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\begin{document}

\title{Distinct spatiotemporal patterns between fungal alpha and beta diversity
of soil--plant continuum in rubber tree}



\author[1]{Yaqing Wei}%
\author[1]{Guoyu  Lan}%
\author[1]{Zhixiang Wu}%
\affil[1]{Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences}%


\vspace{-1em}



  
  \date{March 15, 2025}


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\selectlanguage{english}
\begin{abstract}
Plant-associated microbial communities strongly relate to host health
and productivity. Still, our knowledge of microbial community
spatiotemporal patterns in soil--plant continuum is largely limited.
Here, we explored the spatiotemporal dynamics of fungal communities
across multiple compartments (phyllosphere, leaf endosphere, soil,
rhizosphere, rhizoplane, root endosphere) of rubber tree in two
contrasting seasons collected from Hainan Island and Xishuangbanna. Our
results demonstrate that the fungal alpha and beta diversity exhibited
distinct pattern, the alpha diversity is highly dependent on seasonal
changes, while beta diversity only showed a geographical variation
pattern. The season-specific environmental factors (e.g., climatic
factors) were the most important factors in shaping fungal alpha
diversity across the soil--plant continuum. Physicochemical properties
explained some of microbial beta diversity spatiotemporal variation
observed, with leaf phosphorus (P) and soil available potassium (AK)
likely being the main factors that drove the geographical variation. We
further identified the variation of edaphic (e.g., AK) and leaf
physicochemical factors (e.g., P) were mainly caused by regional sites
(P \textless{} 0.05). Together, our study provide a solid empirical
evidence that the distinct spatiotemporal patterns of alpha and beta
diversity of rubber tree fungal diversity and significantly expand our
understanding of ecological drivers of plant-associated microbial
communities.%
\end{abstract}%



\sloppy


\textbf{Abstract}

Plant-associated microbial communities strongly relate to host health
and productivity. Still, our knowledge of microbial community
spatiotemporal patterns in soil--plant continuum is largely limited.
Here, we explored the spatiotemporal dynamics of fungal communities
across multiple compartments (phyllosphere, leaf endosphere, soil,
rhizosphere, rhizoplane, root endosphere) of rubber tree in two
contrasting seasons collected from Hainan Island and Xishuangbanna. Our
results demonstrate that the fungal alpha and beta diversity exhibited
distinct pattern, the alpha diversity is highly dependent on seasonal
changes, while beta diversity only showed a geographical variation
pattern. The season-specific environmental factors (e.g., climatic
factors) were the most important factors in shaping fungal alpha
diversity across the soil--plant continuum. Physicochemical properties
explained some of microbial beta diversity spatiotemporal variation
observed, with leaf phosphorus (P) and soil available potassium (AK)
likely being the main factors that drove the geographical variation. We
further identified the variation of edaphic (e.g., AK) and leaf
physicochemical factors (e.g., P) were mainly caused by regional sites
(\emph{P} \textless{} 0.05). Together, our study provide a solid
empirical evidence that the distinct spatiotemporal patterns of alpha
and beta diversity of rubber tree fungal diversity and significantly
expand our understanding of ecological drivers of plant-associated
microbial communities.

\textbf{Keywords: Rubber tree; Fungi; Diversity; Spatiotemporal
patterns}

\textbf{Introduction}

Microbial organisms inhabit all biomes of the Earth (Koskella, 2020),
and provide a number of life-support functions for their host (Cordovez
et al., 2019). Therefore, we must develop a better understanding of the
distribution and ecological drivers of aboveground and belowground
microbial communities. Recent studies have demonstrated the immense role
of plant compartment and environmental factors in driving the assembly
of microbiomes (Lan et al., 2023; Wei et al., 2022a; Xu et al., 2024).
Geographic location and seasonal change have been demonstrated to
influence community composition. For example, it was suggested that the
assembly of the phyllosphere bacterial and fungal communities is
predominantly determined by host compartment (epiphytic and endophytic)
and site location (Wei et al., 2022a). As for soil and rhizosphere,
microbiomes are influenced by environmental factors (e.g., site, soil
properties, and climate) (Grady et al., 2019; Lundberg et al., 2012;
Thiergart et al., 2020; Wei et al., 2022b; Xiong et al., 2021; Xu et
al., 2024). However, these studies mainly focused on single niche or
compartment, and a significant knowledge gap exists on how spatial
heterogeneity versus time shape the diversity and structure of microbial
communities along the soil--plant continuum. Different scales have
varying impact on plant microorganisms (Jumpponen and Jones, 2009;
Laforest-Lapointe et al., 2016; Qian et al., 2018; Wang et al., 2023).
Moreover, these examples have shown that soil microbial communities are
influenced by spatial or temporal change, but, understanding of how
seasonal changes (e.g., dry and rainy seasons) affect the compositions
and diversity of soil--plant continuum microbial communities at the
regional scale is still limited.

