The Impact of Exclosure Duration on Plant Species Diversity in a Desert Grassland and the Relative Contribution of Plant Groups

Abstract

Plant species diversity has long been a focal point in ecological studies. In order to study the changes in species diversity at different spatial scales (α, β, and γ diversities) in the restoration process of grassland vegetation in fragile desert steps, this study took desert steppe of Inner Mongolia as the research object and employed a two‐factor experimental design that combined exclosure years (the years when an area was isolated to prevent grazing and other disturbances) with years of monitoring (the years when data were collected). It analyzed the plant groups (dominant species, common species, and rare species) and species diversity, and obtained the preliminary conclusions as follows: The optimal exclosure duration for promoting species diversity balance in desert steppe management is between 16 and 18 years. Short‐term exclosure enhances species diversity by promoting recovery in overgrazed systems, while long‐term exclosure may reduce diversity due to dominant species proliferation and inhibited regeneration. Increasing the duration of exclosure (the period from the initial exclosure year to the year of monitoring) can improve plant species diversity. Exclosure years and years of monitoring exhibited a significantly positive influence on α, β, and γ diversities, with a negative interaction effect between exclosure years and years of monitoring. In addition, plant groups played a significant role in diversity at different spatial scales. Contribution to α diversity ranked as follows: rare species > common species > dominant species; contribution to β diversity ranked as rare species > dominant species > common species; contribution to γ diversity ranked as common species > dominant species > rare species. Rare species played a crucial role in maintaining diversity stability within the community and diminishing gradient differences, and common species were instrumental in upholding landscape features.

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Ecology and Evolution, 2024; 14:e70698
https://doi.org/10.1002/ece3.70698
Ecology and Evolution
RESEARCH ARTICLE OPEN ACCESS
The Impact of Exclosure Duration on Plant Species
Diversity in a Desert Grassland and the Relative
Contribution of Plant Groups
JiaojiaoHuang1 | ShijieLv1 | HongmeiLiu2 | ShengyunMa1
1College of Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, China | 2Forestry Research Institute of Inner Mongolia Autonomous
Region, Hohhot, Inner Mongolia, China
Correspondence: Hongmei Liu (liuhongmei_123@126.com) | Shengyun Ma (msy@imau.edu.cn)
Received: 8 January 2024 | Revised: 22 October 2024 | Accepted: 26 November 2024
Funding: This work was supported by the National Natural Science Foundation of China (32260352), Forestry Research Capability Enhancement Project
(104004002), Inner Mongolia Natural Science Foundation Project (2021MS03042), Inner Mongolia Agricultural University Herbology Discipline Challenge-
Based Project, and Talent Introduction Project of Herbology Discipline of Inner Mongolia Agricultural University.
Keywords: desert steppes| exclosure| α diversity| β diversity| γ diversity
ABSTRACT
Plant species diversity has long been a focal point in ecological studies. In order to study the changes in species diversity at differ-
ent spatial scales (α, β, and γ diversities) in the restoration process of grassland vegetation in fragile desert steps, this study took
desert steppe of Inner Mongolia as the research object and employed a two- factor experimental design that combined exclosure
years (the years when an area was isolated to prevent grazing and other disturbances) with years of monitoring (the years when
data were collected). It analyzed the plant groups (dominant species, common species, and rare species) and species diversity,
and obtained the preliminary conclusions as follows: The optimal exclosure duration for promoting species diversity balance in
desert steppe management is between 16 and 18 years. Short- term exclosure enhances species diversity by promoting recovery in
overgrazed systems, while long- term exclosure may reduce diversity due to dominant species proliferation and inhibited regener-
ation. Increasing the duration of exclosure (the period from the initial exclosure year to the year of monitoring) can improve plant
species diversity. Exclosure years and years of monitoring exhibited a significantly positive influence on α, β, and γ diversities,
with a negative interaction effect between exclosure years and years of monitoring. In addition, plant groups played a significant
role in diversity at different spatial scales. Contribution to α diversity ranked as follows: rare species > common species > domi-
nant species; contribution to β diversity ranked as rare species > dominant species > common species; contribution to γ diversity
ranked as common species > dominant species > rare species. Rare species played a crucial role in maintaining diversity stability
within the community and diminishing gradient differences, and common species were instrumental in upholding landscape
features.
