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\begin{document}

\title{Niche selection and dispersal limitation inclined spatial turnover rates
of soil fungal community in meadow degradation}



\author[1]{yingcheng wang}%
\author[2]{Ye Deng}%
\author[1]{Guangxin Lu}%
\author[3]{Hao Yu}%
\author[2]{Xiongfeng Du}%
\author[2]{Qing He}%
\author[1]{shiting Yao}%
\author[1]{lirong Zhao}%
\author[1]{caixia Huang}%
\author[1]{xiaocheng Wen}%
\affil[1]{Qinghai University}%
\affil[2]{Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences}%
\affil[3]{Affiliation not available}%


\vspace{-1em}



  
  \date{May 29, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
The alpine meadow ecosystem, as the main ecosystem of the Qinghai-Tibet
Plateau, has been heavily degraded over the past several decades due to
overgrazing and climate change. Although soil microorganisms play key
roles in the stability and succession of grassland ecosystems, their
response to grassland degradation has not been investigated at spatial
scale. Here, we systematically analyzed the spatial turnover rates of
soil prokaryotic and fungal communities in degraded and undegraded
meadows through distance-decay relationship (DDR) and species area
relationship (SAR), as well as the community assembly mechanisms behind.
Although the composition and structure of both fungal and prokaryotic
communities showed significant changes between undegraded and degraded
meadows, the steeper spatial turnover rates were only observed in fungi.
Mantel tests indicated that edaphic variables and vegetation factors
showed significant correlations to the fungal community only in degraded
meadow, suggesting soil and vegetation heterogeneity contributed to the
steeper spatial scaling pattern. Correspondingly, a novel phylogenetic
null model analysis (iCAMP) demonstrated that environmental selection
was enhanced in the fungal community assembly process during meadow
degradation. Interestingly, dispersal limitation was also enhanced for
the fungal community in the degraded meadow, and its relative
percentages showed a significant linear increase with the spatial
distance, suggesting that dispersal limitation played a greater role as
distance increased. Our findings indicated the spatial scaling of the
fungal community is altered during meadow degradation by both niche
selection and dispersal limitation. This study provides a new
perspective for the assessment of soil microbial responses to vegetation
changes in alpine areas.%
\end{abstract}%



\sloppy


\textbf{Niche selection and dispersal limitation inclined spatial
turnover rates of soil fungal community in meadow degradation}

\textbf{Running title: Microbial diversity scales divergent in soils}

Yingcheng Wang\textsuperscript{1,2}, Hao Yu\textsuperscript{2,4},
Xiongfeng Du\textsuperscript{2,3}, Qing He\textsuperscript{2,3}, Shiting
Yao\textsuperscript{1}, Lirong Zhao\textsuperscript{1}, Caixia
Huang\textsuperscript{1}, Xiaocheng Wen\textsuperscript{1}, Guangxin
Lu\textsuperscript{1*}, Ye Deng\textsuperscript{2,3*}

\textsuperscript{1} Collage of Agriculture and Animal Husbandry, Qinghai
University, Xining 810016, China

\textsuperscript{2} CAS Key Laboratory for Environmental Biotechnology,
Research Center for Eco-Environmental Sciences, Chinese Academy of
Sciences (CAS), Beijing 100085, China

\textsuperscript{3} College of Resources and Environment, University of
Chinese Academy of Sciences, Beijing 100190, China

\textsuperscript{4} College of Environmental Science and Engineering,
Liaoning Technical University, Fuxin 123000, China

\textsuperscript{*}Correspondence:

Ye Deng, Guangxin Lu

Telephone: 00 86 (010) 6284 0082; 13897216290 Fax: 00 86 (010) 6284 0082

E-mail: yedeng@rcees.ac.cn; lugx74@qq.com



\textbf{Abstract}

The alpine meadow ecosystem, as the main ecosystem of the Qinghai-Tibet
Plateau, has been heavily degraded over the past several decades due to
overgrazing and climate change. Although soil microorganisms play key
roles in the stability and succession of grassland ecosystems, their
response to grassland degradation has not been investigated at spatial
scale. Here, we systematically analyzed the spatial turnover rates of
soil prokaryotic and fungal communities in degraded and undegraded
meadows through distance-decay relationship (DDR) and species area
relationship (SAR), as well as the community assembly mechanisms behind.
Although the composition and structure of both fungal and prokaryotic
communities showed significant changes between undegraded and degraded
meadows, the steeper spatial turnover rates were only observed in fungi.
Mantel tests indicated that edaphic variables and vegetation factors
showed significant correlations to the fungal community only in degraded
meadow, suggesting soil and vegetation heterogeneity contributed to the
steeper spatial scaling pattern. Correspondingly, a novel phylogenetic
null model analysis (iCAMP) demonstrated that environmental selection
was enhanced in the fungal community assembly process during meadow
degradation. Interestingly, dispersal limitation was also enhanced for
the fungal community in the degraded meadow, and its relative
percentages showed a significant linear increase with the spatial
distance, suggesting that dispersal limitation played a greater role as
distance increased. Our findings indicated the spatial scaling of the
fungal community is altered during meadow degradation by both niche
selection and dispersal limitation. This study provides a new
perspective for the assessment of soil microbial responses to vegetation
changes in alpine areas.

