Habitat and host specificity of the rhizosphere fungi form meta-community structure of the Arctic glacial forefield

Habitat and host specificity of the rhizosphere fungi form meta-community structure of the Arctic glacial forefield | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 20 February 2026 V1 Latest version Share on Habitat and host specificity of the rhizosphere fungi form meta-community structure of the Arctic glacial forefield Authors : Shota Masumoto 0000-0001-6029-3632 [email protected] , Shu-Kuan Wong , Cai Yihan , and Masaki Uchida Authors Info & Affiliations https://doi.org/10.22541/au.177157450.02702386/v1 118 views 80 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract The ongoing retreat of glaciers under global warming provides a new opportunity for tundra species to expand their habitats. We investigated the diversity of the fungal community surrounding the rhizome across five successional stages and four host plant species in Ny-Ålesund and Svalbard to understand the assemblage process of the underground community in a glacial forefield. From the meta-barcoding data, habitat- and host-specific species were statistically identified to gain a deeper understanding of the assembly mechanisms, and their influence on the meta-community structure among various successional stages or host plants was assessed. Habitat-specific species reduced during the early succession stages, whereas host-specific species remained constant irrespective of the successional stage. These trends resulted in a relative increase in host-specific species during the early stages, indicating that plant diversity is more crucial for rhizosphere communities in newer habitats. Rhizosphere communities in each host showed distinct responses along the successional gradient, depending on the plant–microbe interactions, such as mycorrhizal types. These various responses are presumed to contribute to the heterogeneity of rhizosphere communities during the early succession stages. Integrating plant–rhizosphere–microbe interactions into successional frameworks is necessary for understanding and predicting ecosystem development in Arctic landscapes, as climate warming accelerates glacier retreat, bare-ground expansion, and biological invasion. Title Habitat and host specificity of the rhizosphere fungi form meta-community structure of the Arctic glacial forefield Abstract The ongoing retreat of glaciers under global warming provides a new opportunity for tundra species to expand their habitats. We investigated the diversity of the fungal community surrounding the rhizome across five successional stages and four host plant species in Ny-Ålesund and Svalbard to understand the assemblage process of the underground community in a glacial forefield. From the meta-barcoding data, habitat- and host-specific species were statistically identified to gain a deeper understanding of the assembly mechanisms, and their influence on the meta-community structure among various successional stages or host plants was assessed. Habitat-specific species reduced during the early succession stages, whereas host-specific species remained constant irrespective of the successional stage. These trends resulted in a relative increase in host-specific species during the early stages, indicating that plant diversity is more crucial for rhizosphere communities in newer habitats. Rhizosphere communities in each host showed distinct responses along the successional gradient, depending on the plant–microbe interactions, such as mycorrhizal types. These various responses are presumed to contribute to the heterogeneity of rhizosphere communities during the early succession stages. Integrating plant–rhizosphere–microbe interactions into successional frameworks is necessary for understanding and predicting ecosystem development in Arctic landscapes, as climate warming accelerates glacier retreat, bare-ground expansion, and biological invasion. Keywords Fungal community, Rhizosphere community, Arctic tundra, Primary succession, Glacial forefield Introduction Climate change, driven by altered temperature and precipitation patterns, has caused the retreat of > 200,000 glaciers globally(Hugonnet et al. 2021). These alterations have been particularly pronounced in the Arctic, which has been warming nearly four times faster than the global average(Rantanen et al. 2021), resulting in widespread and accelerated glacial retreat across the region(Hansen et al. 2010, Parkinson and Comiso 2013, Hugonnet et al. 2021). Over the past 4 to 5 decades, the high arctic archipelago of Svalbard experienced temperature of approximately 3–5°C and precipitation increases of approximately 190 mm (Hanssen-Bauer et al. 2019). Although glaciers currently cover approximately 60% of Svalbard, dramatic climatic changes have led to considerable glacial retreat(Bourriquen et al. 2018). The glacier area of Svalbard has declined by at least 7% since the 1960s, (Bourriquen et al. 2018) and the present glaciated area of approximately 33,000 km 2 is projected to reduce by up to 50% by 2100, potentially converting 20%–38% of the area into a newly exposed terrestrial ecosystem(Bosson et al. 2023). Emerging land surfaces may provide ecological opportunities for plant and microbial species(Ficetola et al. 2024). Consistent with these trends, biomarker evidence from an Arctic fjord sediment core revealed that tundra vegetation development coincided with a decline in the summer sea ice extent and glacier retreat(Ingrosso et al. 2025). Together, these results highlight the criticality of elucidating the successional dynamics of glacier forefields to understand ongoing and future alterations in Arctic biodiversity. Glacier forefields have long been regarded as unrivalled natural laboratories for studying ecological succession (Chapin et al. 1994, Bardgett et al. 2005)because environmental gradients generated by the gradual retreat of glaciers drive pronounced variability in biological communities. Thus, ecologists often establish a series of sampling sites at increasing distances from the glacier tips as representations of temporal sequences (chronosequences) to investigate the alterations in the diversity and composition of plant or microbial communities during primary succession(Chapin et al. 1994, Zumsteg et al. 2012, Brown and Jumpponen 2014). Studies using chronosequences have identified a general successional trajectory characterized by progressive alterations in soil conditions, including increases in soil organic matter and shifts in water availability and pH, accompanied by vegetation development(Chapin et al. 1994, Mori et al. 2017, Mainetti et al. 2021). Soil microbial communities respond to changing soil conditions by sequentially increasing their abundance and diversity(Schipper et al. 2001, Rime et al. 2015, Jiang et al. 2018, Dong et al. 2022). However, the interpretation of community changes along glacier forefields solely as a function of time since deglaciation has some limitations. Sites close to and far from glaciers simultaneously coexist under the same