factors affecting the occurrence of woody plants in understory of sugi

Factors affecting the occurrence of woody plants in understory of sugi (Cryptomeria japonica D.

Don.) plantations in a warm-temperate region in Japan*

Satoshi Ito1, Satoshi Ishigami1, Yasushi Mitsuda1, G. Peter Buckley2

1Faculty of Agriculture, University of Miyazaki2Faculty of Life Sceinces, Imperial College, UK

Abstract

We compared the occurrence of woody plants present in sugi (Cryptomeria japonica D. Don) plantations and

evergreen broadleaved natural forests in a warm-temperate region in order to characterize the understory vegetation of

sugi plantations. The influence of stand attributes on species occurrence in the plantations was evaluated using logistic

regression analysis. Out of 163 species, 65 plantation-preferring species and 31 natural forest-preferring species were

detected. The plantation-preferring species group contained deciduous species (38 of 65 species) that are characteristic

of coppice woodland, but all the natural forest-preferring species were evergreen plants. This indicates that the

composition of the woody understory in sugi plantations of the region is characterized by the species of open,

disturbed habitats. Stand age and the distance from the nearest natural forests were found to significantly affect the

occurrence of evergreen shrubs and plants with gravity-dispersed seeds, respectively, but the light environment of the

stand had less effect. According to the regression model analyses, long-term strategies such as lengthening the rotation

(logging age) or creating patch mosaics of plantations in the matrix of natural forests appeared to be effective in

conserving woodland species that are characteristic of evergreen, broadleaved forests. On the other hand, increasing

light penetration through thinning practices is a short-term strategy that is less likely to be effective in promoting

these species.

Key Words: understory shrubs, broadleaved evergreen forest, logistic regression analysis, species occurrence,

stand attributes, sugi plantations

Introduction

The concept of sustainable forestry emphasizes the

maintenance of both the ecological and economic values

of managed forests (Hansen et al. 1995; Barbour et al.

1997; Moor & Allen, 1999; Hummel 2003). Recent interest

in the multi-functionality of forest ecosystems has

focused on ecological processes even in plantation forests

(Hunter 1990; Hansen et al. 1991; Silbaugh & Betters 1995;

Kimmins 1997; Moore & Allen 1999). Conservation of

species diversity is one of the principles of sustainable

forestry for maintaining ecological values of forests (Crow

1989; Hunter 1990; Burton et al. 1992). In Japan, the

establishment of extensive areas of even-aged sugi

(Cryptomer ia japon ica D . Don) and h inok i

(Chamaecyparis obtusa Endl.) plantations has resulted

in a simplified forest structure which in turn is responsible

for a general decline in species diversity (Kiyono 1990;

Nakagawa and Ito 1997; Nakagawa et al. 1998; Nagaike

2000; Ito et al. 2003; Ito et al. 2004). Similar changes have

occurred in other countries (e.g., Kimball & Hunter 1990;

Moore & Allen, 1999).

Management of conifer plantations has strong and

variable effects on plant species occurrence and diversity

through the establishment of the plantation itself, the

elimination of plants by weeding and the alteration of the

ecological processes caused by changes in stand

structure, landscape structure and physical environments

(Hill 1979; Peterken & Game 1984; Kirby 1988;

Schoonmaker & McKee 1988; Kiyono 1990; Hasegawa

*Accepted manuscript for Journal of Forest Research.

2.1. 針葉樹人工林における木本植物の出現とその規定要因

7

1991; Simmons & Buckley 1992; Wallace et al. 1992;

Parrotta 1995; Wallace & Good 1995; Nyland 1996;

Hasegawa 1998; Harrington & Edwards 1999; Moore &

Allen 1999, Thomas et al. 1999; Battles et al. 2001;

Euskirchen et al. 2001; Brosofske et al. 2001). Thus, in

order to improve the biodiversity of these conifer

plantations in a given region, the factors limiting species

diversity (itself a reflection of the occurrence of individual

species) must be clarified both at the forest and landscape

levels (Michelsen et al. 1996; Ito et al. 2004). However,

little is known about the responses of individual plant

species to plantation management in Japan.

