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# Influence of tree mycorrhizal type, tree species identity, and diversity on forest root-associated mycobiomes

Bala Singavarapu<fnref n="1" />,²,³,¹¹* ID, Hafeez ul Haq<fnref n="1" />,²,³* ID, Friedrich Darnstaedt<fnref n="1" />,² ID, Ali Nawaz<fnref n="1" />,⁴ ID,
Rémy Beugnon³,⁵,⁶ ID, Simone Cesarz³,⁷ ID, Nico Eisenhauer³,⁷ ID, Jianqing Du⁸,⁹ ID, Kai Xue⁸,⁹ ID,
Yanfen Wang⁸,⁹,¹⁰ ID, Helge Bruelheide²,³ ID and Tesfaye Wubet<fnref n="1" />,³ ID

Authors for correspondence:
Tesfaye Wubet
Email: tesfaye.wubet@ufz.de

Bala Singavarapu
Email: balu.singavarapu@gmail.com

Received: 14 July 2023
Accepted: 20 February 2024

New Phytologist (2024) **242**: 1691–1703
**doi**: 10.1111/nph.19722

**Key words:** dual mycorrhizal communities, forest mycobiome, plant–root fungal associations, tree mycorrhizal type, tree species diversity, tree species identity, tree–tree interactions.

## Summary

* Understanding the complex interactions between trees and fungi is crucial for forest ecosystem management, yet the influence of tree mycorrhizal types, species identity, and diversity on tree-tree interactions and their root-associated fungal communities remains poorly understood.

* Our study addresses this gap by investigating root-associated fungal communities of different arbuscular mycorrhizal (AM) and ectomycorrhizal (EcM) tree species pairs (TSPs) in a subtropical tree diversity experiment, spanning monospecific, two-species, and multi-species mixtures, utilizing Illumina sequencing of the ITS2 region.

* The study reveals that tree mycorrhizal type significantly impacts the alpha diversity of root-associated fungi in monospecific stands. Meanwhile, tree species identity's influence is modulated by overall tree diversity. Tree-related variables and spatial distance emerged as major drivers of variations in fungal community composition. Notably, in multi-species mixtures, compositional differences between root fungal communities of AM and EcM trees diminish, indicating a convergence of fungal communities irrespective of mycorrhizal type. Interestingly, dual mycorrhizal fungal communities were observed in these multi-species mixtures.

* This research underscores the pivotal role of mycorrhizal partnerships and the interplay of biotic and abiotic factors in shaping root fungal communities, particularly in varied tree diversity settings, and its implications for effective forest management and biodiversity conservation.

## Introduction

Root-associated fungal communities play versatile roles such as promoting the growth and survival of the plants, influencing the plant community functioning by modulating belowground plant–plant interactions, and contributing to the biogeochemical cycling by mediating plant–soil feedbacks (Clemmensen et al., 2013; Chen et al., 2018; Almario et al., 2022). It is known that the diversity and composition of the root-associated fungal communities are influenced by many biotic and abiotic factors. One of the important biotic components is the identity of the host plant species. A plant can selectively recruit root-inhabiting microbes, for example through specific rhizodeposition

(Eisenhauer *et al.*, 2017). Host–fungi specificity is brought about by shared co-evolutionary histories (Hoeksema *et al.*, 2018). Nearly 80% of vascular plants engage in symbiotic exchanges with specialized root fungi, predominantly arbuscular mycorrhizal fungi (AMF) and ectomycorrhizal fungi (EMF), trading plant-derived carbon for vital nutrients such as phosphorus and nitrogen (Moora, 2014; Brundrett & Tedersoo, 2018). These plants are categorized based on their type of mycorrhizal associations: ectomycorrhizal (EcM) plants affiliate with EMF, while AM plants associate with AMF. This reflects tailored mutualistic relationships, each adapted to specific ecological and physiological needs (Bueno *et al.*, 2017). Studies have shown a positive correlation between the prevalence of a plant mycorrhizal type and the abundance of its respective mycorrhizal fungal communities; ecosystems with a high abundance of EcM plants tend to have

<footnote n="1">¹Department of Community Ecology, UFZ-Helmholtz Centre for Environmental Research, Theodor-Lieser-Str. 4, D-06120, Halle (Saale), Germany; ²Institute of Biology/Geobotany and Botanical Garden, Martin Luther University Halle-Wittenberg, Am Kirchtor 1, 06108, Halle, Germany; ³German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstrasse 4, 04103, Leipzig, Germany; ⁴Department of Digital Health Sciences and Biomedicine, School of Life Sciences, University of Siegen, Am Eichenhang 50, 57076, Siegen, Germany; ⁵CEFE, Univ Montpellier, CNRS, EPHE, IRD, 1919, route de Mende, F-34293, Montpellier Cedex 5, France; ⁶Leipzig Institute for Meteorology, Universität Leipzig, Stephanstraße 3, 04103, Leipzig, Germany; ⁷Institute of Biology, Leipzig University, Puschstrasse 4, 04103, Leipzig, Germany; ⁸College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China; ⁹Beijing Yanshan Earth Critical Zone National Research Station, University of Chinese Academy of Sciences, Beijing, 101408, China; ¹⁰State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Chinese Academy of Sciences, 100101, Beijing, China; ¹¹Present address: Aquatic Geomicrobiology, Institute of Biodiversity|Friedrich Schiller University Jena, Dornburger Strasse 159, Jena, 07743, Germany</footnote>

<footnote>*These authors shared first authorship.</footnote>
greater EMF communities, while those dominated by AM plants
are characterized by higher AMF abundances (Gao *et al.*, 2013;
Neuenkamp *et al.*, 2018).