\textbf{Keywords}

Alpine meadow, grassland degradation, spatial scaling, Qinghai-Tibet
Plateau, soil microbiota



\textbf{1.Introduction}

The grassland of the Qinghai-Tibetan Plateau (QTP) not only provides
important ecological services and functions, such as biodiversity
conservation, carbon sink, climate control center, water resource but
also provides critical ecosystem services such as cultural
communication, tourism, and recreation at local and regional scales
(Dong, Shang, Gao, \& Boone, 2020; Smith et al., 2015). However, the
sustainability of the QTP's grassland ecosystems is being affected by
both anthropogenic and non-anthropogenic disturbances in the form of
rapid global changes (Dong \& Sherman, 2015). It's commonly agreed that
the QTP's grassland ecosystems have been heavily degraded over the past
half century (Dong \& Sherman, 2015; X. L. Li et al., 2013; S. Liu,
Zamanian, Schleuss, Zarebanadkouki, \& Kuzyakov, 2018; Miehe et al.,
2019; Shang \& Long, 2007; Huakun Zhou, Zhao, Tang, Gu, \& Zhou, 2005),
with approximately 90\% of the QTP's alpine grasslands displaying some
levels of degradation, 35\% of which severely degraded into
``black-beach land'', a phenomenon in which the entire turf layer is
eroded reveling bare mineral soil (Harris, 2010; Xuexia Wang et al.,
2015). Grassland degradation is a long and complex process, where the
key process occurs in soils. Soil microorganisms are the main component
of soil vitality, playing a leading role in the processes of soil
formation and evolution. The soil microbial community is more sensitive
than plants and animals to impacts of environmental change (Lau, 2011),
and changes in microbial community composition and activity under
degradation conditions may in turn affect the stability of this
ecosystem under global or local climate changes (Y. Liu et al., 2019; Xu
et al., 2014).

The most obvious feature of grassland degradation is the reduction of
vegetation coverage and increase in exposed patches of soil. Limited
research has been carried out on the changes in soil microbial community
composition and structure during alpine meadow degradation. A previous
study has shown that degraded patch formation in alpine meadow on the
QTP could result in variations of microbial community composition,
structure, and function, but with no significant alteration of soil
microbial alpha diversity (Che et al., 2019). Additionally, the
formation of degraded patches can increase the risk of plant disease and
inorganic N leaching (Che et al., 2019; Y. Li et al., 2016; Heng Zhou,
Zhang, Jiang, Sun, Xiao, Yuxin, et al., 2019). Thus, changes in the
nutrient status and plant diversity due to alpine meadow degradation
could result in alterations of the microbial community composition and
structure, presenting an indication of ecosystem changes (Heng Zhou,
Zhang, Jiang, Sun, Xiao, Yuxin, et al., 2019).

An incresing number of stuides have provided evidences that the majority
of microorganisms exhibit clear biogeographic patterns similar to that
of macroorganisms, despite their microscopic size and hidden diversity
(Lo\selectlanguage{ngerman}ïc Chalmandrier et al., 2019; Green \& Bohannan, 2006; Kivlin \&
Hawkes, 2020; Martiny et al., 2006). These studies have also revealed
that limiting spatial study to a local scale tends to negate the
influence of broad environmental gradients on community structure and
better reveals the signs of local assembly processes, such as biotic
interactions or ecological drift (L. Chalmandrier et al., 2013; Chase,
2014). Distance-decay (DDR) curves offer a directional measure of the
variation in community composition in local sites, and the slope of DDR
(\selectlanguage{greek}\emph{β} \selectlanguage{english}), particularly within a unifrom environment, can provide a
useful test of the relative importance of niche versus neutral processes
(Du et al., 2020; Kranabetter et al., 2018; X.-B. Wang et al., 2017).
Another way to study the effect of spatial scaling is the species-area
relationship (SAR), which describes the law that the species within the
microbial community change with the increasing plot area (Lomolino,
2000). In SAR measurement, the slope of the curve (\emph{z} ) parameter
represents the rate at which species accumulate with increasing area. To
date, a number of studies (Che et al., 2019; Y. Li et al., 2016; Heng
Zhou, Zhang, Jiang, Sun, Xiao, Wu, et al., 2019) have shown changes in
the composition and structure of soil microbial community during meadow
degradation, but no studies have measured the changes of soil microbial
community over spatial scale during this process.

The study of community assembly is very important to explain the
mechanism of species coexistence and diversity maintenance. Species
composition and diversity patterns are affected by drift, diffusion,
differentiation, and selection, among which, the first three tend to be
stochastic processes under specific conditions, while the lattest is a
deterministic process (Vellend, 2010). It has been shown previously that
the process of niche determination and the random process based on
neutral theory have great influence on microbial community assembly
(Ferrenberg et al., 2013; Tian et al., 2017). Understanding the patterns
of variation and assembly mechanisms of soil microbial communities at
different spatial scales during alpine meadow degradation can provide
important insights for alpine meadow health assessment and restoration
management.

In this study, a complex sampling nested design has been implemented,
and total 154 soil samples from QTP were collected with degraded patches
and adjecent undegraded meadows. The distance-related measurements (both
DDR and SAR) were used to explore the changes in spatial turnover rates,
and several null model methods were adopted to measure the assembly
processes during the process of grassland degradation. We hypothesized
that (i) meadow degradation could significantly alter the diversity and
community structures for both prokoryotic and fungal communities in
soils; (ii) degradation would incline the spatial turnover rates of soil
microbial communities; (iii) that meadow degradation has specific
impacts on the mechanisms of microbial community assembly. It is worth
noting that due to the large differences in the sizes, life cycles,
physiology, and functions between fungi and prokaryotes, we could expect
that meadow degradation would impact the diversity, structure, spatial
scaling and assembly process of these two communities differently. Thus,
to determine how far and what assembly processes are behind the impacts
on fungal and prokaryotic communities is one of the major objectives of
this study as well.

