Divergent patterns and assembly processes of soil fungal abundant and rare communities along an elevational gradient in subalpine areas of Southwest China

doi:10.21203/rs.3.rs-2450314/v1

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Divergent patterns and assembly processes of soil fungal abundant and rare communities along an elevational gradient in subalpine areas of Southwest China

https://doi.org/10.21203/rs.3.rs-2450314/v1

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Aim

Understanding the patterns and assembly processes of microbial communities along an elevational gradient remains largely debated.

Methods

We examined soil fungal abundant and rare communities and the underlying drives across a wide elevation from 2100-3950 m (a. s. l.) along the Yulong Mountain of Southwest China.

Results

We found the abundant and rare taxa were divergent in diversity, and only the α diversity of abundant taxa followed a humpback trend and peaked at 2900 m, despite the β diversity were significantly dependent on elevation gradients. Soil fungal abundant and rare taxa showed significant elevation-decay relationship, with more dispersal limitation to abundant taxa than that of rare taxa. Along the elevational gradients, the assembly of abundant fungal sub-communities were governed by combined effect of both environmental factors (soil nitrogen and potassium, soil temperature) and dispersal limitation, whereas the rare fungal sub-communities were merely dominated by stochastic processes (ecological drifts). Network modules analysis revealed higher functional redundancy in rare fungal sub-communities and this influence reinforced neutrality, and hence impelled rare fungal more susceptible to drift.

Conclusion

Our results suggested the divergent pattern and assembly process for soil fungal abundant and rare fungal taxa along an elevational gradient emphasized the stochastic process in fungal communities’ assembly, especially for low abundant taxa.

Alpine Mountain

Biogeography

Community assembly

Elevations

Elucidating species richness along elevational gradients is indispensable to understand the influence of climates on ecosystem functions (Lomolino 2001, Rahbek 2005, Meier et al. 2010, McCain and Knight 2013). Generally, the elevational patterns of macroorganisms followed two different patterns with increasing elevation: diversity monotonically decreases, and diversity peaks in mid-elevation with a hump-shaped patterns (Rahbek 1995, Lomolino 2001, Rahbek 2005, McCain and Knight 2013). However, it has remained debated whether soil microbes follow the same elevational patterns. Bryant et al. (2008) first documented that soil acidobacterial diversity just followed a decreasing trend with increasing elevation contrast to the unimodal pattern of plant diversity (Bryant et al. 2008). Given their small size, high abundant and dispersal rate of microorganisms, microbes are long-assumed to cosmopolitan and following different distribution rules (Fierer et al. 2011, Nottingham et al. 2018).

Recent works have well established that microbial community variation induces by deterministic factors (i.e. species traits, interspecies interaction, environmental filtering) and stochastic processes (i.e. history events, ecosystem drift, dispersal limitation) (Tedersoo et al. 2014, Fierer 2017, Delgado-Baquerizo et al. 2018). It is generally accepted that both deterministic and stochastic processes regulation simultaneously in assembly of local and regional microbial communities, and a conceptual and quantitative paradigm has been proposed that community diversity and dynamics are regulated by four high-level general ecological process: selection, dispersal, speciation or diversification, and ecological drift (Vellend et al. 2014, Ning et al. 2020). However, in contrast with the bacterial and archaeal community, soil fungi are recognized as symbiotic association with living plants and dead plants whether as mycorrhizal partners or parasites, which equally well appreciated their association with ecosystem carbon and nitrogen cycling (van der Heijden et al. 1998, Tedersoo et al. 2014, Peay et al. 2016). We still have a limited understanding on the elevational patterns and assembly processes of soil fungal community, albeit such knowledge is critical to reach general conclusion the prevalence of elevation diversity trend (Lomolino 2001). The influence of elevation on fungi diversity is not only indispensable to a comprehensive understanding of biodiversity distribution, but also answer fundamental questions for predicting the potential influences of climate change over the landscape-scale gradient, especially in alpine forests (Rahbek 2005, Meier et al. 2010, McCain and Knight 2013, Shen et al. 2014). In particular, soil fungal communities, as high diverse at both taxonomic level and metabolic levels, commonly exhibited unbalanced distribution with large number of low-abundant taxa and a small number of high-abundant taxa (Tedersoo et al. 2014, Peay et al. 2016, Jiao and Lu 2020).