Classification of the plant species by functional

grouping is an effective way to characterise the forest

species diversity (Franklin 1988; Crow 1989; Solbrig 1994;

Euskirchen et al. 2001), and is a useful aid for understanding

the response of vegetation to forest management based

on the traits of component species (Thomas et al. 1999;

Ito et al. 2004). Since individual plant species differ from

each other in their reproductive strategies, resource

requirements and tolerance of disturbance, detailed

analyses of the responses of each functional group to

forest management have the potential to provide not only

a better a understanding of the factors limiting individual

plant species but also the management implications for

conserving target species or species groups.

Many studies have pointed out that plantation age

is the major factor affecting the understory species

composition and diversity (Peterken 1993; Nyland 1996,

Kiyono 1990; Ito et al. 2003). Thinning, which modifies

the light environment in the short-term, is another major

factor controlling understory vegetation (Kiyono 1990;

Thomas et al. 1999; Son et al. 2004). The spatial

arrangement of plantation stands in relation to potential

colonising sources is reported to be crucial for biodiversity

conservation (Moore & Allen 1999; Sarlov-Herlin & Fly

2000), while topography will often also affect the

understory composition (Ito et al. 2003).

The objective of this study was to clarify the factors

limiting the occurrence of woody plants (trees, shrubs

and climbing plants) in conifer plantations in relation to

forest management practices. We first compared the

occurrence of woody plants in both sugi plantations and

evergreen, broadleaved natural forests in a warm-temperate

region in order to characterize the understory vegetation

of sugi plantations. We then evaluated the influence of

major stand attributes (stand age, light environment,

microtopography and forest edges), on each species

occurring in sugi plantations. This approach enabled us

to model the effects of management on species occurrence

and from this to predict the effects of different

management scenarios on species diversity.

Methods

1 Data collection

The understory vegetation of sugi plantations and

evergreen, broad-leaved natural forests (Nakagawa et al.

1998, Yamashita et al. 2000) was investigated in Miyazaki

University Forest, located in southeastern Kyushu,

southern Japan (Fig. 1). Sugi plantations in Miyazaki

University Forest have been managed uniformly to a

management schedule, including ground preparation by

hand (not using fire or any herbicide), weeding and shrub-

clearing for 10 years after planting without using any

herbicides, first thinning at c. 25-30 years and a second

thinning taken at c. 60 years.

Nakagawa et al. (1998) earlier investigated

occurrences of woody plants (tree, shrub and climbing

plant species) in belt transects (10m in width and 15-30m

in length, composed of 10m x 2.5m plots; see Fig. 2) placed

in 10-47 year old sugi plantations (181 plots in 15 stands),

and 16-64 year-old evergreen broad-leaved natural forest

stands (48 plots in 7 stands). All plantations had been

restocked, second generation stands succeeding the

previous conifer plantations. Of the 15 plantation stands,

8 were adjacent to conifer plantations and 7 were adjacent

to evergreen, broad-leaved natural forests. All species

8

occurring in the understory (height < 4m) for each plot

were listed and attributed to slope position (upper slope,

mid slope or lower slope) and slope shape (concave or

convex). For each plot an index of the light environment,

gap light index (GLI, Canham 1988), was computed by

HEMIPHOT, a PC-based program for image analysis

(Steege, 1993), using hemispherical photographs taken

1.2m above ground surface. GLI was calculated for the

growing season of the region (April to December) using

the following equation:

100×++=

AdirAdifBdirBdifGLI (1)

where Bdif and Bdir are the cumulative values ofdiffusive and direct light below the canopy during thegrowing season, respectively and Adif and Adir are thecorresponding values above the canopy.

In a separate study, Yamashita et al. (2000) investigatedthe understory vegetation (height <4m) in 119 plots (5mx 5m) in an 80 year-old evergreen broad-leaved naturalforest with varied micro-topography. In their dataset, allwoody plants were listed for each plot.In this study, we combined the two datasets to obtain181 plots for sugi plantations and 167 plots forevergreen broadleaved natural forests, in whichaltogether 163 woody plant species occurred, coveringca. 70% of natural woody flora of the study site. Eachplot had same area (25m2), and lists were available oftree, shrub and climbing plant species. The dataset forplantation plots comprised stand attributes such asstand age, slope position, slope form, distance from thenearest natural forest, GLI and years after the latestthinning (Table 1).