1 | Introduction
The well- being of grassland ecosystems, integral to the global
ecosystem, is intricately linked to biodiversity, ecological bal-
ance, and human welfare (Hector and Bagchi 2007; Kang
et al. 2007). In recent years, global environmental concerns
have arisen due to grassland degradation caused by factors
such as overgrazing (Liang et al. 2009; Schönbach et al.2011)
and climate change (Wang etal. 2007). In response, targeted
restoration measures, including exclosure (Golodets, Kigel,
and Sternberg 2010; Shrestha and Stahl 2008), seasonal fallow
grazing (Katoh etal. 1998), replanting (Feng et al. 2 010), and
This is a n open access ar ticle under the terms of t he Creative Commons Attr ibution License, which p ermits use, dis tribution and repro duction in any medium, p rovided the orig inal work is
properly cited.
© 2024 T he Author(s). Ecology and Evolution publis hed by John Wiley & Sons L td.

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grassland fertilization (Wang etal. 2020), are gradually being
implemented in degraded grasslands. Exclosure refers to the
practice of fencing off or isolating an area to prevent grazing
and other disturbances by large herbivores (Aerts, Nyssen, and
Haile, 2008). It is characterized by low investment, high en-
ergy efficiency, and ease of implementation (Bendz1988; Cong
etal.2021; Teketay etal.2018). The impact of grazing exclosure
on grassland species diversity has consistently been the focus of
academic inquiry. Some studies have indicated that as the du-
ration of exclosure increases, there is an upward trend in plant
species diversity (Abebe etal.2006; Mengistu et al. 2005; Pei,
Fu, and Wan2008). Research on alpine meadow steppe in the
Qinghai- Tibet Plateau revealed that compared to free- grazing
grasslands, exclosure led to increased community cover and
productivity but decreased species diversity (Chen etal. 2021).
Other studies suggested that a 14- year exclosure period is most
conducive to the restoration of degraded grasslands. During this
time, community density and cover continue to increase to their
maximum before gradually decreasing (Shan etal.2008). Hence,
it is believed that short- term exclosure benefits the regeneration
and reproduction of grassland communities (Shashemene2014),
while an excessively prolonged closure period may harm the
grassland (Chen etal.2023; Sun etal.2020). All these findings
underscore that exclosure can effectively enhance the growth of
grassland vegetation, with its impact varying over time.
The effects of exclosure on plant diversity are related to spa-
tial scale (Tang and Fang 2004). Biodiversity can be divided
into α, β, and γ diversities based on different spatial scales
(Whittaker1960), which are both related and different. α diver-
sity pertains to the diversity of species within a specific commu-
nity or habitat, while γ diversity relates to the diversity of species
across a range of habitats within a given region. β diversity, act-
ing as a bridge between α and γ diversity, refers to the rate and
extent of change in species diversity along an environmental
gradient from one community or habitat to another (Anderson
et al. 2011). Exclosures effectively alleviate grazing pressure.
According to Tilman's(1982) resource competition theory, when
the intensity of competition for limited resources is reduced, spe-
cies can more efficiently allocate and utilize available resources.
This enhanced resource partitioning can promote niche differ-
entiation, ultimately leading to an increase in α diversity. At a
medium scale, exclosures may alter the dominance of certain
plant species, leading to changes in plant community structure
and composition. This aligns with the environmental gradient
theory, which emphasizes how variations in spatial conditions
drive β diversity (Whittaker 1960; Anderson, Ellingsen, and
McArdle 2006). At the landscape scale, exclosure typically in-
volves the strategic use of smaller, scattered fenced areas to
study changes in ecosystem structure and function, ultimately
affecting plant species diversity.