contemporary conditions. Therefore, well-developed ecosystems at distal sites can act as sources of seeds, spores, and microbial propagules for newly exposed forefields that are closer to the glacial front. Simultaneously, newly exposed forefields represent highly specific and harsh environmental habitats(Dresch et al. 2019), where strong habitat-specific environmental filtering constrains community assembly. Consequently, later successional stages can be regarded as regional species pools, from which potential colonist species are supplied, whereas early successional communities represent environmentally filtered subsets of these pools(Garrido-Benavent et al. 2020, Mainetti et al. 2021). Consistent with this framework, previous studies have revealed that plant and microbial species richness is higher in later successional stages(Zumsteg et al. 2012, Mainetti et al. 2021), with species composition in the early stages forming subsets of those noted in later succession(Dong et al. 2016, Garrido-Benavent et al. 2020). Thus, habitats at various successional stages can be redefined as meta-communities that share the present moment. The concept of meta-communities is critical for understanding how species colonize the ongoing retreat of glaciers. Successional alterations in plant communities, soil microbial communities, and environmental properties are tightly coupled rather than independent. Vegetation establishment depends on soil development and interactions with rhizosphere microorganisms, and increasing carbon input from primary production improves resource availability for rhizosphere microorganisms(Krauze et al. 2021, Ruka et al. 2023). In the framework of plant–fungal interactions under ground conditions, we need to consider that fungi inhabiting the plant rhizosphere exhibit a wide range of trophic modes and varying degrees of host species specificity(Van Der Heijden et al. 2008, Klironomos et al. 2011). For instance, boreal and temperate areas appear to have a higher degree of host specificity, particularly for ectomycorrhizal fungi, than the Arctic(Ishida et al. 2005, Timling and Taylor 2012, Bonito et al. 2014, Ryberg et al. 2018). Nevertheless, even in Arctic environments, host plant identity can affect the associated fungal communities, especially for plants that form ectomycorrhizal and arbuscular mycorrhizal associations(Becklin et al. 2012, Carteron et al. 2024, Schaefer et al. 2025). The fact that fungal communities vary among plant species implies that distinct communities form in patches around plant roots as they colonize glaciers. However, even for the same host plant, the composition of the rhizosphere community seems successively dependent(Cázares et al. 2005, Fujimura et al. 2012, Dickie et al. 2013). Viewing the plant rhizosphere as an ecological patch, the existence of multiple plant species is likely to create multiple patchy habitats and critical differences in the rhizosphere community; however, whether that patch can be used depends on environmental factors with successional gradients. Therefore, simultaneously investigating the differences between multiple successional habitats and multiple plant species after interpreting the results from the perspective of meta-communities is necessary to understand rhizosphere communities invading bare ground alongside host plants. Additionally, simultaneous consideration of fungal specificity to habitats and host plants is important to interpret such community variables depending on different axes (i.e., succession and host species). Thus, this study demonstrates the variability of rhizosphere fungal communities by identifying fungal specificity for successional habitats or host species using a statistical method. We assessed the contribution of these specialists to fungal assemblages at the meta-community level among the same successional stages but various host plants, or different successional stages but the same host. Understanding the dynamics of rhizosphere fungi with habitat or host specificity in glacial retreat areas contributes to predicting the anticipated rapid expansion of bare ground and the accompanying alterations in biodiversity. Materials and Methods Study site and plot establishment Our study sites were situated near Ny-Alesund (78°55’ N, 11°56’ E) in the northwestern part of Spitsbergen Island, Norway. Ny-Ålesund has a mean annual air temperature of −5.7°C, and a total precipitation of 409 mm, primarily falling as snow. Mean winter and summer air temperatures for the period 1971–2000 were −12.7°C and 3.7°C, respectively (Hanssen-Bauer et al. 2019). The growing season generally spans from mid-June to late August, when the first snowfall event occurs. At the forefield of Austre Brøggerbreen glacier, we established five sampling sites (N1-N5) along a distance gradient from the glacier terminus (Fig. 1a). Field sampling and laboratory measurements Four plant species, Cerastium arcticum (CE), Draba alpina (DR), Saxifraga cespitosa (SXC), Saxifraga oppositifolia (SXO), were sampled from all study sites (Fig. 1). Individual plants that could be clearly identified as single specimens were carefully excavated using their intact root systems to minimize damage. After plant collection, approximately 20 g of soil was sampled from the immediate vicinity of each plant to characterize local soil environmental properties. When partially decomposed litter was present in the upper organic surface layer, soil samples were collected after removing plant debris. Sixty paired plant and soil samples were collected from the five sampling sites (four plant species × three replicates per site). Fresh plant samples were processed to characterize the rhizosphere fungal community structure using DNA-based methods. Roots (approximately 20 mg) were separated from the aboveground tissues, placed into 2 mL tubes containing DNA/RNA Shield (Zymo Research), and stored below 0°C until DNA extraction. The remaining aboveground parts were oven-dried at 70°C for 48 h and weighed to determine biomass. The soil samples were transported to the laboratory for analyzing abiotic environmental properties. Samples were sieved through a 2-mm mesh to remove stones and root fragments and subsequently homogenized. We measured the soil pH, electrical conductivity (Ec), concentration of carbon (C) to nitrogen (N), and gravimetric soil water content. Soil water content was estimated by weighing samples before and after oven drying at 70°C for 48 h. Soil pH and Ec values of the dry soil sampled in water (soil:water weight ratio of 1:5) were measured using pH and Ec meters (Twin pH and Twin Ec, HORIBA Ltd., Kyoto, Japan), respectively. Carbon and nitrogen concentrations were determined using a carbon nitrogen (CN) analyzer (JM1000CN, J-Science Lab Co., Ltd., Kyoto, Japan). All plant and soil samples were imported under post-entry quarantine at the Yokohama Plant Protection Station, with permission from the Japanese Ministry of Agriculture, Forestry, and Fisheries (Permit No. 4Y- 499). DNA extraction, polymerase chain reaction, and DNA sequencing Fungal