\textbf{2. Methods and materials}

2.1 Study sites and soil sampling

This study was carried out in 2019 in Zhenqin County, Yushu Prefecture,
Qinghai Province, China (33\selectlanguage{ngerman}°24\selectlanguage{english}'18.57\selectlanguage{english}"N\selectlanguage{english},97deg20\selectlanguage{english}'46.31\selectlanguage{english}"E; altitude 4500m).
The annual average temperature is -1.6\selectlanguage{english}, and the area belongs to the
cold and warm continental monsoon climate, with a long cold season and
short warm season, where the frost-free period is only 93-126 days. The
main grassland type is alpine meadow, and the dominant vegetation
are\emph{Kobresia pygmaea} , \emph{Kobresia humilis} , \emph{Stipa
purpurea} , and \emph{Potentilla multifida} . The soil type was alpine
meadow soil.

In this study, we selected two typical alpine meadows, undegraded alpine
meadow and degraded alpine meadow, and utilized a nested sampling
method, where smaller sample areas are nested within larger ones (Fig.
1). The center plot (red point, area of 8 m\textsuperscript{2}) serves
as the reference point, 12 pilots of 1 m\textsuperscript{2} were laid
out in four directions at 10, 100, and 1000 m from the central area in
the form of a vertical crossing. The center plot consisted of 17
individual soil cores, while each 1 m\textsuperscript{2} plot was
composed of 5 cores. A total of 154 (2 sample sites x 77 sample points)
sampling points were identified and then vegetation surveys and soil
sample collections were conducted for each sample plot.

2.2 Vegetation measurements and soil sampling

At each sample point, the plant coverage, species, and height in each
0.5 x 0.5 m quadrat were recorded. After plant community measurement,
three soil samples from each quadrat (upper 0-15 cm) were randomly
collected with a soil augur on August 12 and 13, 2019. The three samples
for each quadrat were mixed, homogenized, and sieved (\textless{} 2 mm)
to remove the roots and other plant materials, before being placed on
ice for transport. The soil samples were divided into two parts, one
part was used to determine the physicochemical properties while the
other part was stored at - 80\selectlanguage{english} for use in molecular experiments (DNA
extraction).

2.3 Soil physicochemical properties

The following soil physicochemical properties were determined: pH, total
nitrogen (TN), nitrate nitrogen
(NO\textsubscript{3}\textsuperscript{-}-N), ammonia nitrogen
(NH\textsubscript{4}\textsuperscript{+}-N), soil organic matter (OM),
soil moisture (SM), and soil electrical conductivity (EC). Soil pH was
measured using a pH meter with a soil-to-water ratio of 1:2.5, SM and EC
were measured by TDR 350 in triplicate. Other soil properties were
measured at the Institute of Soil Science, Chinese Academy of Sciences
(Nanjing, China).

2.4 DNA extraction and PCR amplification

Total DNA was extracted from 0.25 g sample of soil using a
PowerSoil\textsuperscript{TM} DNA Isolation Kit (MO BIO Laboratories,
Carlsbad, CA, USA) according to the manufacturer's instructions. The V4
region of the 16S rRNA gene was amplified with barcoded primers 515
forward (5\selectlanguage{english}'-GTGCCAGCMGCCGCGGTAA-3\selectlanguage{english}') and 806 reverse
(5\selectlanguage{english}'-GGACTACHVGGGTWTCTAAT-3\selectlanguage{english}'), and the ITS2 region of the ITS DNA was
amplified with barcoded primers 5.8 forward
(5'-AACTTTYRRCAAYGGATCWCT-3') and 4 reverse
(5'-AGCCTCCGCTTATTGATATGCTTAART-3'). The polymerase chain reaction (PCR)
amplification was carried out in a 50 \selectlanguage{greek}μ\selectlanguage{english}L reaction system: containing 1
\selectlanguage{greek}μ\selectlanguage{english}L of template DNA (20--30 ng/\selectlanguage{greek}μ\selectlanguage{english}L), 1 \selectlanguage{greek}μ\selectlanguage{english}L of both 10 uM forward and
reverse primers, 1 \selectlanguage{greek}μ\selectlanguage{english}L Taq DNA Enzyme (TaKaRa), 25 \selectlanguage{greek}μ\selectlanguage{english}L 10 \selectlanguage{ngerman}× PCR buffer, 1
\selectlanguage{greek}μ\selectlanguage{english}L dNTP mixture and 20 \selectlanguage{greek}μ\selectlanguage{english}L ddH2O. The thermal cycle conditions were as
follows: initial denaturation at 95 \selectlanguage{ngerman}°C for 3 min, followed by 30 (16S)
/35 (ITS) cycles for 15 s at 95 °C, 15 s at 52 °C, 45 s at 72 °C, final
extension at 72°C for 5 min and then held at 4°C.

The PCR products were extracted on a 1\% agarose gel, further purified
using E.Z.N.A.\textsuperscript{TM} Gel Extraction Kit (Omega Bio-tek,
Inc., USA), and quantified using a Qubit fluorometer (Life technologies
Holdings Pte Ltd, Singapore). They were pooled in an equaimolar ratio
(150 ng) for library construction with VAHTSTM Nano DNA Library Prep Kit
for Illumina® (Vazyme Biotech Co., Ltd, Nanjing, China) according to the
manufacturer's instructions. The purified amplicons were sequenced on an
Illumina HiSeq platform at Magigene Biotechnology Co., Ltd. (Guangzhou,
China).