Most previous studies have focused on the abundant taxa because of their important roles in carbon cycling and biomass production (Pedros-Alio 2012, Shade et al. 2014, Jia et al. 2018). While other studies documented the rare taxa had an over-proportional role in biological process and sustaining ecosystem functions (Lynch and Neufeld 2015, Wu et al. 2017, Chen et al. 2020b). Also, it has been reported that ecosystem functions and services are sensitive to the loss of rare taxa (Pendleton et al. 2014, Chen et al. 2020b, Xun et al. 2021). The rare microbial taxa can serve as the microbial “seed bank” to be dominant under suitable conditions or after disturbance (Pedros-Alio 2012, Shade et al. 2014, Xue et al. 2018). Thus, both abundant and rare taxa are very important in regulating and maintain ecosystem functions. However, we still lack data on whether both abundant and rare taxa follow similar biogeography. A wide range of studies have been documented that the abundant rare taxa are regulated by deterministic processes, and the rare taxa are primarily governed by stochastic processes in various ecosystems such as marine water (Mo et al. 2021), fresh water (Chen et al. 2020a), agriculture soil (Jiao and Lu 2019, Jiao and Lu 2020). However, contrasting results which both exhibited similar spatial and temporal patterns were also observed in inland freshwater (Liu et al. 2015, Chen et al. 2020a) and subalpine peatland (Tian et al. 2020). These outcomes indicated that the microbial sub-community’s assembly processes could vary with the environmental gradients (e.g., salinity: fresh water vs marine water; or nutrient availability: marine vs rice soil). While mountain systems offer ideal climate gradients in a short spatial distance, however, how the balance between stochastic and deterministic processes in the fungal sub-communities change with an elevation gradient remains unknown.

In this study, we conducted a field experiment along an elevational gradient from 2100 to 3950 m above sea level (a. s. l) in Yulong Mountain of Southwest China, in order to examine the response of soil fungal abundant and rare communities to elevations. This research will enhance our understanding fungal diversity in response to global climate change. Here, we first hypothesized that the different geographic patterns between soil fungal abundant and rare taxa would be occurred along the elevational gradients, due to only rare species can thrive only in specific niches along the elevation gradient (Jia et al. 2018). Our second hypothesis was that the relative importance of community assembly processes varied between abundant and rare fungal communities because that the assembly processes may be mediated by environmental factors, especially temperature dynamic (Dini-Andreote et al. 2015, Jiao and Lu 2020).

Study area and measurements

We sampled soil samples at eight sites along an elevational transect on Yulong Mountain (27°12″ N, 100°10′50″ E), where is located in the Hengduan Mountains, the center of the global biodiversity hotspot “Mountains of Southwest China” (Myers et al. 2000). The area has a mean annual temperature 8.6 ℃ and annual precipitation of 1372 mm, with a dry season (November to May) and rainy season (June to October) (Luo et al. 2019). The sampling sites were located between 2100 and 3950 m above sea level and geographic distance across all sites was up to 10 Km. In July 2019, 36 plots (20 m × 20 m) were established at the eight elevation belts with six plots per elevational belt below 3300 m (i.e. 2100, 2400, 2600, 2900, 3100, 3300 m) and three plots per elevational belt above 3300 m (i.e. 3600, 3950 m) according to distinct vegetation types and elevation ranges. Each elevation belt, all the plots were arranged at 100 apart. Nine topsoil (0–10 cm) and subsoil (10–20 cm) soil cores were pooled as one complete soil sample after removing gravel and plant detritus. Soil samples were immediately divided into two parts after sieving through 2 mm sieve: one stored at -20 ℃ for chemical and physical analysis, and the other one stored at -80 ℃ for molecular analysis.

