Limitations on tree seedling establishment across ecotonesbetween abandoned fields and adjacent broad-leaved forestsin eastern Japan
Yoshinori Tokuoka • Kentaro Ohigashi •
Nobukazu Nakagoshi
Received: 14 May 2010 / Accepted: 12 November 2010 / Published online: 17 December 2010
� Springer Science+Business Media B.V. 2010
Abstract Field abandonment has increased over
several decades under a long-term recession in
Japanese agriculture. To support effective farmland
management or reforestation, the patterns of tree
recruitment in abandoned fields, which influence
management costs, need to be clarified. We investi-
gated tree seedling establishment and microsite
variables along forest–field transects in 11 abandoned
fields adjacent to secondary broad-leaved forests in
the eastern Kanto region of Japan. Generalized linear
mixed model analysis indicated that tree seedling
establishment in abandoned fields was not correlated
with the period of abandonment. Instead, it was
positively correlated with vegetation openness. The
dominance of a woody vine (Pueraria lobata), an
annual liana (Humulus japonicus), and a dwarf
bamboo (Pleioblastus chino) mainly explained low
vegetation openness within the fields. In addition, the
establishment of evergreen tree seedlings and tree
seedlings dispersed by hoarding was negatively
correlated with the distance from the forest edge. In
the forest interior, taller understory vegetation at the
edge correlated with lower seedling establishment.
These results suggest that seedling establishment
across forest–field ecotones is restricted by the
dominance of competitive natives within abandoned
fields and distance-dependent limitations in both
abandoned fields and adjacent forest.
Keywords Tree seedling � Abandoned field � Forest
adjacency � Microsite limitation � Slow reforestation
Introduction
The pattern of tree seedling encroachment into
abandoned fields varies with the type and magnitude
of disturbances caused by past agricultural activities
(Cramer et al. 2008). Active restoration is required
when the recovery of natural vegetation is limited by
modifications to the original biotic and abiotic
conditions (Hobbs and Cramer 2007). Therefore,
examining the factors that could detract from the goal
of restoration of abandoned fields is important for
effective farmland management and for the conser-
vation of biodiversity.
Y. Tokuoka (&)
Biodiversity Division, National Institute
for Agro-Environmental Sciences, 3-1-3,
Kannondai, Tsukuba-shi, Ibaraki 305-8604, Japan
e-mail: [email protected]
Y. Tokuoka � N. Nakagoshi
Graduate School for International Development and
Cooperation, Hiroshima University, 1-5-1 Kagamiyama,
Higashi-Hiroshima-shi, Hiroshima 739-8529, Japan
K. Ohigashi
Ecosystem Informatics Division, National Institute
for Agro-Environmental Sciences, 3-1-3, Kannondai,
Tsukuba-shi, Ibaraki 305-8604, Japan
123
Plant Ecol (2011) 212:923–944
DOI 10.1007/s11258-010-9868-9
Owing to an agricultural recession that has
persisted over several decades, farmland abandon-
ment in Japan has increased, reaching approximately
8% of the total farmland area in 2005 (http://www.
estat.go.jp/SG1/estat/). To integrate the sustainable
use of farmland and reforestation, it is important to
understand the long-term temporal and spatial pat-
terns of tree establishment in abandoned fields as this
could influence management costs. Arita and Ohkuro
(2007a) documented the dynamics of the transition of
abandoned rice paddy fields to Salix-dominated
woods in central Japan and proposed on extensive
management scheme for resuming paddy field use in
the region based on the development pattern (Arita
and Ohkuro 2007b). However, little is known about
natural reforestation patterns of mesic-abandoned
fields in Japan.
Seed and microsite limitations in a variety of
habitats have been studied by field observation or
factorial experiments as mechanisms that deter-
mine species establishment during revegetation (e.g.,
Eriksson and Ehrlen 1992; Herrera and Laterra 2009;
Holzel 2005). In reforestation, the success of seedling
establishment is critical in determining the pattern and
rate of vegetation change. Under a temperate climate
in the USA, the limitations posed by microsites, such
as herbivory intensity and light availability, on tree
seedlings varied with distance from the forest–field
edge (Cadenasso and Pickett 2000; Meiners et al.
2000; Meiners and Martinkovic 2002; Meiners et al.
2002). In an abandoned field in North Carolina,
interactions of seed phenology, drought stress mitiga-
tors, and herbivory intensity influenced the emergence,
survival, and growth of seedlings of several hardwoods
and Pinus spp. (Desteven 1991a, b). In warm temper-
ate regions in Japan, the dispersal or distribution of
some zoochorous tree species was investigated in
forests (Hoshizaki et al. 1999; Iida 1996, 2004) and
cities (Komuro and Koike 2005). However, the
distribution patterns of tree seedlings across forest–
field ecotones and the site conditions that affect those
patterns are still unknown. Focusing on forest–field
ecotones allows us to examine the relative importance
of seed supply from adjacent forests and field condi-
tions to seedling establishment in abandoned fields. It
also allows us to test the influence of revegetating the
adjacent field on the forest plant community.
Here, we investigated seedling establishment and
microsite conditions in 11 abandoned fields adjacent
to broad-leaved forests in the eastern Kanto region of
Japan. We examined the relationships of seedling
establishment with three microsite variables (vegeta-
tion openness, vegetation height, and soil salinity)
and distance from the forest edge. These variables
seem to reflect competition between tree seedlings
and other plants, distance-dependent limitations of
seed input, herbivory intensity, and soil nutrient
conditions, which vary during the course of revege-
tation after abandonment. The relationship between
period of abandonment and tree seedling establish-
ment in abandoned fields was also examined to
evaluate the time-sequence trends.
We tested how seedling establishment responded
to these variables within forest–field ecotones, within
abandoned fields, and within the forest interior.
Degrees of seedling establishment were represented
by examining the following variables. First, to give
an overview of tree seedling establishment, we tested
the response of the number and richness of tree
seedlings to those site condition variables.
In the warm temperate regions of Japan, shade-
tolerant evergreen trees in the Fagaceae and Lauraceae
dominate the climax forest community (Kira 1991;
Fukushima 2005). In contrast, deciduous trees domi-
nate early- to mid-successional secondary forests
formed after disturbances (Miyawaki 1986). Distribu-
tion patterns and frequencies differ between evergreen
and deciduous trees in both forest and gaps (Manabe
et al. 2000; Miura et al. 2001). These differences in
recruitment and dominance would be partly explained
by the trees’ photosynthetic traits. Kikuzawa (1991)
noted that leaf longevity reflects the adaptability of
trees to different light environments. Moreover, ever-
green trees are more tolerant of nutrient-poor condi-
tions than deciduous trees are (Givnish 2002).
Therefore, second, we considered that gradients in
light and soil environments in open abandoned fields
may influence the two functional groups differently.
The behavior of seed dispersers is another key to
reforestation. In the warm temperate regions of Japan,
acorns (seeds of the Fagaceae) are dispersed mainly
via hoarding by mice (Hoshizaki et al. 1999; Iida
2004; Shimada 2001). The mice predate heavily on
the acorns, and their predation behavior differs
between dense vegetation and open habitat (Wada
1993). Dispersal distance by mice is thought to be
shorter than that by birds, which ingest a variety of
fruits much smaller than acorns (Iida 2004; Komuro
924 Plant Ecol (2011) 212:923–944
123
and Koike 2005). Considering these contrasting
dispersal modes, third, we analyzed the response to
the two main modes of tree seed dispersal at our
study sites: hoarding or ingestion by animals.
Finally, we discuss the management and reforesta-
tion of abandoned field–forest ecotones in this region.
Methods
Study site
Our study sites were abandoned fields adjacent to
secondary forests in the eastern Kanto region (Fig. 1a).
As we lacked land use data, we chose candidate fields
adjacent to broad-leaved forests from aerial photo-
graphs taken within the previous decade. We then
visited the fields to confirm whether or not the field and
forest sizes met our conditions for sampling. To avoid
the selection of poor seed sources, we ascertained the
maturity of the adjacent forest (based on the size of
the tallest trees) and the distribution of saplings of the
dominant species. Few adult trees were found in the
interior of the fields. We ascertained the past agricul-
tural activity of each field from the land owners or
neighbors. Finally, we selected 11 sites that had
experienced the typical cropping history of mesic-
abandoned fields in the region (Table 1). We avoided
former rice paddies that had been drained.
The forests adjacent to the sites were dominated by
local broad-leaved trees, such as Quercus myrsinae-
folia, Q. serrata, Q. acutissima, Castanea crenata,
Celtis sinensis, and Aphananthe aspera (Table 1).
Their saplings grew in the sub-tree or shrub layer.
Mature trees of some species common in secondary
forests in the region (Miyawaki 1986) were observed.
Therefore, we assumed that the adjacent forests had
the potential to supply viable tree seeds to the fields.
Other vegetation patches within a 100 m buffer zone
surrounding the sites were mainly farmland or
coniferous plantations. Their roles as seed sources
were considered to be negligible.
According to the weather station in the nearby city
of Tsukuba, the mean annual temperature for the
period 1971–2000 was 13.5�C, the mean temperature
in August was 25.2�C, and the mean temperature in
January was 2.3�C. The mean annual precipitation
was 1235.6 mm. The soil at each site is a well-
drained volcanic Andosol with high proportions of
glass and amorphous colloidal materials.
Survey plot design
At each site, three transects, extending from the forest
interior into the field, were laid out perpendicular to the
forest–field border, crossing at the midpoint and
quarter points (Fig. 1b). We located 13 quadrats
(1 9 1 m) along each transect at specific distances
from the forest edge, defined as the drip line of the trees
rooted on the forest–field border: at 1, 4, 7, 10, 15, and
20 m into the forest (shown as negative values in
Figs. 1b, 2) and at 1, 4, 7, 10, 15, 20, and 30 m into the
field. Excluding data collected on footpaths crossing
the transects, we analyzed data from 419 quadrats
obtained from August to October in 2008.
Data sampling
In each quadrat, all post-cotyledonous tree seed-
lings \1 m tall were recorded. Seedlings of woody
vines were not recorded. Nomenclature and plant
Fig. 1 a Locations of study
sites. b Schematic diagram
of experimental setup.