Exclosure measures can effectively enhance the ecological envi-
ronment of the grassland. However, variations in grassland deg-
radation may arise due to differing exclosure methods (such as
seasonal and year- round exclosure) and exclosure durations (the
period from the initial exclosure year to the year of monitoring).
Prior studies on the impact of exclosure duration on plant spe-
cies diversity have predominantly focused on α diversity, with
limited attention to β and γ diversities, and the exclosure dura-
tion only considered the exclosure years and ignored the years
of monitoring. Due to the differences between different years
of monitoring, the study of the effects of the duration of exclo-
sure on species diversity only by exclosure years will lead to a
certain bias into the results. For instance, a year of monitoring
with favorable hydrothermal conditions (e.g., adequate rainfall
and moderate temperatures) might exhibit higher species diver-
sity compared to a year with drought or extreme temperatures.
Additionally, in grassland ecosystems, the ecological status
and significance of plant groups (dominant species, common
species, and rare species) vary. Dominant species garner con-
siderable attention due to their predominant role in grasslands
and their significant impact on community species diversity and
ecosystem functionality. However, common and rare species are
often overlooked. Common species have a widespread distribu-
tion and play a crucial role in maintaining community stability,
while rare species, despite their smaller population sizes, may
also have significant impacts on ecosystem dynamics under spe-
cific environmental conditions.
In summar y, this study focuses on the Inner Mongolia desert
steppe and utilizes a two- factor experimental design incorpo-
rating years of monitoring and exclosure years to accurately
assess the impact of exclosure duration on species diversity.
Additionally, it explores whether the role of plant groups (dom-
inant species, common species, and rare species) in influencing
species diversity remains consistent under exclosure conditions.
The study seeks to address the following questions: (1) the re-
sponse of species diversity to the exclosure years (the years when
an area was isolated to prevent grazing and other disturbances)
and the years of monitoring (the years when data were collected
to assess the ecological impacts of exclosure); (2) the variation
characteristics and patterns of species diversity at different spa-
tial scales (α, β, and γ); (3) whether the effects of plant groups
on diversity at different spatial scales (α, β, and γ diversities) are
consistent. The resolution of these inquiries not only clarifies
the impacts of exclosure on species diversity across various spa-
tial scales but also establishes a scientific foundation for grass-
land vegetation restoration and ecological protection.
2 | Materials and Methods
2.1 | Natural Overview of the Study Area
The study area is located in the central region of the Inner
Mongolia Autonomous Region, specifically in the western part of
Xilingol League, Sunit Right Banner (41°55′–43°39′ N,111°08′–
114°16′ E). Situated in the transition zone between typical
grassland and desert, this region has a unique geographical lo-
cation and harsh habitat conditions, making it highly sensitive
to human disturbances and climate change (Yang etal. 2019).
