryforest management promote sustainable forest utilisation inTanzaniardquo International Forestry Review vol 16 no 1 pp 1ndash162014

[21] Ministry ofNatural Resources andTourismParticipatory ForestManagement in Tanzania Facts and Figures Forestry andBeekeeping Division Dar es Salaam Tanzania 2008

[22] E N Chidumayo ldquoSpecies structure in Zambian miombowoodlandrdquo Journal of Tropical Ecology vol 3 no 2 pp 109ndash1181987

[23] J D Lowore ldquoCoppice regeneration in some miombo wood-lands of Malawirdquo FRIM Report 99001 Forestry ResearchInstitute of Malawi 1999

[24] E J Luoga E T F Witkowski and K Balkwill ldquoHarvestedand standing wood stocks in protected and communal miombowoodlands of eastern Tanzaniardquo Forest Ecology and Manage-ment vol 164 no 1ndash3 pp 15ndash30 2002

[25] M Williams C M Ryan R M Rees E Sambane J Fernandoand J Grace ldquoCarbon sequestration and biodiversity of re-growing miombo woodlands in Mozambiquerdquo Forest Ecologyand Management vol 254 no 2 pp 145ndash155 2008

[26] T Banda NMwangulango BMeyer et al ldquoThewoodland veg-etation of the Katavi-Rukwa ecosystem in western TanzaniardquoForest Ecology andManagement vol 255 no 8-9 pp 3382ndash33952008

[27] R A Giliba E K Boon C J Kayombo E B Musamba AM Kashindye and P F Shayo ldquoSpecies composition richnessand diversity in Miombo Woodland of Bereku Forest ReserveTanzaniardquo Journal of Biodiversity vol 2 no 1 pp 1ndash7 2011

[28] D D Shirima P K T Munishi S L Lewis et al ldquoCarbonstorage structure and composition of miombo woodlands inTanzaniarsquos Eastern Arc Mountainsrdquo African Journal of Ecologyvol 49 no 3 pp 332ndash342 2011

[29] P K T Munishi R A P C Temu and G Soka ldquoPlant com-munities and tree species associations in a Miombo ecosystemin the Lake Rukwa basin Southern Tanzania implications forconservationrdquo Journal of Ecology and Natural Environment vol3 no 2 pp 63ndash71 2011

[30] J Dewis and F Freitas ldquoPhysical analysis of soilsrdquo in Physicaland Chemical Methods of Soil andWater Analysis FAO Bulletinno 10 pp 51ndash57 2nd edition 1970

[31] S R Olsen and L E Sommers ldquoPhosphorusrdquo inMethods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 403ndash430 American Societyof Agronomy Madson Wis USA 1982

[32] J D Rhoades ldquoCation exchange capacityrdquo in Methods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 149ndash157 American Society ofAgronomy Madson Wis USA 1982

[33] IMatejovic ldquoDetermination of carbon hydrogen and nitrogenin soils by automated elemental analysis (dry combustionmethod)rdquo Communications in Soil Science and Plant Analysisvol 24 no 17-18 pp 2213ndash2222 1993

[34] J P Moslashberg Soil Analysis Manual Revised Edition Laboratoryof Soil Sciences Department of Soil Science SokoineUniversityof Agriculture Morogoro Tanzania 2001

[35] N C BradyThe Nature and Properties of Soils Macmillan 8thedition 1974

[36] C J Krebs Ecological Methodology Hamper Collins PublishersNew York NY USA 2nd edition 1999

[37] B Husch T W Beers and J A Kershaw Forest MensurationJohn Wiley amp Sons Hoboken NJ USA 4th edition 2003

[38] E E Mwakalukwa H Meilby and T Treue ldquoVolume andaboveground biomass models for dry Miombo Woodland inTanzaniardquo In press

[39] M Kent Vegetation Description and Analysis A PracticalApproach Wiley-Blackwell John Wiley amp Sons Hoboken NJUSA 2nd edition 2012

[40] B McCune and M J Mefford PC-ORD Multivariate Analysisof Ecological Data Version 6 MjM Software Gleneden BeachOre USA 2011

[41] MDufrene andP Legendre ldquoSpecies assemblages and indicatorspecies the need for a flexible asymmetrical approachrdquo EcologyMonography vol 67 pp 777ndash795 1997

[42] J E PeckMultivariate Analysis for Community Ecologists Step-by-Step using PC-ORD MjM Software Design Gleneden BeachOre USA 2010

[43] M A Njana Arborescent species diversity and stocking inMiombo Woodland of Urumwa forest reserve and their contri-bution to Livelihoods Tabora Tanzania [MS thesis] SokoineUniversity of Agriculture Morogoro Tanzania 2008

[44] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal no 200 pp 59ndash70 2004

[45] J Isango ldquoStand structure and tree species composition ofTanzania miombo woodlands a case study from miombowoodlands of community based forest management in Iringadistrictrdquo in MITMIOMBOmdashManagement of Indigenous TreeSpecies For EcosystemRestoration andWood Production in Semi-Arid Miombo Woodlands in Eastern Africa Proceedings ofthe 1st MITMIOMBO Project Workshop held in MorogoroTanzania 6th-12th February 2007 Working Papers of theFinnish Forest Research Institute no 50 pp 43ndash56 2007

[46] J R Landon Booker Tropical Soil Manual A Handbook ForSoil Survey and Agricultural Land Evaluation in the Tropics andSubtropics Longman Scientific amp Technical and John Wiley ampSons 1991

[47] R F Fisher and D Binkley Ecology and Management of ForestSoils John Wiley amp Sons 3rd edition 2000

[48] W A Rees ldquoPreliminary studies into bush utilization by Cattlein Zambiardquo Journal of Applied Ecology vol 11 pp 207ndash214 1974

[49] S M Philip Measuring Trees and Forests CAB InternationalWallingford UK 2nd edition 1994

[50] J D Lowore P G Abbot and M Werren ldquoStackwood volumeestimations formiombowoodlands inMalawirdquoCommonwealthForestry Review vol 73 no 3 pp 193ndash197 1994

[51] D Kubota T Masunaga Hermansah et al ldquoSoil environmentand tree species diversity in tropical rain forest West SumatraIndonesiardquo in Soils of Tropical Forest Ecosystems CharacteristicsEcology and Management A Schulte and D Ruhiyat Eds pp159ndash167 1998

[52] P K T Munishi T H Shear T Wentworth and R A PC Temu ldquoCompositional gradients of plant communities insubmontane rainforests of EasternTanzaniardquo Journal of TropicalForest Science vol 19 no 1 pp 35ndash45 2007

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

EcosystemsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MeteorologyAdvances in

EcologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Marine BiologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental Chemistry

Atmospheric SciencesInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Geological ResearchJournal of

EarthquakesJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BiodiversityInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

Page 12: Research Article Floristic Composition, Structure, and

12 ISRN Biodiversity

Table 3 Pearson-correlation matrix for two topographic and eight edaphic variablesdagger associated with the classified plant communities in theGangalamtumba VLFR (119899 = 35) Applied significance levels lowast5 lowastlowast1 and lowastlowastlowast01 +not significant

Elev Slope pH15 Ca15 K15 N15 Sand15 Clay15 CNrat30Slope 019+

pH15 minus013+ minus033lowast

Ca15 002+ minus020+ 083lowastlowastlowast

K15 minus029+ 000+ 010+ 012+

N15 006+ 036lowast 010+ 041lowastlowast 033lowast

Sand15 minus042lowastlowast 003+ minus053lowastlowastlowast minus074lowastlowastlowast 006+ minus046lowastlowast

Clay15 031+ minus012+ 051lowastlowast 076lowastlowastlowast minus001+ 047lowastlowast minus086lowastlowastlowast

CNrat30 036lowast 010+ minus039lowast minus051lowastlowast minus015+ minus019+ 040lowast minus048lowastlowast

BS minus024+ minus017+ 084lowastlowastlowast 091lowastlowastlowast 015+ 037lowast minus058lowastlowastlowast 060lowastlowastlowast minus051lowastlowastdaggerElev elevation (m) pH15 soil pH at 0ndash15 cm Ca15 Ca2+ (cmol(+)kg) at 0ndash15 cm K15 K+ (cmol(+)kg) at 0ndash15 cm N15 N concentration at 0ndash15 cmSand15 sand () at 0ndash15 cm Clay15 clay () at 0ndash15 cm CNrat30 C N ratio at 15ndash30 cm depth BS base saturation at 0ndash15 cm 119905-value was calculated as119905 = 119903radic(119899 minus 2)(1 minus 119903

2) where 119903 is the Pearson-correlation coefficient and 119899 is the total sample size

Table 4 Species richness observed in other studies from drymiombo woodlands

Plot size(ha)

Totalnumberof plots

Total samplearea(ha)