2 Data analysis

Species preferences for conifer plantations or natural

forests were analyzed using chi-square analysis of all 348

plots. In the analysis, the expected numbers of species

occurrences were assumed to be proportional to total

number of conifer plantation plots (181) and natural forest

plots (167). Species with a significantly higher frequency

(p<0.05) in plantations or natural forests were designated

as ‘plantation-preferring species’ or ‘natural forest-

preferring species’, respectively. Species with no

significant bias were considered ‘non-preference’ species.

Miyazaki University Forests

Natural forests (Yamashita et al. 2000)Natural forests (Nakagawa et al. 1998)Plantations (Nakagawa et al. 1998) 0 500m

N

130E 132E

32N

34N

Miyazaki University Forests

Natural forests (Yamashita et al. 2000)Natural forests (Nakagawa et al. 1998)Plantations (Nakagawa et al. 1998) 0 500m0 500m

N

130E 132E

32N

34N

130E 132E

32N

34N

Fig. 1. Location of the study site and surveyed stands.

Stand edge

Stand 1 Stand 2

Plot (2.5m x 10m)

15～30mBelt transect

Stand edge

Stand 1 Stand 2

Plot (2.5m x 10m)

15～30mBelt transect

Fig. 2. A schematic illustration of the belt transect and

plot arrangement surveyed by Nakagawa et al. (1999).

9

The composition of the plantation-preferring species

and the natural forest-preferring species were then

compared with reference to their life forms, characteristic

habitats and seed dispersal types. Using the descriptions

of Ohwi and Kitagawa (1992), the following life forms were

recognised: evergreen trees, evergreen shrubs, evergreen

climbing plants, deciduous trees, deciduous shrubs and

deciduous climbing plants. We also adopted Okuda’s

(1997) classification of characteristic habitats which are

usually occupied by these plant species, as follows:

evergreen broadleaved natural forests, deciduous

broadleaved natural forests, and coppice woodlands.

Habitats of species not listed by Okuda were classified as

‘unknown’. Finally, primary seed dispersal strategies of

each species were determined according to fruit

morphology and size: frugivore- (all sap fruits), gravity-

(large dry fruits), and wind- (small dry fruits) dispersal

(Kominami et al., 1995; Ito et al., 2003; Ito et al. 2004).

For the 99 species that occurred in plantations

adjacent to natural forests (81 plots), their probabilities of

occurrence in plantations with different stand attributes

were analyzed using logistic regression analysis. The

probability of presence (1) or absence (0) was modeled

using stand attributes (stand age, slope position, slope

form, distance from the nearest natural forest, GLI and

years after the latest thinning) as independent variables

in a stepwise, variable selection. The categorical attributes

(slope position and slope form) were computed by using

dummy variables.

3 Simulations

In order to examine the possible effects of

management on plant species diversity in conifer

plantations, we ran numerical simulations based on the

results of the logistic analyses. We assumed a 0.25ha

plantation stand consisting of 100 grids of 5m x 5m. As a

reference stand, we used the following attributes: 1)

stand shape: 50m x 50m, 2) distance from natural forests:

100m, 3) stand age: 40 years old, 4) years after thinning: 10

years, 5) GLI: 15%, and 6) slope shape and position:

random. We then modified some of the attributes as shown

in Table 2 in order to set different management scenarios:

1) lengthened rotation periods (different stand ages from

Plantation Natural forestTotal Number of plots 181 167Stand age (yr) 10-47 16-80Years after the latest thinning (yr) 15-Mar -GLI (%) 2.2-75.1 -Slope position

Upper slope 19 plots 48 plotsMid slope 59 plots 57 plotsLower slope 103 plots 62 plots

Slope formConcave 17 plots 6 plotsFlat 31 plots 9 plotsConvex 133 plots 33 plotsunknown - 119 plots

Ajdacent stand typeNatural forest 81 plots -Conifer plantation 100 plots -

Table 1 A summary of the stand attributes of the plots.

Stand age Light environment Spatial arrangementStand age (yr) 15, 40, 70, 100 a 40 40

Years after the latest thinning (yr) 10 0, 10 10

GLI (%) 15 3, 15, 40 15

Slope position random random random

Slope form random random random

Stand shape 50m x 50m 50m x 50m 50m x 50m, 10m x 250mconifer plantation/

natural forests

Type of scenarios

Ajdacent stand type conifer plantation conifer plantation

Stand attributes

Table 2 Conditions of simulations predicting plant species diversity under different management scenarios.

a Conditions shown in bold characters denote the modified conditions from the standard stand attributes.

