RESEARCH ARTICLE
Plant diversity is associated with the amount and spatialstructure of soil heterogeneity in meadow steppe of China
Ling Wang • Chen Liu • Diogo Gomes Alves •
Douglas A. Frank • Deli Wang
Received: 29 March 2013 / Accepted: 21 October 2013
� Springer Science+Business Media Dordrecht 2013
Abstract The link between environmental hetero-
geneity and diversity is a major tenet of plant ecology.
Previous studies designed to test the heterogeneity–
diversity hypothesis largely have only included mea-
sures characterizing the overall variation in habitat
(e.g., CV of soil parameters). Rarely has the spatial
structure of that variation been considered in relation
to diversity. Here we examined the spatial variability
(CV) and spatial structure of that variation (i.e. spatial
scale of patchiness) of several main soil variables (C,
N, P, pH, and conductivity) in relation to grassland
plant species richness and diversity (H0). We deter-
mined the relationships of plant species richness and
diversity at two spatial scales (50 9 50 m plot scale,
1 9 1 m quadrat scale) with the whole-plot soil
heterogeneity within an *750 ha natural area of
Kerqin grasslands in northeastern China. We found
that the best models describing species richness at the
0.25 ha and 1 m2 scales included patch size of soil
conductivity and N, respectively. For each of the two
spatial scales, pairs of models best described H0; a
simple regression with CV of soil N and a multiple
regression including soil N patch size and CV at the
0.25 ha scale, and, at the 1 m2 scale, a simple
regression with soil conductivity CV and multiple
regression including CV and patch size of soil N. Soil
N was negatively associated with conductivity, likely
due to sodium, the primary determinant of conductiv-
ity in this meadow steppe system, inhibiting plant
growth and the capacity of soils to accumulate N.
Consequently our results indicated that the heteroge-
neity of soil N was the principal control of plant
species richness and H0. Moreover, our findings
indicate that spatial structure (the average size of a
patch), in addition to CV, was important in determin-
ing grassland species richness and diversity. Our
results indicate that both components of environmen-
tal heterogeneity need to be included in future tests of
the heterogeneity–diversity hypothesis.
Keywords Biodiversity conservation �Soil spatial heterogeneity � Spatial structure �Spatial variability � Heterogeneity–diversity
relationship � Plant diversity � Species richness
Introduction
Spatial heterogeneity of soil resource supply has long
been theoretically recognized as an important driver of
L. Wang � C. Liu � D. G. Alves � D. Wang (&)
Key Laboratory of Vegetation Ecology, Ministry
of Education, Institute of Grassland Science,
Northeast Normal University, Changchun 130024,
People’s Republic of China
e-mail: [email protected]
L. Wang � D. A. Frank
Syracuse University, Life Sciences Complex, Syracuse,
NY 13244-1220, USA
123
Landscape Ecol
DOI 10.1007/s10980-013-9955-0
plant species coexistence and community diversity
(Grime 1979; Tilman 1982). It is widely thought that
heterogeneous environments should maintain more
species than homogeneous ones. Some empirical
studies also have found that plant species diversity is
positively correlated with soil heterogeneity in the
field (e.g. Lundholm and Larson 2003; Davies et al.
2005; Gundale et al. 2006). But negative or non-
existent heterogeneity–diversity relationships (HDRs)
also have been reported in some observational and
empirical studies (Kleb and Wilson 1997; Stevens and
Carson 2002; Gross et al. 2005; Gundale et al. 2011).
The premise of a positive HDR is based on classical
niche theory, which assumes that the performance of a
species is optimized under a particular set of resource
conditions that differ from those of other species. High
variability in soil resources can reduce competition,
thereby allowing for more species to coexist (Tilman
and Pacala 1993). Examining the HRD usually
involves testing for a statistical relationship between
species diversity and environmental heterogeneity,
most often measured as the variation in one or more
soil resources (i.e. coefficient of variation, CV) (see
reviews in Lundholm 2009). However, heterogeneity
is a complex concept that has two important compo-
nents: spatial variability (e.g. CV), using non-spatial
statistics, and spatial structure of variation, determined
with spatially explicit statistics (Adler et al. 2001; Wu
2007). Two communities with the same total variation
in soil resources may differ significantly in the
graininess of the variation; fine vs coarse grain
variation representing small versus larger patches of
resource conditions. Plant size and the spatial scale of
soil resource heterogeneity interact to determine the
intensity of competition, immigration, emigration and
diversity (Hutchings et al. 2003; Dufour et al. 2006;
Reynolds et al. 2007; Lundholm 2009; Tamme et al.