Total numberof species References

0071 70 495 82 [43]0071 80 565 110 [27]0071 133 940 229 [26]0071 247 1746 102 [44]004 40 160 81 [45]025 14 350 69 [25]01 2 020 40 [28]01 152 1520 92 genera [22]0071 35 247 88 This study

annual rainfall of 565ndash1500mm (Table 4) Using plot sizes of004ndash025 ha and sample sizes of 2ndash247 plots a total numberof species ranging from40 (Dbhge 10 cm) to 229 (Dbhge 2 cm)have been reported fromMiombowoodlands [22 25ndash28 43ndash45]

The high number of species reported by Banda et al [26]Chidumayo [22] Isango [45] and Chamshama et al [44] islikely to be a consequence of the spatial scale and coverage ofthese studies as they all cover large areas include more thanone site and operate with large sample sizes For exampleChidumayo [22] included species from both wet and dryMiombo areas in Zambia The study by Sauer and Abdallah[15] who reported a total of 131 species occurring in thetobacco growing zone of Iringa rural district included twoforest reserves and three family-managed forests Thereforeconsidering the climatic conditions in the GVLFR (617mmof rainfall per year) and the sample size (35 plots) thespecies richness reported in this study can be ranked atleast as high or higher than those found in the studiesmentioned The selective sampling approach focusing onvarious microhabitat types adopted by Banda et al [26] mayhave contributed to the large number of species observed

in their study area Similarly the higher number of speciesfound by Giliba et al [27] was probably due to the presenceof riverine forest offering site conditions favourable formanyspecies

The values of the Shannon-Wiener (1198671015840 = 344) andSimpson indices (119863 = 005) reported for large individ-uals in this study are within the range observed for mostcommunities of particular life forms [36] For example 1198671015840usually does not exceed 5 although this maximum valuevaries depending on the type of the biological communitysampled and the sampling approach applied (eg minimumdiameter and size of sample units) A threshold value of 2 for1198671015840 has been mentioned as a minimum value above which

an ecosystem can be regarded as medium to highly diverse[27] Chamshama et al [44] reported three 1198671015840 values of31 32 and 33 from Kitulangalo Miombo forest in EasternTanzania while Njana [43] reported a 1198671015840 value of 340from dry Miombo forest in Western Tanzania The studiesby Sauer and Abdallah [15] and Giliba et al [27] reportedparticularly high values of 346 and 427 respectively Thiscould be attributed to the very large sample sizes used inboth studies and the presence of riverine forest where thechance of encountering many rare species is likely to be highThe forests examined in the mentioned studies receive anaverage annual rainfall of 700ndash1000mm compared to whichthe rainfall in the GVLFR is low (617mm on average per yearcf above)The relatively high diversity found inGVLFRmusttherefore be attributed to other factors than climate The soilanalyses indicate that the soil fertility level in the GVLFRis relatively high with considerable proportions of all 2 1lattice clay minerals (114) (ie illite montmorillonite andvermiculite) plus a good amount of organic matter whichmay suggest that the soil has large reserves of important plantnutrients for example K Mg and Fe The base saturationpercentage (BS) which is normally used to indicate the soilfertility status (Landon 1991) was also high 76 on averageand with 86 of the samples (30 samples) with BS valuesgt50 (fertile soil) and only 14 of the samples (5 samples)with BS below 50 (less fertile soil) As another indicationof high soil fertility status the mean C N ratio was 12 plusmn 043

ISRN Biodiversity 13

(range 7ndash19) for top soil (0ndash15 cm) and 11 plusmn 036 (range 5ndash16) for subsoil (15ndash30 cm) In general the values for both soilstrata fall within the expected range of 8ndash17 Soil pH values(mean 67 plusmn 01 range 567ndash852)were alsowithin the optimalrangewhere all the nutrients that aremost important for plantgrowth (Ca Mg K and P) are available and accessible toplants [46] In this study 97 of the soil samples had pHbelow 8 (one sample had a pH of 852) Fisher and Binkley[47] noted that high pH is almost never a problem in forestsas most trees do well across the full range of common pHvaluesTherefore considering the low average annual rainfallcompared to other forests the relatively high fertility of theGVLFR may be the main factor creating an environmentfavourable to many species thus leading to a quite highspecies diversity observed in this forest

Based on the Importance Value Index Brachystegia spi-ciformis and Combretum molle appeared to be the mostimportant species among harvested trees (stumps) in thestudy area This result agreed very well with the large valuesof basal area and volume and the information obtained fromlocal scouts and members of the village environmental com-mittee who said that the most frequently harvested speciesfor charcoal making include all Brachystegia species found inthe forest (ie Brachystegia spiciformis Brachystegia mangaBrachystegia boehmii and Brachystegia bussei) Among theCombretum species the most important one (based on IVI)Combretum molle is mostly used for house construction andfirewood rather than for charcoal making Apart from theBrachystegia species the only other species mentioned asimportant for charcoal making was Acacia mellifera Otherspecies are only used in case they happen to fall when fellingthe preferred species during the preparation of charcoal kilnsWith respect to stumps Brachystegia spiciformis Brachystegiamanga and Combretum molle are among the ten mostabundant species in terms of density basal area and volumeper hectare Stumps of the other species mentioned are notcommonly found a factwhichmay be due to the small samplesize being unable to capture sites where these species areharvested but may also be related to their limited distributionin the forest as indicated by the estimated dispersion indices(see Table 1)

42 Forest Structure Species densities reported from otherMiombo woodland areas in Tanzania are typically 348ndash1495stemsha for trees with Dbh gt4 cm [24 43 45] Comparedwith this the GVLFR is highly stocked as the estimateddensity is 2296 stemsha for trees with Dbh gt4 cmThemeanstem density of 1521 plusmn 594ha for trees with Dbh ge5 cmis also more than twice as large as values found in otherstudies [25ndash27 44 45 48] A similar pattern is seen whencomparing the density of regeneration between the studiesThe diameter distribution is characterised by a very cleartrend of decreasing stem density with increasing diameterThe shape of the distribution is thus an inverted ldquoJrdquo (Figure 3)which is a common feature of natural forests with activeregeneration and recruitment [49] However not many largetrees were captured by the sample whereas a considerablenumber of relatively large stumps were observed suggestingthat anthropogenic activities such as charcoal making may

have affected the structure and ecological balance of the forest(see Figure 3) Since the woodlands are often hit by fire whichtends to kill the seedlings (especially the late fires) and thusonly few seedlings can be expected to reach larger diameterclasses lack of mature trees and the resulting lack of seedsmay eventually threaten the biodiversity of the forest

The mean basal area of 1355 plusmn 552m2ha observedin this study is slightly above the range of values typicallyreported from the miombo region 75ndash126m2ha [26 28 4344 50] However the basal areas reported by Isango [45] werea bit higher (1504ndash1563m2ha) than observed in this study

Themean total volume inGVLFRwas estimated at 9217plusmn390m3ha for trees with Dbh ge5 cm Other studies in dryMiombo woodlands have reported mean volumes of 167ndash7603m3ha [24 44 45 50] The current standing volume ofGVLFR is thus slightly higher than values typically reportedfor forests in the Miombo ecoregion A plausible reason forthis may be that compared to other forests the GVLFR isstill well stocked despite ongoing human activities such ascharcoalmakingThebasal area observed for stumpswas only072m2ha so there is no indication of intensive extractionover many years This corresponds well with the findings ofTreue et al [20] who conclude that the estimated 04m3haannual extraction of woody biomass from GVLFR is consid-erably below its estimated annual increment of 15m3ha andthat the local forest managers seem capable of regulating theharvesting activities which in addition to village membersrsquocollection for subsistence uses also included commercialcharcoal production by external companies that pay a fee perbag of charcoal extracted to the village government

43 Plant Communities and Species Associations Except forBrachystegia spiciformis the majority of the Brachystegia andJulbernardia species that are common to miombo wood-lands elsewhere are not among the species most commonlyobserved in this study A similar pattern was observed byBanda et al [26] in the Katavi-Rukwa ecosystem wherethe genera that are most common in miombo woodlandsBrachystegia Julbernardia and Isoberlinia were not commonin their study sites Furthermore the four plant communi-ties distinguished in this study are comparable with thosereported by other studies in Tanzania including the work byMunishi et al [29] in theMiombowoodlands of Rukwa basinChunya district Tanzania and the study by Banda et al [26]in the Katavi-Rukwa ecosystem

Elevation was noted by Munishi et al [29] to be themost important factor shaping the species communities intheir study area This study found a similar pattern with thehighest coefficient of correlation observed for elevation sug-gesting that topographical variation is among the strongestdeterminants of community composition in dry Miombowoodlands hence influencing the spatial distribution ofspecies strongly However in our study area edaphic factorsalso influenced the species distribution directly Two plantcommunities occurredmainly on clayey soils with high pH atintermediate elevations one on sandy soils with lowpHat lowelevations and one on sandy-clayey soils at higher elevationsand with neutral soil pH (Figure 5) Specifically it appeared