Furthermore, plant mycorrhizal partners can significantly
influence the diversity and composition of the other
root-associated fungal communities (Toju *et al.*, 2014; Ferlian
*et al.*, 2021; Heklau *et al.*, 2021). However, research shows that
plant species diversity effects on root-associated fungal commu-
nities are not unanimous. For instance, some studies reported the
absence of any significant effects of plant richness on root fungal
communities (Navratilova *et al.*, 2019; Otsing *et al.*, 2021).
Nevertheless, the prevailing pattern shows significant positive
effects of plant richness on fungal richness (Gao *et al.*, 2013;
Hiiesalu *et al.*, 2017; Tedersoo *et al.*, 2020; Ferlian *et al.*, 2021).
In a study highlighting the differences between soil microbial
communities under AM and EcM tree species, Singavarapu
*et al.* (2021) reported significantly higher fungal diversity under
the AM than that of EcM tree species in monocultures. Further-
more, it was shown that with increasing plot tree diversity, the
differences in microbial diversity and composition between AM
and EcM tree species became nonsignificant. In the case of for-
ests, trees might grow in conspecific stands, which should favor
symbiotic associations with their corresponding mycorrhiza type,
or in mixtures of varying diversity, which also includes mixtures
of tree species with different mycorrhiza types. We can only get a
comprehensive understanding of how the root-inhabiting fungi
are structured in these different host species compositions when
they are analyzed in parallel rather than individually. However,
such available comparative studies are very limited (Toju *et al.*
2014; Davison *et al.*, 2020) and there is a necessity to study the
effects of tree mycorrhizal type and tree species identity in differ-
ing tree diversity levels on the root-associated fungi to get better
insights into their community assembly and consequently their
role in ecosystem functioning.

In addition to biotic factors, recent studies emphasize the sig-
nificant influence of environmental elements in shaping
root-inhabiting fungal communities. For instance, a study by
Horn et al. (2017) identified spatial aspects of the environment
as being more influential than plant community composition in
determining the structure of AMF assemblages. Similarly, in one
study, the slope aspect of the site was reported to induce differen-
tial phylogenetic clustering of AMF communities via modifying
the microclimate (Chai et al., 2018). In another study, strong
abiotic environmental filtering provided by the soil environment
was reported to shape the root endophytic fungal communities,
suggesting the importance of the local environment in addition
to biotic factors (David et al., 2016). However, the interactive
effects of tree species identity, tree mycorrhizal type, tree diver-
sity, and the local environmental factors on the root-associated
fungal communities remain unexplored.

To address this research gap, we utilized the biodiversity-
ecosystem functioning (BEF) experiment model, specifically
designed to investigate the impacts of species richness on ecosys-
tem functions. We employed the BEF-China experiment, the
world's largest tree diversity experimental platform, situated in
China (Trogisch et al., 2021). This experiment, with its

deliberate manipulation of plant species richness and composi-
tion, enables the effective disentanglement of biotic factors such
as plant community composition from abiotic factors like soil
properties. Employing an experimental approach is crucial for a
deeper understanding of plant-fungus interactions and their eco-
logical implications (Bruelheide et al., 2014). Considering the
varied root surface exposure between AM and EcM trees for fun-
gal colonization (Bonfante & Anca, 2009), alongside the com-
plex interactions within diverse tree communities and the local
environmental influences (Bruelheide et al., 2014; Luo et al.,
2018), we explored their collective impact on root-associated fun-
gal diversity and community composition. Our specific hypoth-
eses are:

H1 (fungal diversity variation): Higher alpha diversity of root-associated fungi in AM tree species, attributed to their more exposed root surfaces, compared with the partially Hartig net-covered roots of EcM species. Furthermore, we anticipate that the influence of mycorrhizal type and species identity on alpha diversity lessens with increasing tree diversity.

H2 (community composition dynamics): The composition of root-associated fungal communities differs markedly between AM and EcM tree species, influenced by mycorrhizal type, species identity, and tree diversity. We expect a converging taxonomic pattern in fungal communities as tree diversity increases.

H3 (environmental and community influences): Differential impacts of soil properties, spatial distribution, topography, and tree community variables on the root-associated fungal communities in AM vs EcM species, each shaping the communities distinctly.

Through these hypotheses, we aim to thoroughly investigate
how tree diversity, mycorrhizal types, and environmental factors
interplay to shape the dynamics of root-associated communities
in forest ecosystems.

Materials and Methods

Study site, experimental design, and sampling

Our study site is one of the BEF-China tree diversity experimen-
tal sites (Site A), which contains native subtropical tree species
with a diversity gradient ranging from monospecific stands to
24-species mixtures (Bruelheide et al., 2014). The experimental
site was planted in 2009 in the Chinese subtropics (Xingangshan,
Jiangxi Province, Southeast China, 29.08–29.11°N, 117.90–
117.93°E) on a total area of 18.4 ha. The plots are of a size of
25.8 m × 25.8 m, with 400 trees, each spaced on a regular grid
at 1.29 m. The predominant soil types in the site are Cambisols,
along with their derivatives. In this region, Cambisols and Rego-
sols are typically found on ridges, spurs, and crests. Along the
slopes, Cambisols and Acrisols are common, whereas colluvic
Cambisols and Gleysols are mainly found on foot slopes and val-
ley areas (Scholten et al., 2017). In our experimental design (Sup-
porting Information Fig. S1), we followed the tree species pair
(TSP) concept, in which two adjacent trees were selected as target
trees, and the 10 surrounding trees of the respective TSP were
considered as its neighborhood (Trogisch et al., 2021). More
information about the design and establishment of the BEF-China experiment can be found in Yang *et al.* (2013) and Bruelheide *et al.* (2014), and for the sampling design, please refer to Singavarapu *et al.* (2021). We focused on the conspecific TSPs only. Therefore, six EcM and six AM-type TSPs were selected, and each conspecific pair was randomly distributed across 55 plots through the tree diversity gradient (Table S1; Fig. S1; Dataset S1). We sampled three replicates in each of the monospecific stands (denoted as 'Mono'), two-species mixtures (denoted as 'Two'), and multi-tree species mixtures (denoted as 'Multi'), which comprised plots with tree species richness ≥ 4 (Dataset S1). From both adjacent target trees of each TSP (n = 108), root samples were collected resulting in a total of 216 samples with the following six combinations: 'EcM|Mono' (n = 36), 'EcM|Two' (n = 36), 'EcM|Multi' (n = 36), 'AM|Mono' (n = 36), 'AM|Two' (n = 36), and 'AM|Multi' (n = 36). Fine root samples were taken from each of the two trees of a TSP in the tree-tree interaction zone (i.e. the horizontal axis between the two TSP partners). Fine roots of each species within the tree-tree interaction zone were traced starting from the main trunk of the TSPs, ensuring that the samples accurately represent the respective tree species (Fig. S1). Rhizosphere soil attached to the roots was gently removed by shaking and squeezing and further the fine root samples were washed for 3 min in 400 ml sterile water that contained 0.01% Tween™ 80 (Merck KGaA, Darmstadt, Germany) to efficiently remove remaining soil particles and externally bound epiphytic microbes. Subsequently, two more washing steps with 400 ml of sterile water were performed to remove the remaining traces of the detergent. Finally, the washed roots were surface sterilized in 70% ethanol for 2 min, transferred into 5-ml tubes filled with 70% ethanol, and stored at -20°C until DNA extraction.