2010). When the scale of heterogeneity is smaller than
that of the whole plant, the response of plant species
diversity to soil heterogeneity may be negative or zero
(Eilts et al. 2011). Especially for rhizomatous clonal
species, a positive HDR is often not found at small
spatial scales due to the spatially extensive foraging
capability of clonal plants. Therefore, both compo-
nents of heterogeneity (spatial variability and spatial
structure) should be considered while testing the
relationship between heterogeneity and species diver-
sity. To date, the influence of spatial structure of soil
resources on plant diversity has primarily received
theoretical attention (Palmer 1992; Ritchie and Olff
1999; Steiner and Kohler 2003); only a few empirical
studies have addressed the topic (Anderson et al. 2004;
Wijesinghe et al. 2005).
The vast steppe ecosystem of northeastern China
supports a large and economically important livestock
industry (Zhu 1993). The majority of this grassland
region has deteriorated since the 1960s (Zhu 2004).
Grassland productivity and plant diversity have grad-
ually decreased, which has seriously affected local
livestock production and ecosystem services. Manag-
ing plant species diversity is an important component
of range management in general (Fuhlendorf and
Engle 2001) and in meadow steppe of northeastern
China in particular (Wang et al. 2010, 2011). Main-
tenance of meadow steppe plant diversity has become
a matter of urgent concern and a better understanding
of local drivers is crucial for conservation. Large
herbivore grazing, as an important biological deter-
minant controlling plant diversity, has been widely
studied in meadow steppe of northeast China during
the past two decades (e.g. Wang and Ripley 1997; Zhu
et al. 2012). However there is little knowledge about
the underlying contribution of soil source heteroge-
neity in determining plant diversity in this grassland
(Wang and Ba 2008).
The aim of our study was to quantify the relation-
ship between plant diversity and soil spatial hetero-
geneity in the meadow steppe. Firstly, we determined
how soil pH and conductivity (CE), and total nitrogen
(N), carbon (C) and phosphorus (P) were related to
plant diversity. Secondly, we examined how the two
components of the spatial heterogeneity, spatial var-
iability (CV) and spatial structure (spatial grain or
patch size calculated from semivariograms), of the soil
resources were associated with plant diversity.
Materials and methods
Study site description
The study site was located in Kerqin grassland, the
eastern region of the Eurasian Steppe Zone, northeast
China (Gao and Wei 1994). Soils at the site were
mixed saline and alkaline, had high pH (7–10.5) and
were low in nitrogen. The main vegetation type was
meadow steppe, dominated by grass Leymus chinensis
(Trin.) Tzvel. (Wang and Ba 2008). L. chinensis is a
Landscape Ecol
123
widespread dominant grass that is a dominant species
from arid to semi-arid steppe in northern China,
eastern Mongolia and Transbaikalia, Russia (Zhu
1993), with an ability to resist drought, cold and alkali
stress (Shi and Wang 2005). This species also is a
clonal plant that mainly relies on vegetative propaga-
tion for regeneration. L. chinensis produces abundant
rhizomes 5–15 cm below the soil surface, and can
form near monoculture stands. Other species at the site
include the grasses Phragmites australis Trin., Ca-
lamagrostis epigejos Roth. and Chloris virgata
Swartz; the legumes Lespedeza davurica Schindl.
and Medicago ruthenica C. W. Chang; and forbs such
as Kalimeris integrifolia Turcz., Potentilla flagellaris
Willd. Ex Schlecht., Artemisia scoparia Waldstem et
Kitailael and Carex duriuscula C. A. M. Annual net
primary productivity (ANPP) is 2,600–3,500 kg/ha
(Zhu 2004).
This study was performed at the Grassland Eco-
logical Research Station of Northeast Normal Univer-
sity, Jilin Province, China (44�450N, 123�450E). The
site has a semi-arid, continental climate with mean
annual temperature ranging from 4.6 to 6.4 �C, and
annual precipitation ranging from 280 to 400 mm
(Data from the Climatic Station of Changeling
County, Jilin Province from 1997 to 2007). More than
half of the precipitation falls during growing season,
especially between June and August. Annual potential
evapotranspiration is approximately three times as
much as annual precipitation. We conducted our study
in an *750 ha grassland, which had been fenced to
exclude livestock and mown for hay for over 30 years.
Hay was cut in August every year.