14 ISRN Biodiversity

that the Acacia woodland category (Community 5) grows atlow elevations around temporary streams (or at least wherethe ground water table is relatively high) and the Bauhiniawoodland category (Community 24) appearsmostly in placeswith a relatively high percentage of clay (and therefore highvalues of pH Ca and BS) By contrast it appeared that theDalbergia woodland category (Community 3) is located atmore sandy sites (with low values of pH Ca and BS) andthe Brachystegia woodland category (Community 1) seemedto be located mostly at higher elevations where the CN-ratio is quite high Correlations between elevation and thebasic soil variables pH Ca and percentages of sand andclay were low (cf Figure 5) Thus the results indicate thatthe plant communities of the dry miombo woodlands inGVLFR are not only shaped by the topographic variation(elevation) and the groundwater level but also by basic soilcharacteristics The results thus confirm findings from otherstudies detecting effects of elevation and soil characteristicson species composition [51 52]

5 Conclusion

Considering that the sample size used in this study wassmaller than samples used in other studies in dry miombowoodlands the results show that the species diversity inGVLFR is relatively high compared to other forest reservesThe vegetation of GVLFR is characterised by high densitybasal area and volume and despite the scarcity of largediameter trees this indicates that the forest is in a goodcondition The effect of anthropogenic activities is neverthe-less evident and stresses the need for proper managementespecially for economically important species preferred forcharcoalmaking (egBrachystegia spiciformis) if the currentspecies diversity is to be maintained or enhanced A repeatedfuture study would be needed to assess whether the currentcommunity-based management regime yields this intendedoutcome but the available information and analyses allow forsome optimism in this respect

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors wish to thank people from Mfyome villagefor their invaluable assistance during field work Mzee IddiKaheya Damian Chotamasege AugustinoMkwama Libera-tus Simime and Mawazo Nyangwa Furthermore thanks aredue to Venancia Mlelwa from Sokoine University and MadsMadsen Krag from University of Copenhagen for doing thelaboratory work The authors also wish to thank GoodluckMoshi their driverMarcoNjana andNassoroHMagogo theTAFORI botanist for assisting with species identification andKlaus Dons for preparing a study site map Financial supportwas provided by Danida through the ENRECA Project

ldquoParticipatory forest management for rural livelihoods forestconservation and good governance in Tanzaniardquo (no 725)

References

[1] P G H Frost ldquoThe Ecology of Miombo Woodlandsrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 11ndash57 1996

[2] N Burgess J Hales E Underwood et al Terrestrial Ecoregionsof Africa and Madagascar A Conservation Assessment IslandPress World Wildlife Fund 2004

[3] J Clarke W Cavendish and C Coote ldquoRural householdsand miombo woodlands use value and managementrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 101ndash135 1996

[4] B M Campbell A Angelsen A Cunningham Y KaterereA Sitoe and S Wunder ldquoMiombo woodlandsmdashopportunitiesand barriers to sustainable forest managementrdquo httpsener-gypediainfoimages66dMiombo2007pdf

[5] S Syampungani P W Chirwa F K Akinnifesi G Sileshi andO C Ajayi ldquoTheMiombo woodlands at the cross roads poten-tial threats sustainable livelihoods policy gaps and challengesrdquoNatural Resources Forum vol 33 no 2 pp 150ndash159 2009

[6] J I O Abbot and K Homewood ldquoA history of change causesof miombo woodland decline in a protected area in MalawirdquoJournal of Applied Ecology vol 36 no 3 pp 422ndash433 1999

[7] E J Luoga E T F Witkowski and K Balkwill ldquoLand coverand use changes in relation to the institutional frameworkand tenure of land and resources in eastern Tanzania Miombowoodlandsrdquo Environment Development and Sustainability vol7 no 1 pp 71ndash93 2005

[8] FAO The State of Food and Agriculture 2010-2011 Forest andAgriculture Organization Rome Italy 2010

[9] A H Gentry ldquoTropical forest biodiversity distributional pat-terns and their conservational significancerdquo Oikos vol 63 no1 pp 19ndash28 1992

[10] O E Sala F S Chapin III J J Armesto et al ldquoGlobalbiodiversity scenarios for the year 2100rdquo Science vol 287 no5459 pp 1770ndash1774 2000

[11] H J Geist and E F Lambin ldquoProximate causes and underlyingdriving forces of tropical deforestationrdquo BioScience vol 52 no2 pp 143ndash150 2002

[12] R S DeFries ldquoTropical forests deforestation and ecosystemsservices Contributions of remote sensingrdquo in GeoinformaticsFor Tropical Ecosystems P S Roy Ed pp 1ndash32 2003

[13] B M Campbell P Frost and N Bryon ldquoMiombo woodlandsand their use overview and key issuesrdquo in The Miombo inTransition Woodlands and Welfare in Africa B Campbell Edpp 1ndash10 2006

[14] H J Geist ldquoGlobal assessment of deforestation related totobacco farmingrdquo Tobacco Control vol 8 no 1 pp 18ndash28 1999

[15] J Sauer and J M Abdallah ldquoForest diversity tobacco produc-tion and resource management in Tanzaniardquo Forest Policy andEconomics vol 9 no 5 pp 421ndash439 2007

[16] E N Chidumayo and K J Mbata ldquoShifting cultivation ediblecaterpillars and livelihoods in the Kopa area of northernZambiardquo Forests Trees and Livelihoods vol 12 no 3 pp 175ndash1932002

[17] E N Chidumayo and L Kwibisa ldquoEffects of deforestation ongrass biomass and soil nutrient status in miombo woodlandZambiardquo Agriculture Ecosystems and Environment vol 96 no1ndash3 pp 97ndash105 2003

ISRN Biodiversity 15

[18] J F Lund and T Treue ldquoAre we getting there Evidence ofdecentralized forest management from the Tanzanian miombowoodlandsrdquoWorld Development vol 36 no 12 pp 2780ndash28002008

[19] T Blomley and S Iddi Participatory Forest Management inTanzania 1993ndash2009mdashLessons Learned and Experiences toDate Ministry of Natural Resources and Tourism Forestry andBeekeeping Division Dar es Salaam Tanzania 2009

[20] T Treue Y M Ngaga H Meilby et al ldquoDoes participatoryforest management promote sustainable forest utilisation inTanzaniardquo International Forestry Review vol 16 no 1 pp 1ndash162014

[21] Ministry ofNatural Resources andTourismParticipatory ForestManagement in Tanzania Facts and Figures Forestry andBeekeeping Division Dar es Salaam Tanzania 2008

[22] E N Chidumayo ldquoSpecies structure in Zambian miombowoodlandrdquo Journal of Tropical Ecology vol 3 no 2 pp 109ndash1181987

[23] J D Lowore ldquoCoppice regeneration in some miombo wood-lands of Malawirdquo FRIM Report 99001 Forestry ResearchInstitute of Malawi 1999

[24] E J Luoga E T F Witkowski and K Balkwill ldquoHarvestedand standing wood stocks in protected and communal miombowoodlands of eastern Tanzaniardquo Forest Ecology and Manage-ment vol 164 no 1ndash3 pp 15ndash30 2002

[25] M Williams C M Ryan R M Rees E Sambane J Fernandoand J Grace ldquoCarbon sequestration and biodiversity of re-growing miombo woodlands in Mozambiquerdquo Forest Ecologyand Management vol 254 no 2 pp 145ndash155 2008

[26] T Banda NMwangulango BMeyer et al ldquoThewoodland veg-etation of the Katavi-Rukwa ecosystem in western TanzaniardquoForest Ecology andManagement vol 255 no 8-9 pp 3382ndash33952008

[27] R A Giliba E K Boon C J Kayombo E B Musamba AM Kashindye and P F Shayo ldquoSpecies composition richnessand diversity in Miombo Woodland of Bereku Forest ReserveTanzaniardquo Journal of Biodiversity vol 2 no 1 pp 1ndash7 2011

[28] D D Shirima P K T Munishi S L Lewis et al ldquoCarbonstorage structure and composition of miombo woodlands inTanzaniarsquos Eastern Arc Mountainsrdquo African Journal of Ecologyvol 49 no 3 pp 332ndash342 2011

[29] P K T Munishi R A P C Temu and G Soka ldquoPlant com-munities and tree species associations in a Miombo ecosystemin the Lake Rukwa basin Southern Tanzania implications forconservationrdquo Journal of Ecology and Natural Environment vol3 no 2 pp 63ndash71 2011