Values in quadrats indicate
distance (m) from forest
edge
Plant Ecol (2011) 212:923–944 925
123
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926 Plant Ecol (2011) 212:923–944
123
characteristics follow Chibaken-Shiryou-Kenkyuzai-
dan (2003) and Miyawaki et al. (1994).
Three microsite variables were recorded in each
quadrat. To quantify light availability, a hemispher-
ical photograph was taken with a Nikon Coolpix 5000
camera fitted with a Nikon fish-eye converter (FC-E8)
at the center of each quadrat, 50 cm above the ground.
This height placed the lens under competing plants
in the liana and herb layers of all quadrats and took in
most observed seedlings (93% were smaller than
50 cm). Photographs were taken on a cloudy day, or
early in the morning, or just before sunset. Vegetation
openness was calculated from the photographs with
CanopOn 2 software (http://takenaka-akio.cool.ne.jp/
etc./canopon2/). In each quadrat during the seedling
census, the height of the vegetation was measured at the
maximum height of the herb layer [or of dwarf bamboo
(Pleioblastus chino) and juvenile trees taller than 1 m],
which seemed to compete most directly both above and
below ground with seedlings shorter than 1 m. The
electrical conductivity (EC) of the soil pore water was
measured three times in each quadrat with a Delta-T
WET Sensor (WET-2; Delta-T Devices, Ltd.) and
averaged. Plants in the liana and herb layers were
recorded, and their percentage coverage was estimated
by eye in each layer. Unidentifiable small plants, such
as juveniles of herbaceous plants, and post-flowering
individuals of graminoids were excluded from analysis.
Median and lower and upper quartiles of these variables
were calculated to give an overview of plot character-
istics (Table 1).
Statistical analysis
To test for differences in field conditions, we
compared vegetation openness, vegetation height,
and EC among sites by the Steel–Dwass test (Dwass
1960; Steel 1960), a non-parametric multiple test
procedure, at the 5% level of significance (Table 1).
The numbers and species richness of all tree
seedlings, evergreen tree seedlings, deciduous tree
seedlings, tree seedlings dispersed by hoarding, and
tree seedlings dispersed by ingestion were plotted in
box-and-whisker plots against distance from the
forest edge (Fig. 2). These ten variables were used
as response variables in the following analyses.
At most sites, 39 quadrats were examined. To test
the seedling responses to the site variables while
accounting for the lack of independence within sites,
generalized linear mixed models (GLMMs) with a
Poisson error distribution and a log-link function
were used with study site difference as a random
intercept term and the other variables as fixed effect
terms (Table 2). Time since abandonment was
Fig. 2 Box and whisker plots of the number and species
richness of all tree species, evergreen tree species, deciduous
tree species, tree species dispersed by ingestion, and tree
species dispersed by hoarding against distance from the forest
edge. Negative values on the x-axis represent the forest interior
Plant Ecol (2011) 212:923–944 927
123
included only in the analysis of the field-only data set
to test the time-sequence trend of seedling establish-
ment in abandoned fields. Because the time of
abandonment was only approximate, we treated it
as an ordinal variable with four values: 1, \8 years
(n = 4); 2, 10–15 years (n = 3); 3, *20 years
(n = 2); and 4, *40 years (n = 2).
The GLMM analyses were performed with forest–
field data (n = 419), field-only data (n = 227), and
forest interior data (n = 192). Using Akaike’s infor-
mation criterion, we identified the top five competing
models from among 24 (forest–field and forest
interior) or 120 (field-only) candidate models, which
were derived from all combinations of the explana-
tory variables, without any interaction terms, for the
ten response variables.
The relationships between seedling establishment
and the explanatory variables were inferred from the
parameters selected in the top five competing models
and whether the estimated coefficients were positive
or negative. The goodness of fit of each model was
assessed from the proportion of deviance explained
against the null model in which all four fixed effects
were removed. The statistical analyses were done in
R 2.8.1 software (R Development Core Team 2008).
GLMM analyses were performed with the lmer
function in the lme4 package (Bates et al. 2008).
To test the correlation between the vegetation type
of the abandoned fields and the stand parameters
(vegetation openness and vegetation height), first,
hierarchical clustering was performed with 19 liana
species and 28 species in the herb layer from all field
quadrat data (n = 227). Four liana species were
recorded in the herb layer when understory plants
were sparse or liana size was small. Those species
were included as different vegetation components in
the analysis to reflect the structural difference of
vegetation. For clustering, the coverage of each
species was made proportional to the total of all
species coverage in both the liana and herb layers in
each quadrat. A cluster dendrogram of the 227
quadrat vegetation data sets was produced using a
Table 2 Response and explanatory variables used for generalized linear mixed models
Variables Variable range
Min–mean–max
Response
Number of tree seedlings 0–2.28–36
Tree species richness 0–1.08–7
Number of evergreen tree seedlings 0–1.29–36
Evergreen tree species richness 0–0.87–12
Number of deciduous tree seedlings 0–0.47–5
Deciduous tree species richness 0–0.58–5
Number of trees dispersed by ingestion 0–1.18–17
Richness of tree species dispersed by ingestion 0–0.67–5
Number of trees dispersed by hoarding 0–0.98–30
Richness of tree species dispersed by hoarding 0–0.34–2
Explanatory
NF Vegetation openness calculated from
hemispherical photos taken at 50 cm height (%)
0.20–6.87–43.10
NF Vegetation height (m) 0.00–1.68–6.50
NF Soil salinity 7.33–40.00–111.00
NF Distance from forest edge (in m, defined a priori) -20, -15, -10, -7, -4, -1, 1, 4, 7, 10, 15, 20, 30
OF Time since abandonmenta 1, \8 years; 2, 10–15 years; 3, *20 years; 4, *40 years
CR Plot name Plot 1–11
NF numeric fixed effect. OF ordinal scale fixed effect. CR categorical random effect in GLMMsa Included in the analysis of field-only data set
928 Plant Ecol (2011) 212:923–944
123
flexible beta linkage (b = -0.25) with Sorensen
distance (McCune and Grace 2002). The pruning
point of the dendrogram was determined from the
average P value (McCune and Grace 2002) calcu-
lated after indicator species analysis (INSPAN:
Dufrene and Legendre 1997) and the number of
significant indicators tested with the Monte Carlo test
(1000 permutations, P \ 0.05). These analyses were
done in PC-ORD version 4 software (MjM Software,
Gleneden Beach, OR). Differences in vegetation
openness and vegetation height among vegetation
types were compared by the Steel–Dwass test.
Results
We found 955 seedlings of 42 species (35 zoochor-
ous) at the 11 sites (Table 5 in appendix): 191
seedlings of 22 species in the abandoned fields
(n = 227) and 764 seedlings of 37 species in the
forests (n = 192). This contrasting pattern of seed-
ling establishment between forests and fields was also
seen in species richness with distance from the forest
edge. Figure 2 shows abundant seedling presence in
the forest interior, a reduction near the border, and
scarcity in the fields.
According to the results of GLMMs (Tables 6, 7,
and 8 in appendix), the deviance explained by the
fixed effects in the selected 50 models for all ten
response variables ranged from 7.5 to 38.8% for the
forest–field data set, 3.1 to 24.8% for the field-only
data set, and 2.3 to 12.2% for the forest interior
dataset. As shown in Table 3, which summarizes
the best-fitted model for each response variable in the
three habitat units, the forest–field data set gave the
best fit, and the forest interior data set gave the worst.
In the field-only data set, responses of deciduous tree
seedlings and tree seedlings dispersed by ingestion to
the explanatory variables were poor. In the forest
interior data set, responses of numbers of all tree
seedlings, evergreen tree seedlings, and tree seedlings
dispersed by hoarding showed better correlations
with the fixed effects among the ten response
variables.
The GLMMs for the forest–field dataset selected
vegetation openness or distance from the forest edge
in all five competing models of all ten analyses
(Table 6 in appendix). Vegetation height and soil
salinity were selected in some competing models of
all response variables; however, their contribution to
model improvement was slight.
The GLMMs for all tree seedlings and evergreen
tree seedlings in the field-only dataset selected
vegetation openness in all competing models (Table
7 in appendix). All competing models of the number
of tree seedlings and evergreen tree seedlings
selected vegetation height. Distance from forest edge
was selected in four out of five competing models of
evergreen tree seedlings and number of tree seedlings
dispersed by hoarding. Soil salinity was selected in
all five competing models of the number of tree
seedlings dispersed by hoarding. Period of abandon-
ment was the least selected variable.
The GLMMs for the forest interior dataset selected
vegetation height in all competing models of the
better-fitted response variables: numbers of tree
seedlings, evergreen tree seedlings, and tree seedlings
dispersed by hoarding (Table 8 in appendix). Dis-
tance from forest edge was selected in four out of five
competing models for the same response variables.
Vegetation openness and soil salinity were also
selected in some models, but their contribution was
weak.
Whether the coefficient of each parameter was
negative or positive was nearly consistent among
vegetation openness, distance from forest edge, and
vegetation height. The coefficient of vegetation
openness was positive in most models. Those of
vegetation height and distance from the forest edge
were negative in most models. Those of soil salinity
and period of abandonment were not consistent
among models.
By hierarchical clustering and pruning based on
average P value and the number of significant
indicators, the field vegetation was divided into six
types (Table 4), each characterized by indicators as
follows: I, dominated by P. chino; II, dominated by
Pueraria lobata and Humulus japonicus and lacking
dominant herbs; III, dominated by P. lobata and
H. japonicus in the liana layer; IV, dominated by
grasses and Solidago altissima; V, dominated by
Trichosanthes cucumeroides in the liana layer; and
VI, dominated by S. altissima. Comparison of the
stand parameters among the six types indicated that
dense liana dominance (types III, V) led to the lowest
vegetation openness and vegetation height (Fig. 3).