DNA was analyzed in soil samples collected from all quadrats by sequencing the internal transcribed spacer (ITS) region of ribosomal DNA (rDNA) using the Illumina MiSeq platform (Illumina, San Diego, CA, USA) to characterize the fungal community structure. Genomic DNA was extracted using a FastDNA SPIN Kit for Soil (MP Biomedicals, Santa Ana, CA, USA), according to the manufacturer’s protocol. Partial ITS regions were amplified using the primers ITS1F-KYO2 and ITS2-KYO2(Toju et al. 2012), with Illumina overhang adaptor sequences attached to the 5′ ends of each primer. Polymerase chain reaction (PCR) amplification of the ITS region was conducted following the Illumina protocol (Illumina, 2019) using the following thermal cycling conditions: an initial denaturation for 10 min at 94°C, followed by 35 cycles of denaturation for 20 s at 94°C, annealing for 30 s at 55°C, elongation for 20 s at 72°C, and a final extension for 7 min at 72°C. Each PCR was conducted in triplicate, and the resulting amplicons were pooled before the index PCR using the Nextera XT Index Kit (Illumina). The PCR products were purified using Agencourt AMPure XP (Beckman Coulter Genomics, CA, USA). The purified libraries were combined with Phi X control DNA at a ratio of 75:25, and this mixture was utilized as a template for paired-end sequencing using the MiSeq Reagent Kit v3 (600 cycles, 300 bp pair end) on an Illumina MiSeq Desktop Sequencer. Data processing of the ITS regions Sequence processing and bioinformatics analyses were conducted using QIIME2 (version 2024.5) following a standardized ITS amplicon workflow(Bolyen et al. 2019). Raw paired-end reads were trimmed to extract the ITS region using ITSxpress(Rivers et al. 2018). Quality filtering, denoising, and removal of the chimeric sequences were subsequently conducted using DADA2(Callahan et al. 2016). For downstream analyses, the remaining sequences were clustered de novo at a threshold similarity of 97% using VSEARCH (Rognes et al. , 2016), which defined the molecular operational taxonomic units (OTUs Mueller et al. 2016). Taxonomic assignment was conducted using the QIIME 2 feature classifier with the scikit-learn algorithm trained using the UNITE database (version 10)(Abarenkov et al. 2024). Only the sequences assigned to the kingdom Fungi were retained. The final dataset was further filtered to remove singleton OTUs, retain features with a relative abundance >0.01%, and include only OTUs with a prevalence greater than two samples. After filtering, a total of 1,396,726 reads (mean 23,279 ± 21,214 (s.d.) reads per sample, n = 60) were retained, yielding 248 OTUs. The fungal community composition was analyzed using presence/absence data, with OTUs represented by more than one sequence considered present for all subsequent statistical analyses. Datasets from the high-throughput sequencing of the ITS regions were submitted to the NCBI Sequence Read Archive under the accession numbers SAMN55137512-SAMN55137571 (http://trace.ddbj.nig.ac.jp/dra/index.html). Statistical analysis The following analyses were performed using R version 4.5.1 (R Core Team, 2025). Principal component analysis (PCA) of the soil environmental features PCA was conducted to summarize the variation in soil environmental conditions across the sampled quadrats. Five abiotic soil environmental variables (water content, Ec, pH, and C N concentration) were standardized for the analysis. Before the PCA, the water content, C concentration, and N concentration were log-transformed to improve normality. Community composition of the fungal OTUs Sørencen’s dissimilarity indices between all the samples were calculated and visualized using non-metric multidimensional scaling analysis (NMDS) to assess the fungal composition dissimilarity. We conducted a nonparametric permutational multivariate analysis (PERMANOVA Anderson 2001) with 999 permutations using the adonis2() function to test the differences in fungal composition among the five sites or four hosts. Furthermore, the homogeneity of multivariate dispersion (PERMDISP) was tested using the betadisper() function to determine whether the group differences indicated by PERMANOVA were the result of group dispersion or a shift in composition among the groups(Anderson 2006). These analyses were conducted using the R package “vegan” (Okansen et al., 2020). Meta-community analysis among host plants or successional gradient We conducted a metacommunity-level analysis using presence-absence data to assess the dissimilarity patterns of rhizosphere fungal communities across the four host plant species and five successional stages. Samples were grouped into metacommunities to disentangle the effects of plant host identity and successional context. First, we created 20 groups comprising samples of four different plant species per site. Although there were possible 3 4 combinations, we used 20 randomly selected combinations to avoid excessive duplication of the samples used in the combinations. For each metacommunity, we calculated the checker-broad score (C-score), nestedness metric based on overlap and decreasing fill (NODF) and Sørencen’s multiple-site dissimilarity. The C-score quantifies how randomly two species are distributed across a set of habitats, with higher values indicating mutual exclusion among species, suggesting strong competitive interactions or niche partitioning(Stone and Roberts 1990). The NODF score measures the degree of nestedness within a community, in which species-poor assemblages represent the subsets of species-rich assemblages(Song and Rohr 2017). Sørencen’s multiple-site dissimilarity is obtained by generalizing the pairwise similarity, applicable to situations involving multiple sites and captures the overall compositional heterogeneity within metacommunities(Baselga 2010). The C-score and NODF were normalized before analysis, as these indices depend on the total number of species. Second, we constructed a second set of metacommunities comprising samples from five successional sites for each plant species to assess the differences between successional stages within the same host plant species. Twenty combinations of five samples were obtained for each plant species, and the same indices (C-score, NODF and Sørensen’s multiple-site dissimilarity) were calculated. Together, these complementary metacommunity analyses allowed us to compare the patterns of fungal community organization across host plants along successional gradients. Specialist identification for each habitat and host We determined the frequency of bias in the occurrence of individual OTUs across sites and host plant species to identify habitat- and host-specialized fungal taxa. We applied null modeling analyses to evaluate whether the observed frequency patterns deviated from random expectations, a common approach used to link community-level statistical patterns to the underlying assembly mechanisms(Gotelli 2000, Hase et al. 2011). Particularly, the frequency of an OTU occurring in each plant species ranged from 0 to 15 (five sites × three replicates) and the