The total DNA was extracted from 0.5 g of soil using MoBio PowerSoil DNA Extraction Kit (MO BIO, Carlsbad, CA, USA). The primers ITS1f/ITS2 (ITS1f, CTTGGTCATTTAGAGGAAGTAA, ITS2, GCTGCGTTCTTCATCGATGC) was selected to amplify the ITS1 region of the fungal gene on the Illumina Hiseq2500 platform (Illumina, inc., San Diego, CA, USA) using a paired-end (2 ×250 bp) approach (Schmidt et al. 2013). The acquired sequences were processed and filtered for quality using the Microbial Ecology (QIIME) with the DADA2 pipeline (version 1.6.0) (Callahan et al. 2016). For DADA2’s analysis, default settings were used with standard workflow (https://benjjneb.github.io/dada2/tutorial.html). Amplicon sequence variant (ASVs) were collapsed into representative sequences by reads, because ASVs provide greater resolution in amplicon differentiation. The ASV approach has been shown to outperform Operational Taxonomic Unit (OTU) clustering; unlike OUT clustering, ASVs are not compared with a reference database and are retained when they meet an arbitrary similarity cutoff (Callahan et al. 2017). Taxonomic classification was conducted on fungal sequences using UNITE developer’s full-length ITS reference sequences and phylogenetic tree was generated using FAST TREE 2 (Katoh and Standley 2013, Kõljalg et al. 2013). In further, the fungal functional profiles were predicted based on FUNGuild with the confidence level of “probable” or “highly probable” (Nguyen et al. 2016). The raw sequencing data from this study were deposited in the public NCBI database under the BioProject accession number PRJNA735089.

Environmental variables, including pH, soil organic carbon (SOC), total nitrogen, (TN), total sulfur (S), nitrate-nitrogen (NO₃⁻-N), ammonium-nitrogen (NH₄⁺-N) were measured using standard analytical methods (Bao 2000), as detail described by Yang et al. 2018. The total potassium (K), total sodium (Na), and total magnesium (Mg) measured using a Thermo Scientific iCE 3300 Atomic Absorption spectrometer (Thermo Fisher Scientific, Massachusetts, USA).

Statistical analysis

To avoid random effects on the identification of rare taxa, OUTs that contained less than 20 reads were removed, and 27197 sequences from each sample were randomly selected to avoid potential side effects. In this study, we defined “abundant” and “rare” OTUs at the local and regional levels, in accordance with other studies investigating microbial community dynamic (Logares et al. 2014, Liu et al. 2015). Here, at the local level (i.e. in one sample), total abundance of the OTUs above ≥ 1% and ≤ 0.05% were classified as “abundant” and “rare”, respectively. At the regional level (i.e., across all samples), the average relative abundances of the OTUS above ≥ 0.05% and ≤ 0.005% were classified as “abundant” and “rare”, respectively. Given the aim of this study, we focused on the dynamic of abundant and rare OTUs and the intermediate taxa (relative abundance range from 0.0005-0.5% across all samples) with less abundance and richness (less than 12% sequences number) were excluded in further analysis.

All statistical analyses were conducted in the R environment (v3.6.3; http://www.r-project.org/), using “vegan”, “igraph”, “Hmisc”, and “ggplot2” packages, unless otherwise indicated in below context. The fungal α diversity (OTUs richness and Shannon index) and β diversity (Bray-Curtis and unweighted Unifrac distance) were calculated. The geographical distances were calculated from the sampling coordinates by using the “geoXY”. Function of the “SoDA” packages. Distance-decay relationships were calculated as the linear-squares regression relationships between geographic distance and community similarity (based on Bray-Curtis distance).

To avoid the relationship between environmental and spatial factors, the geographic distance was divided into spatial variable by using Moran’s eigenvector maps (Griffith and Peres-Neto 2006). The principal coordinates analysis of neighbor matrices (PCNM) was derived from spatial coordinates by using with “pcnm” function of the “vegan” package. All the detectable spatial scales in the dataset combined with edaphic variables were filtered based on forward selection procedure based on unweighted Unifrac distance. Constrained principal coordinate analyses (CPA) were used to evaluate the effect of elevation, soil depth or edaphic variables on unweighted Unifrac distance of soil fungal communities. To visualize the relationship between edaphic variables or α diversity (OUTs richness and Shannon index) and β diversity (Bray-Curtis distance), nonmetric multidimensional scaling (NMDS) analysis was performed based on Bray-Curtis distance by using the “metaMDS” function of the “vegan” package. Distance-decay relationships were calculated as the linear least-squares regression between geographic distance and community similarity (based on 1- [dissimilarity of Bray-Curtis distance metric]).