Soil characteristics

Before soil core collection, organic layers such as litter and debris were removed from the soil surface. Four soil cores (5 cm diameter; 10 cm depth) were collected from the tree-tree interaction zone (i.e. the horizontal axis between the two partner trees of a TSP) at distances of 5 cm from the center of a TSP (first two cores) and further 20 cm away (other two cores). A composite soil sample was obtained from the four soil cores after pooling, mixing, and removal of root fragments by sieving the mixed soil through a 2-mm mesh size sieve. Soil samples were transported to the field laboratory in a cool box and stored at 4°C until processed. The samples were divided into subsets for various measurements. Soil moisture content was determined by drying the soil at 105°C for 24 h. Soil pH was measured in a 1 : 2.5 soil-water solution with a Thermo Scientific Orion Star A221 pH meter. Soil total organic carbon (TOC) was measured using a TOC Analyzer (Liqui TOC II; Elementar Analysensysteme GmbH, Hanau, Germany). Soil total nitrogen was measured using an auto-analyzer (SEAL Analytical GmbH, Norderstedt, Germany) by the Kjeldahl method (Bradstreet, 1954). Soil total phosphorus was measured following wet digestion with H₂SO₄ and HClO₄ using a UV-VIS spectrophotometer (UV2700;

Shimadzu, Kyoto, Japan). For NH₄⁺ and NO₃⁻ analyses, soil samples stored at 4°C were used, with measurements conducted via the colorimetric method using a Smart Chem 200 Discrete Auto Analyzer (AMS, Italy) after 2 M KCl extraction (Talbot *et al.*, 2014). For more details on soil characteristics, please refer to Singavarapu *et al.* (2021).

DNA extraction, amplicon library preparation, and
sequencing

Before extraction, 25–50 mg of fine root material was dried at 40°C for 20 h in the drying oven. The dried roots were crushed using metal beads from Retsch with a diameter of 5 mm and the vibration mill ‘MM 300’ (Retsch® GmbH, Haan, Germany) with run times of 2–3 min at 30.000 Hz. Genomic DNA was extracted from the crushed root material using the DNeasy® Plant Mini Kit (Qiagen) following the manufacturer’s protocol.

DNA concentrations were measured with a NanoDrop spectrophotometer (Thermo Fisher Scientific, Dreieich, Germany), and the extracts were adjusted to 10 ng µl⁻¹ template concentration. The fungal amplicon libraries were prepared as previously described in (Singavarapu *et al.*, 2021). Briefly, semi-nested PCR was employed to amplify the ITS2 rDNA region using the initial primer combination of ITS1F (Gardes & Bruns, 1993) and ITS4 (White *et al.*, 1990) followed by the primer pair flTS7 (Ihrmark *et al.*, 2012) and ITS4 containing the Illumina adapter sequences. The fungal amplicon libraries were purified with Agencourt AMPure XP beads (Beckman Coulter, Krefeld, Germany). Illumina Nextera XT Indices were added to both ends of the fungal fragments in the indexing PCR. The indexed products were purified again with AMPure beads and then quantified by PicoGreen assay. The amplicon libraries were pooled equimolarly to a final concentration of 4 nM and paired-end sequencing of 2 × 300 bp was performed on an Illumina MiSeq platform (Illumina Inc., San Diego, CA, USA) using MiSeq Reagent kit v3 at the Department of Environmental Microbiology, UFZ, Leipzig, Germany.

Bioinformatics analysis

High-quality reads were extracted from raw reads generated by the Illumina MiSeq Sequencing platform as described in Singavarapu *et al.* (2021) using the Quantitative Insights into Microbial Ecology – *QIIME* 2 v.2022.2 software (Bolyen *et al.*, 2019). Following demultiplexing of forward and reverse reads based on index combinations, primer sequences were trimmed, followed by sequence denoising and grouping into amplicon sequence variants (ASVs) using Cutadapt (Martin, 2011; q2-cutadapt) and DADA2 (Callahan *et al.*, 2016) via (q2-dada2), respectively. The q2-ITsxpress *QIIME2* plugin (Rivers *et al.*, 2018) was used to analyze the fungal ITS dataset, with the ITS2 fungal sequences being detected and trimmed, then denoised and grouped into ASVs using the DADA2 plugin. The q2-feature-classifier (Bokulich *et al.*, 2018) was used to classify fungal ITS ASVs using the classify-sklearn naive Bayes taxonomy classifier against the unitev.8-99-classifier-04.02.2020. The fungal taxonomic data were
assigned to fungal functional guilds using the funguild_assign function of the FUNGuildR package (Nguyen et al., 2016) followed by functional assignment of fungal traits at the genus level using the FungalTraits database (Põlme et al., 2020). The primary and secondary functions were then recoded into trophic modes and parsed to the FUNGuild assignment. We excluded the NAs and guilds with a confidence ranking of ‘possible’ as suggested by Nguyen et al. (2016). The respective metadata, ASV matrices, taxonomic tables, and representative sequences were imported into R using the phyloseq package (McMurdie & Holmes, 2013) for further statistical analysis.