(Before the establishment of the exclosures, this land experi-
enced heavy grazing practices, which led to significant pressure
on the vegetation and soil health. Following the installation of
the exclosures, all grazing activities ceased.) The terrain varies
in elevation from 1000 to 1400 m. The climate is classified as
temperate semi- arid continental monsoon climate with dryness,
abundant sunshine, strong winds, scant rainfall, and significant
temperature variations between day and night. The temperature
ranges from a low of −38.8°C to a high of 38.7°C, with an aver-
age of 5.9°C. The area experiences a frost- free period of 210 days

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and receives an annual average precipitation of 203.5 mm. Total
annual sunshine is approximately 129 days. Prevailing northwest
winds average 4.5 m/s. The annual precipitation for the years
of monitoring 2021 to 2023 was 229.10, 129.70, and 125.60 mm,
respectively. The corresponding average annual temperatures
were 6.69°C, 6.30°C, and 7.23°C (Figure 1). The vegetation in
the study area primarily comprises desert steppe with clusters of
Stipa brevifloris. Throughout the monitoring period from 2021
to 2023, a total of 28 plant species, comprising 13 families and
25 genera, were identified. This included 6 annual and biennial
herbs, 19 perennial herbs, and 3 shrubs. Families exhibiting a
high species diversity include Poaceae (Gramineae) (7 species),
Asteraceae (4 species), Amaryllidaceae (4 species), and Fabaceae
(Leguminosae) (3 species), with monospecific families constitut-
ing 61.5% of the total family count. Based on the vegetation types
(Stipa breviflora + Allium polyrhizum + Cleistogenes songorica)
in the study area and the importance value (IV) data obtained
from 52 sampled plots, plant species were categorized into three
community membership types: dominant species, common spe-
cies, and rare species (Liu2007; Pan etal.2018; Yang etal.2014)
(Table 1). Dominant species encompassed Allium polyrhizum,
Cleistogenes songorica, and Stipa breviflora. Common species
(IV > 1) included nine species such as Convolvulus ammannii,
Neopallasia pectinata, and Eragrostis minor. Meanwhile, rare
species (IV < 1) encompassed 15 species like Allium ramosum,
Pappophorum brachystachyum, and Scorzonera muriculata.
2.2 | Experimental Design
The grassland plots enclosed in 1999 (enclosed area: 1 ha, equiv-
alent to 10,000 m2), 2005 (enclosed area: 2.57 ha, equivalent
to 25,700 m 2), and 2014 (enclosed area: 2.57 ha, equivalent to
25,700 m2) were selected as research sites. From August 2021 to
August 2023, five 1 m × 1 m plots were randomly chosen within
each enclosed plot each year. Additionally, in August 2021,
seven extra 1 m × 1 m plots were randomly selected within the
1999 enclosed plot, making a total of 52 plots (15 plots (2 021) + 15
plots (2022) + 15 plots (2023) + 7 plots (additional 2021) = 52
plots). Plant species, height (utilizing a graduated ruler, the
height of three of the tallest plants of a particular species within
each plot was measured. The average height was then recorded),
cover (a grid- based visual estimation method (Qin etal. 2006)
was employed, dividing each 1 m × 1 m plot into 100 equal- sized
grid cells. The number of grid cells covered by each species was
visually estimated), and density (the number of plant clusters of
each species present within each plot) within each plot were re-
corded for every species present.
2.3 | Plant Species Diversity and Important Value
Calculation
In this paper, the plant species diversity index calculated based
on frequency data was used to explore the effects of different
exclosure years (1999, 2005, and 2014) and years of monitoring
(2021, 2022, and 2023) on α, β, and γ diversities, and the plant
diversity and importance values were calculated as follows:
1. α diversity index: α = number of species in each 1 m2 survey
plot;
2. β diversity index:
𝛽=1−𝛼∕𝛾
(Tuomisto2010) where
𝛼
is
the mean value of the α diversity index for the duration of
exclosure;
3. γ diversity index: γ = total number of species recorded
under each exclosure year;
4. Importance Value (IV): IV = (relative height + relative
cover + relative density)/3 × 100%.
relative height = average height of a species/sum of average
heights of all species;
relative cover = cover of a species/total cover of all species;
FIGUR E  | Precipitation and temperature in the study area for years of monitoring 2021–2023.

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relative density = number of clusters of a species/total
number of clusters of all species.
5. The duration of exclosure = year of monitoring—exclosure
years
2.4 | Statistical Analysis
To address the challenge of unequal sampling sizes across
different years of monitoring, we utilized version 2.6.6 of the
vegan package within R 4.3.0 to perform sample rarefaction
(Gotelli and Colwell 2001), ensuring consistency and compa-
rability in our data. Then to better ref lect the impact of the ex-
closure duration and maintain consistency across variables, we
designated 2014 as the reference year and assigned it a value
of 1. By establishing this reference point, we standardized ex-
closure years relative to 2014. 2005, 9 years prior to 2014, was
represented as 10, indicating a 10- year exclosure duration.