[30] J Dewis and F Freitas ldquoPhysical analysis of soilsrdquo in Physicaland Chemical Methods of Soil andWater Analysis FAO Bulletinno 10 pp 51ndash57 2nd edition 1970

[31] S R Olsen and L E Sommers ldquoPhosphorusrdquo inMethods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 403ndash430 American Societyof Agronomy Madson Wis USA 1982

[32] J D Rhoades ldquoCation exchange capacityrdquo in Methods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 149ndash157 American Society ofAgronomy Madson Wis USA 1982

[33] IMatejovic ldquoDetermination of carbon hydrogen and nitrogenin soils by automated elemental analysis (dry combustionmethod)rdquo Communications in Soil Science and Plant Analysisvol 24 no 17-18 pp 2213ndash2222 1993

[34] J P Moslashberg Soil Analysis Manual Revised Edition Laboratoryof Soil Sciences Department of Soil Science SokoineUniversityof Agriculture Morogoro Tanzania 2001

[35] N C BradyThe Nature and Properties of Soils Macmillan 8thedition 1974

[36] C J Krebs Ecological Methodology Hamper Collins PublishersNew York NY USA 2nd edition 1999

[37] B Husch T W Beers and J A Kershaw Forest MensurationJohn Wiley amp Sons Hoboken NJ USA 4th edition 2003

[38] E E Mwakalukwa H Meilby and T Treue ldquoVolume andaboveground biomass models for dry Miombo Woodland inTanzaniardquo In press

[39] M Kent Vegetation Description and Analysis A PracticalApproach Wiley-Blackwell John Wiley amp Sons Hoboken NJUSA 2nd edition 2012

[40] B McCune and M J Mefford PC-ORD Multivariate Analysisof Ecological Data Version 6 MjM Software Gleneden BeachOre USA 2011

[41] MDufrene andP Legendre ldquoSpecies assemblages and indicatorspecies the need for a flexible asymmetrical approachrdquo EcologyMonography vol 67 pp 777ndash795 1997

[42] J E PeckMultivariate Analysis for Community Ecologists Step-by-Step using PC-ORD MjM Software Design Gleneden BeachOre USA 2010

[43] M A Njana Arborescent species diversity and stocking inMiombo Woodland of Urumwa forest reserve and their contri-bution to Livelihoods Tabora Tanzania [MS thesis] SokoineUniversity of Agriculture Morogoro Tanzania 2008

[44] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal no 200 pp 59ndash70 2004

[45] J Isango ldquoStand structure and tree species composition ofTanzania miombo woodlands a case study from miombowoodlands of community based forest management in Iringadistrictrdquo in MITMIOMBOmdashManagement of Indigenous TreeSpecies For EcosystemRestoration andWood Production in Semi-Arid Miombo Woodlands in Eastern Africa Proceedings ofthe 1st MITMIOMBO Project Workshop held in MorogoroTanzania 6th-12th February 2007 Working Papers of theFinnish Forest Research Institute no 50 pp 43ndash56 2007

[46] J R Landon Booker Tropical Soil Manual A Handbook ForSoil Survey and Agricultural Land Evaluation in the Tropics andSubtropics Longman Scientific amp Technical and John Wiley ampSons 1991

[47] R F Fisher and D Binkley Ecology and Management of ForestSoils John Wiley amp Sons 3rd edition 2000

[48] W A Rees ldquoPreliminary studies into bush utilization by Cattlein Zambiardquo Journal of Applied Ecology vol 11 pp 207ndash214 1974

[49] S M Philip Measuring Trees and Forests CAB InternationalWallingford UK 2nd edition 1994

[50] J D Lowore P G Abbot and M Werren ldquoStackwood volumeestimations formiombowoodlands inMalawirdquoCommonwealthForestry Review vol 73 no 3 pp 193ndash197 1994

[51] D Kubota T Masunaga Hermansah et al ldquoSoil environmentand tree species diversity in tropical rain forest West SumatraIndonesiardquo in Soils of Tropical Forest Ecosystems CharacteristicsEcology and Management A Schulte and D Ruhiyat Eds pp159ndash167 1998

[52] P K T Munishi T H Shear T Wentworth and R A PC Temu ldquoCompositional gradients of plant communities insubmontane rainforests of EasternTanzaniardquo Journal of TropicalForest Science vol 19 no 1 pp 35ndash45 2007

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

EcosystemsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MeteorologyAdvances in

EcologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Marine BiologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental Chemistry

Atmospheric SciencesInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Geological ResearchJournal of

EarthquakesJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BiodiversityInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

Page 13: Research Article Floristic Composition, Structure, and

ISRN Biodiversity 13

(range 7ndash19) for top soil (0ndash15 cm) and 11 plusmn 036 (range 5ndash16) for subsoil (15ndash30 cm) In general the values for both soilstrata fall within the expected range of 8ndash17 Soil pH values(mean 67 plusmn 01 range 567ndash852)were alsowithin the optimalrangewhere all the nutrients that aremost important for plantgrowth (Ca Mg K and P) are available and accessible toplants [46] In this study 97 of the soil samples had pHbelow 8 (one sample had a pH of 852) Fisher and Binkley[47] noted that high pH is almost never a problem in forestsas most trees do well across the full range of common pHvaluesTherefore considering the low average annual rainfallcompared to other forests the relatively high fertility of theGVLFR may be the main factor creating an environmentfavourable to many species thus leading to a quite highspecies diversity observed in this forest

Based on the Importance Value Index Brachystegia spi-ciformis and Combretum molle appeared to be the mostimportant species among harvested trees (stumps) in thestudy area This result agreed very well with the large valuesof basal area and volume and the information obtained fromlocal scouts and members of the village environmental com-mittee who said that the most frequently harvested speciesfor charcoal making include all Brachystegia species found inthe forest (ie Brachystegia spiciformis Brachystegia mangaBrachystegia boehmii and Brachystegia bussei) Among theCombretum species the most important one (based on IVI)Combretum molle is mostly used for house construction andfirewood rather than for charcoal making Apart from theBrachystegia species the only other species mentioned asimportant for charcoal making was Acacia mellifera Otherspecies are only used in case they happen to fall when fellingthe preferred species during the preparation of charcoal kilnsWith respect to stumps Brachystegia spiciformis Brachystegiamanga and Combretum molle are among the ten mostabundant species in terms of density basal area and volumeper hectare Stumps of the other species mentioned are notcommonly found a factwhichmay be due to the small samplesize being unable to capture sites where these species areharvested but may also be related to their limited distributionin the forest as indicated by the estimated dispersion indices(see Table 1)

42 Forest Structure Species densities reported from otherMiombo woodland areas in Tanzania are typically 348ndash1495stemsha for trees with Dbh gt4 cm [24 43 45] Comparedwith this the GVLFR is highly stocked as the estimateddensity is 2296 stemsha for trees with Dbh gt4 cmThemeanstem density of 1521 plusmn 594ha for trees with Dbh ge5 cmis also more than twice as large as values found in otherstudies [25ndash27 44 45 48] A similar pattern is seen whencomparing the density of regeneration between the studiesThe diameter distribution is characterised by a very cleartrend of decreasing stem density with increasing diameterThe shape of the distribution is thus an inverted ldquoJrdquo (Figure 3)which is a common feature of natural forests with activeregeneration and recruitment [49] However not many largetrees were captured by the sample whereas a considerablenumber of relatively large stumps were observed suggestingthat anthropogenic activities such as charcoal making may

have affected the structure and ecological balance of the forest(see Figure 3) Since the woodlands are often hit by fire whichtends to kill the seedlings (especially the late fires) and thusonly few seedlings can be expected to reach larger diameterclasses lack of mature trees and the resulting lack of seedsmay eventually threaten the biodiversity of the forest

The mean basal area of 1355 plusmn 552m2ha observedin this study is slightly above the range of values typicallyreported from the miombo region 75ndash126m2ha [26 28 4344 50] However the basal areas reported by Isango [45] werea bit higher (1504ndash1563m2ha) than observed in this study

Themean total volume inGVLFRwas estimated at 9217plusmn390m3ha for trees with Dbh ge5 cm Other studies in dryMiombo woodlands have reported mean volumes of 167ndash7603m3ha [24 44 45 50] The current standing volume ofGVLFR is thus slightly higher than values typically reportedfor forests in the Miombo ecoregion A plausible reason forthis may be that compared to other forests the GVLFR isstill well stocked despite ongoing human activities such ascharcoalmakingThebasal area observed for stumpswas only072m2ha so there is no indication of intensive extractionover many years This corresponds well with the findings ofTreue et al [20] who conclude that the estimated 04m3haannual extraction of woody biomass from GVLFR is consid-erably below its estimated annual increment of 15m3ha andthat the local forest managers seem capable of regulating theharvesting activities which in addition to village membersrsquocollection for subsistence uses also included commercialcharcoal production by external companies that pay a fee perbag of charcoal extracted to the village government