To examine the effects of assembly processes on variation in fungal β diversity along the elevation gradients, βNTI was used to evaluate the phylogenetic clustering of abundant and rare sub-communities. Briefly, beta mean nearest taxon distance (βMNTD) metric was used to calculate pairwise phylogenetic turnover between communities using the “comdistnt” function (abundance.weighted = TRUE). And then, beta nearest taxon index (βNTI) is the number of standard deviations that the observed βMNTD is from the mean of null distribution (999 randomizations). The absolute value of βNTI above + 2 indicates a deterministic (niche-based) process, and below + 2 indicates a stochastic process (Stegen et al. 2013). The quantification of assembly processes were inferred through phylogenetic bin-based null model analysis (iCAMP) in iCAMP packages under the default parameters (bin.size.limit = 24) (version 1.2.9) (Ning et al. 2020).

Co-occurrence network analysis was conducted based on the interaction patterns of fungal OTUs using SparCC, with the average of 10 iterations and a bootstrap procedure to estimate pseudo-P values from 999 permutations (Friedman and Alm 2012). Networks were visualized with Gephi (http://gephi.github.io/). The topology parameters of the networks were calculated using the igraph package in R. The eigenvalue of each ecological module was calculated by averaging the standardized relative abundance (z-score) of the species within each module (Fan et al. 2019).

General distribution patterns of soil fungal rare and abundant taxa

The obtained 3,783,759 high-quality sequences were clustered into 12,038 OTUs. After removing the less than 20 sequence and resampling to 27,197 sequences per sample, 1,958,184 sequences (7,004 OTUs) were retained (Table S1). The alpha diversity in terms of the OTU richness and Shannon index were calculated for the abundant and rare taxa along elevations. As excepted, the abundant taxa generally accounted for a low proportion of OTUs (11.28%) and large relative abundance in all samples (79.14%), compared to the rare taxa with richness by 71.46% and abundance by 9.30%, respectively (Table S1). There was large phylogenetic diversity in both abundant and rare sub-communities (Fig. 1a). The abundant taxa were primarily consisted of Asomycota and Basidiomycota, while the rare taxa were primarily comprised of much more taxonomic groups including Glomeromycota, Mucoromycota and Rozellomycota than the abundant taxa (Fig. 1a, Fig. S2). In addition, the rare taxa contained more taxonomic and larger presentence than abundant taxa across all soil samples (Fig. 1b).

The α diversity of all taxa showed marginally significant difference between elevations (P = 0.052) and depth (P < 0.001), with a hump shape pattern of subsoil and peaking at 2900 m (Fig. 2a, Table 2S). The α diversity of abundant taxa varied with elevations, and the rare taxa changed with both elevations and depth. Namely, the α diversity of abundant taxa showed a hump shape patter irrespective of soil depth, and the rare taxa show a U-shaped pattern in topsoil and an increasing diversity pattern in subsoil (Fig. 2).

Soil total and sub-communities’ fungal composition significantly varied with elevations and rare sub-community changed with depth according to the constrained principal coordinates analysis (CPA) (Fig. 3; Table S4). Also, a striking separation of communities along elevation gradients was observed. The total and sub-communities’ composition was clustered into three groups (High, Middle and Low) along the elevation gradients (Fig. 3). Significant differences in total and sub-communities were observed among the three groups based on ANOSIM test (Table S4).

The elevation-decay relationship of the abundant and rare taxa sub-communities were determined and defined as the community similarity versus elevational difference for each pairwise set of sampling sites (Fig. 4). The abundant taxa community was steeper than the rare taxa community (0.0316 for abundant; 0.0162 for rare).

Drivers and assembly processes of soil fungal abundant and rare sub-communities

The major environmental variables on the composition of each sub-community were estimated a distance-based linear model with forward selection process. The CPA suggested that soil nitrogen content (N), total potassium (K) and the spatial variables were the most important drivers on the assembly of total and sub-communities (Fig. 3). The composition of fungal community was also closely related with the soil K and soil N contents (Fig S4-6). The magnitude of these community compositions showed a significantly negative relationship with soil fungal Shannon indices in all and rare taxa (Fig S4-6).