frequency of an OTU occurring at each site ranged from 0 to 12 (four species, three replicates). We calculated the standardized effect size (SES) using randomized data to determine the deviation of the obtained frequency variables from chance expectations. Specifically, the frequency SES ( F SES ) is expressed by the following formula: \begin{equation} F_{\text{ses}}=(F_{\text{obs}}\ -F_{\text{null\ AV}}\ \ )/F_{\text{null\ SD}}\text{\ \ }\nonumber \\ \end{equation} where F obs is the observed frequency at the site. Based on a random matrix (sample × OTU) created by randomizing the observed OTU distribution while fixing the total frequency of each OTU, we calculated the frequency of OTU with random distributions ( F null ) for each site. We obtained the average ( F null AV ) and standard deviation (F null SD ) values by performing this process for 999 iterations. Following previous studies using null-modeling approaches, we adopted the z-score criterion and classified an OTU as a specialist when the SES value was > 1.96 (corresponding to the upper 2.5% threshold of a one-tailed test), indicating that the OTU distribution was significantly biased toward specific sites. Using the same approach, F ses values were calculated for the host plant species. Fungal diversity and soil environment features with site gradient and host difference PCA of soil environmental variables across all samples (Fig. 3C) showed that PC1 exhibited high loadings for soil pH, water content, C and N contents, accounting for 76.4% of the total variance. Therefore, PC1 represents the development of organic-rich soils characterized by higher moisture and nutrient availability along the successional gradient, with this trend becoming more pronounced in the later successional stages. PC2 accounted for 11.8% of the total variation and had high loadings for soil Ec, reflecting the alteration in abiotic conditions during the early successional stages (Sites1-3). Together, these two PCA axes accounted for 88.2% of the total variance. A total of 248 fungal OTUs appeared in the dataset, and the richness increased toward the later successional sites (Fig. 2a), regardless of the host plant species. When OTU richness was compared among the host species, the SXO rhizosphere consistently harbored higher fungal richness than the DR rhizosphere, regardless of the site. PCoA based on the OTU composition (Fig. 3b) indicated that site differences (shown by color) explained the overall community dissimilarity compared to host plant differences (shown by symbols). Consistent with this pattern, PERMANOVA results revealed significant effects of site and host species on the fungal community composition (both p<0.001). In PEMDISP analysis, OTU composition showed a significant difference with site but not with species (p = 0.01 and p = 0.80, respectively). These findings indicate that the differences in fungal composition between the sites were due to compositional shifts and dispersion among groups; however, the differences between sites were only due to compositional shifts. Specialist identification for each habitat and host Figure 4 illustrates the number of OTUs linked to plant- and site-specificity. In total, 35 OTUs revealed plant specificity and 162 OTUs showed site specificity. The most common category comprised 144 OTUs classified as Generalist for plant ∩ Specialist for sites. The least common category comprised 17 OTUs classified as Specialist for plant species ∩ Specialist for sites. Figure 4 shows the relative richness of the four specialist groups across the successional gradient. First, the proportion of host plant specialist OTUs was the highest early in the successional stages, whereas the proportion of habitat specialist OTUs increased toward later successional stages (Fig. 4b). Regarding the frequency of each specialist (Fig. 4c, d), habitat specialists were frequent toward later successional stages, whereas the overall host-specific richness did not peak at any specific successional stage. The proportional contribution of the host plant specialists was greater in the early successional stages, whereas habitat specialists predominated in the later stages. Relationship between meta-community indexes and habitat- or host-specific richness In the meta-community analysis combining various host plant samples within each habitat, the NODF was higher toward the early successional stage, although it was the highest in N3 (middle of the succession stages). Site N3 is situated on the riverside and may have been periodically disturbed even after being released from the glacier. Multi-site dissimilarity was correlated with NODF but not with the C-score (Fig. 5c, d). This indicated that rhizosphere fungal communities exhibited pronounced nestedness among host plants in the early successional stage, leading to increased heterogeneity among the host rhizosphere communities. Moreover, NODF significantly correlated with the ratio of the host specialists (Fig. 5e). Contrastingly, metacommunity analyses combining various habitats within the same host plant species showed significant differences in the NODF of each plant using Tukey’s multiple comparison test, and NODF and Multiple-dis were correlated (Fig. 5g, i). This indicated that the community was heterogeneous, even within the same host species, when the rhizosphere fungi revealed greater nestedness among various successional stages. Additionally, NODF significantly correlated with the ratio of host specialists (Fig. 5j). Discussion Soil environment and fungal diversity with successional gradient This study uses a chronosequence method to interpret the order of glacial retreat over time. Soil organic matter content and moisture increased, while soil pH decreased as time elapsed since glacial retreat, that is, with increasing distance from the glacier (Fig. 2). This general trend is likely attributable to the increased biomass accumulation and ecosystem productivity during the later succession stages(Schipper et al. 2001, Mainetti et al. 2021). Additionally, diversity within the rhizosphere community increased in the later succession stages, as shown in previous studies that focused on soil microbial communities(ZHANG et al. 2018, Dong et al. 2022, Masumoto et al. 2023). Contrastingly, the above-ground biomass of individual plants did not markedly differ along the successional gradient (Fig. 2). This likely reflects our sampling strategy, where we selected mature plant samples of similar size rather than randomly sampling individuals to minimize the association with plant growth stages. Although this method cannot completely eliminate the differences in plant development, it decreases the size-related variability among samples. PERMANOVA showed significant differences in fungal community composition between sites and plant species, suggesting that compositional shifts in fungal communities are driven by habitat and host specificity. The NMDS findings suggest that site-related differences explain more variation in the community than plant species differences. However, previous research