Sampling design and measurements
We randomly selected twelve 50 9 50 m plots within
this 750 ha natural grassland. Within each plot, thirty
1 9 1 m quadrats were randomly placed, and the x–y
coordinates of each quadrat centroid was obtained
using a tape measure. This sampling design resulted in
360 sample points (i.e. 30 quadrats 9 12 plots). The
number of tillers for each plant species (abundance of
each species) was recorded for each quadrat. Three soil
samples (4 cm diameter, 15 cm deep) were randomly
collected from each quadrat and then pooled. Soil was
hand-sorted to remove stones and roots, and passed
through a 2-mm mesh sieve. Five soil properties,
including N, C, P, pH and CE, were measured on each
soil sample. Soil pH and CE were measured with an
electrode using standard methods (Richards 1954).
Soil organic C was measured by the Walkley–Black
dichromate oxidation method (Walkley and Black
1934). Total N content was measured using the
Kjeldahl method (A 2300 Kjletec Analyzer Unit, Foss
Tecator, Sweden). We used the Mo–Sb anti-spectro-
photometry method to measure soil total P content.
Soil sampling was carried out in May 2010 and
vegetation was sampled in July 2010.
Data analysis
We calculated plant species richness and diversity at
two spatial scales: 0.25 ha (50 9 50 m plot scale)
and 1 m2 (1 9 1 m quadrat scale). Species richness
at the 0.25 ha plot scale will refer to the total
number of species found in the thirty 1 9 1 m
quadrats in each plot, while species richness at the
1 m2 quadrat scale reflects the average 1 m2 richness
from the 30 quadrats in each plot. Species diversity
was calculated using the Shannon–Wiener diversity
index (H0): H0 = -P
(pi) 9 (ln pi), where pi is the
proportional abundance of species i, summed for all
n species measured. 1 m2 quadrat scale H0 equaled
the average abundance of each species among the 30
quadrats. 0.25 ha plot scale H0 was calculated with
abundance of each species equaling the summed
tiller counts among the 30 quadrats. H0 takes into
account not only the number of species, but also the
distribution of species abundance.
The relationships of spatial heterogeneity of the five
soil parameters with species richness and diversity at
both scales (0.25 ha plot and 1 m2 quadrat) were
examined across the 12 plots. Firstly, CV was
computed for each of the soil variables as one measure
of soil spatial variation. Secondly, the spatial structure
of each of the soil properties in each of the twelve
50 9 50 m plots was determined with semivario-
grams (Fortin and Dale 2005). Semivariograms were
used to estimate an important parameter of heteroge-
neity, range (A0), which is the distance at which the
semivariogram asymptote is reached, and describes
the spatial scale of patchiness (i.e. average patch size).
We computed semivariograms using GS?7.0 software
(Gammadesign Software, Plainwell, MI, USA).
We examined the relationship of whole-plot CV
with species richness and H0 for each soil variable with
Pearson’s correlation coefficient (n = 12). Then we
Landscape Ecol
123
tested the spatial structure of soil parameters in
relation to species richness and H0 by calculating
Pearson’s correlation coefficients (n = 12) between
plant diversity (richness or H0) and measures of range
(A0) for each soil variable. Additionally, we used a
multiple regression to examine how the two compo-
nents of spatial heterogeneity (CV and patch size)
were related to each metric of plant species diversity
(richness or H0). Akaike’s information criterion (AIC)
was used to select the best fit models. The smaller the
AIC value the better the fit. We assumed that AIC
values differing by B2 reflected models providing
similar fit to the data (Burnham and Anderson 1998).
We also compared the relationships of the dominant
species, L. chinensis, with soil heterogeneity (CV and
patch size), species richness, and H0 to help interpret
the general patterns of soil heterogeneity and species
diversity at the site. Associations among soil resource
variables (i.e., pH, CE, C, N, P) also were explored.
All analyses were done using SPSS 16.0 software.
Results
Simple regressions of species richness or H0 with
spatial heterogeneity (CV or average patch size) of soil
variables at two scales (1 m2 and 0.25 ha) did not
reveal a significant relationship for soil C and pH
(Table 1). For soil P, there was a significantly positive
relationship only between diversity and patch size of
soil P at the 1 m2 scale. For soil conductivity, there
were significant and positive relationships between
species richness and patch size for at the 0.25 ha scale,
and between H0 and CV at the 1 m2 scale (Table 1).
The CV of soil N was unrelated to species richness
(Fig. 1a, b), but positively associated with plant
diversity (H) at both spatial scales (Fig. 1c, d;
Table 1). Spatial structure (average patch size) of soil
N was positively correlated with species richness for
both spatial scales (Fig. 2a, b), and H0 at 1 m2 scale
(Fig. 2d), but not for 0.25 ha scale (r = 0.485;
P = 0.109; Fig. 2c). In addition, multiple regressions
revealed that H0 was significantly related to the two
components of heterogeneity of soil N, CV and patch
size, at both spatial scales (Table 1).