1999, 15 years prior to 2014, was represented as 16, signifying a
16- year exclosure duration. Similarly, the 3 years of monitoring
of 2021, 2022, and 2023 were replaced by 1, 2, and 3. Then,
the exclosure years, years of monitoring, and their interaction
terms were taken as independent variables, and α, β, and γ di-
versities are taken as dependent variables, respectively, and the
lm function in R 4.3.0 was used to make a general linear model
to analyze the effects of exclosure years and years of monitor-
ing on α, β, and γ diversities. The results were presented by
plotting point- whisker plots using the ggcoefstat function of
the ggstatsplot 0.12.1 package. Secondly, based on the fitted
TABLE  | Classification of dominant species, common species, and rare species in the study area.
Classification of species Species name Importance value (%)
Dominant species Cleistogenes songorica 21.39
Allium polyrhizum 17.24
Stipa breviflora 10.03
Common species Convolvulus ammannii 11.08
Neopallasia pectinata 11.55
Eragrostis minor 6.79
Caragana stenophylla 5.43
Carex tristachya 3.82
Salsola collina 2.47
Bassia prostrata 2.46
Allium tenuissimum 1.69
Setaria viridis 1.22
Artemisia scoparia 1.20
Rare species Allium ramosum 0.70
Pappophorum brachystachyum 0.47
Scorzonera muriculata 0.44
Aster altaicus 0.25
Tragus mongolorum 0.25
Erodium stephanianum 0.24
Asparagus gobicus 0.24
Tribulus terrestris 0.23
Lappula squarrosa 0.17
Allium mongolicum 0.16
Chloris virgata 0.16
Parthenocissus tricuspidata 0.14
Astragalus galactites 0.08
Gueldenstaedtia verna 0.08
Lagochilus ilicifolius 0.04

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equations, data simulation was performed using Excel 2016's
VBA (Visual Basic for Applications). Calculations were con-
ducted at 0.2- year intervals for both years of monitoring and
exclosure years, resulting in 10,200 combinations. The simu-
lation results were presented by Origin 2024 software. Finally,
using the lmer function in the lme4 1.1.35.1 package of the R
4.3.0, a mixed linear model was built with plant groups as a
fixed effect and year of monitoring and year of exclosure as
random effects. Then, the total variation in α (β, γ) diversity
was further divided into three components: dominant spe-
cies, common species, and rare species, and with the aid of the
mixed linear model, the contribution of different plant groups
to α, β, and γ diversities was analyzed using the glmm.hp. func-
tion of the glmm.hp. 0.1.0 package.
3 | Results and Analysis
3.1 | Effects of Exclosure Years and Years
of Monitoring on Diversity
The regression results of α, β, and γ diversities reveal that the
models fit well, with R2 values of 0.89 (p < 0.01), 0.90 (p < 0.01),
and 0.85 (p < 0.01), respectively. This indicates that a three
models as a whole reaches the significance level (α: AIC = 257,
BIC = 264; β: A IC = −2, BIC = −2; γ: AIC = 64, BIC = 65)
(Figure 2). For α diversity, the interaction between exclosure
year and the year of monitoring has a significant negative ef-
fect (coef ficient = −0.24, p < 0.01), meaning that α diversity de-
creases when exclosure years are earlier (closer to 1999) and the
year of monitoring is later (closer to 2023). Conversely, diversity
increases when the year of monitoring is closer to 2021. Both
the exclosure year (coefficient = 0.61, p < 0.01) and the year of
monitoring (coeff icient = 2.95, p < 0.01) individually show sig-
nificant positive effects on α diversity, indicating their strong
contribution to diversity when exclosure year is held constant.