Monodominance of P. chino led to the second lowest
Plant Ecol (2011) 212:923–944 929
123
Ta
ble
3T
he
bes
t-fi
tted
gen
eral
ized
lin
ear
mix
edm
od
els
of
seed
lin
gre
spo
nse
toex
pla
nat
ory
var
iab
les
alo
ng
fore
st–
fiel
dg
rad
ien
ts,
inab
and
on
edfi
eld
s,an
din
fore
stin
teri
ors
Res
po
nse
var
iab
les
Par
amet
eres
tim
ate
and
stan
dar
der
ror
(SE
)o
fex
pla
nat
ory
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les
AIC
Per
cen
tag
e
dev
ian
ce
exp
lain
ed(I
nte
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t)S
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eget
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n
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enn
ess
SE
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tan
ce
fro
mfo
rest
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e
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etat
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gh
t
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il
sali
nit
y
SE
Ab
and
on
ed
per
iod
aS
E
Fo
rest
–fi
eld
gra
die
nts
(n=
41
9)
––
Tre
ese
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ng
sn
um
ber
0.3
33
0.3
70
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73
0.0
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.00
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99
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70
––
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58
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0.9
Tre
esp
ecie
sri
chn
ess
-0
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00
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60
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.00
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0.0
30
0.0
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-0
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10
.04
6–
–4
60
.82
5.6
Nu
mb
ero
fev
erg
reen
tree
seed
lin
gs
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50
.25
30
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.00
9-
0.0
62
0.0
03
-0
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70
.03
1–
–8
11
.13
8.7
Sp
ecie
sri
chn
ess
of
ever
gre
entr
ee
seed
lin
gs
-1
.24
30
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00
.00
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0.0
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-0
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50
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1–
–3
22
.82
7.2
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mb
ero
fd
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uo
us
tree
seed
lin
gs
-0
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50
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0.0
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-0
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30
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00
.00
80
.00
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–6
90
.88
.6
Sp
ecie
sri
chn
ess
of
dec
idu
ou
str
ee
seed
lin
gs
-1
.41
80
.14
80
.07
70
.00
6-
0.0
16
0.0
02
––
41
8.9
9.7
Nu
mb
ero
ftr
eese
edli
ng
sd
isp
erse
d
by
anim
alin
ges
tio
n
-0
.76
90
.28
00
.06
40
.00
9-
0.0
39
0.0
05
-0
.13
30
.06
30
.01
10
.00
4–
–8
42
.72
0.4
Sp
ecie
sri
chn
ess
of
tree
seed
lin
gs
dis
per
sed
by
anim
alin
ges
tio
n
-0
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80
.21
50
.06
60
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1-
0.0
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0.0
05
-0
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30
.07
8–
–4
22
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8.4
Nu
mb
ero
ftr
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by
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alh
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g
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50
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.08
20
.02
2-
0.0
55
0.0
05
-0
.26
90
.05
2–
–6
82
.03
1.8
Sp
ecie
sri
chn
ess
of
tree
seed
lin
gs
dis
per
sed
by
anim
alh
oar
din
g
-0
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30
.34
8-
0.0
40
0.0
08
-0
.01
60
.00
8–
–2
69
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6.0
Ab
an
do
ned
fiel
ds
(n=
22
7).
Tre
ese
edli
ng
sn
um
ber
-0
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10
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20
.09
00
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8-
0.3
83
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16
31
3.0
11
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Tre
esp
ecie
sri
chn
ess
-1
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70
.41
00
.10
80
.02
1-
0.0
16
0.0
10
20
5.4
10
.6
Nu
mb
ero
fev
erg
reen
tree
seed
lin
gs
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20
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40
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30
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2-
0.0
66
0.0
21
-0
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60
.19
41
54
.82
4.2
Sp
ecie
sri
chn
ess
of
ever
gre
entr
ee
seed
lin
gs
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.97
90
.54
70
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30
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0.0
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0.0
24
11
2.7
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mb
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fd
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uo
us
tree
seed
lin
gs
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60
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80
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22
47
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.3
Sp
ecie
sri
chn
ess
of
dec
idu
ou
str
ee
seed
lin
gs
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00
.45
30
.08
70
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61
72
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.7
Nu
mb
ero
ftr
eese
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ng
sd
isp
erse
d
by
anim
alin
ges
tio
n
-2
.01
80
.53
00
.06
90
.02
42
39
.83
.1
930 Plant Ecol (2011) 212:923–944
123
Ta
ble
3co
nti
nu
ed
Res
po
nse
var
iab
les
Par
amet
eres
tim
ate
and
stan
dar
der
ror
(SE
)o
fex
pla
nat
ory
var
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les
AIC
Per
cen
tag
e
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ian
ce
exp
lain
ed(I
nte
rcep
t)S
EV
eget
atio
n
op
enn
ess
SE
Dis
tan
ce
fro
mfo
rest
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e
SE
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etat
ion
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gh
t
SE
So
il
sali
nit
y
SE
Ab
and
on
ed
per
iod
aS
E
Sp
ecie
sri
chn
ess
of
tree
seed
lin
gs
dis
per
sed
by
anim
alin
ges
tio
n
-2
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70
.45
50
.08
70
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71
60
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.4
Nu
mb
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ftr
eese
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ng
sd
isp
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d
by
anim
alh
oar
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g
0.2
53
0.5
72
-0
.03
40
.01
9-
0.0
46
0.0
15
16
9.8
10
.6
Sp
ecie
sri
chn
ess
of
tree
seed
lin
gs
dis
per
sed
by
anim
alh
oar
din
g
-0
.52
80
.60
5-
0.0
38
0.0
14
81
35
.34
.9
Fo
rest
inte
rio
r(n
=1
92
)
Tre
ese
edli
ng
sn
um
ber
0.7
82
0.3
08
0.0
24
0.0
12
-0
.02
00
.00
6-
0.2
87
0.0
50
0.0
08
0.0
04
––
56
6.4
10
.7
Tre
esp
ecie
sri
chn
ess
0.5
13
0.1
99
0.0
23
0.0
15
-0
.21
50
.07
3–
–1
94
.56
.9
Nu
mb
ero
fev
erg
reen
tree
seed
lin
gs
0.1
42
0.3
86
-0
.03
10
.00
8-
0.3
09
0.0
56
0.0
10
0.0
04
––
50
4.7
10
.4
Sp
ecie
sri
chn
ess
of
ever
gre
entr
ee
seed
lin
gs
0.0
05
0.1
76
-0
.18
40
.08
9–
–1
80
.42
.6
Nu
mb
ero
fd
ecid
uo
us
tree
seed
lin
gs
-0
.32
40
.35
50
.04
50
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0-
0.2
67
0.1
04
––
34
1.1
4.4
Sp
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chn
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of
dec
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ou
str
ee
seed
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gs
-0
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.9
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50
7.9
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Sp
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2.6
2.8
Th
eb
est
mo
del
was
sele
cted
acco
rdin
gto
the
val
ue
of
Ak
aik
e’s
info
rmat
ion
crit
erio
n(A
IC)
for
each
of
ten
resp
on
sev
aria
ble
s.T
he
top
fiv
eco
mp
etin
gm
od
els
are
com
par
edin
Tab
le6
inap
pen
dix
for
fore
st–
fiel
dg
rad
ien
ts,
Tab
le7
inap
pen
dix
for
aban
do
ned
fiel
ds,
and
Tab
le8
inap
pen
dix
for
fore
stin
teri
ors
aA
ban
do
nm
ent
per
iod
was
anal
yze
do
nly
inth
eab
and
on
edfi
eld
dat
aset
Plant Ecol (2011) 212:923–944 931
123
vegetation openness and the tallest vegetation height.
Grass and S. altissima dominance left larger vegeta-
tion openness.
Discussion
Irrespective of habitat, the best-fitted models selected
vegetation openness as a positive parameter (Table 3).
Evergreen trees are shade tolerant and form the main
components of the local climax forest community in
the study region (Kira 1991; Fukushima 2005). The
GLMMs suggested a positive response of evergreen
tree seedlings to greater vegetation openness in the
forest–field and field-only data. This result indicates
that dense vegetation on the abandoned fields pre-
vented light penetration to the soil and limited tree
seedling establishment. On the other hand, the GLMM
of the number of evergreen tree seedlings in the forest
interior showed weaker influence of vegetation open-
ness. This result suggests that the light environments
under the forest canopy at our sites were relatively
homogeneous and not as influential on the shade-
tolerant evergreen seedlings as in some abandoned
fields. Many different functional groups are composed
of competitive plants which hinder regionally typical
reforestation (Royo and Carson 2006; Young and
Peffer 2010). In the biotically complex tropics, the
invasion of competitive plants into an abandoned field
Table 4 Indicator values (IVs) of significant indicator species
in quadrats in abandoned fields (n = 227)
Vegetation type I II III IV V VI P value
No. quadrats 63 9 61 40 12 42
Significant indicator species
Liana layer
Wisteria floribunda 8 17 0 0 0 0 0.030
Pueraria lobata 1 0 62 2 17 0 0.001
Humulus japonicus 0 0 46 0 0 0 0.001
Amphicarpaea bracteata 0 0 0 16 0 2 0.022
Glycine max 0 0 0 14 0 0 0.023
Trichosanthescucumeroides
0 0 0 3 84 0 0.001
Paederia scandens 0 1 0 9 0 28 0.002
Herb layer
Pleioblastus chino 62 1 11 1 10 0 0.001
Pueraria lobata 0 56 0 0 0 0 0.001
Humulus japonicus 0 55 0 0 0 0 0.001
Phytolacca americana 0 20 0 0 0 0 0.003
Miscanthus sinensis 0 0 0 26 0 0 0.003
Imperata cylindrica 0 0 0 14 0 0 0.025
Broussonetia kazinoki 0 0 3 0 23 0 0.007
Solidago altissima 0 0 3 23 1 68 0.001
Lespedeza cuneata 0 0 0 0 0 10 0.027
IV is percentage of vegetation type difference based on relative
abundance and relative frequency of species. Six vegetation types
were classified by hierarchical clustering pruned on the basis of
average P values and the number of significant indicators
IV in bold indicates which vegetation type is represented by the
species listed
Fig. 3 Box and whisker plots of a vegetation openness and
b vegetation height of the six types of quadrat vegetation:
I, dominated by P. chino; II, dominated by P. lobata and
H. japonicus and lacking dominant herbs; III, dominated by
P. lobata and H. japonicus in the liana layer; IV, dominated by
grasses and S. altissima; V, dominated by T. cucumeroides in
the liana layer; and VI, dominated by S. altissima. Differentletters indicate significant difference between pairs of param-
eters (Steel–Dwass test, P \ 0.05)
932 Plant Ecol (2011) 212:923–944
123
hindered reforestation (Cramer et al. 2008). In our
fields, the dominance of vines, such as P. lobata,
H. japonicus, and T. cucumeroides, and a dwarf
bamboo, P. chino, corresponded to lower vegetation
openness (Table 4, Fig. 3). Among them, P. lobata
and P. chino, which expand by clonal growth, are
prevalent across the study region. Young and Peffer
(2010) also cited P. lobata and dwarf bamboos (genus
Sasa) as competitive plants hindering reforestation. In
forest ecosystems, Sasa severely inhibits tree seedling
survival by shading and gives herbivores safe foraging
sites under its dense evergreen culms (Ida and
Nakagoshi 1996; Iida 2004; Ito and Hino 2005;
Maruyama et al. 2004; Narukawa and Yamamoto
2002; Wada 1993). Similarly, P. chino in forests and
mowed grasslands (Kobayashi et al. 1998, 1999) and
P. lobata on a road embankment (Hoshiko 1999)
competitively affected plant species diversity or the
reforestation pathway. These results suggest that the
dominance of competitive native plants may limit
seedling establishment in abandoned fields as well as
in other habitats.