has revealed that the relative criticality of successional stages and host plant species for rhizosphere microbes depends on the study site or trophic strategy(Schipper et al. 2001, Fujimura et al. 2012, Botnen et al. 2014, Carteron et al. 2024). Additionally, two methodological considerations must be considered when interpreting these results. First, as in most glacier forefield studies, the chronosequence approach assumes that spatial variation among sites reflects temporal succession, although unmeasured site-specific patterns may additionally contribute to the noted patterns. Second, as the roots were neither washed nor surface-sterilized before DNA extraction, the fungal community analyzed here represented a continuum from root-associated to surrounding soil fungi. Although this method captures ecologically relevant rhizosphere assemblages, it may decrease the apparent strength of the host-specific associations compared to studies exclusively focusing on mycorrhizal fungi. Occurrence pattern of the habitat- and host-specific fungi According to the null modeling analysis, the number of habitat specialists exceeded that of the host specialists. However, the number of OTUs exceeding a statistical threshold depends on the sample size and analytical procedures. Thus, a direct comparison of absolute numbers should be cautiously interpreted, and we focused instead on the alterations in their relative frequencies across successional stages. The frequency of habitat specialists increased toward later successional stages, indicating that early successional communities represent a subset of late-successional communities (Fig. 4c). This is a trend commonly noted in glacier forefields(Dong et al. 2016, Garrido-Benavent et al. 2020). Considering that late-successional communities can act as regional species pools and sources of fungal propagules, rhizosphere fungi in the early successional stages are likely to be selected from this pool via strong environmental filtering under harsh environmental conditions. However, the frequency of host specialists did not reveal a consistent trend across sites (Fig. 4b). This suggests that species with strong associations with host plants, such as mycorrhizal fungi or pathogens, is retained during the colonization of early successional stages. Functional traits and host dependency influence fungal dispersal and persistence when host plants colonize new habitats(Cázares et al. 2005, Carteron et al. 2024). The differences in environmental and host dependencies between fungal species suggest that habitat specialists predominated in the late successional communities, whereas the proportion of host specialists increased in the early successional communities (Fig. 4b). Additionally, the frequency of host specialists differed depending on host species (Fig. 4d). Previous studies (Väre et al. 1992, Iversen et al. 2015) have reported DR and CE as non-mycorrhizal species (but hyphae resembling Rhizoctonia sp. were noted in the CE roots). SXO and SXC form arbuscular mycorrhizal or endophytic ectomycorrhizal associations(Väre et al. 1992, Iversen et al. 2015, Zhang and Yao 2015). Specifically, the lower frequency of DR-associated specialists in the early successional stages may reflect the absence of strongly interacting fungal partners, such as mycorrhizal fungi. Meta-community analysis In the meta-community analysis of various host species at each site, NODF increased during the early successional stage, whereas the C-score did not (Fig. 5b). NODF enhancement was correlated with multisite dissimilarity (Fig. 5d), indicating that nestedness among communities could increase community dissimilarity (Baselga, 2010). Thus, the heterogeneity of rhizosphere communities among various plants may increase early in succession and is due to the subset of communities observed among the host plants. This means that host differences become a more crucial factor in underground biodiversity within the local habitat at the bare-ground site than at sites with well-developed vegetation. Additionally, the nestedness structure can be considered a diversity bias in terms of community ecology(Anderson et al. 2011), indicating that the fungal community composition of the entire region depends more on the specific host plants at an early successional site. Plant and soil microbes exhibit heterogeneity in their diversity or biomass on a fine scale(Suvanto et al. 2014, Pape and Löffler 2017), driven by environmental filtering(Glassman et al. 2017). In harsher environments, such as tundra, species distributions are concentrated in locally safe sites near a rock as a windbreak or where soil resources are relatively abundant(Jumpponen et al. 1999, Suvanto et al. 2014). However, in this case, where the sampling point is not just a location but also the rhizosphere, the biological interactions between the host and the microbial community should be considered(Peay and Bruns 2014, Vályi et al. 2016). Our results (Fig. 5e) revealed that the richness ratio of the host specialists in the entire community increased the NODF among the plant samples, which is consistent with the requirement to consider such biological interactions. Further details can be found below, broken down by meta-community and site of the same host species. Comparing meta-communities across various sites of the same host species, NODF demonstrated variability among the hosts and explained the multiple-site dissimilarity (Fig. 5g, i). Nestedness across successional stages enhances community heterogeneity, even within the same host, which increases the fungal diversity harbored by the plant species across the entire glacial forefield. NODF changed with the ratio of habitat specialists (Fig. 5j), indicating that the relationship between plants and rhizosphere communities along successional gradients differed with plant species and depended on the variability of habitat specialists. Alterations in microbial communities of the rhizosphere with respect to successional gradients have been reported in several plant species. However, despite the boost provided by metagenomic approaches, no general variability patterns have been identified(Fujimura et al. 2012, Botnen et al. 2014, Carteron et al. 2024, Schaefer et al. 2025). Botnen et al. (2014) revealed a lower host specificity for tundra plants. Contrastingly, Becklin (2012) revealed a higher host contribution to the rhizosphere community than environmental differences. Furthermore, Fujimura et al. (2014) demonstrated that the rhizosphere communities of some host species alter with successional gradients and those that do not. Such variable responses reflect the host dependency of each species on the mycorrhizal type(Becklin et al. 2012, Carteron et al. 2024). In the present study, Draba alpina which is reported to be a non-mycorrhizal plant (Väre et al. 1992), demonstrated the greatest variation among the sites. The rhizosphere community under weak host–fungus interactions may have revealed a subset trend along the successional gradient because more species were selected via environmental