According to AIC statistics, the best model describ-
ing species richness included patch size of soil
conductivity at the 0.25 ha scale and patch size of
soil N content at the 1 m2 scale (Table 1). H at each of
the two spatial scales was best described by pairs of
models with similar AIC values; a simple regression
with CV of soil N and a multiple regression with CV
and patch size of soil N at the 0.25 ha scale, and at the
1 m2 scale, the simple regression with CV of soil
conductivity and the multiple regression including
both CV and patch size of soil N.
Furthermore, the CV of soil N was negatively
correlated with L. chinensis abundance (Fig. 3a).
Table 1 The AIC values and probabilities (P) for regression models of plant species richness or diversity at different scale (0.25 ha
and 1 m2) with CV and/or patch size of spatial heterogeneity for five soil variables (C, N, P, pH and CE)
Dependent variable Variables entered AIC value/P value
Soil N Soil pH Soil CE Soil C Soil P
Richness (0.25 ha scale) CV 34.3/0.16 33.2/0.09 36.7/0.99 35.1/0.90 33.5/0.11
Patch size 30.0/0.02 36.4/0.61 27.0/0.01 34.6/0.20 33.6/0.12
CV, patch size 31.1/0.06 33.7/0.15 28.9/0.03 35.6/0.32 31.3/0.06
Richness (1 m2 scale) CV -9.7/0.16 -9.3/0.20 -10.1/0.14 -7.5/0.78 -7.5/0.91
Patch size -13.8/0.02 -11.4/0.08 -7.6/0.72 -7.5/0.90 -7.4/0.10
CV, patch size -12.6/0.06 -10.6/0.14 -8.2/0.35 5.6/0.95 -5.5/0.99
Diversity (0.25 ha scale) CV -33.4/0.00 -25.7/0.06 -25.7/0.06 -24.5/0.11 -21.5/0.79
Patch size -24.6/0.11 -24.9/0.10 -22.7/0.31 -22.6/0.32 -25.5/0.07
CV, patch size -32.9/0.00 -26.5/0.07 -25.3/0.11 -23.2/0.24 -23.6/0.20
Diversity (1 m2 scale) CV -35.8/0.03 -32.2/0.16 -37.5/0.01 -30.4/0.59 -30.9/0.43
Patch size -35.8/0.03 -33.5/0.10 -30.3/0.67 -30.4/0.59 -36.1/0.03
CV, patch size -37.8/0.02 -32.9/0.16 -35.7/0.06 -28.6/0.82 -35.5/0.06
Landscape Ecol
123
Ric
hnes
s
(# s
peci
es 1
m -2
)
0
0.3
0.6
0.9
1.2
1.5
0.00 0.10 0.20 0.30 0.40 0.50
Div
ersi
ty
(H, 0
.25
ha- 1
)
0
0.4
0.8
1.2
1.6
0.00 0.10 0.20 0.30 0.40 0.50
r = 0.796
P=0.002
Soil N CV
NS
Soil N CVR
ichn
ess
(# s
peci
es0.
25 h
a- 1)
(c)(a)
Soil N CV Soil N CV
r = 0.623
P=0.031
NS(d)(b)
Div
ersi
ty
(H,1
m -2
)
3
4
5
6
7
0.00 0.10 0.20 0.30 0.40 0.50
15
20
25
30
0.00 0.10 0.20 0.30 0.40 0.50
Fig. 1 Relationships of
whole-plot CV of soil N
with plant species richness
or diversity (H0) at 0.25 ha
plot and 1 m2 quadrat scales.
Values are for 12 randomly
located 750 ha fenced plots
Div
ersi
ty
(H,1
m -1
)
Div
ersi
ty
(H,0
.25
ha-1
)
Ric
hnes
s
(# s
peci
es 1
m -1
)
0
0.3
0.6
0.9
1.2
1.5
0 10 20 30 40 50
r = 0.616
P=0.033
3
4
5
6
7
0 10 20 30 40 50
r = 0.642
P=0.024
Soil N patch size (m) Soil N patch size (m)
(d)(b)
Soil N patch size (m)
NS
15
20
25
30
0 10 20 30 40 50
r =0.655
P=0.021
Soil N patch size (m)
(c)(a)
Ric
hnes
s
(# s
peci
es0.