## Statistical analysis

All statistical analyses and data visualizations were performed using R v.4.1.1 (R Core Team, 2020). The datasets were controlled for nonfungal ASVs and were rarefied to 7130 reads per sample. The fungal alpha-diversity measures were calculated using the microbiome package (Lahti & Shetty, 2017). The normality of the diversity indices was tested using Shapiro-Wilk normality test and Wilcoxon rank-sum tests were used to test for the tree mycorrhizal type effect on the observed richness and Shannon diversity indices. A two-way ANOVA was used to test the main and interactive effects of tree species identity and tree diversity on the alpha-diversity indices. For this purpose, the data residuals were checked for normality and homogeneity of variance using the Shapiro-Wilk test and Levene's test, respectively, and furthermore, Box-Cox transformed to meet the normality and homogeneity of variance assumptions using the car package (Fox & Weisberg, 2018). Furthermore, the significant differences among the TSPs within each tree diversity level were verified with Kruskal-Wallis tests, followed by the pairwise-Wilcox test with Benjamini-Hochberg correction for multiple comparisons using the RSTATX package (Kassambara, 2021). To test the main and interactive effects of mycorrhizal types, tree species identity, and diversity levels on the root-associated fungal community compositional variation, nonparametric permutational ANOVA (PERMANOVA) analysis was performed with Bray-Curtis distance using the ‘adonis2’ function of the VEGAN package (Oksanen et al., 2019), followed by a pairwise multilevel comparison using the ‘pairwise.adonis’ function of the pairwiseAdonis package with Benjamini-Hochberg correction for multiple comparisons (Martinez Arbizu, 2017). The pairwise distances were presented as a heatmap using the ‘plothmap’ function of the COMPLEXHEATMAP package (Gu et al., 2016). Distance-based redundancy analysis (dbRDA) ordination analysis was used to visualize the fungal community composition using the phyloseq package. The ASVs were agglomerated at the phylum level using the PHYLOSEQ package to visualize the relative abundance of the top 10 phyla across tree diversity levels of the two mycorrhizal types. The relative abundances of the fungal functional guilds were presented at the tree diversity and tree species levels of the two mycorrhizal types using barplots. We used variation partitioning analysis to measure the contribution of soil, tree, topography, and spatial characteristics on fungal community compositional variation. The tree community variables as a biotic component included tree community

composition, tree species identity, tree and shrub species richness, tree Shannon and Simpson diversity indices, abundance and richness of tree neighborhood, abundance and richness of neighbor AM and EcM TSPs. Soil characteristics (C, N, P, C/N, C/P, N/P, TOC, SOM, NH<sub>4</sub><sup>+</sup>, NO<sub>3</sub><sup>-</sup>, pH, and moisture) and topographical variables (altitude, slope, northness, and eastness) were considered as abiotic components. Vectors from principal coordinates of neighborhood matrices computed from the sampling locations (latitude and longitude) were used to represent the spatial component (Dray et al., 2006). Before variation partitioning, significant variables from each of the four components were selected using dbRDA models ('capscale' function in VEGAN) with stepwise model selection ('ordistep' function in VEGAN).

## Results

The raw sequencing data output for the 216 samples included 3559 881 reads in total. After quality filtering via denoising, merging, chimera, and nontarget taxa removal, 2989 877 reads (84%) remained and were then clustered to 6629 ASVs. All 216 samples were rarefied at 7130 reads per sample, resulting in 6394 ASVs in the final dataset.

### Observed alpha diversity of root-associated fungal communities

Analysis of the effect of the host tree's mycorrhizal type indicated a significant effect on the observed ASV richness and Shannon diversity (Fig. 1a,c). Similarly, the effect of mycorrhizal type was significant for both indices in monospecific stands and two-species mixtures. By contrast, any significant effect of mycorrhizal type was absent in the multi-species plots (Fig. 1b, d). The responses varied between species as was revealed by subsequent two-way analysis of variance (ANOVA), showing a significant main effect of tree species and interactive effects of tree species and tree diversity level on fungal alpha-diversity indices (Table S2). Analyses at the species and genus level aggregation of the ASVs showed similar patterns with the Shannon diversity but not observed richness (Table S3). Further analysis of the role of tree species identity on the alpha-diversity measures within the tree diversity levels revealed that the number of significantly different TSPs declined with increasing tree diversity, according to Kruskal-Wallis tests (*P* < 0.05; Figs S2, S3). Although there were some significant differences within mycorrhizal types, the majority of the significant pairwise differences were observed between AM and EcM tree species in both mono and two-species mixtures, where the AM tree species had higher fungal diversity.