Rubber plantation is the most economically important agro-ecosystem in
tropical China, particularly in Hainan Island and Xishuanbanna
(abbreviated as Banna below) (Lan et al., 2017), where accounting for
more than 90\% of the total rubber plantation area of China (Xu et al.,
2014). It is reported rubber plantation have multiplied quickly
throughout Southeast Asia over the last two decades (Chen et al., 2023;
Li et al., 2015). As far as we know, rubber forests account for almost
25\% and 40\% of the total vegetation area in Hainan Island and Banna
(Lan et al., 2020), respectively. Previous work in Hainan has shown that
seasonal change or site location were the dominant factors resulting in
shifts in soil microbial composition at the local and geographic scales,
respectively (Lan et al., 2018; Lan et al., 2020; Lan et al., 2019; Wei
et al., 2022b). However, these studies were limited, particularly in the
sample sizes scales used. Given the importance of microbes in functional
roles in tropical forests ecosystem, such as nutrient acquisition,
disease resistance, and stress tolerance (Trivedi et al., 2020), and the
central part of rubber plantation of terrestrial ecosystems both in
Hainan and Banna. Moreover, little attention has been paid to the
plant-associated microbial communities in the same scale, as a result,
it is difficult to describe the overall pattern of the soil--plant
continuum. Therefore, it is necessary to study the spatiotemporal
pattern and ecological drivers of the rubber tree soil--plant continuum
microbial communities of these two locations.

\textbf{In this study, we examine fungal communities across multiple
compartments (bulk soils, rhizosphere, rhizoplane, root endosphere,
phylloplane, and leaf endosphere) based on field samples of rubber tree
during both dry and rainy seasons in two major areas of China (} Figure
S1\textbf{). We aimed to (1) determine the distribution pattern of
fungal communities along the soil--plant continuum of rubber tree; (2)
identify the relative importance of spatial heterogeneity versus season
and dominant drivers for driving fungal community at the regional scale.
We hypothesized that (1) both geographic and seasonal factors will
influence the assembly of rubber-associated fungal communities; (2) the
spatiotemporal distribution pattern is mediated by the spatiotemporal
variation of the driving factors.}

\textbf{Methods}

\textbf{Study site and sampling}

The study was conducted in two locations: Hainan Island and Bnna. Hainan
Island experiences a tropical maritime monsoon climate, characterized by
a rainy season from May to October and a dry season from November to
April. Rubber plantations in Hainan are located at low latitudes and
altitudes, making them tropical island-type plantations. On the other
hand, Bnna has a warm and humid climate throughout the year, with dry
(November to April) and rainy seasons (May to October) similar to
Hainan. The rubber plantations in Bnna are situated at higher latitudes
and altitudes, representing a tropical inland static wind plantation
area type with fertile soil (Lan et al., 2020).

We selected six major plantation sites from Danzhou, Wanning, and Ledong
Districts in Hainan Island, as well as from Jinghong, Menglun, and
Mengpeng Districts in Xishuangbanna (Figure S1). At each site, we chose
three plots separated by distances of 5-15 km for sampling, resulting in
a total of 18 plots. The sample collections were carried out in August
to September 2019 and November to December 2020, corresponding to the
rainy and dry seasons, respectively. Therefore, we obtained 36 soil
samples from each plot, resulting in a total of 216 samples, including
those from the phyllosphere, leaf endosphere, soil, rhizosphere,
rhizoplane, and root endosphere compartments. For each sample, we
analyzed water content (WC), pH, leaf phosphorus (P), potassium (K),
nitrogen (N), and organic matter (LOM). Additionally, we quantified soil
total nitrogen (TN), total phosphorus (TP), total potassium (TK),
organic matter (SOM), available potassium (AK), ammonium nitrogen (AN),
nitrate nitrogen (NN), and available phosphorus (AP). The soil, root,
and leaf sampling approach, as well as the analysis of physicochemical
properties, were conducted based on the methods described in our
previous study (Lan et al., 2023; Wei et al., 2022a). We collected
latitude, longitude, and elevation data for each site. Additionally,
data on average monthly precipitation and average monthly temperature
for each month were obtained from the National Meteorological
Information Center. (https://www.data.cma.cn).

