trees on farms in bangladesh 5. growth of top- and

8/3/2019 Trees on Farms in Bangladesh 5. Growth of Top- And

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Trees on farms in Bangladesh: 5. Growth of top- androot-pruned trees in wetland rice fields and yields ofunderstory crops

DRAKE HOCKING1,* and KHAIRUL ISLAM21 Thrushes, Ridge Common Lane, Steep, UK GU32 1AL ; 2 Swiss Development Cooperation,

G.P.O. Box 928, Dhaka, Bangladesh (*Author for correspondence)

Key words: canopy pruning, cereals, pulses, root pruning, tree-crop competition, wheat

Abstract. Growth of trees and seasonal yields of understory crops were measured over a 5-

year period for 4 crops grown under 17 tree species at 8 8 m spacing in wetland rice fields.

All tree species grew well in rice fields, at rates comparable to their growth in forest planta-

tions. Top and root pruning reduced average tree girths by up to 19% and average tree volumesby up to 41%, depending on intensity of pruning. The crops monitored were Oryza sativa,

Triticum aestivum, Corchorus olotorius, andLens culinaris. Crop yields under the trees averaged

93% of the corresponding yields outside the tree canopy. The most important factor affecting

the yields of undercrops was tree size (height and/or girth). Differences among tree species and

the interaction with species of undercrops were not significant after controlling for tree size.

Pruning of roots and branches significantly improved crop yields under trees by amounts

proportional to the intensity of root or top pruning.

Introduction and background

Bangladesh agriculture is dominated by cultivation of wetland rice, with rice-

wheat rotations in the northwestern part. Farmers retain naturally-propagated

field trees of several species (Hocking and Islam, 1994), whose distributiondepends to a large degree on agroecological zone (Quddus et al., 1995).

Without systematic pruning of roots and branches, such trees cause yield

depression for the area under the trees ranging from 10% to about 50%

depending on tree species, tree size, crop season, and the availability of irri-

gation (Hocking, Sarwar and Yousuf, 1997). Farmers perceive that this loss

can be compensated for by the production of wood, fodder and fruits from

the trees so are content to continue the practice. But ways of reducing such

adverse effects of trees need to be explored.

Background to the Village and Farm Forestry Project (VFFP) was given

in Hocking and Islam (1994). The present report describes the main growth

parameters of the trees, and trends in seasonal yields of the main undercrops,

rice and wheat, with increasing tree sizes. Further details of tree growth are

separately reported (Hocking and Islam, 1997).

Crop performance under trees in wetland rice or rice-wheat farming systems

is not well-discussed in the literature. Articles often report the effects of trees

that are still immature and relatively small. A major difficulty in interpreta-

Agroforestry Systems 39: 101115, 1998. 1998 Kluwer Academic Publishers. Printed in the Netherlands.


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tion of conflicting or inconsistent results is the frequent lack of detailed and

complete information about the systems: tree species, size or age, spacing

and/or management, and sometimes crop details as well. These deficienciesare addressed in the present article.

Methods

The site locations and agroecological conditions are described in Hocking and

Islam (1994 and 1995). Trees were planted at a minimum spacing of 8 8 m

mainly on field margins and, where fields were more than 16 m wide, also

within the crop fields. Tree roots and branches were manually pruned to

different degrees of intensity, by the farmers following project advice.

Crop yield measurements

The crop yields underneath trees aged five to nine years were measured over

a period of five years from 1992 to 1995. The total sample for assessing crop

yields consisted of 424 records. Site variation was controlled by comparing

yields under the trees with crop yields in the same fields outside the zone of

influence of the trees. The main crop studied was rice, which is the dominant

monsoon season crop of the region. In Bangladesh, jute (Corchorus olotorius

and C capsularis) is also important; a few samples of C. olotorius were

included in the study. Post-monsoon crops studied included winter rice

(boro), wheat (Triticum aestivum), and pulses (mainly land races ofLens

culinaris).