### Tree mycorrhizal type, tree species identity, and tree diversity effects on root-associated fungal community composition

Analysis of the main and interactive effects of tree mycorrhizal type, tree diversity level, and tree species identity on the root-associated fungal community composition revealed a significant
<figure><img src="image_3.png" /><figcaption>**Fig. 1** Alpha-diversity indices of root-associated fungal communities. (a, c) Comparison of fungal observed richness, and Shannon diversities, respectively between all arbuscular mycorrhizal (AM) and ectomycorrhizal (EcM) TSPs. (b, d) Within the tree diversity level, differences between AM and EcM TSPs for the respective fungal alpha-diversity measures. Blue, EcM samples; Mono, monospecific stands; Multi, multi-species mixtures; Red, AM samples; Two, two-species mixtures. Box plots depict the median (central horizontal line), interquartile range (box boundaries), and extend whiskers to the data points within 1.5 times the interquartile range. Outliers are indicated as individual points beyond the whiskers. Wilcoxon rank-sum tests were used and the statistical significance between groups is denoted by asterisks. *P*-values: ****, *P* < 0.0001; **, *P* < 0.001; *, *P* < 0.05.</figcaption></figure>

effect of all three factors, and in addition, the interactions between tree mycorrhizal type with tree diversity and of tree diversity with tree species identity (Table 1). In total, the tested factors explained 26.57% variance. Analyses at the species and genus level aggregation of the ASVs showed a similar pattern with even more explained variance: 33.41% and 34.01% at species and genus levels, respectively (Table S4). Consistent with the analysis on fungal diversity, the dbRDA showed clearly separated fungal communities of AM and EcM tree mycorrhizal types in monospecific stands and two-species mixtures (Fig. 2), but not in multi-species mixture level. Here, fungal communities of both tree mycorrhizal types clustered closely together (Fig. 2).

## Tree species identity effects across the tree diversity levels

The strong tree species identity and tree diversity level interaction were further investigated using PERMANOVA in each of the tree diversity levels. Tree species identity explained 30.8%, 26.3%, and 19.4% percentage of variance in mono-, two-, and multi-species mixtures, respectively. The contribution of tree mycorrhizal type to the tree species identity effect was 4%, 3.8%, and 1.9% in mono-, two-, and multi-species mixtures, respectively. Furthermore, the pairwise PERMANOVA analysis resulted in 66 potential TSPs, including 15 AM-AM, 15 EcM-EcM, and 36 AM-EcM pairs (Fig. 3). All 66 tested potential tree pairs significantly differed from each other in their fungal community composition in monospecific stands but not in the multi-species mixtures (Fig. 3). In the two-species mixtures, 60 out of

the 66 TSPs (including all the 36 AM-EcM, 14 AM-AM and 10 EcM-EcM TSPs) showed significantly different root fungal community composition (Fig. 3).

## Root-associated fungal community taxonomic composition

The AM trees were predominantly colonized by fungi of the phyla Ascomycota followed by Basidiomycota and then Glomeromycota, whereas the EcM trees were nearly proportionally colonized by members of the phyla Ascomycota and Basidiomycota (Fig. 4a). In general, AM tree species had 20.62% more Ascomycota and 7.1% more Glomeromycota fungal ASVs than the EcM tree species. However, the proportion of Basidiomycotan ASVs was 27.02% lower in AM compared with EcM trees. For AM tree species, there was a slight increase in Basidiomycota with increasing tree diversity, while Ascomycota showed slightly decreasing proportions in multi-species mixtures compared with monospecific stands and two-species mixtures. Glomeromycota covered the highest share in monospecific stands and decreased consistently from monospecific stands to two-species mixtures and multi-species mixtures. For EcM tree species, the proportions of Ascomycota and Basidiomycota were almost not affected by tree diversity (Fig. 4a).

## Root-associated fungal community functional composition

A total of 3063 ASVs accounting for 47.9% of the 6394 ASVs identified in this study were assigned to seven trophic modes.
<table><caption>**Table 1** Permutational multivariate analysis of variance (PERMANOVA) on root-associated fungal communities using Bray-Curtis distance.</caption><thead><tr><th></th><th>df</th><th>R<sup>2</sup></th><th>F</th><th>P</th></tr></thead><tbody><tr><td>Mycorrhizal type (M)</td><td>1</td><td>0.018</td><td>4.298</td><td>0.001***</td></tr><tr><td>Tree diversity (D)</td><td>2</td><td>0.014</td><td>1.776</td><td>0.001***</td></tr><tr><td>Tree species (I)</td><td>10</td><td>0.089</td><td>2.193</td><td>0.001***</td></tr><tr><td>(M × D) Interaction</td><td>2</td><td>0.015</td><td>1.791</td><td>0.001***</td></tr><tr><td>(I × D) Interaction</td><td>20</td><td>0.130</td><td>1.588</td><td>0.001***</td></tr><tr><td>Residual</td><td>180</td><td>0.734</td><td></td><td></td></tr></tbody></table>

P-values: ***, P < 0.001.

Abbreviations: mycorrhizal type (M), tree diversity (D), and tree species identity (I).

<figure><img src="image_4.png" /><figcaption>**Fig. 2** Ordination plots of distance-based redundancy analysis (dbRDA) constrained by mycorrhizal type and tree diversity level using Bray-Curtis distance. Blue, ectomycorrhiza (EcM) samples; Mono, monospecific stands; Multi, multi-species mixtures; Red, arbuscular mycorrhiza (AM) samples; Two, two-species mixtures. Different plotting symbols represent tree diversity levels.</figcaption></figure>

Out of those, 1642 ASVs (53.6%) were exclusively assigned to the three major trophic groups of symbiotroph (770 ASVs), saprotroph (747 ASVs), and pathotroph (125 ASVs), accounting for 25.1%, 24.4% and 4.1%, respectively, of the assigned ASVs (Fig. 4b). The remaining 1421 ASVs (46.4%) were assigned to more than one trophic mode. In the AM tree species, fungi with saprotrophy either as their main trophic mode or as one of their lifestyles were the predominant functional groups with a total of c. 79% relative abundance. On the contrary, EcM trees harbored symbiotrophs (31.7%) and saprotroph-symbiotrophs (28.8%) as the major functional groups in their roots (Fig. 4b). The relative importance of these functional groups also changed across the tree diversity levels within the tree mycorrhizal types. For instance, in AM tree species, the combined relative abundance of symbiotrophs and saprotroph-symbiotrophs increased from monospecific plots to multi-species mixtures after a decline in the two-species mixtures, whereas the opposite is the case for EcM trees (Fig. 4b). A closer look into the symbiotrophs indicated that both the AM and EcM tree species were mainly colonized by their respective mycorrhizal fungal partners in the monospecific plots. An exception was *Sapindus mukorossi* which, as AM tree species, hosted also EMF (Fig. 4c). In the two-species mixtures, dual mycorrhizal partners were observed in four of the AM and one of the EcM tree species, whereas dual mycorrhizal fungal communities were observed in all species when they grew in the multi-species mixtures. However, the degree to which AM or

EcM tree species were associated with their contrasting mycorrhizal partner varied from species to species, with the AM tree species *Liquidambar formosana* and *Koelreutheria bipinnata* hosting even more EMF than AM fungi (Fig. 4c).