Vegetation height (as well as vegetation openness)
seemed to reflect a limitation on tree seedling
establishment because the parameter estimated by
the GLMMs was negative in most models. Its
contribution to model improvement was highest in
the three better-fitted response variables of forest
interior data (numbers of all tree seedlings, evergreen
seedlings, and seedlings dispersed by hoarding).
Vegetation height of forest floor quadrats was weakly
and positively correlated with distance from forest
edge (Spearman’s rho = 0.31, P \ 0.001). This
result indicates that the edge environment made the
forest floor vegetation taller and limited the estab-
lishment of the above tree seedlings. Previous studies
stated that the condition of adjacent vegetation
strongly influenced the seedling population at the
forest edge (reviewed by Harper et al. 2005).
Cadenasso and Pickett (2000) revealed that seedling
damage by voles was greater in intact edge vegetation
than in thinned edge plots. The limitation of seedling
establishment by taller understory vegetation at the
forest edge at our sites may have a similar origin and
be explained by the influence of the adjacent
abandoned field vegetation. In part, the presence of
the clonal dwarf bamboo P. chino across the forest–
field ecotone causes an edge–field interaction. Mono-
dominant tall culms of the dwarf bamboo on the
abandoned fields at sites 1, 3, and 5 probably
contributed a higher culm density and taller culm
presence at the edges than in the forest interior
because dwarf bamboo culms at open sites translocate
carbon to ramets in adjacent shaded habitats (Saitoh
et al. 2002).
In the forest–field data, most competing models
indicated a negative effect of distance from the forest
edge on all measures of seedling establishment
(Table 6 in appendix). Seedling number and species
richness were higher in the forest interior than within
the fields (Fig. 2). The selection of distance from the
forest edge in most models of the forest–field dataset
may reflect the contrasting suitability of seedling
establishment along the transects. Yet in the field-
only data, models of the number and richness of
evergreen tree seedlings and of the number of tree
seedlings dispersed by hoarding gave a better corre-
lation with distance from the forest edge (Table 3). In
contrast, a poor fit of the explanatory variables to
seedlings dispersed by ingestion suggests that the
transect scale is too small and the chance of seed
dispersal from adjacent forests by birds is almost the
same across each field. The dispersal of zoochorous
species in forest and urban ecosystems was highest
near seed sources and decreased with increasing
distance (Iida 2004; Komuro and Koike 2005); and
acorns of Q. serrata were found within 45 m of the
mother trees (Iida 2004). Our transects reached 30 m
from the forest edge. If seed dispersal from the forest
to the field is similar to that in forests, then more
seeds would land closer to the forest edge, especially
those of zoochorous species such as oaks. Therefore,
the effects of distance from the forest edge on
seedling establishment seen in the field-only dataset
might reflect seed input abundance because more
than half of the evergreen tree seedlings in fields were
Q. myrsinaefolia (28/49) and all tree seedlings
dispersed by hoarding belonged to the Fagaceae
(Table 5 in appendix). However, the behavior of
mice, the main acorn dispersers, differed among
structurally different vegetation patches (Wada
1993). A precise understanding of their behavior in
non-canopy abandoned fields would be important for
clarifying the dispersal of acorns. In addition, the
much lower seedling establishment in the fields might
also imply the effects of microsite limitations, for
example, the intensity of herbivory by insects and
mammals, which varied across different vegetation
Plant Ecol (2011) 212:923–944 933
123
patches (Cadenasso and Pickett 2000; Louda 1989;
Meiners et al. 2000). Here, the effects of seed and
microsite limitations with distance from the forest
edge were not distinguishable because of the lack of
direct observation of seed input and herbivory.
Therefore, seed input and herbivory of seeds and
seedlings in forest-field ecotones must be monitored
to reveal the mechanisms underlying the distance-
dependent limitations.
The effect of soil salinity on the seedlings was less
obvious among the explanatory variables except in
the number of tree seedlings dispersed by hoarding in
field-only data. The result suggests that the soil
salinity detected at our sites does not greatly influ-
ence the pattern of tree seedling recruitment. From a
physiological perspective, excess soil nutrients some-
times harm tree seedlings; for example, nitrate
reduced the survival of tree seedlings (Catovsky
and Bazzaz 2002; Mandak and Pysek 2001), and
phosphate reduced plant biomass (Standish et al.
2007b). The negative influence of higher soil salinity
on the tree seedlings dispersed by hoarding in the
field-only data may indicate a direct negative effect
of soil nutrient status on their establishment in the
abandoned fields. In addition, in the northern USA,
soil nutrient status influenced the pattern or rate of
succession (Gleeson and Tilman 1990; Inouye et al.
1987; Inouye and Tilman 1988). Therefore, if soil
salinity strongly influences the community assem-
blage after abandonment in our study region, its
indirect contribution to limiting the success of tree
seedling establishment by altering the revegetation
pathway cannot be ignored. These direct and indirect
effects of soil status need to be experimentally
examined to elucidate the soil-related pattern of
evergreen tree seedling establishment at our sites.
Diverse trajectories of vegetation development in
abandoned fields were recently recognized (Cramer
et al. 2008; Hobbs and Cramer 2007; Standish et al.
2007a). The diversity was proposed to be due to past
agricultural activities, which altered biotic and abi-
otic conditions. Our analyses show that some fields
abandoned for several decades still have few seed-
lings, and that time since abandonment was not
correlated well with the establishment of tree seed-
lings in the fields (Table 3). The main causes of the
slow seedling establishment seem to be the domi-
nance of competitive natives and the distance from
the seed source.
The effect of distance from the seed source needs
further study to clarify the relative importance of seed
limitations and microsite limitations, including her-
bivory intensity, which may vary across forest–field
ecotones. However, the association between vegeta-
tion openness and seedling emergence indicates that
using active restoration measures to control compe-
tition is essential for quick reforestation in the study
region. The effectiveness of other active reforestation
measures, such as seed broadcasting, seedling trans-
planting, and herbivory control, are still unclear and
therefore need further study. Moreover, our results
imply the importance of both field management and
the management of field edges and adjacent vegeta-
tion because clonal plants, such as dwarf bamboo,
and woody vines will invade newly abandoned
farmland from adjacent land. In addition, some
seedlings at the forest edge seemed to suffer from
more severe limitations than those in the forest
interior. This growth depression may be partly caused
by the regeneration of vegetation in the adjacent
abandoned field. Therefore, management of aban-
doned fields and adjacent vegetation is important for
the success of tree seedling establishment and
reforestation in forest–field ecotones.
Acknowledgments We thank H. Yamaguchi and T. Ara of
the experimental farm management division of NIAES for their
support in the field surveys.
Appendix
See Tables 5, 6, 7, and 8.