The βNTI of abundant and rare taxa across the elevation gradients exhibited unimodal patterns. The stochastic assembly processes were dominant in the abundant taxa (|βNTI| < 2), while there was a shift towards dominance of deterministic processes (|βNTI| > 2) in the rare taxa at the middle elevation levels (Fig. 4b). To account for quantifying their relative importance of assembly mechanisms, iCAMP was applied to the abundant and rare taxa communities along the elevation gradient. Dispersal limitation and drift were proved to more important than other processes in fungal community assembly, with average relative importance by 22.2–76.2% and 11.4–65.6%, respectively (Fig. 5; Fig. S7). Moreover, the process of dispersal limitation was dominant in the abundant taxa, and the process of drift was dominant in the rare taxa (Fig. S9). With increasing elevation, there was not significant difference in heterogeneous and homogeneous selection of the abundance and rare taxa (Fig. S9).

Coexistence in soil fungal abundant and rare sub-communities

A co-occurrence network was constructed for the abundant and rare taxa, the network topological significantly differed along the elevation gradients (Fig. 6). The negative relationships were only detected in the abundant taxa (Fig. S10). The average path lengths (avgL) of the abundant fungal network were highest in the middle elevation, while the avgL of the rare fungal network were highest in the low elevation, which indicated a complex topology in each sub-community network. Ecological clusters of sub-communities strongly correlated with different fungal guilds, whereas the environmental factors and fungal guilds individual related with ecological clusters in fugal the of sub-communities (Fig. 8). Together, this suggested that the abundant taxa were more complex than the rare taxa, and each sub-community was dominant with individual environmental factors, respectively.

When we compared the network stability in sub-communities of the abundant and rare taxa by randomly removing the percentage nodes. The network structure in the sub-communities, irrespective of the abundant and rare taxa (Fig. 7b). Topological features of degree distribution patterns also proved that the sub-communities of fungal communities presented typical power-law distribution patters at the higher node degree (> 22), which indicated the random degree distribution patter due to the stochastic processes might interference the degree distribution patters (Fig. 7a).

Distinct distributions but similar biogeographic patterns between soil fungal abundant and rare taxa

Our study was the first attempt to explored that shifts in soil fungal abundant and rare sub-communities along elevational gradients of the Yulong Mountains of southwest China. Generally, we observed the higher richness and diversity for the rare microbial sub-communities than the abundant (Fig. 2a, c, e), indicating the rare microbes were important contributors to soil fungal α diversity (Shade et al. 2014, Lynch and Neufeld 2015). A minor review had identified half of these studies that soil microbes showed a decreasing pattern along elevational gradient (Shen et al. 2019). Our results indicated that the fungal α diversity did not show significant trend in either total or rare sub-communities, with a unimodal trend and a peak of abundant sub-community at the around middle elevation (2900 m). The lack of any apparent elevational pattern in total fungal community contrasted with previous typical results in Rocky Mountain (Bryant et al. 2008) and Changbai Mountain in China (Shen et al. 2014), although it is not surprising, in which those study studies only concentrated only on the soil acidobacteria and arbuscular mycorrhizal (AM) sub-community.