## Biotic and abiotic components shaping the root-associated fungal communities

Variation partitioning analysis unraveled the contribution of soil, tree community, topography, and spatial components on the root-associated mycobiome composition (Fig. 5). Overall, more variation was explained in the EcM dataset (Fig. 5c). Across all tree mycorrhiza types, the fungal community composition was mainly influenced by the tree (10.0%), spatial (9.6%), and soil (2.2%) related variables, while their shared contribution was always < 1% (Fig. 5a). In EcM tree species, soil characteristics were more important (5.3%) than in AM tree species (2%).

## Discussion

High tree diversity dilutes the effects of tree mycorrhizal type and tree species identity on the alpha diversity of root-associated mycobiota

As expected (H1), we found significant effects of the tree mycorrhizal type on the alpha diversity (richness and Shannon
<caption>**Fig. 3** Heatmap based on pairwise permutational multivariate analysis of variance (PERMANOVA) to test effects of tree diversity on tree species root-associated fungal community composition. (a) Arbuscular mycorrhizal (AM) tree species pairs (TSPs), (b) Ectomycorrhizal (EcM) TSPs, and (c) AM-EcM TSPs. CaHe, Castanea henryi; CaSc, Castanopsis sclerophylla; CyGl, Cyclobalanopsis glauca; KoBi, Koelreuteria bipinnata; LiFo, Liquidambar formosana; LiGl, Lithocarpus glaber; Mono, monospecific stands; Multi, multi-species mixtures; ChAx, Choerospondias axillaris; NySi, Nyssa sinensis; QuFa, Quercus fabri; QuSe, Quercus serrata; SaMu, Sapindus mukorossi; SaSe, Sapium sebiferum; Two, two-species mixtures. BH adjusted *P*-values: **, *P* < 0.01; *, *P* < 0.05.</caption>

diversity) of root fungi and a higher diversity in AM than that of
EcM tree species. In line with our findings, Heklau *et al.* (2021)
reported higher fungal richness in AM tree species roots com-
pared with that of EcM in a temperate forest experiment. From
the same experiment, Ferlian *et al.* (2021) reported higher AMF
in AM and higher EMF in EcM tree species roots, pointing out
the importance of the tree mycorrhizal type on root fungal diver-
sity. In addition, Ferlian *et al.* (2021) also reported the effects of
tree species identity and the neighbor tree mycorrhizal types on
the AMF and EMF phylogenetic diversity, which fully complies
with our results. In our study, the observed high fungal alpha
diversity in AM tree species roots can be attributed to the highly
diverse fungal species reservoir available in the soils of AM trees
(Singavarapu *et al.*, 2021). This might be because, in AM tree-
dominated habitats co-existence of AMF with a diverse group of
saprophytic fungi, known to facilitate decomposition and nutri-
ent cycling, could support the observed high fungal diversity as
compared with EcM tree-dominated habitats characterized by
the slower decomposition rates and competitive limitation of
other fungal decomposers by the ECM fungal partners (Midgley
*et al.*, 2015; Jacobs *et al.*, 2018; Tedersoo & Bahram, 2019).
Despite the prevalent use of ASVs as microbial taxonomic units
in recent studies, Kauserud (2023) notes that ASVs tend to over-
estimate alpha diversity. Our analysis of the same at species and
genus level aggregation of the ASVs indicated that this

overestimation effect was mainly in terms of the observed rich-
ness but not on the Shannon diversity. While ASVs offer a taxo-
nomic resolution surpassing the species level, it is imperative to
interpret results with caution when solely relying on ASVs for
ITS marker-based fungal community analyses. The ITS region's
significant variability, compounded by high intraspecific and
intragenomic variations, likely contributes to this overestimation
of richness. However, our Shannon diversity analysis at higher
taxonomic levels shows patterns consistent with ASV-level results,
reaffirming the validity of our findings in uncovering ecological
trends. Moreover, our comparative analysis across various taxo-
nomic resolutions suggests that clustering sequences at a lower
identity threshold may lead to an underrepresentation of
observed taxa richness, highlighting the need for careful selection
of analytical approaches in future research.

Additionally, we found that tree diversity level modulates the
effects of both tree mycorrhizal type and tree species identity on
the root-associated fungal communities as all effects that were sig-
nificant in monospecific stands or two-species mixtures disap-
peared in multi-tree species mixtures, confirming the second part
of our hypothesis (H1). In general, higher plant diversity facili-
tates diverse microhabitats, providing divergent niche opportu-
nities and different substrate resources for numerous soil
microbes (Hooper *et al.*, 2000; Waldrop *et al.*, 2006). This view
is further supported by the higher diversity of fungal taxonomic