For β diversity, the interaction term shows a small negative
effect (coefficient = −0.01, p > 0.05), while the exclosure year
(coefficient = 0.03, p < 0.05) and the year of monitoring (coeffi-
cient = 0.18, p < 0.01) both significantly increase diversity. For
γ diversity, the interaction term (coefficient = −0.47, p > 0.05)
and exclosure year (coefficient = 1.26, p > 0.05) both have non-
significant effects, indicating limited interaction between these
factors on gamma diversity. However, the year of monitoring
(coefficient = 5.03, p < 0.05) has a strong positive impact, sug-
gesting that species richness at the larger community scale in-
creases substantially over the year of monitoring.
3.2 | Variation of α, β, and γ Diversities Across
Exclosure Years and Years of Monitoring
α, β, and γ diversities were simulated using the fitted equations
obtained from the regression, and it is found that the α, β, and γ
diversities show a “saddle” shape under the influence of the year
of exclosure and the year of monitoring (Figure3). Speci fically,
the grassland community exhibits the minimum α, β, and γ di-
versities when the exclosure year is 2014, and the year of monitor-
ing is 2021. Subsequently, as the year of monitoring progresses to
2022 and 2023, the duration of exclosure for the grassland com-
munity gradually increases, leading to a more rapid ascent in α,
β, and γ diversities to higher levels. Conversely, during the exclo-
sure year of 1999, as the year of monitoring regresses from 2023
to 2021, the duration of exclosure for the grassland community
progressively shortened, resulting in a swifter increase in α, β,
and γ diversities. The α, β, and γ diversities all reach their maxi-
mum when the year of monitoring is 2021.
The simulated data are compared with the original data to
find the theoretical optimal values of α, β, and γ diversities
(Table2). It can be seen that the theoretical optimal value of α
diversity is 9.39, and the best exclosure year is approximately
1999. From the perspective of the year of monitoring, the op-
timum year of monitoring aligns with approximately 2021.
FIGUR E  | Point- whisker plots of the effects of exclosure year and year of monitoring and their interaction terms on α, β, and γ diversities (point
estimates of regression coefficients are shown as points, and confidence intervals as whiskers). Exclosure.year:Monitoring.year denotes the interac-
tion term; R- squared and p- value are the overall goodness- of- fit and p- value of each regression model, respectively;

𝛽
denotes the coefficient estimate
of the respective variable, t denotes the t value of the respective variable with degrees of freedom, and p denotes the p- value of the respective variable;
AIC and BIC stand for the Akaike information criterion and the Bayesian information criterion.

6 of 10 Ecology and Evolution, 2024
Regarding β diversity, the theoretical optimal value is 0.52, in-
dicating the optimal range for exclosure years spans from 20 02
to 2003, while the optimal years of monitoring fall within the
range of 2021 to 2022. As for γ diversity, the theoretical opti-
mal value is 14.94, suggesting the optimal exclosure year is
roughly 1999, and the optimal year of monitoring corresponds
to approximately 2022. Projecting the years of exclosure onto
the plane of α, β, and γ diversities in Figure3 reveals that the
optimal exclosure year is around 2005 (Figure4). During this
period, α, β, and γ diversity values are stable and balanced.
In contrast, shorter exclosure durations (7–9 years) show
increasing diversity, while longer exclosure durations (over
22 years) show a decline in diversity. Therefore, exclosure year
around 2005 provides the optimal balance for maintaining
species diversity.
3.3 | Effects of Plant Groups on α, β, and γ
Diversities
The outcomes of the mixed linear model reveal a significant
impact of plant groups on α, β, and γ diversities (p < 0 .0 1)
(Table 3). The total variation in α (β and γ) diversity was fur-
ther decomposed into three components: dominant species,
common species, and rare species, allowing for an analysis of
the magnitude of the contribution made by each plant groups.
Concerning α diversity, rare species make the most substantial
contribution, followed by dominant species and, lastly, common
species (Table4). In terms of β diversity, dominant species have
the greatest impact, followed by rare species and, lastly, com-
mon species. Similarly, for γ diversity, common species make
the most significant contribution, followed by rare species and,
finally, dominant species.