\textbf{DNA extraction and \emph{sequencing}}

Microbial community DNA was extracted from soil, root, and leaf samples
using the FastDNA\selectlanguage{ngerman}® Spin Kit for Soil (MP Biomedicals), following the
manufacturer's instructions. The hypervariable region ITS of the fungal
gene was amplified using the primer pairs ITS1F
(5'-CTTGGTCATTTAGAGGAAGTAA-3') and ITS2R (5'-GCTGCGTTCTTCATCGATGC-3')
(Adams et al., 2013). Sequencing was conducted on the Illumina MiSeq
platform, following standard protocols. All samples were pooled in
equimolar concentrations and subjected to paired-end sequencing on the
Illumina MiSeq platform. The paired-end sequences were merged to
generate single sequences of approximately 300 bp. These sequences were
then quality-filtered (maximum expected error = 0.2), and singletons
were removed using USEARCH v.10. (Edgar, 2010). The raw reads obtained
from the sequencing were deposited into the NCBI Sequence Read Archive
(SRA) database (Accession Number: SRP342019).

\textbf{Data analysis}

The raw fastq files were demultiplexed and subjected to quality
filtering using QIIME (Caporaso et al., 2010) (version 1.17).
Operational Taxonomic Units (OTUs) were clustered at a 97\% similarity
cutoff using UPARSE version 7.1 (Edgar, 2013). Chimeric sequences were
identified and removed using UCHIME. The taxonomy of each representative
sequence of the OTUs was determined using the RDP Classifier version 2.2
(Wang et al., 2007) against the ITS database with a confidence threshold
of 0.7.

Diversity indices were based on resampled sequences using the MOTHUR
program (Schloss et al., 2009). Alpha diversity (observed OTU richness)
index was calculated for each sample using the \emph{vegan} package
(Oksanen et al., 2022) in the R environment (version 4.3.1). We modeled
the alpha diversity as a response variable and site location and
seasonal change as fixed effects. The relative importance of the
location and season for alpha diversity was evaluated by analysis of
variance (ANOVA) (Way and Klasson, 2020), with the p values corrected
using the false discovery rate (FDR) method. Principal coordinate
analysis (PCoA) was conducted using Bray--Curtis distances for the 216
samples to explore fungal community compositional differences (beta
diversity) in different compartments, seasons and locations, and then
was visualized by using \emph{ggplot2} (Wickham, 2009). The relative
importance of the locations/sites and two seasons for explaining the
variation in environmental variables and the alpha diversity of fungi
were evaluated by two-way ANOVA. The permutational multivariate analysis
of variance (PERMANOVA) in the R vegan package was used to test the
variations in fungal beta diversity as explained by locations and
seasons (Jiao et al., 2022).

Random forest (RF) analysis (rfPermute function in \emph{rfPermute}
package in R) (Archer, 2013) was used to identify the main environmental
drivers for soil fungal alpha diversity (Delgado-Baquerizo et al., 2016;
Trivedi et al., 2016). To reveal the relationship between alpha
diversity and environmental factors, a linear (linear least-squares
regression analysis) or nonlinear regression was used based on RF
results. The Mantel test was performed to evaluate the influence of soil
properties, climate factors and leaf properties upon fungal community of
different compartments, using the mantel function of the \emph{ecodist}
package (Goslee and Urban, 2007) and \emph{vegan} package for R (Oksanen
et al., 2022) and visualized by using the \emph{linkET} packge (Huang,
2021). We used variation partitioning to quantify the relative
importance of seasonal change (dry and rainy season), climatic factors
(temperature and precipitation), physicochemical properties (soil
including soil pH, WC, SOM, TK, TN, TP, AN, NN, AK, AP; leaf including
pH, WC, LOM, K, N, P) and geographic variables (Yeh et al., 2015).
Latitudinal and longitudinal data for each site was transferred to
rectangular data to represent spatial distance by function pcnm
of\emph{Vegan} package, and variation partitioning analyses were
conducted with function varpart in the \emph{vegan} package for R
(Oksanen et al., 2022).