934 Plant Ecol (2011) 212:923–944
123
Ta
ble
5N
um
ber
of
seed
lin
gs
fou
nd
atth
e1
1st
ud
ysi
tes,
leaf
ph
eno
log
y,
pla
nt
size
,an
dse
edd
isp
ersa
lty
pes
Sp
ecie
sL
eaf
ph
eno
log
yP
lan
tsi
zea
Mic
rosi
teA
ban
do
ned
fiel
dF
ore
st
Sit
e1
23
45
67
89
10
11
12
34
56
78
91
01
1
No
.q
uad
rats
21
21
21
21
21
21
20
21
21
21
18
18
18
18
18
18
18
12
18
18
18
18
See
dd
isp
ersa
lty
peb
Qu
ercu
sm
yrsi
na
efo
lia
Ev
erg
reen
Tre
eA
nim
al(H
)7
44
19
–3
––
––
83
29
36
32
15
22
35
8–
–
Cel
tis
sin
ensi
sD
ecid
uo
us
Tre
eA
nim
al(I
)–
––
––
–9
–1
37
–1
62
9–
10
12
94
20
5–
Lig
ust
rum
ob
tusi
foli
um
Sem
i-ev
erg
reen
Sh
rub
An
imal
(I)
––
––
––
––
––
––
1–
––
––
–1
48
1
Bro
uss
on
etia
kazi
no
kiD
ecid
uo
us
Sh
rub
An
imal
(I)
–7
––
––
12
11
5–
––
2–
––
––
––
––
Lig
ust
rum
jap
on
icu
mE
ver
gre
enS
hru
bA
nim
al(I
)–
––
––
––
––
––
–3
––
––
33
––
––
Ap
ha
na
nth
ea
sper
aD
ecid
uo
us
Tre
eA
nim
al(I
)–
–2
––
–2
11
1–
11
0–
1–
18
––
5–
Qu
ercu
sse
rra
taD
ecid
uo
us
Tre
eA
nim
al(H
)–
–1
–1
––
15
2–
––
12
21
––
41
––
Neo
lits
ease
rice
aE
ver
gre
enT
ree
An
imal
(I)
––
––
––
––
––
––
11
21
24
–3
–1
5
Pru
nu
sg
raya
na
Dec
idu
ou
sT
ree
An
imal
(I)
––
4–
––
12
––
–1
11
–2
21
1–
1–
–
Au
cub
aja
po
nic
aE
ver
gre
enS
hru
bA
nim
al(I
)–
–1
––
––
––
––
–1
12
5–
–1
1–
––
Rh
us
java
nic
aD
ecid
uo
us
Su
b-t
ree
An
imal
(I)
––
6–
––
–1
0–
––
–1
––
1–
––
–2
–
Eu
rya
jap
on
ica
Ev
erg
reen
Su
b-t
ree
An
imal
(I)
––
––
––
––
––
–1
––
–1
14
–2
1–
–
Eu
on
ymu
sa
latu
sD
ecid
uo
us
Sh
rub
An
imal
(I)
2–
––
1–
––
––
–2
5–
––
––
11
3–
Tra
chyc
arp
us
fort
un
eiE
ver
gre
enS
ub
-tre
eA
nim
al(I
)–
––
––
––
––
––
––
––
––
––
–2
13
Ca
mel
lia
sin
ensi
sE
ver
gre
enS
hru
bG
rav
ity
––
––
––
––
––
––
–3
1–
––
––
65
Pru
nu
sb
uer
ger
ian
aD
ecid
uo
us
Tre
eA
nim
al(I
)–
––
––
–2
7–
1–
––
––
––
–2
––
–
Cry
pto
mer
iaja
po
nic
aE
ver
gre
enT
ree
Win
d–
–1
0–
––
1–
1–
––
––
––
––
––
––
Vib
urn
um
dil
ata
tum
Dec
idu
ou
sS
hru
bA
nim
al(I
)1
––
––
––
1–
––
52
––
––
––
––
–
Ca
sta
nea
cren
ata
Dec
idu
ou
sT
ree
An
imal
(H)
––
––
1–
–1
–1
––
22
––
––
1–
1–
Sym
plo
cos
core
an
aD
ecid
uo
us
Sh
rub
An
imal
(I)
––
––
––
––
––
–8
––
––
––
––
––
Ch
am
aec
ypa
ris
ob
tusa
Ev
erg
reen
Tre
eG
rav
ity
––
––
––
––
7–
––
––
––
––
––
––
Ma
llo
tus
jap
on
icu
sD
ecid
uo
us
Tre
eA
nim
al(I
)–
––
––
––
4–
––
–1
––
––
–1
––
–
Ilex
rotu
nd
aE
ver
gre
enT
ree
An
imal
(I)
––
––
––
––
––
–6
––
––
––
––
––
Ma
gn
oli
ap
raec
oci
ssim
aD
ecid
uo
us
Tre
eA
nim
al(I
)1
––
––
––
––
––
3–
––
––
2–
––
–
Zel
kova
serr
ata
Dec
idu
ou
sT
ree
Win
d–
––
––
––
––
––
–5
––
––
––
––
–
Ace
rp
alm
atu
mD
ecid
uo
us
Tre
eW
ind
––
––
––
––
––
––
4–
––
––
––
––
Deu
tzia
cren
ata
Dec
idu
ou
sS
hru
bW
ind
––
––
––
–2
–2
––
––
––
––
––
––
Ma
chil
us
thu
nb
erg
iiE
ver
gre
enT
ree
An
imal
(I)
––
––
––
––
––
––
––
––
3–
––
1–
Ilex
cren
ata
Ev
erg
reen
Sh
rub
An
imal
(I)
1–
––
––
––
––
–1
––
––
–1
––
––
Sty
rax
jap
on
ica
Dec
idu
ou
sS
ub
-tre
eA
nim
al(H
)–
––
––
––
––
––
–3
––
––
––
––
–
Plant Ecol (2011) 212:923–944 935
123
Ta
ble
5co
nti
nu
ed
Sp
ecie
sL
eaf
ph
eno
log
yP
lan
tsi
zea
Mic
rosi
teA
ban
do
ned
fiel
dF
ore
st
Sit
e1
23
45
67
89
10
11
12
34
56
78
91
01
1
No
.q
uad
rats
21
21
21
21
21
21
20
21
21
21
18
18
18
18
18
18
18
12
18
18
18
18
See
dd
isp
ersa
lty
peb
Za
nth
oxy
lum
sch
inif
oli
um
Ev
erg
reen
Sh
rub
An
imal
(I)
––
––
––
––
––
–1
1–
––
––
––
––
Za
nth
oxy
lum
pip
erit
um
Dec
idu
ou
sS
hru
bA
nim
al(I
)–
––
––
––
––
––
1–
––
––
––
–1
–
Ca
llic
arp
aja
po
nic
aD
ecid
uo
us
Sh
rub
An
imal
(I)
––
––
––
––
––
––
––
–2
––
––
––
Rh
us
tric
ho
carp
aD
ecid
uo
us
Su
b-t
ree
An
imal
(I)
––
––
––
––
––
–1
1–
––
––
––
––
Ch
aen
om
eles
jap
on
ica
Dec
idu
ou
sS
hru
bA
nim
al(I
)–
––
––
––
––
––
1–
––
––
––
––
–
Qu
ercu
sa
cuti
ssim
aD
ecid
uo
us
Tre
eA
nim
al(H
)–
––
––
–1
––
––
––
––
––
––
––
–
Eu
on
ymu
sa
latu
sD
ecid
uo
us
Sh
rub
An
imal
(I)
––
––
––
––
––
––
––
––
––
––
–1
Sa
mb
ucu
sra
cem
osa
Dec
idu
ou
sS
hru
bA
nim
al(I
)–
––
––
––
––
––
––
––
–1
––
––
–
Ka
lop
an
ax
pic
tus
Dec
idu
ou
sT
ree
An
imal
(I)
––
––
––
––
––
––
1–
––
––
––
––
Ca
mel
lia
jap
on
ica
Ev
erg
reen
Su
b-t
ree
Gra
vit
y–
––
––
––
––
––
––
––
––
1–
––
–
Mo
rus
au
stra
lis
Dec
idu
ou
sS
ub
-tre
eA
nim
al(I
)1
––
––
––
––
––
––
––
––
––
––
–
Pru
nu
sja
ma
saku
raD
ecid
uo
us
Tre
eA
nim
al(I
)–
––
––
––
––
––
––
––
–1
––
––
–
aT
ree[
10
m,
sub
-tre
e5
–1
0m
,sh
rub\
5m
bA
nim
al(I
),d
isp
erse
dv
iain
ges
tio
n;
An
imal
(H),
dis
per
sed
via
ho
ard
ing
by
rod
ents
or
bir
ds
936 Plant Ecol (2011) 212:923–944
123
Ta
ble
6C
om
par
iso
no
fth
eto
pfi
ve
gen
eral
ized
lin
ear
mix
edm
od
els
of
seed
lin
gre
spo
nse
tofo
ur
exp
lan
ato
ryv
aria
ble
sal
on
gfo
rest
–fi
eld
gra
die
nts
(n=
41
9)
Res
po
nse
var
iab
les
Par
amet
eres
tim
ate
and
stan
dar
der
ror
(SE
)o
fex
pla
nat
ory
var
iab
les
AIC
DA
ICP
erce
nta
ge
dev
ian
ce
exp
lain
ed(I
nte
rcep
t)S
EV
eget
atio
n
op
enn
ess
SE
Dis
tan
cefr
om
fore
sted
ge
SE
Veg
etat
ion
hei
gh
t
SE
So
il
sali
nit
y
SE
Tre
ese
edli
ng
sn
um
ber
0.3
33
0.3
70
0.0
73
0.0
13
-0
.04
10
.00
5-
0.1
99
0.0
70
11
58
.00
.03
0.9
0.1
95
0.4
51
0.0
74
0.0
13
-0
.04
30
.00
6-
0.1
92
0.0
70
0.0
03
0.0
05
11
59
.11
.13
0.9
-0
.25
50
.43
30
.08
00
.01
3-
0.0
50
0.0
05
0.0
06
0.0
05
11
81
.82
3.8
29
.4
-0
.01
20
.36
10
.07
80
.01
3-
0.0
47
0.0
05
11
83
.32
5.3
29
.2
0.9
35
0.3
39
-0
.04
40
.00
6-
0.2
43
0.0
73
12
27
.36
9.3
26
.6
Tre
esp
ecie
sri
chn
ess
-0
.36
00
.15
60
.06
90
.00
8-
0.0
30
0.0
03
-0
.12
10
.04
64
60
.80
.02
5.6
-0
.25
30
.21
30
.06
80
.00
8-
0.0
29
0.0
04
-0
.12
40
.04
6-
0.0
02
0.0
04
46
2.5
1.7
25
.6
-0
.58
30
.13
50
.07
30
.00
8-
0.0
34
0.0
03
46
3.4
2.6
24
.8
-0
.52
00
.19
30
.07
30
.00
8-
0.0
34
0.0
03
-0
.00
20
.00
44
65
.34
.52
4.8
0.2
55
0.1
35
-0
.03
10
.00
4-
0.1
84
0.0
49
49
5.7
34
.91
9.5
Nu
mb
ero
fev
erg
reen
tree
seed
lin
gs
-0
.85
50
.25
30
.10
80
.00