10

15 to 100 years old), 2) altered light environment by

thinning (different GLI from 3 to 40%, and years after

thinning from 0 to 10 years), and 3) altered spatial

arrangement (surrounded by conifer plantation,

surrounded by natural forest, and a narrower stand shape

[10m x 250m] surrounded by a natural forest). Using these

different stand conditions, we predicted the absence or

presence of each species in each 5m x 5m grid for 99species

occurred in plantations adjacent to natural forests.

Predictions were made from the probability function

obtained by the logistic analyses for 64 species (see

Results). For the other 35 species for which significant

models were not obtained, their relative frequencies in

the plantation plots (number of plots where the species

occurred / 181plots) was used as the basis of occurrence

probability. The prediction for each scenario was repeated

10,000 times, and Shannon’s species diversity index (H’)

was calculated for each trial by following equation:

∑= ii ppH log' (2)

where pi was the relative dominance of species i, and

was calculated as relative frequency in 100 grids. H’ was

separately calculated for each life form, characteristic

habitat and seed dispersal type to compare their

proportion between tested scenarios.

Results

1 Species Occurrence

Of the 163 species, 150 and 141 species occurred in

plantations and natural forests, respectively, with 128

species common to both. Twenty-two and thirteen species

only occurred in plantations and natural forests,

respectively. Including these 35 species, a total of 96

species were found to prefer a particular stand type: 65

preferring plantation and 31 natural forest. The remaining

67 species had no preference.

12 (18.5) a 13 (41.9) 7 (10.4)11 (16.9) 16 (51.6) 16 (23.9)

4 (6.2) 2 (6.5) 4 (6.0)9 (13.8) 0 (0) 19 (28.4)

16 (24.6) 0 (0) 17 (25.4)13 (20.0) 0 (0) 4 (6.0)

23 (35.4) 24 (77.4) 26 (38.8)4 (6.2) 0 (0) 4 (6.0)

25 (38.5) 0 (0) 27 (40.3)13 (20.0) 7 (22.6) 10 (14.9)

14 (21.5) 7 (22.6) 23 (34.3)46 (70.8) 24 (77.4) 38 (56.7)

5 (7.7) 0 (0) 6 (9.0)

65 31 67

Wind

Total

Seed dispersal typeGravityFrugivore

Evergreen natural forestDeciduous natural forestCoppicesunknown

Deciduous shrubDeciduous climbing

Characteristic habitat

Evergreen treeEvergreen shrubEvergreen climbingDeciduous tree

Plantation-preferring species Natural forest-preferringspecies Non-preference species

Life form

Table 3 Number and proportion of species in the plantation-preferring species, the natural forest preferring species and non-

preference species in relation to life form, characteristic habitat and seed dispersal type.

a Figures in parentheses are the proportion of the number of species to the total of each species groups.

11

The plantation-preferring species contained 38

deciduous species (58% of 65 species) including pioneer

trees and shrubs such as Mallotus japonicus (Thunb.)

Muell. Arg. and Rosa onoei Makino, though several

evergreen Quercus species (Q. glauca Thunb., Q. salicina

Blume and Q. gilva Blume) also appeared in this group

(Table 3). On the other hand, all the natural forest-preferring

species were evergreen trees (Table 3). When comparing

the proportion of characteristic habitats, plantation-

preferring species were characteristic of coppices (25

species, 39%), while the natural forest-preferring species

included no coppice species (Table 3). There was no clear

difference in the proportion of seed dispersal types

between the plantations- and the natural forest-preferring

species (Table 3).