2.5 Processing of the sequencing data

Raw reads of the 16S rRNA and ITS genes were submitted to a publicly
available sequence analysis pipeline
(\emph{http://mem.rcees.ac.cn:8080}) which consisted of an integrated
series of bioinformatics tools (Feng et al., 2017; Zhang et al., 2017).
The raw reads were assigned to samples according to the barcodes,
allowing for one mismatch. Forward and reverse sequences were combined
by FLASH (Magoc \& Salzberg, 2011). The Btrim program (Kong, 2011) was
used to filter out unqualified sequences with a threshold Quality Score
\textgreater{} 20, and minimum length of 140bp for 16s, 300bp for ITS.
Any sequences with ambiguous bases were remove and only reads with
length between 245/307 and 260/341 bp for 16s/ITS were retained for
further analysis. Operational taxonomic units (OTUs) with 97\%
similarity cutoff were clustered using UPARSE (Edgar, 2013). Taxonomic
annotation was conducted using the RDP Classifier database. To correct
for sampling error, 153 samples of 16S and 147samples of ITS were
randomly resampled to the same reads number (33,159 for 16S and 35,654
for ITS datasets). The resampled OTU table was used for downstream
analyses.

2.6 Statistical analysis

The effect of undegraded and degraded meadows on the soil
physicochemical variables were determined using a two-way nested
analysis of variance (ANOVA). The soil microbial \selectlanguage{greek}α-\selectlanguage{english}diversity was
estimated using observed richness, Shannon index, and phylogenetic
diversity. Principal coordinates analysis (PCoA), a non-binding data
dimension reduction analysis method, was used to assess community
composition, similarities, and differences among samples by first
sorting a series of eigenvalues and eigenvectors and then selecting the
top most characteristic values and performances in the coordinate system
to determine the underlying principal component affecting the sample
community composition differences. Patterns of community dissimilarity
among sample were determined by Sorensen distance and Bray-Curtis
distance. The rate of distance-decay of the microbial community was
calculated as the slope of ordinary least-squares regression on the
relationship between geographic distance (log transformed) and community
similarity (log transformed) within the `vegan' R package (Dixon, 2003).
To examine relationships between area and species richness diversity, we
performed SAR analysis within the `tidyr' and `mmSAR' R packages
(Guilhaumon, Mouillot, \& Gimenez, 2010). The distances of each sampling
location to the plot center were \(\frac{\sqrt{2}}{2}\),
1,\(\sqrt{2}\), 2, 10, 100 and 1000 m, yielding sampling areas of
1, 2, 4, 8, 200, 2\selectlanguage{ngerman}×10\textsuperscript{4} and
2×10\textsuperscript{6}m\textsuperscript{2}. Permutation tests were then
performed to determine whether the turnover rates (\selectlanguage{greek}\emph{β} \selectlanguage{english}and \emph{z}
values) were significantly different between transect. The significance
of the slopes of the two curves was tested using `lsmeans' R package
(Lenth, 2016), using analysis of variance (ANOVA) to test. The
significance of the relationship between community dissimilarity and
geographical distance, environmental variables distance in undegraded
and degraded alpine meadows were assessed using the Mantel and partial
Mantel tests within the `ecodist' R package (Goslee \& Urban, 2007). To
determine the relative importance of geographic distance and
environmental factors in structuring microbial communities, we conducted
multiple regression analysis using multiple regression on matrices (MRM)
approach within the `ecodist' R package.

For the microbial community, we used to the method proposed by Tucker et
al (Tucker, Shoemaker, Davies, Nemergut, \& Melbourne, 2015) to quantify
the significance of the observed difference of the microbial communities
in the undegraded alpine meadow and degraded alpine meadow from random
expectation for all communities. If the deviation value of the Null
model is close to zero, it indicates that the stochastic process is more
important in the community, otherwise, they are considered to be
dominated by deterministic processes. Then, we used the new mathematical
framework of quantitative description of ecological stochastic processes
proposed by Ning (Ning, Deng, Tiedje, \& Zhou, 2019) and normalized
stochasticity ratio was used to measure the importance of stochastic
ratio in the process of community assembly, that is, whether assembly
was dominated by deterministic (\textless{}50\%) or stochastic
(\textgreater{}50\%) processes. Furthermore, a framework to
quantitatively infer community assembly mechanisms by phylogenetic
bin-based null model analysis (iCAMP) (Ning et al., 2020). We first
calculated the framework for microbial community assembly in degraded
meadows using iCAMP (\emph{http://ieg3.rccc.ou.edu:8080} ), and showed
the relative importance of different processes in the turnover of each
bin in each group of samples, then correlated each community process
with geographical distance to determine the contribution of each
assembly process to the microbial community.