<figure><img src="image_5.png" /></figure>
<figure><img src="image_6.png" /><figcaption>**Fig. 4** Taxonomic and functional composition of root-associated fungal communities across tree diversity levels. (a) Phylum level taxonomic composition of arbuscular mycorrhizal (AM) and ectomycorrhizal (EcM) tree species, (b) trophic mode level functional composition of AM and EcM tree species, (c) functional guild level composition of symbiotrophs of all tree species. First six EcM tree species followed by six AM tree species. *CaHe*, *Castanea henryi*; *CaSc*, *Castanopsis sclerophylla*; *ChAx*, *Choerospondias axillaris*; *CyGl*, *Cyclobalanopsis glauca*; *KoBi*, *Koelreuteria bipinnata*; *LiFo*, *Liquidambar formosana*; *LiGl*, *Lithocarpus glaber*; *Mono*, monospecific stands; *Multi*, multi-species mixtures; *NySi*, *Nyssa sinensis*; *QuFa*, *Quercus fabri*; *QuSe*, *Quercus serrata*; *SaMu*, *Sapindus mukorossi*; *SaSe*, *Sapium sebiferum*; *Two*, two-species mixtures.</figcaption></figure>

and functional groups in multi-tree species mixtures in our data
and explains the decreasing importance of tree mycorrhizal type
and tree species identity effects on the observed alpha diversity.
The positive tree diversity effect is also seen in the significant
interaction of tree species identity with tree diversity on root fun-
gal diversity of EcM tree species. The higher fungal alpha

diversity (here, in EcM tree species) in our multi-tree species mix-
tures could have a positive effect on ecosystem functioning. In
support, a previous experiment of suppressing fungi associated
with both AM and EcM tree species, (Yang *et al.*, 2022) showed
the key role of fungi in mediating the observed positive tree
diversity-plant productivity relationship at our study site.
(a)

<figure><img src="image_7.png" /></figure>

(b)

<figure><img src="image_8.png" /></figure>

(c)

<figure><img src="image_9.png" /><figcaption>**Fig. 5** Variance partitioning analysis depicting the contribution of soil, tree community variables, topography, and spatial parameters to the root-associated fungal community composition. (a) Overall, (b) arbuscular mycorrhizal (AM) tree species, and (c) ectomycorrhizal (EcM) tree species.</figcaption></figure>

## Tree diversity modulated compositional dynamics of root-associated fungal communities

Confirming our hypothesis (H2), root fungal community composition differed between AM and EcM tree species. Our findings from the PERMANOVA analysis corroborate the reports of tree species-associated root fungal communities (Kuang et al., 2021; Otsing et al., 2021), tree mycorrhizal type effects on root-associated fungi (Toju et al., 2014; Heklau et al., 2021) and relationships between root fungal community composition and tree species richness (Gao et al., 2013; Heklau et al., 2021; but see, Otsing et al., 2021). Our comparative analysis at species and genus levels not only corroborated the community composition dynamics observed at the ASV level but also accounted for a greater proportion of variance. This could be indicative of more pronounced biological interactions or enhanced ecological relevance at these higher taxonomic levels. Alternatively, it may be resulted from the aggregation of ASV data reducing complex diversity and fine-scale variability, thereby increasing the statistical power of our analyses. Evolutionary relationships of root-associated fungal taxa, especially the mycorrhizal communities with their tree hosts, could play a pivotal role in community assembly dynamics. Ectomycorrhizal symbiosis originated multiple times (c. ≥ 80 times) c. 190–200 million years ago across multiple lineages of Mucoromycota, Ascomycota, and mainly Basidiomycota (Miyauchi et al., 2020). Despite their repeated convergent evolution, which results in genetically diverse and functionally similar associations, EMF share broad genetic similarities and are also phylogenetically very close to their saprotrophic ancestors (Miyauchi et al., 2020; Strassert & Monaghan, 2022). Predominantly high abundances of EMF together with the fungal taxa with saprotrophic lifestyle in the root fungal communities of EcM TSPs explain the lower number of significant differences found between EcM TSPs in the pairwise analysis of TSPs' root fungal community composition. Furthermore, we assumed that EMF affected the recruitment of other nonmycorrhizal fungal taxa, particularly the saprotrophs, through competitive interactions and preferential selection (Churchland & Grayston, 2014; Fernandez & Kennedy, 2016). By contrast, the fungal phylogeny places the AMF, which belongs to the phylum Glomeromycota,

in a clade distant to Dikarya (i.e. both Ascomycota and Basidiomycota) and between the Dikarya and Mucoromycota (Strassert & Monaghan, 2022). Probably owing to their limited genomic potential in breaking down organic compounds, AMF were reported to have cooperative interactions with saprotrophs (Verbruggen et al., 2017; Miyauchi et al., 2020). Therefore, they might positively influence the recruitment of various fungal taxa with the saprotrophic lifestyle which was apparent in the root fungal community functional guild composition of AM TSPs. Altogether, these phylogenetically distant taxa comprising Ascomycota, Basidiomycota, and Glomeromycota explain the higher number of significant differences found within AM TSPs and between AM and EcM TSPs in monospecific stands and two-tree species mixtures. Furthermore, confirming the second part of hypothesis H2, the fungal communities between the AM and EcM trees converged in multi-tree species mixtures as shown by the ordination and pairwise PERMANOVA analyses. This convergence is facilitated by the co-occurrence of different tree species with different mycorrhizal types (Singavarapu et al., 2021). This also explains the absence of tree mycorrhizal type and tree species identity effects in multi-tree species mixtures. Besides, it was reported that a phylogenetically and taxonomically diverse neighborhood can provide a larger fungal species pool for any of the co-occurring tree species (Cheng & Yu, 2020; Mony et al., 2021).