Crop yields in Bangladesh are highly variable, being markedly affected by

different farmer practices and by seasons and years. To control for effect of

site variation, each sample from undersample trees was accompanied by amatching sample taken from the open field outside the tree canopy. Crop

samples consisted of 1 m2 plots, cut and bundled by hand. The under-tree

sample was located 0.5 m from the trunk of the tree and at a random location

around the circumference except for trees on or near field margins, where

the sample location was restricted to the area belonging to the owner of the

tree. The outside tree samples were cut from the open part of the same field

at a distance from the tree of at least twice the canopy diameter, where crop

yield is unaffected by the tree under these conditions (Hocking, Sarwar and

Yousuf, 1997). Sometimes this was not possible owing to the small size of

the field.

After harvesting, the samples were threshed, cleaned and winnowed by

hand using local procedures, usually with the help of the farmer and his/her

family. The weight (g) of grain (in the case of jute, weight of stems) was taken

with a calibrated spring balance. Moisture content (%) of the grain was

measured with a commercial grain moisture meter, calibrated daily. Samples

were then returned to the owner.

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At each observation date, it was noted whether the crop field was irrigated

or not. At the start of the study in 1986, 70% of fields had irrigation; by 1991

this had increased to 92% and by 1994 all fields in the study were irrigated.

Tree measurements

The tree growth data reported here are based on 5,482 observations of height

and girth at breast height (gbh) of trees of 17 species, planted during the period

19871990. Crop effects are often related to crown diameter of the trees,

which is itself correlated with trunk diameter or girth (Dawkins, 1963). Tree

girths were measured at breast height (1.3 m) (gbh) with a tape measure.

Tree heights to highest growing point were estimated to the nearest 0.1 m with

a Suunto optical hypsometer. The location of the tree within the field or on

the margin, and whether the tree was pruned or not and pruning intensity, were

also noted.

Degree of branch pruning was estimated visually on a scale of 14, where1 =


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Tree species: 17 species of different ages and sizes.

Tree location: within the field; or on the field margin

Tree size: by gbh and heightTree canopy management: 25-percentiles branches removed

Tree rooting intensity: root counts in sample trenches.

Agroecological zone (AEZ): 7 zones (UNDP/FAO, 1988)

Soil texture: silt, clay-loam, sandy-loam, red lateritic

Year: 1992 to 1995 inclusive.

Land elevation: (relative vulnerability to inundation)

high (almost never flooded)

medium-high (1530 cm water for short periods)

medium-low (1530 cm water for long periods)

NGO: the field-level cooperating partners to the VFFP

Analysis of data

Routine procedures were used for range and consistency checks and standard

tests were applied for extreme out-liers. Data were processed using the General

Linear Model of GENSTAT, Release 3.2. An initial series of analyses estab-

lished which factors were most important (alone and serially) to the response

variable, and these were included in the main model. Minor factors were then

tested individually and those significant at the 5% level of probability were

included. Data for some factor combinations such as rooting intensity were

available in fewer replications, so their significances were tested separately

using the same model with sequential sub-sets of the data.

The main response variable was crop yield under the trees as a percentage

of yield outside the trees. Independence of yield outside the tree from influ-

ences of the tree parameters was tested by analyzing the ratio (yield under

tree)/(yield outside tree) + (yield under tree); this analysis produced the sameset of significance tables as the simple ratio (yield under tree)/(yield outside

tree).

The influence of tree size (computed) was tested by analysis of the influ-

ence of observed gbh and height individually and in combination. The best

fit in the regression analysis was obtained with the log transformation of tree

volume, (gbh)2 height.

Results and discussion

Growth of trees

Average tree heights and girths by ages (all species) and by species (all ages)

are given in Table 1. Pruning the roots and/or the branches independently

reduced tree size for age in direct proportion to the intensity of pruning. Details

for individual species are published elsewhere (Hocking and Islam, 1997),

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because there were no significant tree species effects on yield of understory

crops (see below).