\textbf{Results}

\textbf{Community composition and environmental variables}

A total of 9036, 7861, 11001, 10261, 9701, 3846 operational taxonomic
units (OTUs) were detected for the six compartments (phyllosphere, leaf
endosphere, soil, rhizosphere, rhizoplane, root endosphere,
respectively). Among these OTUs, the majority were assigned to the
classes \emph{Dothideomycetes (18.10\%)} and Sordariomycetes (16.51\%),
Eurotiomycetes (10.64\%), Tremellomycetes (9.46\%), and Agaricomycetes
(8.37\%) at the class level (Figure S2).

Among the six measured leaf environmental variables, water content (WC),
leaf pH, and organic matter (SOM) showed strong seasonal variations,
with higher values during the rainy season compared to the dry season.
Leaf phosphorus (P) variables, on the other hand, were more influenced
by geographical location or site rather than seasonal changes (Figure 1,
S3). In contrast, the ten measured soil physicochemical properties were
primarily explained by geographical locations or sites. Variables such
as available potassium (AK), soil pH, total nitrogen (TN), total
potassium (TK), total phosphorus (TP), water content (WC), organic
matter (SOM), nitrate nitrogen (NN), and available phosphorus (AP) were
largely influenced by the specific sites where sampling was conducted.
In addition, mean seasonal precipitation and mean seasonal temperature
showed significant seasonal variations. Approximately 97.6\% (\emph{P}
\selectlanguage{english}<0.001) of the variation in precipitation and 96.4\% (\emph{P} \selectlanguage{english}<0.001)
of the variation in temperature were explained by sampling seasons.
During the rainy season, leaf water content, precipitation, and
temperature were significantly higher compared to the dry season.
(Figure 2, S4).

\textbf{Spatiotemporal pattern of the fungal community}

In terms of alpha diversity, the observed OTU richness in the
phyllosphere, rhizosphere, rhizoplane, and soil compartments were
roughly equal, while the leaf endosphere showed significantly higher
alpha diversity in Banna compared to Hainan, while the root endosphere
exhibited the opposite trend (Figure S5a, Table S1). When considering
the seasonal effect, the observed OTU richness of bacterial communities
in the leaf endosphere (\emph{P} \selectlanguage{english}<0.01), root endosphere (\emph{P}
\selectlanguage{english}<0.05), and rhizoplane (\emph{P} \selectlanguage{english}<0.01) were significantly higher
during the rainy season compared to the dry season (Figure S5b, Table
S1). However, when analyzing the seasonal effect separately, distinct
patterns were observed. In Banna, the alpha diversity of all
compartments was significantly higher during the rainy season compared
to the dry season. In Hainan, although the alpha diversity of the root
endosphere and rhizoplane were similar between the rainy and dry
seasons, and the leaf endosphere showed significantly higher alpha
diversity during the rainy season, the phyllosphere, rhizosphere, and
soil compartments exhibited significantly higher alpha diversity during
the dry season. Overall, the trend in alpha diversity was higher in the
dry season compared to the rainy season in Hainan (Figure 3a).

When analyzing the microbial composition based on the Bray-Curtis
distance, we observed that geographical location had a significant
effect on the beta diversity of fungal communities in all compartments
(\emph{P} \selectlanguage{english}<0.01), while seasonal effects were not significant (Figure
3). For instance, geographical location accounted for 6.62\%, 7.35\%,
9.13\%, 8.07\%, 17.67\%, and 18.78\% of the variation in the soil,
rhizosphere, rhizoplane, root endosphere, phyllosphere, and leaf
endosphere, respectively. Additionally, we observed a much greater
effect of site variation compared to seasonal variation in all
compartments (Figure S6). In summary, our findings indicate that
geographical location/site has a significant impact on fungal
composition, while season does not.

\textbf{Drives of environmental factors in shaping rubber tree fungal
community}

Among all environmental factors, leaf water content (WC), temperature,
and precipitation were identified as the most important predictors of
fungal alpha diversity in different compartments (Figure 4, Figure S5b).
These findings were further supported by simple linear and nonlinear
regression analyses. For instance, significant and positive simple
linear regressions were observed between leaf WC, temperature, and
fungal alpha diversity in the leaf endosphere and root endosphere
compartments. Additionally, a similar mid-peak pattern was observed in
four datasets, where richness peaked at mid-temperature in the
phyllosphere and rhizosphere compartments, and peaked at
mid-precipitation in the soil and rhizoplane compartments. These results
indicate that climatic factors play a significant role in driving the
alpha diversity of fungi in rubber tree ecosystems.