25 h
a-1)
0
0.4
0.8
1.2
1.6
0 10 20 30 40 50
Fig. 2 Relationships
between whole-plot average
patch size of soil N and plant
species richness or diversity
(H0) at 0.25 ha plot and 1 m2
quadrat scales. Average
patch size was obtained
from range parameter (A0)
measured using geostatistics
0
150
300
450
600
750
0.00 0.10 0.20 0.30 0.40 0.50
Soil N CV
r = -0.613
P=0.034
L. c
hine
sis
abun
danc
e
(Num
ber
of in
divi
dual
m-2
)
(a)
NS
Soil N patch size (m)
L. c
hine
sis
abun
danc
e
(Num
ber
of in
divi
dual
m-2
)
(b)
0
150
300
450
600
750
0 10 20 30 40 50
Fig. 3 Relationships
between the abundance of L.
chinensis (per m2). a Whole-
plot CV of soil nitrogen,
b whole-plot average patch
size of soil N for 12 plots
Landscape Ecol
123
There was no relationship between average patch size
of soil N and L. chinensis abundance (r = -0.514;
P = 0.087; Fig. 3b). Not surprisingly, L. chinensis
abundance was negatively correlated to both plant
species richness (r = -0.257; P \ 0.0001; Fig. 4a)
and H0 (r = -0.680; P \ 0.0001; Fig. 4b). There
were negative relationships of soil N with pH and CE
(Fig. 5a, b).
Discussion
There is no consensus on what soil variables, spatial
scales, and components of heterogeneity are most
important in determining species diversity (Lundholm
2009). Theory suggests that the spatial heterogeneity of
the most limiting resource should govern plant species
diversity (MacArthur 1970; Tilman 1982). Here we
explored how spatial heterogeneity in five soil variables
(C, N, P, pH and CE) were associated with plant
diversity. Soil N and P are generally considered the first
and second most limiting soil nutrients in temperate
grasslands, respectively. Soil C is associated with
cation exchange capacity and soil moisture content.
Soil conductivity can be governed by a variety of soil
properties, but in our system is primarily a function of
sodium concentration. High soil pH is a function of
high concentrations of base cations and influences the
availability of P for plant uptake. Our results indicated
that the spatial heterogeneity of soil N and conductivity
were the most important factors controlling species
richness and H0 in this grassland ecosystem (Table 1).
Nitrogen is a limiting nutrient in this system (Wang
et al. 2002). And high soil conductivity, largely
governed by sodium concentration, inhibits plant
growth (Shi and Wang 2005). These two soil variables
were negatively related to one another (Fig. 5b). The
negative link between soil N and conductivity may be a
function of high soil sodium content reducing plant
productivity and thus the capacity of soil to accumulate
organic material and, concomitantly, N. If correct, the
results indicate that species richness and diversity at
both spatial scales were governed by the heterogeneity
of soil N, a plant-growth limiting resource in this
ecosystem.
Results of our study indicated that the influence of
soil heterogeneity on plant species diversity was
complex and strongly dependent on both components
of heterogeneity (spatial variability and structure) and
varied according to which plant diversity metric was
considered (species richness or H0). Our results did not
support the observed relationship between plant
species richness and spatial variability (CV) of soil
resources that has been reported in most previous
studies (see Lundholm 2009). There were positive
relationships between H0 and CV of soil N at both
L.c
hine
sis
abun
danc
e
(Num
ber
of in
divi
dual
m-2
)
0
200
400
600
800
1000
1200
0.00 0.50 1.00 1.50 2.00 2.50
Diversity index (H )
r = -0.680
P<0.0001
(b)
0
200
400
600
800
1000
1200
0 2 4 6 8 10 12
Species richness (# species)L
.chi
nesi
sab
unda
nce
(Num
ber
of in
divi
dual
m-2
)
(a)
r = -0.257
P<0.0001
Fig. 4 The relationships of
abundance of L. chinensis
with species richness and
diversity (H0). Values are for
360 1-m2 quadrats across 12
plots
-500
0
500
1000
1500
2000
2500
0.00 0.05 0.10 0.15 0.20 0.25 0.306
7
8
9
10
11
0.00 0.05 0.10 0.15 0.20 0.25 0.30
(a)
Soil N (%)
Soil
pH
r = -0.651
P<0.0001
r = -0.553
P<0.0001
(b)
Soil N (%)
Soil
CE
(s
cm)
Fig. 5 Relationships of soil
N with a pH and
b conductivity. Values are
for 360 1-m2 quadrats across
12 plots
Landscape Ecol
123
spatial scales. However, there was no significant
relationship between species richness and CV for any
measured soil property. Instead, spatial structure of
variation played an important role. Species richness
was best described by the spatial structure (patch size)
of soil conductivity at the 0.25 ha scale and the patch
size of soil N at the 1 m2 scale. Furthermore, among
the best models describing H0 at both of spatial scales
were multiple regressions that included both compo-
nents of heterogeneity, CV and patch size. Conse-
quently the spatial structure of variation (i.e. the
average patch size) in soil resources was at least as
important as a component of variation (CV) in
determining plant diversity in meadow steppe habitat.
