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: wangd@nenu.edu.cn

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

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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).

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