9-
0.0
62
0.0
03
-0
.26
70
.03
18
11
.10
.03
8.7
-1
.00
90
.28
00
.11
00
.00
9-
0.0
64
0.0
03
-0
.25
80
.03
10
.00
30
.00
38
12
.51
.53
8.8
-1
.64
60
.27
10
.11
90
.00
9-
0.0
72
0.0
03
0.0
08
0.0
03
83
9.2
28
.13
6.6
-1
.27
60
.25
80
.11
50
.01
0-
0.0
67
0.0
03
84
1.2
30
.23
6.3
-0
.01
50
.22
5-
0.0
70
0.0
03
-0
.28
80
.03
68
48
.83
7.8
35
.7
Sp
ecie
sri
chn
ess
of
ever
gre
en
tree
seed
lin
gs
-1
.24
30
.11
20
.06
00
.00
8-
0.0
52
0.0
03
-0
.12
50
.03
13
22
.80
.02
7.2
-1
.46
80
.09
30
.06
40
.00
8-
0.0
57
0.0
03
32
3.5
0.7
26
.6
-1
.13
60
.15
70
.05
90
.00
8-
0.0
51
0.0
03
-0
.12
70
.03
1-
0.0
02
0.0
03
32
4.7
1.9
27
.3
-1
.39
70
.13
80
.06
40
.00
8-
0.0
56
0.0
03
-0
.00
20
.00
33
25
.42
.62
6.6
-0
.75
90
.08
2-
0.0
55
0.0
03
-0
.14
80
.03
23
27
.54
.72
5.6
Nu
mb
ero
fd
ecid
uo
us
tree
seed
lin
gs
-0
.98
50
.33
40
.06
20
.00
9-
0.0
11
0.0
04
-0
.21
30
.06
00
.00
80
.00
46
90
.80
.08
.6
-0
.63
60
.27
60
.05
90
.00
9-
0.0
08
0.0
04
-0
.21
70
.06
16
91
.10
.38
.3
-0
.52
00
.27
10
.05
80
.00
9-
0.2
95
0.0
51
69
2.3
1.5
7.9
-0
.66
50
.31
20
.05
90
.00
9-
0.3
06
0.0
52
0.0
04
0.0
04
69
3.7
2.9
8.0
-1
.38
30
.32
20
.06
90
.00
9-
0.0
19
0.0
03
0.0
08
0.0
04
69
7.0
6.2
7.5
Sp
ecie
sri
chn
ess
of
dec
idu
ou
s
tree
seed
lin
gs
-1
.41
80
.14
80
.07
70
.00
6-
0.0
16
0.0
02
41
8.9
0.0
9.7
-1
.20
20
.16
60
.07
30
.00
7-
0.0
12
0.0
03
-0
.11
80
.04
64
19
.10
.21
0.1
-1
.21
60
.19
10
.07
60
.00
6-
0.0
14
0.0
03
-0
.00
50
.00
34
20
.41
.49
.8
-0
.96
80
.20
80
.07
20
.00
7-
0.0
10
0.0
03
-0
.12
20
.04
6-
0.0
05
0.0
03
42
0.4
1.5
10
.3
-0
.69
40
.19
00
.07
00
.00
7-
0.1
98
0.0
40
-0
.00
90
.00
34
21
.02
.09
.7
Plant Ecol (2011) 212:923–944 937
123
Ta
ble
6co
nti
nu
ed
Res
po
nse
var
iab
les
Par
amet
eres
tim
ate
and
stan
dar
der
ror
(SE
)o
fex
pla
nat
ory
var
iab
les
AIC
DA
ICP
erce
nta
ge
dev
ian
ce
exp
lain
ed(I
nte
rcep
t)S
EV
eget
atio
n
op
enn
ess
SE
Dis
tan
cefr
om
fore
sted
ge
SE
Veg
etat
ion
hei
gh
t
SE
So
il
sali
nit
y
SE
Nu
mb
ero
ftr
eese
edli
ng
sd
isp
erse
d
by
anim
alin
ges
tio
n
-0
.76
90
.28
00
.06
40
.00
9-
0.0
39
0.0
05
-0
.13
30
.06
30
.01
10
.00
48
42
.70
.02
0.4
-1
.03
50
.26
70
.06
80
.00
9-
0.0
44
0.0
04
0.0
12
0.0
04
84
5.1
2.4
20
.0
-0
.27
70
.19
90
.06
30
.00
9-
0.0
35
0.0
04
-0
.14
50
.06
38
47
.44
.71
9.8
-0
.54
10
.18
50
.06
70
.00
9-
0.0
40
0.0
04
85
0.7
7.9
19
.3
-0
.15
20
.26
7-
0.0
39
0.0
05
-0
.21
00
.06
20
.01
10
.00
48
80
.33
7.6
16
.6
Sp
ecie
sri
chn
ess
of
tree
seed
lin
gs
dis
per
sed
by
anim
alin
ges
tio
n
-0
.77
80
.21
50
.06
60
.01
1-
0.0
26
0.0
05
-0
.16
30
.07
84
22
.40
.01
8.4
-0
.88
90
.31
50
.06
60
.01
2-
0.0
27
0.0
06
-0
.15
90
.07
80
.00
30
.00
54
24
.21
.81
8.4
-1
.07
70
.18
30
.07
20
.01
1-
0.0
31
0.0
05
42
4.7
2.4
17
.5
-1
.23
60
.29
10
.07
20
.01
1-
0.0
33
0.0
05
0.0
04
0.0
06
42
6.3
3.9
17
.6
-0
.47
10
.20
20
.06
30
.01
1-
0.3
53
0.0
71
44
3.7
21
.41
3.8
Nu
mb
ero
ftr
eese
edli
ng
sd
isp
erse
d
by
anim
alh
oar
din
g
-1
.24
50
.55
20
.08
20
.02
2-
0.0
55
0.0
05
-0
.26
90
.05
26
82
.00
.03
1.8
-1
.14
30
.59
80
.08
00
.02
3-
0.0
54
0.0
06
-0
.27
60
.05
5-
0.0
02
0.0
05
68
3.9
1.8
31
.9
-0
.61
60
.46
7-
0.0
62
0.0
05
-0
.28
20
.05
26
90
.78
.73
0.8
-0
.42
20
.50
5-
0.0
59
0.0
06
-0
.29
60
.05
4-
0.0
04
0.0
05
69
1.9
9.9
30
.8
-1
.70
20
.53
70
.09
30
.02
1-
0.0
60
0.0
05
70
9.0
26
.92
8.9
Sp
ecie
sri
chn
ess
of
tree
seed
lin
gs
dis
per
sed
by
anim
alh
oar
din
g
-0
.74
30
.34
8-
0.0
40
0.0
08
-0
.01
60
.00
82
69
.20
.01
6.0
-0
.55
20
.39
4-
0.0
35
0.0
08
-0
.10
70
.08
6-
0.0
16
0.0
08
26
9.6
0.4
16
.5
-0
.94
60
.42
10
.02
20
.02
9-
0.0
39
0.0
08
-0
.01
50
.00
82
70
.71
.51
6.2
-1
.38
20
.25
5-
0.0
45
0.0
07
27
1.0
1.8
14
.8
-0
.71
50
.47
40
.01
70
.03
0-
0.0
34
0.0
08
-0
.10
10
.08
7-
0.0
16
0.0
08
27
1.3
2.1
16
.6
938 Plant Ecol (2011) 212:923–944
123
Ta
ble
7C
om
par
iso
no
fth
eto
pfi
ve
gen
eral
ized
lin
ear
mix
edm
od
els
of
seed
lin
gre
spo
nse
tofi
ve
exp
lan
ato
ryv
aria
ble
sin
aban
do
ned
fiel
ds
(n=
22
7)
Res
po
nse
var
iab
les
Par
amet
eres
tim
ate
and
stan
dar
der
ror
(SE
)o
fex
pla
nat
ory
var
iab
les
AIC
DA
ICP
erce
nta
ge
dev
ian
ce
exp
lain
ed(I
nte
rcep
t)S
EV
eget
atio
n
op
enn
ess
SE
Dis
tan
ce
fro
m
fore
st
edg
e
SE
Veg
etat
ion
hei
gh
t
SE
So
il
sali
nit
y
SE
Ab
and
on
ed
per
iod
SE
Tre
ese
edli
ng
sn
um
ber
-0
.78
10
.59
20
.09
00
.01
8-
0.3
83
0.1
16
31
3.0
0.0
11
.1
-0
.70
70
.59
20
.09
20
.01
8-
0.0
08
0.0
08
-0
.37
40
.11
63
13
.90
.91
1.4
-0
.71
10
.66
80
.08
90
.01
9-
0.3
82
0.1
16
-0
.00
10
.00
73
15
.02
.01
1.1
-0
.69
51
.18
60
.09
40
.01
8-
0.3
82
0.1
17
-0
.04
10
.48
33
15
.02
.01
1.1
-0
.79
20
.67
80
.09
20
.01
9-
0.0
09
0.0
09
-0
.37
50
.11
60
.00
20
.00
83
15
.92
.91
1.4
Tre
esp
ecie
sri
chn
ess
-1
.63
70
.41
00
.10
80
.02
1-
0.0
16
0.0
10
20
5.4
0.0
10
.6
-1
.23
30
.53
60
.10
30
.02
1-
0.0
15
0.0
10
-0
.20
40
.14
02
05
.40
.01
1.5
-0
.75
30
.64
50
.08
90
.02
2-
0.2
11
0.1
39
-0
.01
30
.00
92
05
.50
.01
1.5
-1
.18
90
.54
50
.09
40
.02
2-
0.0
13
0.0
09
20
5.6
0.2
10
.5
-1
.36
70
.53
40
.09
90
.02
2-
0.2
17
0.1
41
20
5.7
0.3
10
.5
Nu
mb
ero
fev
erg
reen
tree
seed
lin
gs
-1
.82
20
.93
40
.15
30
.03
2-
0.0
66
0.0
21
-0
.65
60
.19
41
54
.80
.02
4.2
-3
.18
21
.67
60
.15
70
.03
2-
0.0
66
0.0
21
-0
.65
30
.19
30
.64
70
.64
51
55
.91
.12
4.7
-1
.54
01
.05
60
.14
80
.03
4-
0.0
61
0.0
23
-0
.63
60
.19
5-
0.0
07
0.0
16
15
6.6
1.8
24
.3
-2
.84
61
.74
10
.15
20
.03
4-
0.0
61
0.0
23
-0
.63
30
.19
4-
0.0
07
0.0
16
0.6
22
0.6
21
15
7.7
2.9
24
.8
-1
.15
60
.97
10
.12
30
.03
2-
0.5
27
0.1
83
-0
.03
00
.01
41
62
.77
.92
0.1
Sp
ecie
sri
chn
ess
of
ever
gre
en
tree
seed
lin
gs
-2
.97
90
.54
70
.14
30
.03
6-
0.0
45
0.0
24
11
2.7
0.0
13
.2
-1
.78
20
.81
70
.10
20
.03
6-
0.0
33
0.0
17
11
3.0
0.3
12
.9
-1
.89
30
.84
00
.11
50
.03
7-
0.0
32
0.0
25
-0
.02
40
.01
81
13
.10
.41
4.5
-3
.79
71
.04
80
.15
10
.03
7-
0.0
45
0.0
24
0.3
66
0.3
68
11
3.7
1.1
14
.0
-2
.66
20
.81
40
.14