filtering. Conversely, communities in the rhizosphere that harbor more plant specialists show less variation along the gradient, providing a stable metacommunity across the entire glacial forefield. Conclusion This study provides a cross-cutting assessment of the effects of succession and host differences on the rhizosphere fungi assembly in a glacial forefield. While the effects of succession and plant species diversity on microbial communities have been shown in several studies(Gardes and Dahlberg 1996, Brundrett 2009, Dickie et al. 2013, Bradley et al. 2014), conceptualizing plant rhizospheres as patch-like habitats has helped us to systematically understand underground biodiversity and the processes that drive it in the area. According to the meta-community analysis, which defined habitat and host specialists, fungi screened out during the early successional stage were primarily non-specific to plants, which led to an increase in the relative criticality of host variation for local fungal diversity at the early successional stage. Additionally, the development of nestedness structures along the successional gradient varied between the host species, and certain plants were more likely to provide independent habitats for rhizosphere fungi despite environmental variation in the glacial forefield. Consequently, variations in nested structure development among the host species contributed to rhizosphere community divergence among plants in the early successional stage. Moreover, fungal diversity was biased around the specific hosts with robust interactions. Plant and rhizosphere fungal interactions are bidirectional(Kardol et al. 2007, Mangan et al. 2010) and mycorrhizal fungi help plants invade new ecosystems(Nara 2006, Van der Putten et al. 2013). However, this study assumed that plants were used as a factor in determining the dynamics of rhizosphere communities. Although the rhizosphere has long been likened to a “black box” in terms of belowground biodiversity and function, recent advances in high-throughput DNA sequencing have markedly enhanced our ability to resolve plant and rhizosphere-microbe relationships. Integrating plant-rhizosphere-microbe interactions into successional frameworks is essential for understanding and predicting ecosystem development in Arctic landscapes, given that climate warming accelerates glacier retreat, bare-ground expansion, and biological invasion. References Abarenkov, K., Nilsson, R. H., Larsson, K. H., Taylor, A. F. S., May, T. W., Frøslev, T. G., Pawlowska, J., Lindahl, B., Põldmaa, K., Truong, C., Vu, D., Hosoya, T., Niskanen, T., Piirmann, T., Ivanov, F., Zirk, A., Peterson, M., Cheeke, T. E., Ishigami, Y., Jansson, A. T., Jeppesen, T. S., Kristiansson, E., Mikryukov, V., Miller, J. T., Oono, R., Ossandon, F. J., Paupério, J., Saar, I., Schigel, D., Suija, A., Tedersoo, L. and Kõljalg, U. 2024. The UNITE database for molecular identificationãnd taxonomic communication of fungiãnd other eukaryotes: sequences, taxaãnd classifications r econsider ed. - Nucleic Acids Res. 52: D791–D797. Anderson, M. J. 2001. A new method for non-parametric multivariate analysis of variance. - Austral Ecol. 26: 32–46. Anderson, M. J. 2006. Distance-based tests for homogeneity of multivariate dispersions. - Biometrics 62: 245–253. Anderson, M. J., Crist, T. O., Chase, J. M., Vellend, M., Inouye, B. D., Freestone, A. L., Sanders, N. J., Cornell, H. V., Comita, L. S., Davies, K. F., Harrison, S. P., Kraft, N. J. B., Stegen, J. C. and Swenson, N. G. 2011. Navigating the multiple meanings of β diversity: A roadmap for the practicing ecologist. - Ecol. Lett. 14: 19–28. Bardgett, R. D., Bowman, W. D., Kaufmann, R. and Schmidt, S. K. 2005. A temporal approach to linking aboveground and belowground ecology. - Trends Ecol. Evol. 20: 634–641. Baselga, A. 2010. Partitioning the turnover and nestedness components of beta diversity. - Global Ecology and Biogeography 19: 134–143. Becklin, K. M., Hertweck, K. L. and Jumpponen, A. 2012. Host Identity Impacts Rhizosphere Fungal Communities Associated with Three Alpine Plant Species.: 682–693. Bolyen, E., Rideout, J. R., Dillon, M. R., Bokulich, N. A., Caporaso, J. G., et al. 2019. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. - Nat. Biotechnol. 37: 852–857. Bonito, G., Reynolds, H., Robeson, M. S., Nelson, J., Hodkinson, B. P., Tuskan, G., Schadt, C. W. and Vilgalys, R. 2014. Plant host and soil origin influence fungal and bacterial assemblages in the roots of woody plants. - Mol. Ecol. 23: 3356–3370. Bosson, J. B., Huss, M., Clément, J. C., Costes, G., Fischer, M., Poulenard, J. and Arthaud, F. 2023. Future emergence of new ecosystems caused by glacial retreat. in press. Botnen, S., Vik, U., Carlsen, T., Eidesen, P. B., Davey, M. L. and Kauserud, H. 2014. Low host specificity of root-associated fungi at an Arctic site. - Mol. Ecol. 23: 975–985. Bourriquen, M., Mercier, D., Baltzer, A., Fournier, J., Costa, S. and Roussel, E. 2018. Paraglacial coasts responses to glacier retreat and associated shifts in river floodplains over decadal timescales (1966–2016), Kongsfjorden, Svalbard. - Land Degrad. Dev. 29: 4173–4185. Bradley, J. A., Singarayer, J. S. and Anesio, A. M. 2014. Microbial community dynamics in the forefield of glaciers. - Proceedings of the Royal Society B: Biological Sciences in press. Brown, S. P. and Jumpponen, A. 2014. Contrasting primary successional trajectories of fungi and bacteria in retreating glacier soils. - Mol. Ecol. 23: 481–497. Brundrett, M. C. 2009. Mycorrhizal associations and other means of nutrition of vascular plants: Understanding the global diversity of host plants by resolving conflicting information and developing reliable means of diagnosis. - Plant Soil 320: 37–77. Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J. A. and Holmes, S. P. 2016. DADA2: High-resolution sample inference from Illumina amplicon data. - Nat. Methods 13: 581–583. Carteron, A., Cantera, I., Guerrieri, A., Marta, S., Bonin, A., Ambrosini, R., Anthelme, F., Azzoni, R. S., Almond, P., Alviz Gazitúa, P., Cauvy-Fraunié, S., Ceballos Lievano, J. L., Chand, P., Chand Sharma, M., Clague, J. J., Cochachín Rapre, J. A., Compostella, C., Cruz Encarnación, R., Dangles, O., Eger, A., Erokhin, S., Franzetti, A., Gielly, L., Gili, F., Gobbi, M., Hågvar, S., Khedim, N., Meneses, R. I., Peyre, G., Pittino, F., Rabatel, A., Urseitova, N., Yang, Y., Zaginaev, V., Zerboni, A., Zimmer, A., Taberlet, P., Diolaiuti, G. A., Poulenard, J., Thuiller, W., Caccianiga, M. and Ficetola, G. F. 2024. Dynamics and drivers of mycorrhizal fungi after glacier retreat. - New Phytologist 242: 1739–1752. Chapin, F. S., Walker, L. R., Fastie, C. L. and Sharman, L. C. 1994. Mechanisms of Primary Succession Following Deglaciation at Glacier Bay, Alaska. - Ecol. Monogr. 