The major physicochemical and climatic factors to the fungal composition
were further identified using the Mantel tests. Of the most important
environmental factors contributing to the leaf composition, leaf P had
the largest observed effect, followed by \textbf{temperature} and
precipitation, while soil AK affect the composition most in all root-
associated compartments (Figure 5, Table S2). Specifically, temperature
and precipitation were significantly correlated with the fungal
communities in different compartments to a certain extent (Table S2).
The contributions of seasonal, environmental, climatic and geographic
variables to the variation in fungal composition were quantified by
variation partitioning (VPA). Geographic factors were better predictors
of fungal composition than seasonal, environmental and climatic ones
(Figure 6), confirming a stronger effect of spatial variation in driving
the composition of soil fungi.

\textbf{Discussion}

Revealing the spatiotemporal pattern of microbial communities is a
fundamental topic in ecology, which have been explored extensively in
microbial ecology over the last two decades (Chu et al., 2020).
Furthermore, the significant effect of the seasonal change in regulating
the alpha diversity of soil bacteria and fungi was found at the regional
scale (Hainan) in our previous study (Wei et al., 2022b). Still very few
studies have mapped the temporal and spatial distribution changes of
microbial communities of the soil--plant continuum. Here we explored the
spatiotemporal of soil--plant continuum fungal community in the rubber
tree across different niches and regions, doing so can help to clarify
the drivers of space and seasonal change upon microbial community
variations. Our findings provide robust empirical evidence that the
spatiotemporal variation of fungal diversity in rubber tree was mainly
shaped by seasonal change, but only spatial impacts significantly
altered microbial beta diversity.

Our results demonstrate that the alpha diversity of soil--plant
continuum fungal community is highly dependent on seasonal changes,
which is in line with previous studies that have observed significant
seasonal variations in microbial diversity (Fournier et al., 2020; Lan
et al., 2018; Rasche et al., 2011; Xiang et al., 2021; Zhang et al.,
2020). In our study, we provide evidence suggesting that climatic
factors play a crucial role in mediating the seasonal variation of
fungal alpha diversity. Climatic factors have been identified as the
best predictors of soil fungal richness and community composition at a
global scale (Bahram et al., 2018; Tedersoo et al., 2014). Importantly,
our study further extends this earlier observations at the soil--plant
continuum and now provides widespread evidence that climatic factors
mediating the alpha diversity of plant microbiome. Among the
environmental variables, we found that temperature and precipitation
were the dominant predictor for fungal richness, which has also been
found in numerous previous studies (Bahram et al., 2018;
Delgado-Baquerizo et al., 2017; Fierer, 2017; Hiiesalu et al., 2017; Liu
et al., 2020; Tedersoo et al., 2014). Notably, the alpha diversity are
sensitive to temperature and precipitation, displaying an unimodal
pattern in most compartments, except for the leaf endosphere and root
endosphere which showed a linear pattern. Given that temperature and
precipitation are generally higher during the rainy season and higher in
Hainan compared to Banna, this further supports the observed unimodal
pattern in most compartments. Thus, it is not surprising to find that
the contrasted seasonal change pattern in Hainan and Banna. Furthermore,
we observed a stronger seasonal effect compared to a geographical
location effect on some environmental predictors. Specifically, leaf
physicochemical factors such as water content (WC) and climatic factors
such as temperature and precipitation were primarily influenced by
seasonal changes, contributing to the mechanisms driving microbial
seasonal variations.