It has been suggested that the strength and shape of
the HDR depends on the variable used and the scale at
which it is measured (Costanza et al. 2011). The
likelihood of finding a positive HDR should increase
as the spatial scale examined increases (Tilman 1982).
Studies have found lack of support for HDRs mostly
at small-scales (\50 m2) (e.g. Collins and Wein 1998;
Baer et al. 2004; Reynolds et al. 2007). Our study
included a larger scale (0.25 ha) to test the HDR, but
still found no strong support for HDR if we only
considered species richness as a diversity measure-
ment, and CV as a heterogeneity measurement.
Another factor, which may explain whether or not
such a relationship occurs, is the range or magnitude
of variation in soil properties. If the level of soil
variation across samples is too small, the HDR will be
difficult to discriminate. Our data showed that most
important soil variables-N demonstrated both a larger
range and a higher variation across 360 sample
quadrats (0.03–0.28 %) (see Fig. 5). Therefore this
factor was also precluded in our study.
Most observational studies have used species
richness as a measure of diversity. Although there
was no relationship between variability of soil
resources and species richness in our study, we found
that soil N variability (CV) was significantly and
positively correlated with H0 at both spatial scales. H0
includes components of evenness. In meadow steppe,
plant species evenness is important because of its
greater impacts on grassland productivity (Li and
Wang 1996). Variability of soil limiting resources is
clearly the dominant factor in controlling species
evenness in our study. L. chinensis is the dominant
species in meadow steppe in northeastern China
because of its strong competitive capacity and
tolerance to saline-alkali stress. Abundance of L.
chinensis was negatively correlated with species
evenness of grassland. It was also found that there
was a stronger negative relationship between abun-
dance of L. chinensis and H0 than richness (Fig. 4).
Our results showed that soil N variability (CV) was
negatively correlated with the abundance of L. chin-
ensis (Fig. 3a). High soil N variability resulted in low
abundance of L. chinensis, thereby reducing the
competitive pressure for other species and increasing
species evenness. It is difficult to assign a cause for
high soil N variability resulting in low L. chinensis
abundance in this study, because these results are only
correlative. Future studies could experimentally
examine effects of soil resources heterogeneity on L.
chinensis growth to improve the understanding of
plant diversity patterns in China meadow steppe. It has
been suggested that both intra- and inter-specific
competitive interactions will be more severe in
heterogeneous soil than in uniform soils with the
same overall nutrient supply (Hutchings et al. 2003).
The biomass of L. chinensis probably was significantly
reduced by competition in the heterogeneous environ-
ment with high CV.
Spatial heterogeneity is a complex parameter that
includes both a measure of the magnitude of spatial
variation and the structure of that spatial variation (Li
and Reynolds 1995). Palmer (1992) was the first to
explore the effect of the geometrical configuration of
environmental variability on species richness by
computer simulation, and demonstrated that the effect
of a landscape’s environmental variability on species
richness is affected by the degree of spatial depen-
dence. In Palmer’s study, it was predicted that
increasing fractal dimension should increase species
number, but the effect of variability (CV) on species
richness was still larger. Only a few previous studies
have empirically investigated the spatial configuration
of habitats in relation to plant species richness
(Anderson et al. 2004; Dufour et al. 2006). Dufour
et al. (2006) found that richness generally increased
with increasing environmental variability and decreas-
ing spatial aggregation in a managed montane wooded
pasture. Anderson et al. (2004) showed that pattern of
species richness at a large spatial scale (1,000 m2) was
controlled by the patch size and fractal dimension of
NO3- in the Serengeti National Park, Tanzania. Our
study further empirically demonstrated an effect of
spatial structure (patch size) of soil limiting resource-N
Landscape Ecol
123
on species richness and a combination of CV and patch
size of soil N on H0 in a meadow steppe ecosystem.