In contrast to traditional wisdom, a diversity pattern driven by soil pH was not detected in the total or sub communities, even if the soil pH covered a quite a wide range, from acidic to neutral (5.22–7.46) in this present study (Fig. S3, S5). Thus, other factors including soil ammonium nitrogen (NH₄⁺-N), and total nitrogen content (TN) and total potassium (K) than soil pH largely more explained significant variable of total fungal richness (Fig. 3, Fig S5). Unexpectedly, there were few studies that reported soil K as a major variable explaining soil fungal richness (Singh et al. 2013). In a nutrient limited ecosystem, fungi are the primary decomposers in soil organic layer to address nutrient need of plant and microbes. Some studies observed that soil TN and NH₄⁺-N determined the fungal altitude distribution according to the fundamental energy sources and component elements for microorganisms (Fierer 2017). Soil potassium K content was proved to mineralize by mycorrhization, and this uptake benefited to aboveground vegetable in the form of abiotic stress tolerance and chemical elements homeostasis maintenance (Dominguez-Nuñez et al. 2016, Thi-Minh-Dien et al. 2020). Incubation experiment research documented soil K was also documented strong correlations with soil microbial activity (Thi-Minh-Dien et al. 2020). Although previous finding was also conducted in a sub-tropical forest in southern China, the contrasting observations might result from that K was not readily leach from organic matter because of relative low decomposition rate with increasing elevation (Mori et al. 2019). And this “humpback” tendency was consistent with the changing pattern in of vascular plant species richness along altitudinal gradients on Yulong Mountains, where tree species both richness and evenness diversity exhibited a unimodal relationship with a maximal value at 2965 m (Luo et al. 2019). There are several possible explanations with the different response of abundant and rare taxa to the elevation. First, soil nutrient availability (e.g. NH₄⁺-N, TN, C/N) made the largest contribution to the variation of fungal diversity paralleling with the previous studies (Singh et al. 2012, Shen et al. 2015, Peay et al. 2017), especially they were strong predicators for the changing trend in rare taxa (Fig. S3, S4). Second, patterns in of the diversity and distribution of the aboveground plant and soil microorganisms driven by temperature along elevational gradients were according based on metabolic theory of ecology (Hendershot et al. 2017, Nottingham et al. 2018). Indeed, we found the nutrient availability and soil temperature jointly play a critical role in abundant taxa diversity (Fig. 3, Fig. S5). The mid-elevation zones were also the transition for soil microorganisms’ activities from nutrient deficit to temperature limitation (Fig. S3) (Nottingham et al. 2015). Other several elevational studies also proved the dominant effect of temperature in driving the microbial communities where soil pH ceased to be a limited factor (Nottingham et al. 2018). Thus, we inferred that the influence of temperature was likely overwhelmed by nutrient availability in the high elevation levels (> 3100 m). Once considering the β diversity, different elevation zones harbored distinct fungal communities of abundant and rare taxa (Fig. 3, Fig. S5), possibly because the potential different mechanisms existed in structuring fungal communities along the elevational gradients (Nottingham et al. 2018). Additionally, our finding confirmed that the a-diversity of rare taxa explained more variation in fungal community dissimilarities compared to the abundant taxa (Fig. S7, S8), suggesting that the rare taxa were susceptible to drift (stochastic process) and/or founder effect with low abundance or frequency (Vellend et al. 2014, Xun et al. 2019).

Different assembly processes dominated soil fungal abundant and rare sub-communities

The most striking result of this study was the dispersal limitation dominated in the abundant taxa, whereas the pure stochastic process (i.e. drift) was dominant in the rare fungal communities (Fig. 5, Fig. S9). Although elevational difference also impacted the assembly of the abundant and rare sub communities, the elevation-decay relationship of abundant taxa (R² = 0.43, slope = 0.159 unit /Km) was stronger and steeper than that of the rare taxa (R² = 0.32, slope = 0.072 unit /Km) (Fig. 4a). These results corresponded well with previous findings that fungal community’s assembly in agriculture soil (Jiao and Lu 2020) and picoeukaryotic abundant taxa in the northwestern Pacific Ocean (Wu et al. 2017). Alternatively, some studies showed that rare taxa were more limited by dispersal in contaminated soil (Jiao et al. 2017a) or subtropical bays (Mo et al. 2018), even deterministic process in wetland soil in Tibetan Plateau (Wan et al. 2021). The apparent discrepancy was possibly ascribed to habitats-environments (Mo et al. 2018, Shade 2018) and geography distance (Liu et al. 2015, Hendershot et al. 2017). The dispersal of abundant taxa in our study was perhaps limited by strong coupling between the plant and fungi along the elevation gradient (Shen et al. 2014, Nottingham et al. 2018). Jiao et al. (2017b) also found that the dispersal of abundant taxa in terrestrial ecosystem were limited when the fluidity diminished rather than those in aquatic ecosystem (Mo et al. 2018). Different from microeukaryotic plankton communities in freshwater ecosystems, filamentous fungi in soil were interconnected to form a network, thus further aggravated the reduction of liquidity and increase in dispersal limitation (Powell et al. 2015, Peay et al. 2016). Additionally, a recent study provides experimental evidences for the significant effect of stochastic process in the structuring communities in high α diversity, indicating the stochastic process has strong role in the rare sub-community but not the abundant sub-communities (Xun et al. 2019).