In contrast, we provide solid evidence that the beta diversity of
soil--plant continuum only showed a geographical variation pattern. This
aligns with previous studies that have shown spatial factors to be more
important in shaping soil microbial communities across large spatial
scales (Fierer and Jackson, 2006; Lauber et al., 2013; Wei et al.,
2022b; Zhang et al., 2020). The effect of site location was far more
influential than the seasonal change in regulating the communities of
both soil bacteria and fungi at the regional scale (only in Hainan) in
our previous study (Wei et al., 2022b). Given that biogeographic
patterns variation of community similarity indicates the influence of
historical factors (Ma et al., 2017; Martiny et al., 2006), compare to
our previous studies (research in Hainan soil samples) (Wei et al.,
2022b), the stronger geographical variation pattern suggests that the
pronounced impact of historical event on fungal community structure in
soil--plant continuum of rubber tree. For fungal beta diversity, leaf
phosphorus (P) and soil available potassium (AK) were the most important
factors in leaf and soil samples, respectively. Besides, major taxa
belonging to \emph{Dothideomycetes} and Eurotiomycetes in leaf samples,
according to their life strategies, which have been assigned as
copiotrophic fungi, this might explain why leaf samples responded to
altered leaf nutrients (e.g., leaf P), which have already been
demonstrated (Evans et al., 2014; Ho et al., 2017; Li et al., 2021;
Placella et al., 2012). It is worth noting that leaf P and AK which is a
highly localized variable, were evidently stronger affected by sampling
sites. In all, we found a stronger geographic location effect than
seasonal effect upon fungal beta diversity estimates. Furthermore,
geographic factors contributed a larger proportion of variation relative
to edaphic and climatic factors to the beta diversity of rubber leaf
than soils that of soil--plant continuum, indicating a stronger effect
of stochastic processes in driving the beta diversity of rubber leaf.
These results was also confirmed by the VPA models and Mantel test, and
are also consistent with previous observations (Lan et al., 2022).

\textbf{Conclusion}

Our results demonstrate that the alpha diversity is highly dependent on
seasonal changes, while beta diversity only showed a geographical
variation pattern. Especially, our work showed that spatiotemporal
variation in fungal community alpha and beta diversity was mainly driven
by climatic factors and soil properties (e.g., AK), leaf properties
(e.g., P), respectively. Moreover, the leaf P and AK were mainly
explained by the geographic location effect rather than the seasonal
effect, and climatic factors showed opposite pattern. Taken together,
our study provides empirical evidence for the distinct spatiotemporal
patterns and driving factors between alpha and beta diversity in the
fungal community of the soil-plant continuum in rubber trees.

\textbf{Author contributions}

Yaqing Wei and Guoyu Lan planned and designed research; Yaqing Wei and
Guoyu Lan performed experiments; Yaqing Wei, Guoyu Lan, Zhixiang Wu
conducted fieldwork; Yaqing Wei analyzed the data and wrote the
manuscript.

\textbf{Declaration of competing interest}

The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to
influence the work reported in this paper.

\textbf{Data Availability}

Raw reads were deposited into the NCBI Sequence Read Archive (SRA)
database (Accession Number: SRP342019).

\textbf{Funding}

This work was supported by the National Natural Science Foundation of
China (32271603), the Hainan Province Science and Technology Special
Fund (ZDYF2024SHFZ096), the Earmarked Fund for Chinese Agricultural
Research Systems (CARS-33-ZP3), and the Central Public-interest
Scientific Institution Basal Research Fund (NO. 1630022024013).

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\textbf{Supporting information}

Additional supporting information is available in the supplement
materials.

\textbf{Supplementary figures}

\textbf{Figure S1} Study sites on Hainan Island and Xishuangbanna. Red
solid circles indicate study sites on the maps. Each site was further
divided into 3 plots, totaling 18 sampling plots.

\textbf{Figure S2} Spatiotemporal changes in fungal community
composition (class level) in different compartments of rubber trees.

\textbf{Figure S3} Environmental variables in dry and rainy seasons
among the six sampling sites of rubber tree leaves. The significant
differences between seasons and locations were detected by two-way
ANOVA. N: Total nitrogen, P: Total phosphorus, K: Total potassium, WC:
Water content, LOM: Leaf organic matter.

\textbf{Figure S4} Environmental variables in dry and rainy seasons
among the six sampling sites of rubber tree soils. The significant
differences between seasons and locations were detected by two-way
ANOVA. WC: Water content, SOM: Soil organic matter, pH: Soil pH, AN:
Ammonium nitrogen, NN: Nitrate nitrogen AP: Available phosphorus, AK:
Available potassium, TN: Total nitrogen, TP: Total phosphorus, TK: Total
potassium.

\textbf{Figure S5} Boxplots showing the number of OTUs between the two
locations (a) and seasons (b). Leaf.WC: Leaf water content.

\textbf{Figure S6} Principal coordinates analysis (PCoA) of taxonomic
similarity based on Bray-Curtis distances (OTU level). Six compartments
in Hainan (a) and Banna (b). LD: Ledong, DZ: Danzhou, WN: Wanning; MP:
Mengpeng, JH: Jinghong, ML: Menglun.