\textbf{3. Results}

3.1 Edaphic physicochemical properties in degraded and undegraded
meadows

Some measured vegetation factors and soil physicochemical properties
exhibited significant differences between degraded and undegraded alpine
meadows (Table S1). The soil total nitrogen (TN) organic matter (OM),
electrical conductivity (EC), vegetation coverage, species richness,
above-ground fresh biomass (FB), and above-ground dry biomass (DB) were
significantly lower in degraded meadow than undegraded meadow, while
soil pH and vegetation average height were significantly higher. The
soil NH\textsubscript{4}\textsuperscript{+}-N,
NO\textsubscript{3}\textsuperscript{-}-N, and soil moisture (SM) showed
no significant differences. In addition, we found no significant
correlations between soil properties or vegetation factors and
geographical distance in either the degraded or undegraded alpine
meadows (Fig. S1). These results suggested that although the meadow
degradation significantly altered some edaphic variables and vegetation
factors, it did not obviously change the soil and vegetation
heterogeneity, at least at our sampling scale (within
2km\textsuperscript{2}).

3.2 Diversity and structure of microbial community have been altered
during meadow degradation

Soil prokaryotic \selectlanguage{greek}α-\selectlanguage{english}diversity differed significantly between the two
sample plots. Specifically, compared to undegraded alpine meadow, the
observed richness of soil prokaryotes was significantly lower in the
degraded alpine meadow (Fig. 2a). In addition, the degradation
significantly affected the soil prokaryotes community composition.
Compare to the undegraded meadow, the degradation significantly
increased relative abundance of Actinobacteria, Bacteroidetes and
Thaumarchaeota by 3.21\%, 22.14\%, 66.71\%, and decreased relative
abundance of Verrucomicrobia and Planctomycetes by approximately 31.85\%
and 7.25\% (Fig. 2d). Meadow degradation also significantly affected
soil fungal richness, with the degraded meadow displaying a
significantly higher richness (Fig. 2a). Meanwhile, the composition of
fungal community was also altered (Fig. 2d). Most of fungi in the meadow
were classified as Ascomycota (90\%), Basidiomycota (4.11\%),
Entorrhizomycota (0.19\%) and Chytridiomycota (0.17\%). Specifically,
the degradation significantly decreased relative abundance of
Basidiomycota, Entorrhizomycota and Chytridiomycota by 39.51\%, 93.11\%
and 53.04\%, and significantly increased relative abundance of
Ascomycota by 2.73\%.

PCoA analysis suggested that the meadow degradation significantly alter
the structure of soil fungal and prokaryotic communities, with the
results showing their \selectlanguage{greek}\emph{β} -\selectlanguage{english}diversity at degraded alpine meadow and
undegraded alpine meadow were clearly separated from each other (Fig.
2b, c). Dissimilarity analysis further proved that there were
significant differences between degraded and undegraded meadows (Table
S2).

3.3 Spatial scale variation of soil microbial community

Community dissimilarity and geographic distance for each pairwise set of
samples clearly displayed a significant distance-decay relationship
(DDR) for both prokaryotic and fungal communities (Fig. 3a, b). However,
while the slope of the degraded alpine meadow was steeper than
undegraded alpine meadow for both, it was only significantly so for
fungi (Fig. 3c, \emph{P} \textless{}0.05). Therefore, strong
distance-decay relationships of both fungi and prokaryotes were observed
in the alpine meadow, but the degradation only significantly increased
the spatial turnover rate for fungal community.

The species area relationship reflects the increase of richness with
increasing sampling area. In this study, there were significant positive
correlations between the estimated richness and sampling area in both
fungi and prokaryotes (Fig. 3d, e). Notably, the different SAR fitting
models showed similar AIC values (the difference between maximum and
minimum less than 10) in degraded and undegraded meadows for both
prokaryotes and fungi (Table S3), indicating that the power model, which
is the most commonly used model, was appropriate to describe SAR in the
current study. The analysis of soil microbial species area relationship
in degraded alpine meadow showed that the conversion rate of species
increases significantly with the degradation of the alpine meadow. The
conversion rate of soil fungi species diversity showed an increasing,
but not significant, trend for degraded of alpine meadow (\emph{z} =
0.0690) (Fig. 3f), as compared with undegraded alpine meadow (\emph{z} =
0.0620) (Fig. 3e). Soil prokaryotes showed the same trend as fungi, but
with a lower slope increase than fungi (\emph{z} = 0.0245 for
undegraded, and \emph{z} = 0.0294 for degraded meadow, Fig. 3d). The
above results indicated that the conversion rate of soil microorganisms
could be accelerated during the degradation of alpine meadow.

3.4 Geographic distance had significant impacts on both prokaryotic and
fungal communities but soil/vegetation parameters only showed
significant impacts on fungi in degraded meadow

To distinguish the impacts of geographic distance, vegetation factors,
and soil parameters on soil microbial communities, Mantel and partial
Mantel tests (\emph{i.e.} Bray-Curtis dissimilarity) were adopted. The
results revealed that the dissimilarity of the prokaryotic communities
in undegraded and degraded alpine meadows were both strongly correlated
with geographic distance, and not correlated with environmental
distances for edaphic and vegetation variables (Table 1). However, the
community dissimilarity of fungi displayed different trends in
undegraded and degraded alpine meadows. In undegraded meadow, just like
prokaryotes, the fungal community was strongly correlated with
geographic distance and not correlations with either edaphic or
vegetation variables (Table 1). However, in degraded meadow, geographic
distance, edaphic variables, and vegetation factors were all
significantly correlated with fungal community by both Mantel and
partial Mantel tests (Table 1), indicating that not only spatial
distance but also soil/vegetation variations had significant impacts on
fungal community in degraded meadow.