However, the abundant and rare taxa structure followed a less typical power-law distribution pattern (Fig. 6, Fig. 7a), which indicated that all the OTUs in the network were equally distributional homogenization (Newman 2003, Ma et al. 2016). The same patterns of robustness of the co-occurrence relationships between abundant and rare taxa further confirmed equally roles of microbial structure (Fig. 7b), supporting the evidence that the rank abundance distribution for abundant and rare taxa indicated stochastic processes also played an important role in both abundant and rare communities assembly process (Newman 2003, Ma et al. 2016, Fan et al. 2018). Instead, the co-occurrence networks had stronger negative correlation in the abundance sub-community compared with that of the rare taxa (Fig. S10), which could be interpreted as high within-species competition, and also could be expected as the structure of abundant taxa exerted increasing negative feedbacks and low stability (Faust and Raes 2012, Fan et al. 2018). We found that the more modules of rare taxa did not depend on the fungal functional groups, potentially due to the highly functional redundancy. These rare taxa which should be vulnerable to ecology drift appeared to be share a similar or the same function at a low population. This finding has been directly demonstrated by numerous manipulated microcosm experiments (Zhou et al. 2013, Jiao et al. 2017b). Furthermore, they imply that functional redundancy increased neutrality and made rare populations more susceptible to drift.

Our finding clearly provided important insights for explaining eukaryotic soil microbial diversity for soil fungal abundant and rare taxa in alpine forests along an elevational gradient in Yulong Mountain of Southwest China. The pattern of diverged diversity and assembly processes between abundant and rare taxa along an elevational gradient were observed. The α diversity of abundant taxa had a humpback trend along the elevational gradient rather than rare taxa, whereas the β diversity of both abundant and rare taxa showed three distinct groups from the low to high elevation levels. Spatial distance and soil nutrient availability were important determinants for fungal community structure. Both deterministic and stochastic processes simultaneously affected the fungal community assembly, especially dispersal limitation dominated the abundant taxa, and neutral processes (e.g. ecological drift) were particularly pronounced for rare taxa. The analysis of functional prediction revealed that abundant taxa occupied more unique functional traits than rare taxa, suggesting that abundant taxa contributed to maintaining the functional diversity and rare taxa played a key role in maintaining the taxonomic diversity. This conclusion was in contrast to other studies that different ecological driving forces govern the biography of abundant and rare taxa, implying more complex mechanisms might be at play to shape both sub-communities, and tremendous diversity of the rare biosphere might be subjected to more complicated ecological process. Nevertheless, it is challenging to directly examine ecological drift in microbial communities due to the uncertainty in assessing microbial dormancy and extinction, and it is also extremely difficult to manipulate or reconstruct assembly history in natural ecosystems because of different initial conditions (Zhou et al. 2013). Taken together, our results provided a new perspective for the distinct assembly mechanisms underlying the similar biogeography of rare and abundant soil fungal along the elevational gradient, advancing important knowledge for regional-scale microbial distributions.

Acknowledgements

This research was financially supported by the National Natural Science Foundation of China (32130069), the “Strategic Priority Research Program B of the Chinese Academy of Sciences” (XDB15010200), the China Postdoctoral Science Foundation (2019M663587), the major Program for Basic Research Project of Yunnan Province (202101BC070002) and the special Project for Social Development of Yunnan Province (202103AC100001). We are grateful to Baima Snow Mountain complex ecosystem vertical transect Field Observation and research Station for help with field work.

We declare no conflict of interest.

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Divergent patterns and assembly processes of soil fungal abundant and rare communities along an elevational gradient in subalpine areas of Southwest China

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Abstract

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Introduction

Methods And Materials

Study area and measurements

Statistical analysis

Results

General distribution patterns of soil fungal rare and abundant taxa

Drivers and assembly processes of soil fungal abundant and rare sub-communities

Coexistence in soil fungal abundant and rare sub-communities

Discussion

Distinct distributions but similar biogeographic patterns between soil fungal abundant and rare taxa

Different assembly processes dominated soil fungal abundant and rare sub-communities

Conclusions And Implications

Declarations

References

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