\textbf{Supplementary tables}

\textbf{Table S1} The significant effect of location and season on
fungal alpha diversity was detected by two-way ANOVA.

\textbf{Table S2} Mantel test results for the correlation between
community similarity and environmental.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1} Environmental variables in dry and rainy seasons
between two locations of rubber tree leaves. The significant differences
between seasons and locations were detected by two-way ANOVA. N: Total
nitrogen, P: Total phosphorus, K: Total potassium, WC: Water content,
LOM: Leaf organic matter. *, \emph{P} \textless{} 0.05; **, \emph{P}
\textless{} 0.01, ***, \emph{P} \textless{} 0.001\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Figure 2} Environmental variables in dry and rainy seasons
between two locations of rubber tree soils. The significant differences
between seasons and locations were detected by two-way ANOVA. WC: Water
content, SOM: Soil organic matter, pH: Soil pH, AN: Ammonium nitrogen,
NN: Nitrate nitrogen AP: Available phosphorus, AK: Available potassium,
TN: Total nitrogen, TP: Total phosphorus, TK: Total potassium. *,
\emph{P} \textless{} 0.05; **, \emph{P} \textless{} 0.01, ***, \emph{P}
\textless{} 0.001\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\textbf{Figure 3} Alpha diversity of rubber tree fungal community (a).
Significant differences between seasons in each sampling area are marked
by stars. (b) Principal coordinates analysis (PCoA) of taxonomic
similarity based on Bray-Curtis distances (OTU level). P: phyllosphere,
PE: leaf endosphere, S: soil, R: rhizosphere, RP: rhizoplane, RE: root
endosphere, ***\emph{P} \textless{} 0.001; **\emph{P} \textless{} 0.01;
*\emph{P} \textless{} 0.05.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\textbf{Figure 4} Drivers of soil bacterial \selectlanguage{greek}α-\selectlanguage{english}diversity across different
compartments. Random forest (RF) analyses identifying the importance of
potential predictors of fungal richness. RF Importance = Increase in \%
mean square error. Red and blue columns represent \emph{P} \textless{}
0.05 and \emph{P} \textgreater{} 0.05, respectively. Relationships
between environmental factors and the bacterial \selectlanguage{greek}α-\selectlanguage{english}diversity was
estimated via linear least-squares regression analysis. Solid circle
(red: dry season; blue: rainy season) indicate samples from Banna; Solid
triangle (red: dry season; blue: rainy season) indicate samples from
Hainan. P: phyllosphere, PE: leaf endosphere, S: soil, R: rhizosphere,
RP: rhizoplane, RE: root endosphere, WC: Water content, N: Leaf
nitrogen, P: Leaf phosphorus, K: Leaf potassium, LOM: Leaf organic
matter, SOM: Soil organic matter, pH: Soil pH, AN: Ammonium nitrogen,
NN: Nitrate nitrogen AP: Available phosphorus, AK: Available potassium,
TN: Total nitrogen, TP: Total phosphorus, TK: Total potassium, Pre:
Precipitation, Tem: Temperature.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

\textbf{Figure 5} Correlation analysis among edaphic properties,
climatic characteristics and microbial communities in the rubber tree
microbial community determined using the Mantel test. The color of the
line represents the significance of the correlations (P-values). The
width of the line represents the size of the correlation coefficients
(Mantel's r). The size and color of the squares represents the values of
the correlation coefficients (Pearson's r). WC: Water content, Leaf.N:
Leaf nitrogen, Leaf.P: Leaf phosphorus, Leaf.K: Leaf potassium LOM: Leaf
organic matter; SOM: Soil organic matter, pH: Soil pH, AN: Ammonium
nitrogen, NN: Nitrate nitrogen AP: Available phosphorus, AK: Available
potassium, TN: Total nitrogen, TP: Total phosphorus, TK: Total
potassium, Pre: Precipitation, Tem: Temperature.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image6/image6}

\end{center}
\end{figure}

\textbf{Figure 6} Variation partitioning analysis (VPA) showing the
effects of leaf, soil properties, climatic factors and geographic
factors, and season, on the microbial community composition in the
microbial beta diversity. The values indicate the percentage of
variation significantly explained by each section.

\selectlanguage{english}
\FloatBarrier
\end{document}