64: 149–175. Cázares, E., Trappe, J. M. and Jumpponen, A. 2005. Mycorrhiza-plant colonization patterns on a subalpine glacier forefront as a model system of primary succession. - Mycorrhiza 15: 405–416. Dickie, I. A., Martínez-garcía, L. B., Koele, N., Grelet, G., Tylianakis, J. M., Peltzer, D. A. and Richardson, S. J. 2013. Mycorrhizas and mycorrhizal fungal communities throughout ecosystem development.: 11–39. Dong, K., Tripathi, B., Moroenyane, I., Kim, W., Li, N., Chu, H. and Adams, J. 2016. Soil fungal community development in a high Arctic glacier foreland follows a directional replacement model, with a mid-successional diversity maximum. - Sci. Rep. in press. Dong, K., Yu, Z., Kerfahi, D., Lee, S. seob, Li, N., Yang, T. and Adams, J. M. 2022. Soil microbial co-occurrence networks become less connected with soil development in a high Arctic glacier foreland succession. - Science of the Total Environment in press. Dresch, P., Falbesoner, J., Ennemoser, C., Hittorf, M., Kuhnert, R. and Peintner, U. 2019. Emerging from the ice-fungal communities are diverse and dynamic in earliest soil developmental stages of a receding glacier. 21: 1864–1880. Ficetola, G. F., Marta, S., Guerrieri, A., Cantera, I., Bonin, A., Cauvy-fraunié, S., Ambrosini, R., Caccianiga, M., Anthelme, F., Azzoni, R. S., Almond, P. and Gazitúa, P. A. 2024. The development of terrestrial ecosystems emerging after glacier retreat. - Nature in press. Fujimura, K. E., Egger, K. N. and Newsham, K. K. 2012. Host plant and environment influence community assembly of High Arctic root-associated fungal communities. - Fungal Ecol. 5: 409–418. Gardes, M. and Dahlberg, a 1996. Mycorrhizal diversity in arctic and alpine tundra: An open question. - New Phytologist 133: 147–157. Garrido-Benavent, I., Pérez-Ortega, S., Durán, J., Ascaso, C., Pointing, S. B., Rodríguez-Cielos, R., Navarro, F. and de los Ríos, A. 2020. Differential Colonization and Succession of Microbial Communities in Rock and Soil Substrates on a Maritime Antarctic Glacier Forefield. - Front. Microbiol. 11: 1–19. Glassman, S. I., Wang, I. J. and Bruns, T. D. 2017. Environmental filtering by pH and soil nutrients drives community assembly in fungi at fine spatial scales. - Mol. Ecol. 26: 6960–6973. Gotelli, N. J. 2000. Null model analysis of species co-occurrence patterns. - Ecology 81: 2606–2621. Hansen, J., Ruedy, R., Sato, M. and Lo, K. 2010. GLOBAL SURFACE TEMPERATURE CHANGE.: 1–29. Hanssen-Bauer, I., Førland, E. J., Hisdal, H., Mayer, S., Sandø, A. B., Sorteberg, A., Adakudlu, M., Andresen, J., Bakke, J., Beldring, S., Benestad, R., Bilt, W., Bogen, J., Borstad, C., Breili, K., Breivik, Ø., Børsheim, K. Y., Christiansen, H. H., Dobler, A., Engeset, R., Frauenfelder, R., Gerland, S., Gjelten, H. M., Gundersen, J., Isaksen, K., Jaedicke, C., Kierulf, H., Kohler, J., Li, H., Lutz, J., Melvold, K., Mezghani, A., Nilsen, F., Nilsen, I. B., Nilsen, J. E. Ø., Pavlova, O., Ravndal, O., Risebrobakken, B., Saloranta, T., Sandven, S., Schuler, T. V, Simpson, M. J. R., Skogen, M., Smedsrud, L. H., Sund, M., Vikhamar-Schuler, D., Westermann, S. and Wong, W. K. 2019. Climate in Svalbard 2100. - Norwegian Centre for Climate Services (NCCS): 105. Hase, J. O. M. C., Raft, N. A. J. B. K., Mith, K. E. G. S., Ellend, M. A. R. K. V and Al, C. E. T. 2011. Using null models to disentangle variation in community dissimilarity from variation in a -diversity. in press. Hugonnet, R., McNabb, R., Berthier, E., Menounos, B., Nuth, C., Girod, L., Farinotti, D., Huss, M., Dussaillant, I., Brun, F. and Kääb, A. 2021. Accelerated global glacier mass loss in the early twenty-first century. - Nature 592: 726–731. Illumina. Fungal metagenomic sequencing demonstrated protocol (1000000064940 v01). https://support.illumina.com/downloads/f ungal- metagenomic- sequencing- demonstrated- protocol- 10000 00064940.html (2 May 2019, date last accessed). Ingrosso, G., Ceccarelli, C., Giglio, F., Giordano, P., Hefter, J., Langone, L., Miserocchi, S., Mollenhauer, G., Nogarotto, A., Sabino, M. and Tesi, T. 2025. Greening of Svalbard in the twentieth century driven by sea ice loss and glaciers retreat. - Commun. Earth Environ. in press. Ishida, T. A., Nara, K. and Hogetsu, T. 2005. Host effects on ectomycorrhizal fungal communities : insight from eight host species in mixed conifer – broadleaf forests. in press. Iversen, C. M., Sloan, V. L., Sullivan, P. F., Euskirchen, E. S., Mcguire, A. D., Norby, R. J., Walker, A. P., Warren, J. M. and Wullschleger, S. D. 2015. The unseen iceberg: Plant roots in arctic tundra. - New Phytologist 205: 34–58. Jiang, Y., Lei, Y., Yang, Y., Korpelainen, H., Niinemets, Ü. and Li, C. 2018. Divergent assemblage patterns and driving forces for bacterial and fungal communities along a glacier forefield chronosequence. - Soil Biol. Biochem. 118: 207–216. Jumpponen, A., Väre, H., Mattson, K. G., Ohtonen, R. and Trappe, J. M. 1999. Characterization of “safe sites” for pioneers in primary succession on recently deglaciated terrain. - Journal of Ecology 87: 98–105. Kardol, P., Cornips, N. J., Van Kempen, M. M. L., Bakx-Schotman, J. M. T. and Van Der Putten, W. H. 2007. Microbe-mediated plant-soil feedback causes historical contingency effects in plant community assembly. - Ecol. Monogr. 77: 147–162. Klironomos, J., Zobel, M., Tibbett, M., Stock, W. D., Rillig, M. C., Parrent, J. L., Moora, M., Koch, A. M., Facelli, J. M., Facelli, E., Dickie, I. A. and Bever, J. D. 2011. Forces that structure plant communities: Quantifying the importance of the mycorrhizal symbiosis. - New Phytologist 189: 366–370. Krauze, P., Wagner, D., Yang, S., Spinola, D. and Kühn, P. 2021. Influence of prokaryotic microorganisms on initial soil formation along a glacier forefield on King George Island, maritime Antarctica. - Sci. Rep. 11: 1–15. Mainetti, A., D’Amico, M., Probo, M., Quaglia, E., Ravetto Enri, S., Celi, L. and Lonati, M. 2021. Successional Herbaceous Species Affect Soil Processes in a High-Elevation Alpine Proglacial Chronosequence. - Front. Environ. Sci. in press. Mangan, S. A., Schnitzer, S. A., Herre, E. A., MacK, K. M. L. L., Valencia, M. C., Sanchez, E. I. and Bever, J. D. 2010. Negative plant-soil feedback predicts tree-species relative abundance in a tropical forest. - Nature 466: 752–755. Masumoto, S., Mori, A. S., Nishizawa, K., Naka, M., Matsuoka, S., Wong, S. K. and Uchida, M. 2023. Synergistic effects of succession and microtopography of moraine on the fungal spatial diversity in a glacier forefield. - FEMS Microbiol. Ecol. 99: 1–10. Mori, A. S., Osono, T., Cornelissen, J. H. C., Craine, J., Uchida, M., Mori, A. S., Osono, T., Cornelissen, J. H. C., Craine, J., Uchida, M., Mori, A. S., Osono, T., Cornelissen, J. H. C., Craine, J., Uchida, M., Mori, A. S., Osono, T., Cornelissen, J. H. C. and Craine, J. 2017. Biodiversity-ecosystem function relationships change through primary succession. - Oikos 126: 1637–1649. Mueller, R. C., Gallegos-Graves, L., Zak, D. R. and Kuske, C. R. 2016. Assembly of Active Bacterial and Fungal Communities Along a Natural Environmental Gradient. - Microb. Ecol. 71: 57–67. Nara, K. 2006. Ectomycorrhizal networks and seedling establishment during early primary succession. - New Phytologist 169: 169–178. Oksanen, J., and others. 