The underlying mechanism for soil heterogeneity
influencing species richness and diversity is complex,
especially when variability and spatial pattern of soil
variables are considered simultaneously. Maintenance of
species diversity mainly depends on the two processes:
colonization and competition (Chesson 2000). High
variability of a limiting soil resource will offer more
habitat types, thereby opportunities for more species to
colonize. However, if the variables are subdivided in
space in many small patches, species will more easily be
threatened with extinction caused by stochastic events
since local population sizes will be small in small habitats
(Palmer 1992), especially for the weak competitive or
rare species. Furthermore, it has been shown that large
patches benefit weaker competitors, while small patches
benefit stronger competitors (Stoll and Prati 2001). This
knowledge may explain the positive relationship
between average patch size of soil resources (N) and
species richness found in our study. Thus as the average
patch size of a limiting soil resource (N) increased, the
competition from the dominant species, L. chinensis,
likely declined and the competitiveness of uncommon
and rare species strengthen. Thus increasing patch size
likely promoted species coexistence.
Results of this study suggest that the spatial
heterogeneity of a limiting soil resource, N, was
closely associated with the species richness and
diversity (H0) of a China meadow steppe ecosystem.
Furthermore, we showed that spatial structure of soil
resources, in addition to the magnitude of soil resource
variation (CV), is important in determining grassland
plant diversity. Future tests of the HDR hypothesis
should explicitly consider how the spatial configura-
tion of resource variation influences species diversity.
Acknowledgments This project was supported by the
National Natural Science Foundation of China (Nos.
31072070, 31230012), NECT-11-0612 and the Fundamental
Research Funds for the Central Universities (11CXPY003) and
the State Agricultural Commonweal Project (201003019).
References
Adler PB, Raff DA, Lauenroth WK (2001) The effect of grazing
on the spatial heterogeneity of vegetation. Oecologia
128:465–479
Anderson TM, Samuel JM, Mark ER (2004) Scale-dependent
relationships between the spatial distribution of a limiting
resource and plant species diversity in an African grassland
ecosystem. Oecologia 139:277–287
Baer SG, Blair JM, Collins SL, Knapp AK (2004) Plant com-
munity responses to resource availability and heterogene-
ity during restoration. Oecologia 139:617–629
Burnham KP, Anderson DR (1998) Model selection and mul-
timodel inference. Springer, New York
Chesson P (2000) Mechanisms of maintenance of species
diversity. Annu Rev Ecol Syst 31:343–366
Collins B, Wein G (1998) Soil heterogeneity effects on canopy
structure and composition during early succession. Plant
Ecol 138:217–230
Costanza JK, Moody A, Peet RK (2011) Multi-scale environ-
mental heterogeneity as a predictor of plant species rich-
ness. Landscape Ecol 26:851–864
Davies KF, Chesson P, Harrison S, Inouye BD, Melbourne BA,
Rice KJ (2005) Spatial heterogeneity explains the scale
dependence of the native–exotic diversity relationship.
Ecology 86:1602–1610
Dufour A, Gadallah F, Wagner HH, Guisan A, Buttler A (2006)
Plant species richness and environmental heterogeneity in
a mountain landscape: effects of variability and spatial
configuration. Ecography 29:573–584
Eilts JA, Mittelbach GG, Reynolds HL, Gross KL (2011)
Resource heterogeneity, soil fertility, and species diversity:
effects of clonal species on plant communities. Am Nat
177:574–588
Fortin MJ, Dale M (2005) Spatial analysis: a guide for ecologist.
Cambridge University Press, Cambridge
Fuhlendorf SD, Engle DM (2001) Restoring heterogeneity on
rangelands: ecosystem management based on evolutionary
grazing patterns. Bioscience 51(8):625–632
Gao YS, Wei SC (1994) The Kerqin grassland of China. Jilin
Science & Technology Press, Changchun, pp 17–44
Grime JP (1979) Plant strategies and vegetation processes.
Wiley, Chichester, p 34
Gross KL, Mittelbach GG, Reynolds HL (2005) Grassland in-
vasibility and diversity: responses to nutrients, seed input,
and disturbance. Ecology 86:476–486
Gundale MJ, Metlen KL, Fiedler CE, Deluca TH (2006)
Nitrogen spatial heterogeneity influences diversity fol-
lowing restoration in a Ponderosa pine forest, Montana.