Multiple Regression Model (MRM) was used to further identify the
relative contributions of each environmental factor versus geographic
distance to prokaryotic and fungal communities.
NO\textsubscript{3}\textsuperscript{-}-N and pH explained a significant
proportion of variation in fungi community dissimilarity in the degraded
alpine meadow (\emph{P} = 0.001 for
NO\textsubscript{3}\textsuperscript{-}-N; \emph{P} = 0.001 for pH), OM
explained a significant proportion of variation in fungi community
dissimilarity in the undegraded alpine meadow (\emph{P} = 0.007) (Table
S4). Overall, like the Mantel and partial Mantel tests, the geographic
distance showed higher impact on prokaryotes and fungal community, but
edaphic factors have some influence on the fungal community only.

3.5 Variations of ecological processes in the microbial community
assembly in degraded alpine meadow

Null model analysis was used to disentangle the relative importance of
stochastic and deterministic processes in microbial assembly within
degraded alpine meadow. The null model approach, based on taxonomic
\selectlanguage{greek}β-\selectlanguage{english}diversity, showed that the zero deviation values of prokaryotes and
fungal communities were significantly different (ANOVA, \emph{P}
\textless{}0.010, Table S5), indicating that there was a significant
difference between the observed community dissimilarity and the
dissimilarity expected by random chance during meadow degradation. We
used two null-model-based approaches NST and iCAMP to measure the
relative importance of assembly processes, including determinism
(homogenous and heterogeneous selections) and stochastic (dispersal
limitation and drifts) (Table S5, Fig. 4a, d). As the NST result shows,
stochasticity (\textgreater{}80\%) was much stronger than determinism
(\textless{}20\%) in shaping the community assembly for prokaryotes in
both undegraded and degraded meadows. Unlike the prokaryotes, the
stochasticity was stronger in undegraded meadow (58\% \emph{v.s.} 42\%),
but weaker in degraded meadow (34\% \emph{v.s.}66\%) (Table S5) for the
fungal community. Then, through the use of iCAMP, we found that
dispersal limitation dominated the stochasticity process in both
prokaryotic and fungal communities (Fig. 4a, d). It was especially
interesting, from the combined results of NST and iCAMP, that
determinism process showed a stronger impact on the community assembly
for fungi than stochasticity in degraded alpine meadow (Table S5). Thus,
when we precisely distinguished each assembly process over spatial
distance, it was found that the fungal percentage of dispersal
limitation rose significantly while the homogeneous selection decreased
as distance increased (Fig. 4f), and this trend was no found in
undegraded alpine meadow (Fig. 4e), however, the dispersal limitation
and homogeneous selection of prokaryotes showed a stable curve with the
increase of distance (Fig. 4b, c). This trend suggested that the impact
of dispersal limitation would be strengthened along spatial distance,
playing an increasingly more important role in shaping the community
assembly for fungi in degraded meadow.

\textbf{4. Discussion}

The results of this study showed that alpine meadow degradation
significantly altered soil prokaryotic and fungal communities, in terms
of \selectlanguage{greek}\emph{α} \selectlanguage{english}and \selectlanguage{greek}\emph{β} -\selectlanguage{english}diversities, as well as community compositions
(Fig. 2). This result was consistent with other studies where microbial
communities significantly differed along alpine meadow and alpine steppe
degradation on the Qinghai-Tibetan Plateau (Y. Li et al., 2016; Heng
Zhou, Zhang, Jiang, Sun, Xiao, Wu, et al., 2019). Alterations of the
soil microbial community were mainly attributed to the change of soil
variables and influence of external activities on the meadow (Fan, Kong,
Wang, Yue, \& Li, 2020; Guo et al., 2018). A recent study demonstrated
the formation of degraded patches in vegetation significantly altered
the physicochemical properties of soil and further changed the soil
bacterial community (Xiaojie Wang et al., 2020). Therefore, the most
obvious phenomenon of meadow degradation, the alternation of vegetation
and soil properties, could significantly affect the diversity of soil
prokaryotes and fungi, subsequently changing their community structure.
Different microorganisms exhibit distinct ecological functions in the
biogeochemical cycling of elements, and microbial community structure
could influence a variety of ecosystem processes (Allison et al., 2013).
Therefore, microbial community composition is intimately associated with
the functions of this common ecosystem of the alpine QTP (Bier et al.,
2015; Che et al., 2015). In addition, these environmental changes might
also lead to different spatial scaling patterns of microorganisms, which
could be important for understanding microbial diversity mechanisms and
their regulation of key ecosystem processes (Chu, Gao, Ma, Fan, \&
Delgado-Baquerizo, 2020).

In this study, we observed significant DDR and SAR for prokaryotic and
fungal communities in both undegraded and degraded meadows (Fig. 3).
Previous studies have demonstrated soil prokaryotic or fungal
communities with clear spatial scaling patterns either in DDR or SAR
(Deng et al., 2016; Deng et al., 2018; Liang et al., 2015; X.-B. Wang et
al., 2017; J. Zhou, Kang, Schadt, \& Garten, 2008), but rarely both
simultaneously (Du et al., 2020), especially for both prokaryotes and
fungi. We observed steeper turnover slopes in the fungal community
(\selectlanguage{greek}\emph{β} \selectlanguage{english}=0.0077-0.0142, \emph{z} =0.0620-0.0690) than the prokaryotic
community (\selectlanguage{greek}\emph{β} \selectlanguage{english}=0.0030-0.0035, \emph{z} =0.0245-0.0294), indicating
the soil fungal community had greater dissimilarity over geographic
distance than prokaryotes (Fig. 3). Community similarity with increasing
geographic distance is a well-described pattern of biodiversity, from
macro-organisms to microorganisms (Morlon et al., 2008; Soininen,
McDonald, \& Hillebrand, 2007), and these spatial turnover patterns are
explained by species characteristics (\emph{e.g.} body size, migration
ability and evolution), the scale of geographic distance, and
environmental factors (geology, geomorphology, climate, and soil
texture) (Noss, 1990; Whittaker, Willis, \& Field, 2001). In this study,
fungal species showed higher turnover rates than prokaryotes in
identical sample sites, suggesting the species characters of fungi,
either larger cell sizes and/or slower migration rates, have contributed
the heterogeneous local adaptation of fungal communities.