43 Plant Communities and Species Associations Except forBrachystegia spiciformis the majority of the Brachystegia andJulbernardia species that are common to miombo wood-lands elsewhere are not among the species most commonlyobserved in this study A similar pattern was observed byBanda et al [26] in the Katavi-Rukwa ecosystem wherethe genera that are most common in miombo woodlandsBrachystegia Julbernardia and Isoberlinia were not commonin their study sites Furthermore the four plant communi-ties distinguished in this study are comparable with thosereported by other studies in Tanzania including the work byMunishi et al [29] in theMiombowoodlands of Rukwa basinChunya district Tanzania and the study by Banda et al [26]in the Katavi-Rukwa ecosystem

Elevation was noted by Munishi et al [29] to be themost important factor shaping the species communities intheir study area This study found a similar pattern with thehighest coefficient of correlation observed for elevation sug-gesting that topographical variation is among the strongestdeterminants of community composition in dry Miombowoodlands hence influencing the spatial distribution ofspecies strongly However in our study area edaphic factorsalso influenced the species distribution directly Two plantcommunities occurredmainly on clayey soils with high pH atintermediate elevations one on sandy soils with lowpHat lowelevations and one on sandy-clayey soils at higher elevationsand with neutral soil pH (Figure 5) Specifically it appeared

14 ISRN Biodiversity

that the Acacia woodland category (Community 5) grows atlow elevations around temporary streams (or at least wherethe ground water table is relatively high) and the Bauhiniawoodland category (Community 24) appearsmostly in placeswith a relatively high percentage of clay (and therefore highvalues of pH Ca and BS) By contrast it appeared that theDalbergia woodland category (Community 3) is located atmore sandy sites (with low values of pH Ca and BS) andthe Brachystegia woodland category (Community 1) seemedto be located mostly at higher elevations where the CN-ratio is quite high Correlations between elevation and thebasic soil variables pH Ca and percentages of sand andclay were low (cf Figure 5) Thus the results indicate thatthe plant communities of the dry miombo woodlands inGVLFR are not only shaped by the topographic variation(elevation) and the groundwater level but also by basic soilcharacteristics The results thus confirm findings from otherstudies detecting effects of elevation and soil characteristicson species composition [51 52]

5 Conclusion

Considering that the sample size used in this study wassmaller than samples used in other studies in dry miombowoodlands the results show that the species diversity inGVLFR is relatively high compared to other forest reservesThe vegetation of GVLFR is characterised by high densitybasal area and volume and despite the scarcity of largediameter trees this indicates that the forest is in a goodcondition The effect of anthropogenic activities is neverthe-less evident and stresses the need for proper managementespecially for economically important species preferred forcharcoalmaking (egBrachystegia spiciformis) if the currentspecies diversity is to be maintained or enhanced A repeatedfuture study would be needed to assess whether the currentcommunity-based management regime yields this intendedoutcome but the available information and analyses allow forsome optimism in this respect

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors wish to thank people from Mfyome villagefor their invaluable assistance during field work Mzee IddiKaheya Damian Chotamasege AugustinoMkwama Libera-tus Simime and Mawazo Nyangwa Furthermore thanks aredue to Venancia Mlelwa from Sokoine University and MadsMadsen Krag from University of Copenhagen for doing thelaboratory work The authors also wish to thank GoodluckMoshi their driverMarcoNjana andNassoroHMagogo theTAFORI botanist for assisting with species identification andKlaus Dons for preparing a study site map Financial supportwas provided by Danida through the ENRECA Project

ldquoParticipatory forest management for rural livelihoods forestconservation and good governance in Tanzaniardquo (no 725)

References

[1] P G H Frost ldquoThe Ecology of Miombo Woodlandsrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 11ndash57 1996

[2] N Burgess J Hales E Underwood et al Terrestrial Ecoregionsof Africa and Madagascar A Conservation Assessment IslandPress World Wildlife Fund 2004

[3] J Clarke W Cavendish and C Coote ldquoRural householdsand miombo woodlands use value and managementrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 101ndash135 1996

[4] B M Campbell A Angelsen A Cunningham Y KaterereA Sitoe and S Wunder ldquoMiombo woodlandsmdashopportunitiesand barriers to sustainable forest managementrdquo httpsener-gypediainfoimages66dMiombo2007pdf

[5] S Syampungani P W Chirwa F K Akinnifesi G Sileshi andO C Ajayi ldquoTheMiombo woodlands at the cross roads poten-tial threats sustainable livelihoods policy gaps and challengesrdquoNatural Resources Forum vol 33 no 2 pp 150ndash159 2009

[6] J I O Abbot and K Homewood ldquoA history of change causesof miombo woodland decline in a protected area in MalawirdquoJournal of Applied Ecology vol 36 no 3 pp 422ndash433 1999

[7] E J Luoga E T F Witkowski and K Balkwill ldquoLand coverand use changes in relation to the institutional frameworkand tenure of land and resources in eastern Tanzania Miombowoodlandsrdquo Environment Development and Sustainability vol7 no 1 pp 71ndash93 2005

[8] FAO The State of Food and Agriculture 2010-2011 Forest andAgriculture Organization Rome Italy 2010

[9] A H Gentry ldquoTropical forest biodiversity distributional pat-terns and their conservational significancerdquo Oikos vol 63 no1 pp 19ndash28 1992

[10] O E Sala F S Chapin III J J Armesto et al ldquoGlobalbiodiversity scenarios for the year 2100rdquo Science vol 287 no5459 pp 1770ndash1774 2000

[11] H J Geist and E F Lambin ldquoProximate causes and underlyingdriving forces of tropical deforestationrdquo BioScience vol 52 no2 pp 143ndash150 2002

[12] R S DeFries ldquoTropical forests deforestation and ecosystemsservices Contributions of remote sensingrdquo in GeoinformaticsFor Tropical Ecosystems P S Roy Ed pp 1ndash32 2003

[13] B M Campbell P Frost and N Bryon ldquoMiombo woodlandsand their use overview and key issuesrdquo in The Miombo inTransition Woodlands and Welfare in Africa B Campbell Edpp 1ndash10 2006

[14] H J Geist ldquoGlobal assessment of deforestation related totobacco farmingrdquo Tobacco Control vol 8 no 1 pp 18ndash28 1999

[15] J Sauer and J M Abdallah ldquoForest diversity tobacco produc-tion and resource management in Tanzaniardquo Forest Policy andEconomics vol 9 no 5 pp 421ndash439 2007

[16] E N Chidumayo and K J Mbata ldquoShifting cultivation ediblecaterpillars and livelihoods in the Kopa area of northernZambiardquo Forests Trees and Livelihoods vol 12 no 3 pp 175ndash1932002

[17] E N Chidumayo and L Kwibisa ldquoEffects of deforestation ongrass biomass and soil nutrient status in miombo woodlandZambiardquo Agriculture Ecosystems and Environment vol 96 no1ndash3 pp 97ndash105 2003

ISRN Biodiversity 15

[18] J F Lund and T Treue ldquoAre we getting there Evidence ofdecentralized forest management from the Tanzanian miombowoodlandsrdquoWorld Development vol 36 no 12 pp 2780ndash28002008

[19] T Blomley and S Iddi Participatory Forest Management inTanzania 1993ndash2009mdashLessons Learned and Experiences toDate Ministry of Natural Resources and Tourism Forestry andBeekeeping Division Dar es Salaam Tanzania 2009

[20] T Treue Y M Ngaga H Meilby et al ldquoDoes participatoryforest management promote sustainable forest utilisation inTanzaniardquo International Forestry Review vol 16 no 1 pp 1ndash162014

[21] Ministry ofNatural Resources andTourismParticipatory ForestManagement in Tanzania Facts and Figures Forestry andBeekeeping Division Dar es Salaam Tanzania 2008

[22] E N Chidumayo ldquoSpecies structure in Zambian miombowoodlandrdquo Journal of Tropical Ecology vol 3 no 2 pp 109ndash1181987

[23] J D Lowore ldquoCoppice regeneration in some miombo wood-lands of Malawirdquo FRIM Report 99001 Forestry ResearchInstitute of Malawi 1999

[24] E J Luoga E T F Witkowski and K Balkwill ldquoHarvestedand standing wood stocks in protected and communal miombowoodlands of eastern Tanzaniardquo Forest Ecology and Manage-ment vol 164 no 1ndash3 pp 15ndash30 2002

[25] M Williams C M Ryan R M Rees E Sambane J Fernandoand J Grace ldquoCarbon sequestration and biodiversity of re-growing miombo woodlands in Mozambiquerdquo Forest Ecologyand Management vol 254 no 2 pp 145ndash155 2008