FIGUR E  | Results of α, β, and γ diversity si mulations based on regression e quations. T he color changes f rom purple to red to indicate the g radual
increase in the diversity of α (β, γ).
TABLE  | Results of α, β, and γ diversity simulation optimization.
Year of
monitoring
Exclosure
year
Optimal
value
α diversity 2021 1999 9.39
β diversity 2021–2022 2002–2003 0.52
γ diversity 2022 1999 14.94

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4 | Discussion
4.1 | Optimal Exclosure Duration for Desert
Steppe Grassland Management
Exclosure represents an extreme approach to grassland man-
agement, exhibiting both protective and destructive effects on
the ecological environment (Xu etal.2020). The key to effective
grassland management is determining the exclosure duration
most conducive to vegetation recovery while judiciously balanc-
ing the proportions of “rest” and “use” (Li etal.2013). Research
by Liu etal. demonstrates that species diversity tends to increase
initially and then decrease with extended exclosure durations.
Short- term exclosure can sig nificantly enhance species diversity,
whereas long- term exclosure may diminish it, which aligns with
the findings of our study (Liu etal.2023; Wu etal.2009).
Based on our findings, short- term exclosure (7–9 years) is optimal
for rapidly improving grassland conditions, especially in ecosys-
tems that have previously experienced heavy grazing pressure.
During this phase, the absence of grazing allows for substantial
vegetation recovery, particularly of rare and sensitive species that
might not survive under continuous grazing pressure. Short- term
exclosures also reduce competition between species, providing an
ideal window for diversity to peak. During medium- term exclosure
(16–18 years), represents a period of equilibrium where species
diversity stabilizes. At this stage, resource availability and habitat
conditions peak, supporting a diverse array of species and forming a
FIGUR E  | Results obtained by projecting backward the plane where the y–z axis is located in Figure3. The figure reveals different levels of
fluctuation in α, β, and γ diversities around 20 05. Before and after 2005, diversity levels change with varying years of monitoring, but around the
exclosure year 2 005, species diversity remains at a st able level. This indicates that the exclosure year 2 005 is optimal for maintaining species diversity
and ecosystem health.
TABLE  | Effects of plant groups on α, β, and γ diversities.
Response variable Main effect F p
α diversity Plant groups 80.03 0.00***
β diversity Plant groups 103.03 0.00***
γ diversity Plant groups 17.75 0.00***
***p < 0.01.
TABLE  | Contributions of different plant groups to α, β, and γ
diversities (%).
Dominant
species
Common
species
Rare
species
α diversity 8.81 40.88 50.31
β diversity 45.72 8.19 46.09
γ diversity 21.96 58.68 19.36

8 of 10 Ecology and Evolution, 2024
stable and diverse grassland ecosystem. Importantly, long- term ex-
closure (over 22 years) can lead to a decline in species diversity. This
decline may result from the over- proliferation of dominant species,
which increases competition for resources. And accumulated dead
leaves on the surface can obstruct sunlight, water, and nutrients
from penetrating the soil, inhibiting plant regeneration and repro-
duction, and thus reducing species diversity (Liu etal. 2019). In
summary, our findings suggest that the optimal exclosure dura-
tion for desert steppe management is 16–18 years for maintaining
species diversity balance. Short- term exclosure enhances rapid
vegetation recovery, while medium- term exclosure promotes eco-
system stability. Exclosures exceeding 22 years may require active
management to avoid negative effects such as reduced biodiversity.
Moreover, determining the optimal duration of exclosure should
also consider factors such as the degree of grassland degradation
(Teng etal.2020), seasonal variations (Angassa and Oba2010), and
exclosure methods (Yang etal.2022). These factors significantly in-
fluence species diversity and ecosystem health.
4.2 | Differential Contributions of Plant Groups to
α, β, and γ Diversities
The α, β, and γ diversities were significantly influenced by plant
groups, with distinct contributions from different plant categories.