Among the 99 species tested using logistic analyses,

significant models (p<0.05) were obtained for 64 species

(Table 4). Stand age was a significant variable for 42

species. Twenty-four species of the plantation-preferring

species had a tendency to occur in younger stands, while

only one species of the natural forest-preferring species

tended to occur in younger stands. The number of years

after thinning had both positive and negative effects,

mainly increasing the occurrence of the plantation-

preferring species. GLI had positive effects on 11 of the

plantation-preferring species. The distance from the

VariablesStand agepositive (old) 7 (12) a 3 (21) 4 (16) 14 (14)negative (young) 24 (40) 1 (7) 3 (12) 28 (28)

Years after the latestthinning

positive (long) 11 (18) 1 (7) 3 (12) 15 (15)negative(short) 12 (20) 2 (14) 3 (12) 17 (17)

GLIpositive(light) 11 (18) 2 (14) 6 (24) 19 (19)negative(dark) 3 (5) 0 (0) 2 (8) 5 (5)

Distance from thenearest natural forest

positive(far) 7 (12) 0 (0) 1 (4) 8 (8)negative(close) 9 (15) 0 (0) 8 (32) 17 (17)

Slope positionUpper slope 15 (25) 5 (36) 9 (36) 29 (29)Mid slope 10 (17) 0 (0) 6 (24) 16 (16)Lower slope 6 (10) 1 (7) 4 (16) 11 (11)

Slope formConcave 6 (10) 1 (7) 4 (16) 11 (11)Flat 2 (3) 0 (0) 2 (8) 4 (4)Convex 5 (8) 1 (7) 6 (24) 12 (12)

Number of species forwhich significantmodel was obtained

42 (70) 5 (36) 17 (68) 64 (65)

Total number ofspecies examined 60 (100) 14 (100) 25 (100) 99 (100)

Plantation-preferring Natural forest-preferring Non-preference species Total

Table 4 A summary of logistic regression analyses of occurrence probability conducted for 64 species. Figures indicate the

number of species which the variables were significant in the regressions.

a Figures in parentheses are the proportion of the number of species to the total of examined species in each species category.

12

nearest natural forest had a negative influence on 9 of the

plantation-preferring species. However, 7 plantation-

preferring species were influenced positively by the same

variable. There were fewer effects of these two variables

(GLI and the distance) on the occurrence of the natural

forest-preferring species. Slope position showed generally

high influences (56 of 99 species).

2 Simulation results

Figures 3-5 show the predicted species diversity index

(H’) based on significant logistic regression models for

64 species (in upper panels a, b and c of Figs. 3-5), and

based on random occurrence for 35 species (in the lower

panels d, e and f of Figs. 3-5). The predicted species

diversity index for 35 species of random occurrence had

small proportion to the total diversity, and quite small

variations though the different scenarios (the lower panels

[d, e and f] of Figs. 3-5). The diversity predicted for 64

species using models with different stand age (Fig. 3a)

indicated an increase in diversity of evergreen shrubs,

together with a corresponding decrease in deciduous

shrubs along an increasing stand age gradient. This was

associated with an increase in the diversity of species

characteristic of evergreen, broadleaved forest habitats

and a decrease in those associated with coppice

woodland, respectively (Fig. 3b). There was no clear trend

in the change of seed dispersal types except for a decline

of the wind-dispersal type in older stands (Fig. 3c).

Simulation of different light environments due to

thinning effects (Figs. 4a, b and c) indicated fewer

differences in H’ between scenarios than in stand-age

scenarios, although there were slight increases of H’ in

evergreen trees and deciduous shrubs (Fig. 4a), the

coppice woodland type (Fig. 4b) and the gravity- or the

frugivore-dispersal type (Fig. 4c) at 40% GLI. The effect

Gravity Frugivore WindEGT EGS EGCDET DES DEC

EGBL DEBL COP UN

0

1

2

3

4

H'

0

1

2

15 40 70 100Stand age (yr)

H'

c)

f)

0

1

2

3

4

H'

0

1

2

15 40 70 100Stand age (yr)

H'

a)

d)

0

1

2

3

4

H'

Stand Age (yr)

0

1

2

15 40 70 100

H'

b)

e)

Gravity Frugivore WindGravity Frugivore WindEGT EGS EGCDET DES DECEGT EGS EGCDET DES DEC

EGBL DEBL COP UNEGBL DEBL COP UN

0

1

2

3

4

H'

0

1

2

15 40 70 100Stand age (yr)

H'

c)

f)

0

1

2

3

4

H'

0

1

2

15 40 70 100Stand age (yr)

H'

c)

f)

0

1

2

3

4

H'

0

1

2

15 40 70 100Stand age (yr)

H'

a)

d)

0

1

2

3

4

H'

0

1

2

15 40 70 100Stand age (yr)