[26] T Banda NMwangulango BMeyer et al ldquoThewoodland veg-etation of the Katavi-Rukwa ecosystem in western TanzaniardquoForest Ecology andManagement vol 255 no 8-9 pp 3382ndash33952008

[27] R A Giliba E K Boon C J Kayombo E B Musamba AM Kashindye and P F Shayo ldquoSpecies composition richnessand diversity in Miombo Woodland of Bereku Forest ReserveTanzaniardquo Journal of Biodiversity vol 2 no 1 pp 1ndash7 2011

[28] D D Shirima P K T Munishi S L Lewis et al ldquoCarbonstorage structure and composition of miombo woodlands inTanzaniarsquos Eastern Arc Mountainsrdquo African Journal of Ecologyvol 49 no 3 pp 332ndash342 2011

[29] P K T Munishi R A P C Temu and G Soka ldquoPlant com-munities and tree species associations in a Miombo ecosystemin the Lake Rukwa basin Southern Tanzania implications forconservationrdquo Journal of Ecology and Natural Environment vol3 no 2 pp 63ndash71 2011

[30] J Dewis and F Freitas ldquoPhysical analysis of soilsrdquo in Physicaland Chemical Methods of Soil andWater Analysis FAO Bulletinno 10 pp 51ndash57 2nd edition 1970

[31] S R Olsen and L E Sommers ldquoPhosphorusrdquo inMethods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 403ndash430 American Societyof Agronomy Madson Wis USA 1982

[32] J D Rhoades ldquoCation exchange capacityrdquo in Methods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 149ndash157 American Society ofAgronomy Madson Wis USA 1982

[33] IMatejovic ldquoDetermination of carbon hydrogen and nitrogenin soils by automated elemental analysis (dry combustionmethod)rdquo Communications in Soil Science and Plant Analysisvol 24 no 17-18 pp 2213ndash2222 1993

[34] J P Moslashberg Soil Analysis Manual Revised Edition Laboratoryof Soil Sciences Department of Soil Science SokoineUniversityof Agriculture Morogoro Tanzania 2001

[35] N C BradyThe Nature and Properties of Soils Macmillan 8thedition 1974

[36] C J Krebs Ecological Methodology Hamper Collins PublishersNew York NY USA 2nd edition 1999

[37] B Husch T W Beers and J A Kershaw Forest MensurationJohn Wiley amp Sons Hoboken NJ USA 4th edition 2003

[38] E E Mwakalukwa H Meilby and T Treue ldquoVolume andaboveground biomass models for dry Miombo Woodland inTanzaniardquo In press

[39] M Kent Vegetation Description and Analysis A PracticalApproach Wiley-Blackwell John Wiley amp Sons Hoboken NJUSA 2nd edition 2012

[40] B McCune and M J Mefford PC-ORD Multivariate Analysisof Ecological Data Version 6 MjM Software Gleneden BeachOre USA 2011

[41] MDufrene andP Legendre ldquoSpecies assemblages and indicatorspecies the need for a flexible asymmetrical approachrdquo EcologyMonography vol 67 pp 777ndash795 1997

[42] J E PeckMultivariate Analysis for Community Ecologists Step-by-Step using PC-ORD MjM Software Design Gleneden BeachOre USA 2010

[43] M A Njana Arborescent species diversity and stocking inMiombo Woodland of Urumwa forest reserve and their contri-bution to Livelihoods Tabora Tanzania [MS thesis] SokoineUniversity of Agriculture Morogoro Tanzania 2008

[44] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal no 200 pp 59ndash70 2004

[45] J Isango ldquoStand structure and tree species composition ofTanzania miombo woodlands a case study from miombowoodlands of community based forest management in Iringadistrictrdquo in MITMIOMBOmdashManagement of Indigenous TreeSpecies For EcosystemRestoration andWood Production in Semi-Arid Miombo Woodlands in Eastern Africa Proceedings ofthe 1st MITMIOMBO Project Workshop held in MorogoroTanzania 6th-12th February 2007 Working Papers of theFinnish Forest Research Institute no 50 pp 43ndash56 2007

[46] J R Landon Booker Tropical Soil Manual A Handbook ForSoil Survey and Agricultural Land Evaluation in the Tropics andSubtropics Longman Scientific amp Technical and John Wiley ampSons 1991

[47] R F Fisher and D Binkley Ecology and Management of ForestSoils John Wiley amp Sons 3rd edition 2000

[48] W A Rees ldquoPreliminary studies into bush utilization by Cattlein Zambiardquo Journal of Applied Ecology vol 11 pp 207ndash214 1974

[49] S M Philip Measuring Trees and Forests CAB InternationalWallingford UK 2nd edition 1994

[50] J D Lowore P G Abbot and M Werren ldquoStackwood volumeestimations formiombowoodlands inMalawirdquoCommonwealthForestry Review vol 73 no 3 pp 193ndash197 1994

[51] D Kubota T Masunaga Hermansah et al ldquoSoil environmentand tree species diversity in tropical rain forest West SumatraIndonesiardquo in Soils of Tropical Forest Ecosystems CharacteristicsEcology and Management A Schulte and D Ruhiyat Eds pp159ndash167 1998

[52] P K T Munishi T H Shear T Wentworth and R A PC Temu ldquoCompositional gradients of plant communities insubmontane rainforests of EasternTanzaniardquo Journal of TropicalForest Science vol 19 no 1 pp 35ndash45 2007

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

EcosystemsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MeteorologyAdvances in

EcologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Marine BiologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental Chemistry

Atmospheric SciencesInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Geological ResearchJournal of

EarthquakesJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BiodiversityInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

Page 14: Research Article Floristic Composition, Structure, and

14 ISRN Biodiversity

that the Acacia woodland category (Community 5) grows atlow elevations around temporary streams (or at least wherethe ground water table is relatively high) and the Bauhiniawoodland category (Community 24) appearsmostly in placeswith a relatively high percentage of clay (and therefore highvalues of pH Ca and BS) By contrast it appeared that theDalbergia woodland category (Community 3) is located atmore sandy sites (with low values of pH Ca and BS) andthe Brachystegia woodland category (Community 1) seemedto be located mostly at higher elevations where the CN-ratio is quite high Correlations between elevation and thebasic soil variables pH Ca and percentages of sand andclay were low (cf Figure 5) Thus the results indicate thatthe plant communities of the dry miombo woodlands inGVLFR are not only shaped by the topographic variation(elevation) and the groundwater level but also by basic soilcharacteristics The results thus confirm findings from otherstudies detecting effects of elevation and soil characteristicson species composition [51 52]

5 Conclusion

Considering that the sample size used in this study wassmaller than samples used in other studies in dry miombowoodlands the results show that the species diversity inGVLFR is relatively high compared to other forest reservesThe vegetation of GVLFR is characterised by high densitybasal area and volume and despite the scarcity of largediameter trees this indicates that the forest is in a goodcondition The effect of anthropogenic activities is neverthe-less evident and stresses the need for proper managementespecially for economically important species preferred forcharcoalmaking (egBrachystegia spiciformis) if the currentspecies diversity is to be maintained or enhanced A repeatedfuture study would be needed to assess whether the currentcommunity-based management regime yields this intendedoutcome but the available information and analyses allow forsome optimism in this respect

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors wish to thank people from Mfyome villagefor their invaluable assistance during field work Mzee IddiKaheya Damian Chotamasege AugustinoMkwama Libera-tus Simime and Mawazo Nyangwa Furthermore thanks aredue to Venancia Mlelwa from Sokoine University and MadsMadsen Krag from University of Copenhagen for doing thelaboratory work The authors also wish to thank GoodluckMoshi their driverMarcoNjana andNassoroHMagogo theTAFORI botanist for assisting with species identification andKlaus Dons for preparing a study site map Financial supportwas provided by Danida through the ENRECA Project

ldquoParticipatory forest management for rural livelihoods forestconservation and good governance in Tanzaniardquo (no 725)

References

[1] P G H Frost ldquoThe Ecology of Miombo Woodlandsrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 11ndash57 1996

[2] N Burgess J Hales E Underwood et al Terrestrial Ecoregionsof Africa and Madagascar A Conservation Assessment IslandPress World Wildlife Fund 2004

[3] J Clarke W Cavendish and C Coote ldquoRural householdsand miombo woodlands use value and managementrdquo in TheMiombo in Transition Woodlands and Welfare in Africa BCampbell Ed pp 101ndash135 1996

[4] B M Campbell A Angelsen A Cunningham Y KaterereA Sitoe and S Wunder ldquoMiombo woodlandsmdashopportunitiesand barriers to sustainable forest managementrdquo httpsener-gypediainfoimages66dMiombo2007pdf

[5] S Syampungani P W Chirwa F K Akinnifesi G Sileshi andO C Ajayi ldquoTheMiombo woodlands at the cross roads poten-tial threats sustainable livelihoods policy gaps and challengesrdquoNatural Resources Forum vol 33 no 2 pp 150ndash159 2009