2020. vegan: Community ecology package (2.5-7). Available from https://CRAN.R-project.org/package=vegan Pape, R. and Löffler, J. 2017. Determinants of arctic-alpine pasture resources: The need for a spatially and functionally fine-scaled perspective. - Geografiska Annaler, Series A: Physical Geography 99: 353–370. Parkinson, C. L. and Comiso, C. 2013. On the 2012 record low Arctic sea ice cover : Combined impact of preconditioning and an August storm. 40: 1356–1361. Peay, K. G. and Bruns, T. D. 2014. Spore dispersal of basidiomycete fungi at the landscape scale is driven by stochastic and deterministic processes and generates variability in plant-fungal interactions. - New Phytologist 204: 180–191. R Core Team. 2025. R: A Language and Environment for Statistical Computing . R Foundation for Statistical Computing. https://www.R-project.org/. Rantanen, M., Karpechko, A. Y., Lipponen, A., Ruosteenoja, K., Vihma, T., Laaksonen, A., Nordling, K. and Hyvärinen, O. 2021. than the globe since 1979.: 1–10. Rime, T., Hartmann, M., Brunner, I., Widmer, F., Zeyer, J. and Frey, B. 2015. Vertical distribution of the soil microbiota along a successional gradient in a glacier forefield. - Mol. Ecol. 24: 1091–1108. Rivers, A. R., Weber, K. C., Gardner, T. G., Liu, S. and Armstrong, S. D. 2018. ITSxpress: Software to rapidly trim internally transcribed spacer sequences with quality scores for marker gene analysis. - F1000Res. in press. Ruka, A. T., Čapková, K., Řeháková, K., Angel, R., Chroňáková, A., Kopecký, M., Macek, M., Dvorský, M. and Doležal, J. 2023. Bacterial and plant community successional pathways in glacier forefields of the Western Himalaya. - Eur. J. Soil Biol. in press. Ryberg, M., Larsson, E., Molau, U., Ryberg, M., Larsson, E. and Molau, U. 2018. Ectomycorrhizal Diversity on Dryas octopetala and Salix reticulata in an Alpine Cliff Ecosystem Ectomycorrhizal Diversity on Dryas octopetala and Salix reticulata in an Alpine Cliff Ecosystem. in press. Schaefer, S. R., Montaño-López, F., Holland-Moritz, H., Pries, C. H. and Ernakovich, J. G. 2025. Rhizosphere bacteria and fungi are differentially structured by host plants, soil mineralogy, and ectomycorrhizal communities in the Alaskan Tundra. - Arct. Sci. 11: 1–18. Schipper, L. A., Degens, B. P., Sparling, G. P. and Duncan, L. C. 2001. Changes in microbial heterotrophic diversity along five plant successional sequences. - Soil Biol. Biochem. 33: 2093–2103. Song, C. and Rohr, R. P. 2017. Why are some plant – pollinator networks more nested than others ?: 1417–1424. Stone, L. and Roberts, A. 1990. The checkerboard score and species distributions. - Oecologia 85: 74–79. Suvanto, S., Le Roux, P. C. and Luoto, M. 2014. Arctic-alpine vegetation biomass is driven by fine-scale abiotic heterogeneity. - Geografiska Annaler, Series A: Physical Geography 96: 549–560. Timling, I. and Taylor, D. L. 2012. Peeking through a frosty window: Molecular insights into the ecology of Arctic soil fungi. - Fungal Ecol. 5: 419–429. Toju, H., Tanabe, A. S., Yamamoto, S. and Sato, H. 2012. High-coverage ITS primers for the DNA-based identification of ascomycetes and basidiomycetes in environmental samples. - PLoS One in press. Van Der Heijden, M. G. A., Bardgett, R. D. and Van Straalen, N. M. 2008. The unseen majority: Soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems. - Ecol. Lett. 11: 296–310. Van der Putten, W. H., Bardgett, R. D., Bever, J. D., Bezemer, T. M., Casper, B. B., Fukami, T., Kardol, P., Klironomos, J. N., Kulmatiski, A., Schweitzer, J. A., Suding, K. N., Van de Voorde, T. F. J. and Wardle, D. A. 2013. Plant-soil feedbacks: The past, the present and future challenges. - Journal of Ecology 101: 265–276. Vályi, K., Mardhiah, U., Rillig, M. C. and Hempel, S. 2016. Community assembly and coexistence in communities of arbuscular mycorrhizal fungi. - ISME Journal 10: 2341–2351. Väre, H., Vestberg, M. and Eurola, S. 1992. Mycorrhiza and root-associated fungi in Spitsbergen. - Mycorrhiza 1: 93–104. ZHANG, Q., WANG, Q., OUYANG, H., LAN, S. and HU, C. 2018. Pyrosequencing Reveals Significant Changes in Microbial Communities Along the Ecological Succession of Biological Soil Crusts in the Tengger Desert of China. - Pedosphere 28: 350–362. Zhang, T. and Yao, Y.-F. 2015. Endophytic Fungal Communities Associated with Vascular Plants in the High Arctic Zone Are Highly Diverse and Host-Plant Specific. - PLoS One 10: e0130051. Zumsteg, A., Luster, J., Göransson, H., Smittenberg, R. H., Brunner, I., Bernasconi, S. M., Zeyer, J. and Frey, B. 2012. Bacterial, Archaeal and Fungal Succession in the Forefield of a Receding Glacier. - Microb. Ecol. 63: 552–564. Figure legends Fig. 1 Study site location and site map ( a ). Study plants: Cerastium arcticum (b), Draba alpina (c), Saxifraga cespitosa (d), S. oppositifolia (e). Bar = 2 cm. Fig. 2 Soil environment factors, plant above biomass, and fungal OTU richness in different site and host plants. Fig. 3 (a) Principal component analysis (PCA) of the soil environmental factors. (b) Nonmetricmulti-dimensional scaling ordination (nMDS) plot of the fungal communities based on the OTU data. The color and shape of the points refer to the site and plant host. Fig. 4 Specialist and generalist components for each sample. (a) Number of OTUs defining specific types over all samples. (b) Relative frequency of each specific type in various sites. (c) Frequency of the habitat specialists on each site. (d) Frequency of the host specialists in each plant species. Fig. 5 The C-score and NODF of the meta-community consist of different plant species in each successional site (a, b), and those of the meta-community consist of different sites in each species (f, g). The correlations of multiple-site dissimilarity with C-score and NODF of plants meta-community in each site (c, d) and site meta-community in each plant (h, i). The correlations of NODF with the relative richness of the host (e) and habitat specialists (j). Black lines indicate statistically significant (p < 0.05) linear model fits; the shaded area represents the corresponding 95% confidence intervals. Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Information & Authors Information Version history V1 Version 1 20 February 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords arctic tundra fungal community glacial forefield primary succession rhizosphere community Authors Affiliations Shota Masumoto 0000-0001-6029-3632 [email protected] University of Tsukuba View all articles by this author Shu-Kuan Wong National Institute of Polar Research View all articles by this author Cai Yihan The University of Tokyo View all articles by this author Masaki Uchida National Institute of Polar Research View all articles by this author Metrics & Citations Metrics Article Usage 118 views 80 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Shota Masumoto, Shu-Kuan Wong, Cai Yihan, et al. Habitat and host specificity of the rhizosphere fungi form meta-community structure of the Arctic glacial forefield. Authorea . 20 February 2026. DOI: https://doi.org/10.22541/au.177157450.02702386/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. 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