Crop yields outside the trees

The observed mean crop yields outside the trees, by crop species, are given

in Table 2.

To control for site variables, values for crop yield outside trees were tested

by analyzing the data for influence of site factors, and of tree factors after

controlling for site factors. The main site factors were (crop species) + (year)

105

Table 1. Mean heights and girths at breast height by age (all species) (A.) and species (all

ages) (B.) of sampled trees in northwestern Bangladesh, 19901995.

(A.) by tree ages (all species)

Age of trees (years)

3 4 5 6 7 8 All ages

Mean height (m) 004.7 06.3 07.7 08.9 09.1 10.5 007.4

St. dev. 000.8 00.7 00.6 01.0 01.2 01.5 000.9

Mean gbh (cm) 022.0 37.3 41.5 44.9 48.3 59.5 040.6

St. dev. 002.1 03.0 03.6 04.3 05.5 07.2 004.1

N 100 84 76 61 49 54 424

(B.) by tree species (all ages)

Tree species Mean Std Mean Std

height dev gbh dev

(m) (cm) N

Acacia auriculiformis 06.3 0.9 38 04.1 022

Acacia mangium 05.2 0.8 35 06.3 014

Acacia nilotica 05.9 1.2 30 09.1 100

Albizia procera 07.6 1.0 53 04.6 003

Albizia saman 06.2 1.1 41 05.4 023

Anthocephalus cadamba 07.6 1.3 58 05.5 007

Azadirachta indica 05.8 0.8 37 03.7 005

Cassia siamea 08.1 1.1 53 04.5 010

Dalbergia sissoo 06.7 1.3 40 04.7 012

Eucalyptus camaldulensis 13.7 1.6 59 16.8 100

Faidherbia albida 07.1 1.2 50 10.2 012

Gmelina arborea 06.8 0.7 43 09.1 010

Leucaeana leucocephala 07.0 1.3 39 12.3 006

Melia azederach 07.6 1.5 51 04.6 054

Swietenia mahogani 06.1 0.9 45 05.3 020Terminalia arjuna 08.3 1.2 48 05.7 020

Terminalia bellirica 04.9 0.7 37 04.4 003

Grand mean 08.5 44 424


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+ (AEZ) + (soil type) + (NGO), which together explained 52% of the variance.

Tree factors (height, gbh, roots, pruning) were not significant for crop yields

outside the trees after controlling for site variables.

Crop yields under the trees

Crop yields under the trees averaged 93% of the corresponding yields outside

the trees (Table 3). Differences among tree species were small and not

significant (P = 0.05) after controlling for tree size and other factors.

106

Table 2. Mean crop yields outside the trees, by crop species, for all years and sites associated

with various tree species in northwestern Bangladesh, 19901995.

Monsoon season (wet) Post-monsoon crops

Early Main Jute Irrigated Irrigated Unirrigated

rice rice rice wheat pulses

(aus) (aman) (boro)

Crop yields (kg/ha) 2080 2381 297 3420 1904 666

St. Dev. 0079 0075 041 0091 0072 056

N 0010 0265 004 0111 0023 011

Table 3. Crop yields under trees as percentages of yields outside trees, by tree species

(controlling for height); in northwestern Bangladesh, 19901995.

Tree species Mean Std dev N

crop yield

(%)

Acacia auriculiformis 090 17 022

Acacia mangium 099 09 014

Acacia nilotica 094 17 100

Albizia procera 101 10 003

Albizia saman 091 15 023

Anthocephalus cadamba 097 10 007

Azadirachta indica 093 06 005

Cassia siamea 102 12 010

Dalbergia sissoo 098 18 012

Eucalyptus camaldulensis 088 20 100

Faidherbia albida 095 09 012

Gmelina arborea 092 04 010

Leucaeana leucocephala 098 11 006

Melia azederach 089 14 054

Swietenia mahogani 092 09 020Terminalia arjuna 093 08 020

Terminalia bellirica 087 06 003

Grand mean 093 16 424


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Factors influencing crop yield under the trees

The main factors independently affecting the crop yield under trees as a

percentage of yields outside the trees were the size and species of the tree(Tables 4 and 5); after controlling for tree size, species became less signifi-

cant. The explanatory variables for the general model for the yield percentage

were (tree sp) + (height) + (ghb) + (soil type) + (NGO) + (roots). This model

explained 41% of the variance in crop yield percentage.