[6] J I O Abbot and K Homewood ldquoA history of change causesof miombo woodland decline in a protected area in MalawirdquoJournal of Applied Ecology vol 36 no 3 pp 422ndash433 1999

[7] E J Luoga E T F Witkowski and K Balkwill ldquoLand coverand use changes in relation to the institutional frameworkand tenure of land and resources in eastern Tanzania Miombowoodlandsrdquo Environment Development and Sustainability vol7 no 1 pp 71ndash93 2005

[8] FAO The State of Food and Agriculture 2010-2011 Forest andAgriculture Organization Rome Italy 2010

[9] A H Gentry ldquoTropical forest biodiversity distributional pat-terns and their conservational significancerdquo Oikos vol 63 no1 pp 19ndash28 1992

[10] O E Sala F S Chapin III J J Armesto et al ldquoGlobalbiodiversity scenarios for the year 2100rdquo Science vol 287 no5459 pp 1770ndash1774 2000

[11] H J Geist and E F Lambin ldquoProximate causes and underlyingdriving forces of tropical deforestationrdquo BioScience vol 52 no2 pp 143ndash150 2002

[12] R S DeFries ldquoTropical forests deforestation and ecosystemsservices Contributions of remote sensingrdquo in GeoinformaticsFor Tropical Ecosystems P S Roy Ed pp 1ndash32 2003

[13] B M Campbell P Frost and N Bryon ldquoMiombo woodlandsand their use overview and key issuesrdquo in The Miombo inTransition Woodlands and Welfare in Africa B Campbell Edpp 1ndash10 2006

[14] H J Geist ldquoGlobal assessment of deforestation related totobacco farmingrdquo Tobacco Control vol 8 no 1 pp 18ndash28 1999

[15] J Sauer and J M Abdallah ldquoForest diversity tobacco produc-tion and resource management in Tanzaniardquo Forest Policy andEconomics vol 9 no 5 pp 421ndash439 2007

[16] E N Chidumayo and K J Mbata ldquoShifting cultivation ediblecaterpillars and livelihoods in the Kopa area of northernZambiardquo Forests Trees and Livelihoods vol 12 no 3 pp 175ndash1932002

[17] E N Chidumayo and L Kwibisa ldquoEffects of deforestation ongrass biomass and soil nutrient status in miombo woodlandZambiardquo Agriculture Ecosystems and Environment vol 96 no1ndash3 pp 97ndash105 2003

ISRN Biodiversity 15

[18] J F Lund and T Treue ldquoAre we getting there Evidence ofdecentralized forest management from the Tanzanian miombowoodlandsrdquoWorld Development vol 36 no 12 pp 2780ndash28002008

[19] T Blomley and S Iddi Participatory Forest Management inTanzania 1993ndash2009mdashLessons Learned and Experiences toDate Ministry of Natural Resources and Tourism Forestry andBeekeeping Division Dar es Salaam Tanzania 2009

[20] T Treue Y M Ngaga H Meilby et al ldquoDoes participatoryforest management promote sustainable forest utilisation inTanzaniardquo International Forestry Review vol 16 no 1 pp 1ndash162014

[21] Ministry ofNatural Resources andTourismParticipatory ForestManagement in Tanzania Facts and Figures Forestry andBeekeeping Division Dar es Salaam Tanzania 2008

[22] E N Chidumayo ldquoSpecies structure in Zambian miombowoodlandrdquo Journal of Tropical Ecology vol 3 no 2 pp 109ndash1181987

[23] J D Lowore ldquoCoppice regeneration in some miombo wood-lands of Malawirdquo FRIM Report 99001 Forestry ResearchInstitute of Malawi 1999

[24] E J Luoga E T F Witkowski and K Balkwill ldquoHarvestedand standing wood stocks in protected and communal miombowoodlands of eastern Tanzaniardquo Forest Ecology and Manage-ment vol 164 no 1ndash3 pp 15ndash30 2002

[25] M Williams C M Ryan R M Rees E Sambane J Fernandoand J Grace ldquoCarbon sequestration and biodiversity of re-growing miombo woodlands in Mozambiquerdquo Forest Ecologyand Management vol 254 no 2 pp 145ndash155 2008

[26] T Banda NMwangulango BMeyer et al ldquoThewoodland veg-etation of the Katavi-Rukwa ecosystem in western TanzaniardquoForest Ecology andManagement vol 255 no 8-9 pp 3382ndash33952008

[27] R A Giliba E K Boon C J Kayombo E B Musamba AM Kashindye and P F Shayo ldquoSpecies composition richnessand diversity in Miombo Woodland of Bereku Forest ReserveTanzaniardquo Journal of Biodiversity vol 2 no 1 pp 1ndash7 2011

[28] D D Shirima P K T Munishi S L Lewis et al ldquoCarbonstorage structure and composition of miombo woodlands inTanzaniarsquos Eastern Arc Mountainsrdquo African Journal of Ecologyvol 49 no 3 pp 332ndash342 2011

[29] P K T Munishi R A P C Temu and G Soka ldquoPlant com-munities and tree species associations in a Miombo ecosystemin the Lake Rukwa basin Southern Tanzania implications forconservationrdquo Journal of Ecology and Natural Environment vol3 no 2 pp 63ndash71 2011

[30] J Dewis and F Freitas ldquoPhysical analysis of soilsrdquo in Physicaland Chemical Methods of Soil andWater Analysis FAO Bulletinno 10 pp 51ndash57 2nd edition 1970

[31] S R Olsen and L E Sommers ldquoPhosphorusrdquo inMethods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 403ndash430 American Societyof Agronomy Madson Wis USA 1982

[32] J D Rhoades ldquoCation exchange capacityrdquo in Methods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 149ndash157 American Society ofAgronomy Madson Wis USA 1982

[33] IMatejovic ldquoDetermination of carbon hydrogen and nitrogenin soils by automated elemental analysis (dry combustionmethod)rdquo Communications in Soil Science and Plant Analysisvol 24 no 17-18 pp 2213ndash2222 1993

[34] J P Moslashberg Soil Analysis Manual Revised Edition Laboratoryof Soil Sciences Department of Soil Science SokoineUniversityof Agriculture Morogoro Tanzania 2001

[35] N C BradyThe Nature and Properties of Soils Macmillan 8thedition 1974

[36] C J Krebs Ecological Methodology Hamper Collins PublishersNew York NY USA 2nd edition 1999

[37] B Husch T W Beers and J A Kershaw Forest MensurationJohn Wiley amp Sons Hoboken NJ USA 4th edition 2003

[38] E E Mwakalukwa H Meilby and T Treue ldquoVolume andaboveground biomass models for dry Miombo Woodland inTanzaniardquo In press

[39] M Kent Vegetation Description and Analysis A PracticalApproach Wiley-Blackwell John Wiley amp Sons Hoboken NJUSA 2nd edition 2012

[40] B McCune and M J Mefford PC-ORD Multivariate Analysisof Ecological Data Version 6 MjM Software Gleneden BeachOre USA 2011

[41] MDufrene andP Legendre ldquoSpecies assemblages and indicatorspecies the need for a flexible asymmetrical approachrdquo EcologyMonography vol 67 pp 777ndash795 1997

[42] J E PeckMultivariate Analysis for Community Ecologists Step-by-Step using PC-ORD MjM Software Design Gleneden BeachOre USA 2010

[43] M A Njana Arborescent species diversity and stocking inMiombo Woodland of Urumwa forest reserve and their contri-bution to Livelihoods Tabora Tanzania [MS thesis] SokoineUniversity of Agriculture Morogoro Tanzania 2008

[44] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal no 200 pp 59ndash70 2004

[45] J Isango ldquoStand structure and tree species composition ofTanzania miombo woodlands a case study from miombowoodlands of community based forest management in Iringadistrictrdquo in MITMIOMBOmdashManagement of Indigenous TreeSpecies For EcosystemRestoration andWood Production in Semi-Arid Miombo Woodlands in Eastern Africa Proceedings ofthe 1st MITMIOMBO Project Workshop held in MorogoroTanzania 6th-12th February 2007 Working Papers of theFinnish Forest Research Institute no 50 pp 43ndash56 2007

[46] J R Landon Booker Tropical Soil Manual A Handbook ForSoil Survey and Agricultural Land Evaluation in the Tropics andSubtropics Longman Scientific amp Technical and John Wiley ampSons 1991

[47] R F Fisher and D Binkley Ecology and Management of ForestSoils John Wiley amp Sons 3rd edition 2000

[48] W A Rees ldquoPreliminary studies into bush utilization by Cattlein Zambiardquo Journal of Applied Ecology vol 11 pp 207ndash214 1974