30
.03
8-
0.0
47
0.0
24
-0
.19
10
.23
11
14
.11
.51
3.7
Nu
mb
ero
fd
ecid
uo
us
tree
seed
lin
gs
-1
.84
60
.51
80
.06
80
.02
22
47
.90
.03
.3
-1
.43
80
.61
90
.06
50
.02
2-
0.1
97
0.1
50
24
8.2
0.3
4.0
-0
.88
81
.05
60
.00
70
.02
2-
0.4
27
0.4
34
24
8.9
1.1
3.7
-2
.12
20
.64
10
.07
30
.02
30
.00
60
.00
82
49
.31
.53
.6
-1
.72
20
.72
50
.06
90
.02
3-
0.2
01
0.1
51
0.0
06
0.0
08
24
9.6
1.7
4.2
Plant Ecol (2011) 212:923–944 939
123
Ta
ble
7co
nti
nu
ed
Res
po
nse
var
iab
les
Par
amet
eres
tim
ate
and
stan
dar
der
ror
(SE
)o
fex
pla
nat
ory
var
iab
les
AIC
DA
ICP
erce
nta
ge
dev
ian
ce
exp
lain
ed(I
nte
rcep
t)S
EV
eget
atio
n
op
enn
ess
SE
Dis
tan
ce
fro
m
fore
st
edg
e
SE
Veg
etat
ion
hei
gh
t
SE
So
il
sali
nit
y
SE
Ab
and
on
ed
per
iod
SE
Sp
ecie
sri
chn
ess
of
dec
idu
ou
s
tree
seed
lin
gs
-2
.13
00
.45
30
.08
70
.02
61
72
.30
.05
.7
-1
.81
90
.59
00
.08
40
.02
6-
0.1
48
0.1
71
17
3.5
1.3
6.2
-1
.74
50
.63
70
.08
10
.02
6-
0.0
08
0.0
10
17
3.6
1.3
6.1
-1
.46
40
.93
50
.08
40
.02
6-
0.2
94
0.3
77
17
3.7
1.4
6.1
-2
.05
50
.46
60
.08
90
.02
6-
0.0
07
0.0
11
17
3.9
1.6
6.0
Nu
mb
ero
ftr
eese
edli
ng
s
dis
per
sed
by
anim
alin
ges
tio
n
-2
.01
80
.53
00
.06
90
.02
42
39
.80
.03
.1
-2
.49
60
.66
90
.07
60
.02
50
.01
00
.00
82
40
.40
.63
.7
-0
.82
71
.07
10
.06
60
.02
4-
0.5
34
0.4
47
24
0.4
0.6
3.7
-1
.32
81
.18
30
.07
30
.02
50
.00
90
.00
8-
0.5
13
0.4
57
24
1.2
1.4
4.2
-1
.74
20
.63
80
.06
60
.02
4-
0.1
29
0.1
66
24
1.2
1.4
3.4
Sp
ecie
sri
chn
ess
of
tree
seed
lin
gs
dis
per
sed
by
anim
alin
ges
tio
n
-2
.28
70
.45
50
.08
70
.02
71
60
.70
.05
.4
-1
.42
70
.93
20
.08
20
.02
8-
0.3
82
0.3
81
16
1.7
1.0
6.0
-2
.00
60
.66
60
.08
30
.02
8-
0.0
06
0.0
11
16
2.4
1.7
5.6
-2
.23
10
.47
30
.08
90
.02
7-
0.0
05
0.0
13
16
2.5
1.8
5.5
-2
.16
70
.61
20
.08
60
.02
8-
0.0
55
0.1
88
16
2.6
1.9
5.4
Nu
mb
ero
ftr
eese
edli
ng
s
dis
per
sed
by
anim
alh
oar
din
g
0.2
53
0.5
72
-0
.03
40
.01
9-
0.0
46
0.0
15
16
9.8
0.0
10
.6
0.6
09
0.6
67
-0
.03
20
.01
9-
0.2
35
0.1
62
-0
.04
40
.01
51
70
.00
.21
1.6
-0
.15
70
.70
30
.04
40
.04
3-
0.0
38
0.0
19
-0
.04
20
.01
51
70
.91
.11
1.1
0.1
46
0.8
01
0.0
50
0.0
45
-0
.03
60
.02
0-
0.2
50
0.1
66
-0
.04
00
.01
51
71
.01
.11
2.2
0.6
46
0.6
73
-0
.27
00
.16
2-
0.0
53
0.0
14
17
1.2
1.3
9.8
Sp
ecie
sri
chn
ess
of
tree
seed
lin
gs
dis
per
sed
by
anim
alh
oar
din
g
-0
.52
80
.60
5-
0.0
38
0.0
14
81
35
.30
.04
.9
-0
.46
20
.60
6-
0.0
21
0.0
19
9-
0.0
33
0.0
15
31
36
.00
.75
.9
-0
.24
60
.74
8-
0.1
20
0.1
73
5-
0.0
39
0.0
14
91
36
.81
.65
.3
-0
.76
70
.73
10
.02
60
.04
45
-0
.03
60
.01
51
13
7.0
1.7
5.1
-0
.74
50
.86
2-
0.0
37
0.0
14
80
.08
90
.24
61
37
.11
.95
.1
940 Plant Ecol (2011) 212:923–944
123
Ta
ble
8C
om
par
iso
no
fth
eto
pfi
ve
gen
eral
ized
lin
ear
mix
edm
od
els
of
seed
lin
gre
spo
nse
tofo
ur
exp
lan
ato
ryv
aria
ble
sin
fore
stin
teri
or
(n=
19
2)
Res
po
nse
var
iab
les
Par
amet
eres
tim
ate
and
stan
dar
der
ror
(SE
)o
fex
pla
nat
ory
var
iab
les
AIC
DA
ICP
erce
nta
ge
dev
ian
ce
exp
lain
ed(I
nte
rcep
t)S
EV
eget
atio
n
op
enn
ess
SE
Dis
tan
ce
fro
m
fore
sted
ge
SE
Veg
etat
ion
hei
gh
t
SE
So
il
sali
nit
y
SE
Tre
ese
edli
ng
sn
um
ber
0.7
82
0.3
08
0.0
24
0.0
12
-0
.02
00
.00
6-
0.2
87
0.0
50
0.0
08
0.0
04
56
6.4
0.0
10
.7
1.0
12
0.2
83
-0
.02
00
.00
6-
0.3
00
0.0
49
0.0
07
0.0
04
56
7.9
1.5
10
.2
1.1
69
0.2
44
0.0
21
0.0
12
-0
.01
50
.00
6-
0.3
01
0.0
50
56
9.0
2.6
10
.0
1.3
44
0.2
22
-0
.01
50
.00
6-
0.3
12
0.0
50
56
9.8
3.4
9.5
1.3
34
0.2
34
0.0
22
0.0
12
-0
.32
10
.05
05
73
.57
.09
.0
Tre
esp
ecie
sri
chn
ess
0.5
13
0.1
99
0.0
23
0.0
15
-0
.21
50
.07
31
94
.50
.06
.9
0.7
28
0.1
41
-0
.24
00
.07
21
94
.70
.25
.8
0.4
17
0.2
35
0.0
24
0.0
15
-0
.00
70
.00
9-
0.1
97
0.0
76
19
5.9
1.4
7.2
0.6
46
0.2
53
0.0
24
0.0
15
-0
.21
10
.07
4-
0.0
04
0.0
05
19
6.0
1.4
7.1
0.6
42
0.1
83
-0
.00
70
.00
9-
0.2
24
0.0
74
19
6.2
1.6
6.0
Nu
mb
ero
fev
erg
reen
tree
seed
lin
gs
0.1
42
0.3
86
-0
.03
10
.00
8-
0.3
09
0.0
56
0.0
10
0.0
04
50
4.7
0.0
10
.4
0.0
60
0.4
43
0.0
10
0.0
27
-0
.03
00
.00
8-
0.3
06
0.0
57
0.0
11
0.0
04
50
6.6
1.9
10
.5
0.6
47
0.3
16
-0
.02
20
.00
7-
0.3
33
0.0
57
50
8.2
3.5
9.4
0.6
12
0.3
74
0.0
05
0.0
27
-0
.02
20
.00
7-
0.3
32
0.0
57
51
0.2
5.4
9.4
0.8
93
0.3
06
-0
.34
50
.05
65
15
.81
1.1
7.7
Sp
ecie
sri
chn
ess
of
ever
gre
entr
ee
seed
lin
gs
0.0
05
0.1
76
-0
.18
40
.08
91
80
.40
.02
.6
0.2
44
0.3
02
-0
.02
70
.02
9-
0.2
07
0.0
93
18
1.5
1.1
3.1
-0
.11
70
.23
2-
0.0
10
0.0
12
-0
.16
60
.09
11
81
.81
.42
.9
0.0
20
0.2
83
-0
.18
30
.09
00
.00
00
.00
61
82
.42
.02
.6
0.1
36
0.3
30
-0
.03
10
.03
1-
0.0
12
0.0
13
-0
.18
90
.09
41
82
.72
.33
.5
Nu
mb
ero
fd
ecid
uo
us
tree
seed
lin
gs
-0
.32
40
.35
50
.04
50
.02
0-
0.2
67
0.1
04
34
1.1
0.0
4.4
-0
.20
80
.38
80
.04
50
.02
00
.00
80
.01
2-
0.3
00
0.1
15
34
2.6
1.5
4.5
-0
.28
10
.41
60
.04
40
.02
0-
0.2
65
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43
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Plant Ecol (2011) 212:923–944 941
123
Ta
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30
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71
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81
33
.61
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.1
942 Plant Ecol (2011) 212:923–944
123
References
Arita H, Ohkuro T (2007a) A maintenance system aimed to
control wood vegetation of abandoned paddy field-study
based on a survey of Ohshima-are Jouetsu-shi Niigata,
Japan. Trans Jpn Soc Irrig Drain Rural Eng 249:255–260
(In Japanese with English summary)
Arita H, Ohkuro T (2007b) The expense of restoring aban-
doned paddy fields invaded by trees to a sound condition-
study on a survey of Ohshima-are Jouetsu-shi Niigata,
Japan. Trans Jpn Soc Irrig Drain Rural Eng 249:247–254
(In Japanese with English summary)
Bates D, Maechler M, Dai B (2008) Linear mixed-effects
models using S4 classes. R package version 0.999375-28.