Ecol Appl 16:479–489
Gundale MJ, Fajardo A, Lucas RW, Nilsson M, Wardle DA
(2011) Resource heterogeneity does not explain the
diversity–productivity relationship across a Boreal island
fertility gradient. Ecography 34:887–896
Hutchings MJ, John EA, Wijesinghe DK (2003) Toward
understanding the consequences of soil heterogeneity
for plant populations and communities. Ecology 84:222–
2334
Kleb H, Wilson S (1997) Vegetation effects on soil resource
heterogeneity in prairie and forest. Am Nat 150:283–298
Li H, Reynolds JF (1995) On definition and quantification of
heterogeneity. Oikos 73:280–284
Li Xiaobo, Wang Deli (1996) The effects of grazing on the plant
diversity on the Leymus chinensis grassland in Jilin Prov-
ince. J Northeast Norm Univ 2:94–98
Landscape Ecol
123
Lundholm JT (2009) Plant species diversity and environmental
heterogeneity: spatial scale and competing hypotheses.
J Veg Sci 20:377–391
Lundholm JT, Larson DW (2003) Relationships between spatial
environmental heterogeneity and plant species diversity on
a limestone pavement. Ecography 26:715–722
MacArthur RH (1970) Species packing and competitive equi-
libria for many species. Theor Popul Biol 1:1–11
Palmer MW (1992) The coexistence of species in fractal land-
scapes. Am Nat 139:375–397
Reynolds HL, Mittelbach GG, Darcy-Hall TL, Houseman G,
Gross KL (2007) No effect of varying soil resource het-
erogeneity on plant species richness in a low fertility
grassland. J Ecol 95:723–733
Richards LA (1954) Diagnosis and improvement of saline and
alkali soils. USDA Handbook 60
Ritchie ME, Olff H (1999) Spatial scaling laws yield a synthetic
theory of biodiversity. Nature 400:557–560
Shi DC, Wang DL (2005) Effects of various salt-alkaline mixed
stresses on Aneurolepidium chinense (Trin.) Kitag. Plant
Soil 271:15–26
Steiner NC, Kohler W (2003) Effects of landscape patterns on
species richness: a modelling approach. Agric Ecosyst
Environ 98:353–361
Stevens MHH, Carson WP (2002) Resource quantity, not
resource heterogeneity, maintains plant diversity. Ecol Lett
5:420–426
Stoll P, Prati D (2001) Intraspecific aggregation alters compet-
itive interactions in experimental plant communities.
Ecology 82:319–327
Tamme R, Hiiesalu I, Laanisto L, Szava-Kovats R, Partel M
(2010) Environmental heterogeneity, species diversity and
co-existence at different spatial scales. J Veg Sci 21:796–801
Tilman D (1982) Resource competition and community struc-
ture. Princeton University Press, Princeton
Tilman D, Pacala S (1993) The maintenance of species richness
in plant communities. In: Ricklefs RE, Schluter D (eds)
Species diversity in ecological communities: historical and
geographyraphical perspectives. University of Chicago
Press, Chicago, pp 13–25
Walkley A, Black IA (1934) An examination of Degtjareff
method for determining soil organic matter and a proposed
modification of the chromic acid titration method. Soil Sci
37:29–37
Wang DL, Ba L (2008) Ecology of meadow steppe in northeast
China. Rangel J 30:247–2524
Wang RZ, Ripley EA (1997) Effects of grazing on a Leymus
chinensis grassland on the Songnen plain of north-eastern
China. J Arid Environ 36:307–318
Wang SP, Zhou GS, Lu YC, Zou JJ (2002) Distribution of soil
carbon, nitrogen, and phosphorous along Northeast China
Transect (NECT) and their relationships with climatic
factors. Acta Phytoecol Sinica 26(5):513–517
Wang L, Wang DL, He ZB, Liu GF, Hodgkinson KC (2010)
Mechanisms linking plant species richness to foraging of a
large herbivore. J Appl Ecol 47:868–875
Wang L, Wang DL, Liu JS, Huang Y (2011) Diet selection
variation of a large herbivore in a feeding experiment with
increasing species numbers and different plant functional
group combinations. Acta Oecol 37:263–268
Wijesinghe DK, John EA, Hutchings MJ (2005) Does pattern of
soil resource heterogeneity determine plant community
structure? An experimental investigation. J Ecol 93:99–112
Wu JG (2007) Landscape ecology-pattern, process, scale and
hierarchy, 2nd edn. High Education Press, Beijing
Zhu TC (1993) Natural grasslands of China. In: Coupland RT
(ed) Ecosystems of the World 8B. Elsevier, Amsterdam,
pp 66–82
Zhu TC (2004) Biological ecology of Leymus chinensis. Jilin
Science & Technology Press, Changchun
Zhu H, Wang DL, Wang L, Bai YG, Fang J, Liu J (2012) The
effects of large herbivore grazing on meadow steppe plant
and insect diversity. J Appl Ecol 49:1075–1083
Landscape Ecol
123
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