Agroecological zone (AEZ), soil texture, and NGO were almost inter-

changeable in the model, because each NGO operated in a relatively small

area comprising only one or a few AEZs and soils, and soil texture is itself

a major determinant of AEZ so differences were small and not statistically

significant (P = 0.05).

107

Table 4. Factors influencing the ratio of yield of crops under to outside the trees in northwestern

Bangladesh, 19901995; showing statistical significance.

Main effects

Tree-related factors Sole After When added

factor height to model

Height *** Included Model term

Girth ** *** Model term

Tree species *** * Model term

Rooting intensity NS * Model term

Tree age ** ** NS

Pruning intensity NS NS NS

Location margin or centre NS NS NS

Site factors Sole After When addedfactor NGO to model

NGO *** Included Model term

Soil type *** *** Model term

AEZ *** * NS

Year ** *** *

Crop species NS NS NS

Elevation NS NS NS

Two-way interactions Significance when

added to model

Tree sp year *

Tree sp height NS

Tree sp girth NSTree sp crop sp NS

Note: One, two or three asterisks indicate probability at the 5%, 1%, and 0.1% levels; NS means

non-significant.


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The relative elevation of the field was not a significant factor either,

possibly because differences (if any) attributable to elevation were alreadyreflected in the crop species being grown. Location of the trees on field

margins or within the fields was also not a significant factor for crop yields.

Availability of irrigation could not be tested because nearly all records were

for fields seasonally irrigated in the year of observation.

The effect of crop species and seasons

Differences in yield percentage under trees attributable to individual crop

species and seasons were small and not statistically significant overall,

although yield percentages under trees of post-monsoon crops (especially

pulses) were generally smaller than those of monsoon season crops (Table

6).

The smaller seasonal effect, in contrast to the large difference between

seasons found by Hocking, Sarwar and Yousuf (1997), may be accounted for

by the facts that all the fields in the current sample had irrigation, and most

of the trees had been managed by top and root pruning to some degree.

108

Table 5. Accumulated analysis of variance for factors influencing crop yields under trees in

northwestern Bangladesh, 19901995.

Change Degrees Variance Fof freedom ratio (probability)

+ tree height 001 17.83


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The effect of tree size

Tree height was the strongest predictor of crop yield percentage under trees

after controlling for AEZ and year. The regression equation was used to predictcrop yield percentages under trees for a smoothed series of tree heights and

girths (Table 7). Crop yield percentages associated with the tallest (25 m) trees

were 40% less than those associated with the shortest (5 m) trees. Tree girth

was also significant. For girth, crop yield percentages associated with the

fattest (140 cm girth) trees were 21% less than those associated with the

thinnest (20 cm) trees. Both associations were probably due to the much

larger shady canopy of the taller and fatter trees, even when averaged over

all pruning levels.

The effect of tree species

The influence of tree species on crop yield percentage under trees interacted

with tree size as there were large differences in mean size of the different

tree species. After controlling for tree size, differences in crop yield percentageunder different tree species were small and few were significant (Table 3

above). There was no striking pattern of influences that could be associated

with any particular group of tree species, such as nitrogen-fixing species.

The effects of branch and root pruning

After controlling for AEZ, year, and tree height, the effects of branch pruning

intensity and root intensity were significant at the 5% level of probability.

The more branches were pruned, the higher was the yield percentage under

the tree (Table 8A). Crop yields under trees pruned more than 50%, or under

pollarded trees, were not significantly different from yield outside the trees.