More importantly, we observed that the spatial turnover rates
(\selectlanguage{greek}\emph{β}\selectlanguage{english}and \emph{z} ) for fungi were significantly steeper in degraded
meadow than undegraded meadow (Fig. 3b, e), which demonstrated that the
turnover of fungal communities across space was accelerated during the
degradation process in alpine meadow. However, this trend was less
apparent for prokaryotes as the difference between DDR slopes was quite
small (undegraded meadow \selectlanguage{greek}\emph{β} \selectlanguage{english}= 0.0030; degraded meadow \selectlanguage{greek}\emph{β} \selectlanguage{english}=
0.0035) (Fig. 3a). It was consistent with our expectation that soil
prokaryotes and fungi communities change differently over spatial scale
during the degradation of alpine meadow. The general consensus is that
there are two primary processes that alter the spatial turnover rates of
microorganisms. The first is niche selection, that soil heterogeneity
may increase with geographical distance, and thus when species are
selected from local taxa pool based on their niche preferences, the
community composition may become increasingly different with
environmental changes (Bell, 2010). The other is that it is mainly due
to microbial dispersal limitation (Cho \& Tiedje, 2000; Peay,
Garbelotto, \& Bruns, 2010) which describes when the movement and
colonization of species in a new location is restricted, leading to
more-dissimilar structures among communities (J. Zhou \& Ning, 2017).
This explanation emphasizes that capacity of organisms themselves
(\emph{i.e.} motoricity, competitiveness and adaptability), rather than
environmental selection, determines species distributions over spatial
scaling. But at local scale, which process, niche selection or dispersal
limitation, contribute more in the spatial patterns of microbial
communities?

For niche selection, we found there was no clear edaphic heterogeneity
within the sampling area (2-kilometer width) for both degraded and
undegraded meadow (\emph{r} \textsubscript{M}=-0.0153-0.0229,\emph{P}
\textgreater{}0.05) (Fig. S1). Meanwhile, the Mantel tests and multiple
regression on matrices (MRM) clearly demonstrated that both prokaryotic
and fungal communities were shifted by geographical distance, even with
partialling the edaphic and vegetation variables (Table 1, S4), however,
in degraded meadow only the fungi were shifted by edaphic and vegetation
variables. This suggested species heterogeneity at the local scale did
exist, but might not be determined by edaphic variables. In addition, we
used two null-model-based approaches NST and iCAMP to measure the
relative importance of assembly processes, both deterministic
(homogenous and heterogeneous selections), and stochastic (dispersal
limitation and drifts) (Table S5, Fig. 4a, d). From these results, we
found niche selection (or determinism) played a lesser role in community
assembly than stochasticity for both prokaryotes and fungi in undegraded
meadow and for prokaryotes in degraded meadow. This observation was
quite different with our previous study in a temperate typical
grassland, which demonstrated that deterministic processes, including
both heterogeneous and homogeneous selections, played dominant roles in
accelerating turnover rates for spatial assembly of prokaryotes along
soil depth (Du et al., 2020). But in the current study, niche selection
was not the dominant factor that impacted the spatial scaling patterns
in alpine meadow, suggesting that spatial scaling patterns could be
formed by different assembly mechanisms in different ecosystems.

For dispersal limitation, at first, it was found that stochasticity
(\textgreater{}80\%) was much stronger than determinism
(\textless{}20\%) in shaping the community assembly for prokaryotes in
both undegraded and degraded meadows, and also stronger in undegraded
meadow (58\% \emph{v.s.} 42\%) for the fungal community (Table S5).
Then, by using iCAMP, we found that dispersal limitation dominated the
stochastic process in both prokaryotic and fungal communities (Fig. 4a,
d), indicating the DDR and SAR patterns in alpine meadow were primarily
determined by dispersal limitation, especially for prokaryotes. These
results are corroborated by other studies that showed spatial
environmental heterogeneity is not coupled to increased species sorting,
while other factors, such as dispersal limitation or priority effects
could be critical (Comte, Monier, Crevecoeur, Lovejoy, \& Vincent, 2016;
Powell et al., 2015). More interestingly, in degraded meadow,
deterministic processes showed a stronger impact on fungal community
assembly than stochasticity (Table S5), which was consistent with the
results from Mantel and MRM tests that demonstrated edaphic variables
had significant correlations with fungal community irrespective of
whether or not the geographic distance was partialed (Table 1, S4).
However, when we precisely distinguished each assembly process along the
spatial distance, it was found that the percentage of dispersal
limitation rose significantly while homogeneous selection dropped off as
distance increased (Fig. 4f). This trend suggested the impact of
dispersal limitation would strengthen over spatial distance, and that it
played an increasingly greater role in shaping the community assembly of
fungi in degraded meadow. Together, these results suggested that at
local scale niche selection and dispersal limitation are both important
in increasing the spatial turnover rates of the fungal community in
degraded alpine meadow, which was in contrast with the stochasticity
dominated mechanism of prokaryotes in the same habitat and also the
fungi in undegraded meadow.