http://lme4.r-forge.r-project.org/. Accessed 13 Dec 2008
Cadenasso ML, Pickett STA (2000) Linking forest edge
structure to edge function: mediation of herbivore dam-
age. J Ecol 88:31–44
Catovsky S, Bazzaz FA (2002) Nitrogen availability influences
regeneration of temperate tree species in the understory
seedling bank. Ecol Appl 12:1056–1070
Chibaken-Shiryou-Kenkyuzaidan (2003) Chibaken-no-shizen-
shi (4) Chibaken-shokubutsushi [Natural Source Book of
Chiba Prefecture (4) Flora of Chiba Prefecture]. Chiba-
nippousha, Chiba (in Japanese)
Cramer VA, Hobbs RJ, Standish RJ (2008) What’s new about
old fields? Land abandonment and ecosystem assembly.
Trends Ecol Evol 23:104–112
Desteven D (1991a) Experiments on mechanisms of tree
establishment in old-field succession—seedling emer-
gence. Ecology 72:1066–1075
Desteven D (1991b) Experiments on mechanisms of tree
establishment in old-field succession—seedling survival
and growth. Ecology 72:1076–1088
Dufrene M, Legendre P (1997) Species assemblages and
indicator species: the need for a flexible asymmetrical
approach. Ecol Monogr 67:345–366
Dwass M (1960) Some k-sample rank-order tests. In: Olkin I
et al (eds) Contributions to probability and statistics.
Stanford university press, California, pp 198–202
Eriksson O, Ehrlen J (1992) Seed and microsite limitation of
recruitment in plant populations. Oecologia 91:360–364
Fukushima T (2005) Natural vegetation (climax) and substi-
tutional vegetation. In: Fukushima A, Iwase T (eds)
Nihon-no-shokusei [Vegetation of Japan]. Asakura Pub-
lishing Co. Ltd., Tokyo, pp 10–11 (in Japanese)
Givnish TJ (2002) Adaptive significance of evergreen vs.
deciduous leaves: solving the triple paradox. Silva
Fennica 36:703–743
Gleeson SK, Tilman D (1990) Allocation and the transient
dynamics of succession on poor soils. Ecology 71:1144–
1155
Harper KA, Macdonald SE, Burton PJ, Chen J, Brosofske KD,
Saunders SC, Euskirchen ES, Roberts D, Jaiteh MS,
Esseen PA (2005) Edge influence on forest structure and
composition in fragmented landscapes. Conserv Biol
19:768–782
Herrera LP, Laterra P (2009) Do seed and microsite limitation
interact with seed size in determining invasion patterns in
flooding Pampa grasslands? Plant Ecol 201:457–469
Hobbs RJ, Cramer VA (2007) Old field dynamics: regional and
local differences, and lessons for ecology and restoration.
In: Cramer VA, Hobbs RJ (eds) Old fields. Island Press,
Washington, pp 309–318
Holzel N (2005) Seedling recruitment in flood-meadow spe-
cies: the effects of gaps, litter and vegetation matrix. Appl
Veg Sci 8:115–124
Hoshiko T (1999) The influence of management to change of
Pinus densiflora community on man-made slopes along
expressway. J Jpn Soc Reveg Technol 25:25–34
Hoshizaki K, Suzuki W, Nakashizuka T (1999) Evaluation of
secondary dispersal in a large-seeded tree Aesculusturbinata: a test of directed dispersal. Plant Ecol 144:
167–176
Ida H, Nakagoshi N (1996) Gnawing damage by rodents to the
seedlings of Fagus crenata and Quercus mongolica var.
grosseserrata in a temperate Sasa grassland deciduous
forest series in southwestern Japan. Ecol Res 11:97–103
Iida S (1996) Quantitative analysis of acorn transportation by
rodents using magnetic locator. Vegetatio 124:39–43
Iida S (2004) Indirect negative influence of dwarf bamboo on
survival of Quercus acorn by hoarding behavior of wood
mice. For Ecol Manag 202:257–263
Inouye RS, Tilman D (1988) Convergence and divergence of
old-field plant-communities along experimental nitrogen
gradients. Ecology 69:995–1004
Inouye RS, Huntly NJ, Tilman D, Tester JR (1987) Pocket
gophers (Geomys bursarius), vegetation, and soil-nitrogen
along a successional sere in east central Minnesota.
Oecologia 72:178–184
Ito H, Hino T (2005) How do deer affect tree seedlings on a
dwarf bamboo-dominated forest floor? Ecol Res 20:
121–128
Kikuzawa K (1991) A cost-benefit analysis of leaf habit and
leaf longevity of trees and their geographic pattern. Am
Natural 138:1250–1263
Kira T (1991) Forest ecosystems of east and southeast Asia in a
global perspective. Ecol Res 6:185–200
Kobayashi T, Hori Y, Nemoto N (1998) Effects of mowing on
the species diversity in relation to the dominance of
dwarf-bamboo Pleioblastus chino Makino in a semi-nat-
ural grassland. Grassl Sci 44:173–176
Kobayashi T, Saito A, Hori Y (1999) Species diversity of the
understory dominated by dwarf-bamboo Pleioblastuschino Makino in a secondary forest with different num-
bers of years after the last mowing. J Jpn Soc Reveg
Technol 24:201–207
Komuro T, Koike F (2005) Colonization by woody plants in
fragmented habitats of a suburban landscape. Ecol Appl
15:662–673
Louda SM (1989) Differential predation pressure: a general
mechanism for structuring plant communities along
complex environmental gradients. Trends Ecol Evol
4:158–159
Manabe T, Nishimura N, Miura M, Yamamoto S (2000)
Population structure and spatial patterns for trees in a
temperate old-growth evergreen broad-leaved forest in
Japan. Plant Ecol 151:181–197
Mandak B, Pysek P (2001) The effects of light quality, nitrate
concentration and presence of bracteoles on germination
Plant Ecol (2011) 212:923–944 943
123
of different fruit types in the heterocarpous Atriplex sag-ittata. J Ecol 89:149–158
Maruyama R, Maruyama M, Konno Y (2004) Effects of
understory vegetation and litter on the establishment of
Abies sachalinensis and Picea jezoensis seedlings in a
conifer forest in Hokkaido, Northern Japan. Jpn J Ecol
54:105–115 (In Japanese with English summary)
McCune B, Grace JB (2002) Analysis of ecological commu-
nities. MjM Software, Gleneden Beach, p 300
Meiners SJ, Martinkovic MJ (2002) Survival of and herbivore
damage to a cohort of Quercus rubra planted across a
forest–old-field edge. Am Midl Nat 147:247–255
Meiners SJ, Handel SN, Pickett STA (2000) Tree seedling
establishment under insect herbivory: edge effects and
interannual variation. Plant Ecol 151:161–170
Meiners SJ, Pickett STA, Handel SN (2002) Probability of tree
seedling establishment changes across a forest–old field
edge gradient. Am J Bot 89:466–471
Miura M, Manabe T, Nishimura N, Yamamoto SI (2001)
Forest canopy and community dynamics in a temperate
old-growth evergreen broad-leaved forest, south-western
Japan: a 7-year study of a 4-ha plot. J Ecol 89:841–849
Miyawaki A (1986) Vegetation of Japan, vol. 8, Kanto. Shib-
undo, Tokyo (in Japanese with German and English
summary)
Miyawaki A, Okuda S, Fujiwara R (1994) Handbook of Jap-
anese vegetation. Shibundo, Tokyo (in Japanese)
Narukawa Y, Yamamoto S (2002) Effects of dwarf bamboo
(Sasa sp.) and forest floor microsites on conifer seedling
recruitment in a subalpine forest, Japan. For Ecol Manag
163:61–70
R Development Core Team (2008) R: a language and envi-
ronment for statistical computing. R Foundation for Sta-
tistical Computing, Vienna. http://www.R-project.org
Royo AA, Carson WP (2006) On the formation of dense
understory layers in forests worldwide: consequences and
implications for forest dynamics, biodiversity, and suc-
cession. Can J For Res 36:1345–1362
Saitoh T, Seiwa K, Nishiwaki A (2002) Importance of physi-
ological integration of dwarf bamboo to persistence in
forest understorey: a field experiment. J Ecol 90:78–85
Shimada T (2001) Hoarding behaviors of the two wood mouse
species: different preference for acorns of two Fagaceae
species. Ecol Res 16:127–133
Standish RJ, Cramer VA, Wild SL, Hobbs RJ (2007a) Seed
dispersal and recruitment limitation are barriers to native
recolonization of old-fields in western Australia. J Appl
Ecol 44:435–445
Standish RJ, Stokes BA, Tibbett M, Hobbs RJ (2007b) Seed-
ling response to phosphate addition and inoculation with
arbuscular mycorrhizas and the implications for old-field
restoration in Western Australia. Environ Exp Bot
61:58–65
Steel RGD (1960) A rank sum test for comparing all pairs of
treatments. Technometrics 2:197–207
Wada N (1993) Dwarf bamboos affect the regeneration of
zoochorous trees by providing habitats to acorn-feeding
rodents. Oecologia 94:403–407
Young TP, Peffer E (2010) ‘‘Recalcitrant understory layers’’
revisited: arrested succession and the long life-spans of
clonal mid-successional species. Can J For Res 40:
1184–1188
944 Plant Ecol (2011) 212:923–944
123