Rare species emerged as pivotal contributors to α diversity, surpass-
ing common and dominant species. This prominence arises from
the ability of rare species to respond rapidly to specific environmen-
tal conditions (Wamelink, Goedhart, and Frissel2014), which can
allow them to adapt successfully when such conditions align with
their ecological requirements. Consequently, under favorable envi-
ronmental changes, rare species can thrive in local habitats. Their
occupation of specific ecological niches further distinguishes them
from other species. This allows rare species to manifest high α di-
versity in local environments. In contrast, exclosure tends to induce
substantial overlap between common and dominant species within
ecological niches, escalating competition for resources in the same
area (Slobodchikoff and Schulz1980). This process leads to the for-
mation of a relatively homogeneous ecological community, thereby
diminishing their contribution to α diversity.
Concerning β diversity, rare species exert the greatest influ-
ence, succeeded by dominant species, with common species
contributing the least. This is because the majority of species in
communities are rare. Rare species typically inhabit specific mi-
croenvironments, leading to a greater diversity of species com-
position among different sites, thereby increasing β diversity.
Dominant species, characterized by broad ecological niche oc-
cupancy (Grime1998), high abundance, and strong competitive-
ness, maintain consistent species compositions across diverse
gradients. Thus, they contribute relatively less to β diversity.
Common species exhibit relatively stable population dynamics
among different sites. Their widespread distribution leads to less
pronounced differences in species composition among different
habitats, resulting in the smallest contribution to β diversity.
Regarding γ diversity, common species play more substantial
roles, while dominant and rare species contribute less. Common
species often possess weed- like characteristics, such as rapid
growth and wide adaptability. They also have disturbance resis-
tance and serve as bridges between different ecosystems, mak-
ing significant contributions to overall γ diversity and ecosystem
stability. Rare species, although enhancing γ diversity by their
presence, exhibit lower relative abundance in ecosystems, lim-
iting their overall contribution (James and Rathbun 1981).
Dominant species, by successfully occupying a wide range of
ecological niches, reduce opportunities for other species within
the same niches, thereby impacting γ diversity.
5 | Conclusion
There is a negative interaction effect between exclosure years and
years of monitoring, and the optimal exclosure period falls within
the range of 16–18 years. Plant groups exert significant effects on α,
β, and γ diversities, though these effects vary. In terms of α diver-
sity, its contribution was as follows: rare species, common species,
and dominant species; in terms of β diversity, its contribution was
from large to small: rare species, dominant species, and common
species; in terms of γ diversity, its contribution was from large to
small: common species, dominant species, and rare species. It can
be seen that rare species play a critical role in maintaining the sta-
bility of diversity within the community and mitigating gradient
differences within the ecosystem; common species emerge as es-
sential contributors to maintaining landscape characteristics.
Author Contributions
Jiaojiao Huang: conceptualization (equal), investigation (equal),
writing – original draft (equal), writing – review and editing (equal).
Shijie Lv: formal analysis (equal), investigation (equal). Hong mei Liu:
funding acquisition (equal), investigation (equal), resources (equal).
Shengy un Ma: investigation (equal), supervision (equal).
Acknowledgments
This work wa s supported by the National Natural Science Foundation of
China (32260352), Forestry Research Capability Enhancement Project
(2024NLTS03), Inner Mongolia Natural Science Foundation Project
(2021MS03042), Inner Mongolia Agricultural University Herbology
Discipline Challenge- Based Project, and Talent Introduction Project of
Herbology Discipline of Inner Mongolia Agricultural University. And
the authors would like to thank the editor and referees for their ver y
constructive comments in revising this paper.
Conflicts of Interest
The authors declare no conflicts of interest.
Data Availability Statement
The data that support the findings of this study are available in the
Supporting Information of this article.
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Supporting Information
Additional supporting information can be found online in the
Supporting Information section.