H'

a)

d)

0

1

2

3

4

H'

Stand Age (yr)

0

1

2

15 40 70 100

H'

b)

e)

0

1

2

3

4

H'

Stand Age (yr)

0

1

2

15 40 70 100

H'

b)

e)

Fig. 3. Predicted species diversity index (H’) simulated along different stand ages. a,d) Composition of the life form

composition (EGT, evergreen trees; EGS, evergreen shrubs; EGC, evergreen climbing plants ; DET, deciduous trees;

DES, deciduous shrubs; DEC, deciduous climbing plants). b,e) Composition of the characteristic habitat (EGBL,

evergreen broadleaved forests type; DEBL, deciduous broadleaved forest type; COP, Coppice woodland type; UN,

unknown). c, f) Composition of seed dispersal types. Upper panels (a, b, c) indicate H’ of those predicted by GLM

results. Lower panels (d, e, f) indicate those predicted based on relative frequency of the species. For details of

prediction, see text.

13

of time after the thinning (0 or 10 years) had less effect on

species diversity.

Different spat ia l arrangements of s tands

demonstrated that for those stands surrounded by natural

forests, irrespective of shape, small increases occurred in

the evergreen broadleaved forest type (Fig. 5b) and

gravity-dispersal type (Fig. 5c), but a decrease in the wind-

dispersal type (Fig. 5c).

Discussion

1. Composition of ‘the plantation-preferring species’

Forty per cent of the species found in plantations

(65 of 150 species) tended to prefer plantations to natural

forests. The plantation-preferring species contained a

large proportion of deciduous plants that are

characteristic of deciduous, broadleaved forest or

frequently disturbed coppice forests. Most pioneer species

in the evergreen broadleaved forest region of Japan have

the deciduous leaf habit more usually associated with cool

temperate forests, but are common in the warm-temperate

region on frequently disturbed sites such as riparian

margins (Sakai and Ohsawa, 1994; Ito and Nogami, 2005).

Thus, it is suggested that the understory vegetation of

sugi plantations retains many characteristics of disturbed

open habitats in the region, even under the moderately

closed canopies of the production forests investigated in

this study. This is consistent with previous reports for

plantations in warm-temperate region (Ito et al., 2004) and

other plantations elsewhere (Takeda and Kimura, 1988;

Nagaike, 2002), and reflects the influence of intensive

disturbance (establishment of plantations) and

continuous disturbances (subsequent management

H'

0

1

2

3

4

0

1

2

H'

3 15 40 3 15 40GLI (%)

0 years afterthinning


0

1

2

3

4

H'

0

1

2

H'

3 15 40 3 15 40GLI (%)



0

1

2

3

4

H'

0

1

2

H'

3 15 40 3 15 40GLI (%)




EGBL DEBL COP UN

c)

f)

a)

d)

b)

e)

H'

0

1

2

3

4

0

1

2

H'

3 15 40 3 15 40GLI (%)



H'

0

1

2

3

4

0

1

2

H'

3 15 40 3 15 40GLI (%)



0

1

2

3

4

H'

0

1

2

H'

3 15 40 3 15 40GLI (%)



0

1

2

3

4

H'

0

1

2

H'

3 15 40 3 15 40GLI (%)



0

1

2

3

4

H'

0

1

2

H'

3 15 40 3 15 40GLI (%)



0

1

2

3

4

H'

0

1

2

H'

3 15 40 3 15 40GLI (%)





c)

f)

a)

d)

b)

e)

Fig. 4. Predicted species diversity index (H’) simulated along different light environments and years after the

latest thinning. a, d) Composition of the life form composition (EGT, evergreen trees; EGS, evergreen shrubs;

EGC, evergreen climbing plants ; DET, deciduous trees; DES, deciduous shrubs; DEC, deciduous climbing

plants). b, e) Composition of the characteristic habitat (EGBL, evergreen broadleaved forests type; DEBL,

deciduous broadleaved forest type; COP, Coppice woodland type; UN, unknown). c, f) Composition of seed

dispersal types. Upper panels (a, b, c) indicate H’ of those predicted by GLM results. Lower panels (d, e, f)

indicate those predicted based on relative frequency of the species. For details of prediction, see text.