[49] S M Philip Measuring Trees and Forests CAB InternationalWallingford UK 2nd edition 1994

[50] J D Lowore P G Abbot and M Werren ldquoStackwood volumeestimations formiombowoodlands inMalawirdquoCommonwealthForestry Review vol 73 no 3 pp 193ndash197 1994

[51] D Kubota T Masunaga Hermansah et al ldquoSoil environmentand tree species diversity in tropical rain forest West SumatraIndonesiardquo in Soils of Tropical Forest Ecosystems CharacteristicsEcology and Management A Schulte and D Ruhiyat Eds pp159ndash167 1998

[52] P K T Munishi T H Shear T Wentworth and R A PC Temu ldquoCompositional gradients of plant communities insubmontane rainforests of EasternTanzaniardquo Journal of TropicalForest Science vol 19 no 1 pp 35ndash45 2007

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

EcosystemsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MeteorologyAdvances in

EcologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Marine BiologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental Chemistry

Atmospheric SciencesInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Geological ResearchJournal of

EarthquakesJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BiodiversityInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

Page 15: Research Article Floristic Composition, Structure, and

ISRN Biodiversity 15

[18] J F Lund and T Treue ldquoAre we getting there Evidence ofdecentralized forest management from the Tanzanian miombowoodlandsrdquoWorld Development vol 36 no 12 pp 2780ndash28002008

[19] T Blomley and S Iddi Participatory Forest Management inTanzania 1993ndash2009mdashLessons Learned and Experiences toDate Ministry of Natural Resources and Tourism Forestry andBeekeeping Division Dar es Salaam Tanzania 2009

[20] T Treue Y M Ngaga H Meilby et al ldquoDoes participatoryforest management promote sustainable forest utilisation inTanzaniardquo International Forestry Review vol 16 no 1 pp 1ndash162014

[21] Ministry ofNatural Resources andTourismParticipatory ForestManagement in Tanzania Facts and Figures Forestry andBeekeeping Division Dar es Salaam Tanzania 2008

[22] E N Chidumayo ldquoSpecies structure in Zambian miombowoodlandrdquo Journal of Tropical Ecology vol 3 no 2 pp 109ndash1181987

[23] J D Lowore ldquoCoppice regeneration in some miombo wood-lands of Malawirdquo FRIM Report 99001 Forestry ResearchInstitute of Malawi 1999

[24] E J Luoga E T F Witkowski and K Balkwill ldquoHarvestedand standing wood stocks in protected and communal miombowoodlands of eastern Tanzaniardquo Forest Ecology and Manage-ment vol 164 no 1ndash3 pp 15ndash30 2002

[25] M Williams C M Ryan R M Rees E Sambane J Fernandoand J Grace ldquoCarbon sequestration and biodiversity of re-growing miombo woodlands in Mozambiquerdquo Forest Ecologyand Management vol 254 no 2 pp 145ndash155 2008

[26] T Banda NMwangulango BMeyer et al ldquoThewoodland veg-etation of the Katavi-Rukwa ecosystem in western TanzaniardquoForest Ecology andManagement vol 255 no 8-9 pp 3382ndash33952008

[27] R A Giliba E K Boon C J Kayombo E B Musamba AM Kashindye and P F Shayo ldquoSpecies composition richnessand diversity in Miombo Woodland of Bereku Forest ReserveTanzaniardquo Journal of Biodiversity vol 2 no 1 pp 1ndash7 2011

[28] D D Shirima P K T Munishi S L Lewis et al ldquoCarbonstorage structure and composition of miombo woodlands inTanzaniarsquos Eastern Arc Mountainsrdquo African Journal of Ecologyvol 49 no 3 pp 332ndash342 2011

[29] P K T Munishi R A P C Temu and G Soka ldquoPlant com-munities and tree species associations in a Miombo ecosystemin the Lake Rukwa basin Southern Tanzania implications forconservationrdquo Journal of Ecology and Natural Environment vol3 no 2 pp 63ndash71 2011

[30] J Dewis and F Freitas ldquoPhysical analysis of soilsrdquo in Physicaland Chemical Methods of Soil andWater Analysis FAO Bulletinno 10 pp 51ndash57 2nd edition 1970

[31] S R Olsen and L E Sommers ldquoPhosphorusrdquo inMethods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 403ndash430 American Societyof Agronomy Madson Wis USA 1982

[32] J D Rhoades ldquoCation exchange capacityrdquo in Methods of SoilAnalysis Part 2 Agronomy Monograph No 9 A L Page R HMiller and P R Keeney Eds pp 149ndash157 American Society ofAgronomy Madson Wis USA 1982

[33] IMatejovic ldquoDetermination of carbon hydrogen and nitrogenin soils by automated elemental analysis (dry combustionmethod)rdquo Communications in Soil Science and Plant Analysisvol 24 no 17-18 pp 2213ndash2222 1993

[34] J P Moslashberg Soil Analysis Manual Revised Edition Laboratoryof Soil Sciences Department of Soil Science SokoineUniversityof Agriculture Morogoro Tanzania 2001

[35] N C BradyThe Nature and Properties of Soils Macmillan 8thedition 1974

[36] C J Krebs Ecological Methodology Hamper Collins PublishersNew York NY USA 2nd edition 1999

[37] B Husch T W Beers and J A Kershaw Forest MensurationJohn Wiley amp Sons Hoboken NJ USA 4th edition 2003

[38] E E Mwakalukwa H Meilby and T Treue ldquoVolume andaboveground biomass models for dry Miombo Woodland inTanzaniardquo In press

[39] M Kent Vegetation Description and Analysis A PracticalApproach Wiley-Blackwell John Wiley amp Sons Hoboken NJUSA 2nd edition 2012

[40] B McCune and M J Mefford PC-ORD Multivariate Analysisof Ecological Data Version 6 MjM Software Gleneden BeachOre USA 2011

[41] MDufrene andP Legendre ldquoSpecies assemblages and indicatorspecies the need for a flexible asymmetrical approachrdquo EcologyMonography vol 67 pp 777ndash795 1997

[42] J E PeckMultivariate Analysis for Community Ecologists Step-by-Step using PC-ORD MjM Software Design Gleneden BeachOre USA 2010

[43] M A Njana Arborescent species diversity and stocking inMiombo Woodland of Urumwa forest reserve and their contri-bution to Livelihoods Tabora Tanzania [MS thesis] SokoineUniversity of Agriculture Morogoro Tanzania 2008

[44] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal no 200 pp 59ndash70 2004

[45] J Isango ldquoStand structure and tree species composition ofTanzania miombo woodlands a case study from miombowoodlands of community based forest management in Iringadistrictrdquo in MITMIOMBOmdashManagement of Indigenous TreeSpecies For EcosystemRestoration andWood Production in Semi-Arid Miombo Woodlands in Eastern Africa Proceedings ofthe 1st MITMIOMBO Project Workshop held in MorogoroTanzania 6th-12th February 2007 Working Papers of theFinnish Forest Research Institute no 50 pp 43ndash56 2007

[46] J R Landon Booker Tropical Soil Manual A Handbook ForSoil Survey and Agricultural Land Evaluation in the Tropics andSubtropics Longman Scientific amp Technical and John Wiley ampSons 1991

[47] R F Fisher and D Binkley Ecology and Management of ForestSoils John Wiley amp Sons 3rd edition 2000

[48] W A Rees ldquoPreliminary studies into bush utilization by Cattlein Zambiardquo Journal of Applied Ecology vol 11 pp 207ndash214 1974

[49] S M Philip Measuring Trees and Forests CAB InternationalWallingford UK 2nd edition 1994

[50] J D Lowore P G Abbot and M Werren ldquoStackwood volumeestimations formiombowoodlands inMalawirdquoCommonwealthForestry Review vol 73 no 3 pp 193ndash197 1994

[51] D Kubota T Masunaga Hermansah et al ldquoSoil environmentand tree species diversity in tropical rain forest West SumatraIndonesiardquo in Soils of Tropical Forest Ecosystems CharacteristicsEcology and Management A Schulte and D Ruhiyat Eds pp159ndash167 1998

[52] P K T Munishi T H Shear T Wentworth and R A PC Temu ldquoCompositional gradients of plant communities insubmontane rainforests of EasternTanzaniardquo Journal of TropicalForest Science vol 19 no 1 pp 35ndash45 2007

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

EcosystemsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MeteorologyAdvances in

EcologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Marine BiologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental Chemistry

Atmospheric SciencesInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Geological ResearchJournal of

EarthquakesJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BiodiversityInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

Page 16: Research Article Floristic Composition, Structure, and

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

EcosystemsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MeteorologyAdvances in

EcologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Marine BiologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental Chemistry

Atmospheric SciencesInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Geological ResearchJournal of

EarthquakesJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BiodiversityInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of