This suggests that light competition through shading was a major cause of

crop yield depression.

Numbers of roots found ranged from 0 to 144; the more roots were presentin the sampling trenches, the lower was the crop yield percentage under the

109

Table 7. Crop yield under trees as percentage of yield outside trees, in northwestern Bangladesh,

19901995; as predicted by tree height (A.) and tree girth (B.) (controlling for crop species,

AEZ, year, tree species; and gbh or height).

A. Tree height B. Tree girth

Tree Crop s.e. Tree Crop s.e.

height (m) yield (%) girth (cm) yield (%)

05 99 14 020 103 16

10 89 32 040 100 09

15 79 21 060 099 2220 69 23 080 096 31

25 59 37 100 091 37

120 087 28

140 082 51


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trees. For presentation of results, the model predictions are given on a log

scale of root numbers (Table 8B). The strong negative correlation of number

of roots with crop yield suggests important below-ground competition.

Combined effects of tree height and rooting intensity

The strongest predictors of crop yield percentage under trees after control-

ling for site variables were tree height and rooting intensity. It is instructive

to present these as combined effects in a single figure (Figure 1).

General discussion and conclusions

The main findings of this work were:

1. Most trees grew well in, or on the margins of, rice fields of northern

Bangladesh.

2. Yields of rice or wheat underneath such trees (including pruned ones)

averaged about 93% of yields outside the tree.

3. Tree size was the most important factor influencing crop yields under

trees.

4. Pruning of tops and roots of the trees improved the yield percentage of

undercrops compared to unpruned trees, by amounts proportionate to degree

of pruning. Top and root pruning also reduced growth of all tree species

proportionately.

5. Within the limits of the time frame of the experiment, the tree species was

unimportant to crop yields underneath.

110

Table 8. Crop yield under trees as percentage of yield outside trees, in northwestern Bangladesh,

19901995; as influenced byA. branch pruning; orB. Nos. of roots. (Means of all crop species,

all tree species, and all years.)

A. Effect of branch pruning B. Effect of numbers of roots

Pruning Crop Std. N Nos of Crop Std

intensity yield dev. roots yield dev.

(%) (%) (%)

75 *106 18 005 008 92 010

016 90 013

Mean 0*94 15 175 032 85 026

064 76 057

128 59 119

* This value is a mean of 5 records for Leucaena leucocephala only.

Note: Log scale for root numbers.


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In common with the present study, other authors report that trees signifi-

cantly depress yields of rice or wheat by amounts inversely related to distance

and directly related to age and presumably size of the trees (Dhukia et al.,1988; Keli-Zagbahi et al., 1990; Wahid Rashid et al., 1991; Khybri et al.,

1992; Khan and Ehrenreich, 1994; Puri et al., 1995). In other studies, trees

sometimes have no apparent effects on rice or wheat crops (Takeda, 1990;

Singhal and Panwar, 1991; Wu, 1996). The interaction of trees and undercrops

is clearly made up of complex biophysical elements that include benefits of

shelter (Huxley, 1993; Wu, 1996) and improvements in soil nutrient status

(Sae-Lee et al., 1992) as well as the negative effects of competition for light,

water, and/or nutrients (e.g. Sharma and Singh, 1992). Shading often appears

to be a dominant cause of adverse crop effects (Sae-Lee et al., 1992; Salazari

et al., 1993). Below-ground competition is more likely to be a contributing

factor where and when water and/or nutrients are in short supply (Singhal and

Panwar, 1991; Salazari et al., 1993).

Although crop yields often may be reduced, the value of the trees may com-

pensate or more than compensate (Wang and Shogren, 1992; ZL Jiang et al.,

1994; Wu, 1996). For many tree species, intermediate harvests of minor tree

products such as leaves and branches for fodder and domestic fuel alleviate

111

Figure 1. The effect of tree height and numbers of tree roots in sample trenches on the crop

yield under trees, expressed as a ratio of yield under trees to that in the open, in northwestern

Bangladesh, 1990 to 1995.