Our study systematically revealed the changes in the soil microbial
communities during the degradation process of alpine meadow on the
Qinghai-Tibet Plateau, and revealed the mechanisms driving community
assembly. The results indicated that diversity, community composition,
and structure of soil microorganisms were significantly shifted by
alpine meadow degradation. In addition, both prokaryotes and fungi
followed clear spatial scaling patterns, while degradation can
accelerate the spatial turnover rates of fungi, which could be driven by
both niche selection and dispersal limitation simultaneously.

\textbf{Acknowledgements}

This study supported by the Natural Science Foundation of Qinghai
Province (Grant No. 2021-ZJ-915), and National Nature Science Foundation
of China (NSFC Grant No. 31860103). The authors are very grateful to Dr.
James W. Voordeckers for his suggestions and grammar corrections on this
paper.

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\textbf{Author Contributions}

YW, YD, GL, and HY conceived and designed the experiments. YW, SY, LZ,
CH and XW performed the experiments. YW, XD and QH analyzed the data, YW
and YD wrote the paper. All authors have reviewed and agreed with the
paper.

\textbf{Data Accessibility}

The raw sequence data from this study were deposited in the NCBI
database with the sdudy accession number: PRJNA706905.

\textbf{Table 1. Mantel and Partial Mantel tests between the Bray-Curtis
dissimilarity of microbial communities and geographic distances/edaphic
variables/vegetation factors.}\selectlanguage{english}
\begin{longtable}[]{@{}lllllllllll@{}}
\toprule
& & & Prokaryotes & Prokaryotes & Prokaryotes & Prokaryotes & Fungi &
Fungi & Fungi & Fungi\tabularnewline
\midrule
\endhead
& Environmental factors & Partialling & Undegraded & Undegraded &
Degraded & Degraded & Undegraded & Undegraded & Degraded &
Degraded\tabularnewline
& & & r\textsubscript{M} & \emph{P} & r\textsubscript{M} & \emph{P} &
r\textsubscript{M} & \emph{P} & r\textsubscript{M} &
\emph{P}\tabularnewline
Mantel & Geographic distance & & 0.165 & 0.043* & 0.124 & 0.029* & 0.194
& 0.016** & 0.164 & 0.005**\tabularnewline
& Edaphic variables & & -0.148 & 0.982 & 0.000 & 0.500 & 0.007 & 0.443 &
0.163 & 0.003**\tabularnewline
& Vegetation factors & & -0.101 & 0.909 & -0.023 & 0.657 & 0.123 & 0.067
& 0.200 & 0.001***\tabularnewline
Partial Mantel & Geographic distance & Edaphic variables & 0.170 &
0.040* & 0.124 & 0.030* & 0.194 & 0.015** & 0.169 &
0.005**\tabularnewline
& Edaphic variables & Geographic distance & -0.154 & 0.982 & 0.002 &
0..465 & 0.002 & 0.493 & 0.167 & 0.001***\tabularnewline
& Geographic distance & Vegetation factors & 0.167 & 0.049* & 0.124 &
0.038* & 0.196 & 0.018** & 0.166 & 0.007**\tabularnewline
& Vegetation factors & Geographic distance & -0.104 & 0.928 & -0.024 &
0.691 & 0.126 & 0.070 & 0.202 & 0.001***\tabularnewline
\bottomrule
\end{longtable}

Environmental factors and geographic distance significantly correlated
with community differences at the level of 0.0001***, 0.01**, and 0.05*.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Fig. 1. The nested sampling design and the physiognomy of
undegraded and degraded alpine meadows on the Qinghai-Tibet Plateau.}

\textbf{Fig. 2. The diversity and structure of soil microbial
communities in degraded and undegraded alpine meadows.} (a) The richness
of soil microbial communities, and the significance of Student\emph{t}
-test **: \emph{P} \textless{}0.01; ***\emph{P} \textless{}0.001.
Principal coordinate analysis (PCoA) of the prokaryotic community (b)
and the fungal community (c). (d) The relative abundances of the
dominant phyla in degraded and undegraded alpine meadow.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\textbf{Fig. 3} \textbf{Distance-decay relationship (DDR) and
species-area relationship (SAR) for the soil prokaryotic and fungal
communities} . (a) DDR based on Sorensen dissimilarity along geographic
distances for the prokaryotic community; (b) DDR for the fungal
community; (c) DDR slope significance test of soil prokaryotes and
fungi; (d) SAR based on estimated richness (Chao1 value) in certain
areas for the prokaryotic community; (e) SAR for the fungal community;
(f) SAR slope significance test of prokaryotes and fungi.

\textbf{Fig. 4 The assembly process of microbial communities in degraded
and undegraded alpine meadows based on iCAMP measurement.} (a) The
percentages of different assembly processes for prokaryotic communities
in degraded and undegraded meadows. (b) The relative percentages of
different assembly process over geographic distances for prokaryotes in
undegraded alpine meadow. (c) The relative percentages of different
assembly process over geographic distances for prokaryotes in degraded
alpine meadow. (d) The percentages for different assembly processes of
fungal communities in degraded and undegraded meadows. (e) The relative
percentages of different assembly process over geographic distances for
fungi in undegraded alpine meadow. (f) The relative percentages of
different assembly process over geographic distances for fungi in
degraded alpine meadow.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\selectlanguage{english}
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