14

practices such as weeding and thinning). This indicates a

positive contribution of conifer plantations to the

conservation of coppice woodland species.

2. Factors affecting the species occurrence

Logistic analyses revealed a number of different

factors affecting the occurrence of 64 out of the 99 species

examined. These were associated with species’

preferences to plantations or natural forests. Variations in

species characteristics, such as leaf habit, characteristic

habitat types and seed dispersal mechanisms, were also

indicated to be related to different stand attributes and

management scenarios in the simulation results. Although

the variation in total species diversity predicted by the

simulations was relatively small, this was mainly because

of 35 species, for which significant models were not

obtained in the logistic analysis. Predicting random

occurrences for these species in 100-cell grids per plot,

based on averaging 10,000 selections might be expected

to have a smoothing effect on the diversities calculated

for each different scenario. However, this result applies to

a relatively small portion and variations in total diversity,

and inversely, the importance of the 64 species predicted

by significant models in the variations in total species

diversity in plantations.

Among the stand attributes tested, stand age had a

significant influence on the evergreen or broadleaved leaf

character of the species and their characteristic habitats;

older stands contained more evergreen, natural forest

0

1

2

3

4

H'

0

1

2

PLA NAT NARSpatial stand arrangement

H '

0

1

2

3

4

H'

0

1

2


H'

0

1

2

3

4

H'

0

1

2


H'


EGBL DEBL COP UN

c)

f)

a)

d)

b)

e)

0

1

2

3

4

H'

0

1

2


H '

0

1

2

3

4

H'

0

1

2


H '

0

1

2

3

4

H'

0

1

2


H'

0

1

2

3

4

H'

0

1

2


H'

0

1

2

3

4

H'

0

1

2


H'

0

1

2

3

4

H'

0

1

2


H'



c)

f)

a)

d)

b)

e)

Fig. 5. Predicted species diversity index (H’) simulated along different spatial stand arrangements. Horizontal axes

denote the spatial arrangement of the stand: PLA, a square-shape (50m x 50m) stand surrounded by conifer

plantations (100m distant from the nearest natural forest patch); NAT, a square-shape (50m x 50m) stand

surrounded by natural forests; and NAR, a narrow-shape (10m x 250m) stand surrounded by natural forests. a, d)

Composition of the life form composition (EGT, evergreen trees; EGS, evergreen shrubs; EGC, evergreen climbing

plants ; DET, deciduous trees; DES, deciduous shrubs; DEC, deciduous climbing plants). b, e) Composition of the

characteristic habitat (EGBL, evergreen broadleaved forests type; DEBL, deciduous broadleaved forest type; COP,

Coppice woodland type; UN, unknown). c, f) Composition of seed dispersal types. Upper panels (a, b, c) indicate

H’ of those predicted by GLM results. Lower panels (d, e, f) indicate those predicted based on relative frequency

of the species. For details of prediction, see text.

15

species. Similar results were reported by Kiyono (1990)

for hinoki plantations and Ito et al. (2003) for sugi

plantations. The plantation-preferring species also tended

to occur in younger stands, corresponding to their

requirement for disturbance. The simulation results also

displayed an increase in the diversity of evergreen shrubs

characteristic of evergreen broadleaved forest type with

stand age, indicating their ability to recolonise and

respond to developmental changes in the canopy and

light conditions in the understory.

Light levels were less correlated with the occurrence

of the species examined. This was partly because the

surveyed stands had been generally well thinned, and no

stands completely lacked understory vegetation. Thinning

practice in the region is mostly associated with shrub-

clearing procedure before each thinning episode. The

negative influence of this clearing treatment on understory

vegetation also might reduce the positive effects of the

improvement of light climate by thinning. Although 19

species preferred lighter conditions (higher GLI) in the

affected by human disturbances in plantations

(unpublished data).

In conclusion, our results demonstrate the

effectiveness of different management strategies in

acheiving different conservation targets in conifer

plantations. Long-term strategies such as lengthening the

rotation period (logging age), or the formation of patch

during their young ages by continuous human

disturbances.

Acknowledgements

We wish to thank the staff of the Miyazaki University

Forests for cooperation in the fieldwork. Part of the work

was supported by Grant-in-Aid for Scientific Research

from JSPS (No. 15380110).

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factors affecting the occurrence of woody plants in understory of sugi

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