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current losses of undercrops. However, Khybri et al. (1992) found that net

income was less after 13 years for three combined tree/crop systems in

northern India, although annual harvests of branches were taken, than for purearable crops.

In the present study, the factors affecting the crop yield percentage under

trees were mainly tree-related, whereas crop yield outside the trees was influ-

enced mainly by site-related factors. Owing to small field sizes, some of the

larger trees unavoidably had an effect on the crop sampled from outside the

canopy but within the same field. But this effect on the outside sample was

small and became non-significant when controlled for crop yield ratio

(under/outside).

The effect on crop yield under pruned trees varied little among the different

tree species within the size and time limits of the present study, in contrast

to the differences in yield percentages observed under trees of different species

when not pruned (Hocking, Sarwar, and Yousuf, 1997). Tree size (height

and/or girth), and the degree of branch and root pruning, were the most impor-tant factors affecting yield ratio of undercrops. These observations support the

earlier inference that, in the monsoon season, competition for light is the

dominant influence whereas in the post-monsoon season, below-ground com-

petition enters the equation more strongly. These factors accounted for the

main variance in yield ratios, and there was no residual yield depression effects

that required attribution to other factors like allelopathy.

Independently of tree species, knowledge of the strong influence of tree

size offers farmers the management option of harvesting trees at a smaller

size. This would minimize the extent of crop yield depression and the period

over which it is suffered. Of course, a clear choice is subject to knowledge

of the relative prices of the crops and the tree products. The unit volume

price of wood increases with dimensions, so the trade-off with crop yield at

larger tree sizes is complex and subject to external variables.Root pruning and branch pruning, as recommended by the project, had

strong independent and combined effects on alleviating the yield depressing

effect even of big trees. But such pruning slows the growth of the trees

(Hocking and Islam, 1997). A better understanding of such trade-offs permits

farmers to make informed decisions on management. In the present study,

not many farmers pruned the branches heavily, although they knew about the

adverse effects of shading (Quddus et al., 1995); mainly because they also

knew about the high value of wood and about the slowing of tree growth that

accompanies branch pruning (Hocking, Sarwar and Yousuf, 1997).

Literature reports of beneficial effects of trees or short-duration woody

hedgerows on the rice undercrop attribute this mainly to improved soil fer-

tility relating to litter fall, or to micro-climate amelioration (Vityakon et al.,

1988 and 1993; Sae-Lee et al., 1992; Huxley, 1993; Osman et al., 1995);

although in some studies on special problem soils this effect was not found

(Dagar et al., 1995). Such an effect has not yet been quantified in the present

112


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study but is expected to be beneficial to soil fertility in the long term through

recycled nutrients.

Most farmers participating in the VFFP are content with the productivityof the combined systems and have expanded their area of cropland under

systematic agroforestry. The earliest farmer partners are into their second

generation of trees in crop fields. This speaks for their experience and con-

fidence in the system. The expected longer-term benefits to soil structure and

fertility maintenance, if realized, can only add to their satisfaction. The project

has developed much farmer-oriented extension material based on this research,

which is available on request.

Acknowledgements

The authors gratefully acknowledge the financial support of the Swiss gov-

ernment. All of our field partners, farmers, NGOs and field staff alike, con-

tributed to technical understanding of tree performance. Many scientific

colleagues contributed through discussions or reviews of early drafts of this

paper, among whom we acknowledge particularly Shahadad Hussain, Werner

Hunziker, Roger Mead, Peter Huxley, and Peter Savill. Arifur Rahman

Siddiqui and Amzul Huda of the VFFP Coordination Office ensured the timely

collection of data in the field.

Invaluable advice on statistical analysis and interpretation was provided by

Professor Roger Mead of Reading University, UK. Help with data manage-

ment and analysis was provided by Joan Knock, Carlos Barahona and Andrew

Jack of Reading University Statistical Services Centre.

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