Analyzing the same tree species' root fungal communities at different tree diversity levels led us to an intriguing finding. We observed the co-existence of AM and EcM mycorrhizal fungal communities within the roots of both EcM and AM tree species in multi-tree species mixtures. By contrast, as expected, these tree species hosted only their respective mycorrhizal partners (i.e. EMF on EcM plants & AMF on AM plants) in monospecific stands. However, despite the careful preparation of our root samples, there is still the possibility of contamination by, for example, spores or mycelia from the other mycorrhiza type. Nonetheless, our sequencing-based identification and its taxonomic resolution clearly demonstrate that the co-existence of AM and EcM fungi was almost totally absent in monospecific stands. While dual mycorrhiza formation in both EcM and AM plants has been reported in the literature (Teste et al., 2020; Heklau
et al., 2021), causal mechanisms are still poorly understood. Our results underline the importance of ecological interactions that might be precursory to evolutionary changes in plant traits (here, plant mycorrhizal status). Using populations of the same native plant species grown in prairies and postagricultural grasslands (Delavaux & Bever, 2022) provided evidence for the evolution of differential growth responses to different AMF taxa and shifts in their co-evolutionary trajectories. Furthermore, the capacity for facultative biotrophy was reported for saprotrophs when they developed EcM-like structures such as mantle and Hartig net while colonizing the conifer seedling roots *in vitro* (Smith et al., 2017). These observations suggest that changes in ecological interactions, as brought about by mixing host trees, can induce rapid shifts in the co-evolutionary relationships between plants and their associated microbes. Collectively, our findings of the concurrent presence of AM and EcM fungi within the roots of tree species at high diversity levels indicate the possibility for dual mycorrhiza formation. However, proving this phenomenon requires verification through detailed microscopic observations and molecular analyses, as exemplified by Heklau et al. (2021).

## Differential contribution of biotic and abiotic factors in driving the assembly of root-associated fungal communities

We hypothesized (H3) that the contribution of soil, spatial, topographic, and tree community variables differ in explaining the variation in root-associated fungal community composition of AM trees and EcM tree species. We found confirmation from soil variables as they explained more variation in root-associated fungal communities of EcM than that of AM tree species. This observation is also in agreement with previous research demonstrating the importance of soil chemistry structure for EcM assemblages (Nguyen et al., 2020). Tree community variables are one of the top drivers of the root-associated fungal communities across the different tree mycorrhizal types, indicating the strength of the co-evolutionary relationships between fungi and their hosts. Concordant with our results, the importance of plant-related variables such as functional traits, phylogeny, and neighborhood in shaping the root-associated fungal communities has been emphasized before (Wang et al., 2019; Cheng & Yu, 2020; Zhu et al., 2022). An even more important predictor for structuring the root-inhabiting fungal communities was spatial distance, which confirms findings from other studies (Toju et al., 2014; Horn et al., 2017; Koyama et al., 2019). However, there was only a very small amount of jointly explained variance with tree mycorrhizal type, which shows the strengths of our experimental design that made sure that these factors were independent of each other. The high importance of spatial distance might be brought about by the fungal spore dispersal ability. Another explanation for the importance of space might be unmeasured variables in our study that were captured by space (Horn et al., 2014). All in all, our analyses highlighted the differential contribution of biotic and abiotic factors in driving the assembly of root-associated fungal communities of EcM and AM tree species,

suggesting the importance of understanding the underlying ecological and evolutionary relationships.

## Conclusions

Our experimental research has revealed the significant impact of tree mycorrhizal types, species identity, and diversity on the composition and diversity of forest root-associated mycobiomes. This study sheds light on the dynamics of root-associated fungal communities, highlighting how mycorrhizal types, tree species diversity, and environmental factors interact to shape these communities. A key finding is the presence of dual mycorrhizal fungal communities in mixed tree species environments, illustrating the potential for such ecological interactions to drive evolutionary changes in plant-fungal relationships. This suggests that planting trees with different mycorrhizal fungal partners can enhance root-associated fungal diversity, offering ecological benefits. These insights advance our understanding of the factors influencing root-associated mycobiome diversity and co-existence, crucial for both ecological theory and practical applications in forest management activities such as afforestation and reforestation.

## Acknowledgements

We are grateful for the funding from the Deutsche Forschungs-gemeinschaft (DFG, German Research Foundation) – 319936945/GRK2324 and the University of Chinese Academy of Science (UCAS) to the International Research Training Group TreeDì. We thank the support of the TreeDì coordinators and members of the research group. Special thanks to the local helpers involved in the field sampling campaign. In addition, BS, TW, HB, RB, SC, and NE acknowledge the support of the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, funded by the German Research Foundation (FZT 118). We also thank the editor and reviewers for their constructive feedback, which helped us improve the manuscript. Open Access funding enabled and organized by Projekt DEAL.

## Competing interests

None declared.

## Author contributions

TW, HB and BS contributed to the conceptualization. TW, HB, SC and NE secured relevant funds. TW, SC, NE, KX and YW provided the laboratory facilities. BS, FD and RB contributed to the field sampling. FD, BS, AN, RB and JD generated the data. TW and BS contributed to the bioinformatic analysis and data curation. TW, FD and BS contributed to the statistical analysis and visualization. BS and HuH contributed to the writing of the original manuscript draft and are joint first authors for this work. TW, HB, RB, SC, NE, AN, JD, KX, YW, HuH and BS contributed to the review and editing of the manuscript. TW contributed to the project administration and supervision. All authors have read and agreed to this version of the manuscript.
ORCID

Rémy Beugnon ID https://orcid.org/0000-0003-2457-5688

Helge Bruelheide ID https://orcid.org/0000-0003-3135-0356

Simone Cesarz ID https://orcid.org/0000-0003-2334-5119

Friedrich Darnstaedt ID https://orcid.org/0009-0000-3602-7975

Jianqing Du ID https://orcid.org/0000-0003-2841-7679

Nico Eisenhauer ID https://orcid.org/0000-0002-0371-6720

Ali Nawaz ID https://orcid.org/0000-0002-4413-6685

Bala Singavarapu ID https://orcid.org/0000-0002-0147-895X

Hafeez ul Haq ID https://orcid.org/0000-0001-9331-4700

Yanfen Wang ID https://orcid.org/0000-0001-5666-9289

Tesfaye Wubet ID https://orcid.org/0000-0001-8572-4486

Kai Xue ID https://orcid.org/0000-0002-5990-4448

Data availability

The datasets generated for this study can be found in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) under bioproject no.: PRJNA993998.

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## Supporting Information

Additional Supporting Information may be found online in the Supporting Information section at the end of the article.

**Dataset S1** Information of tree species, TSPs, plot, and tree species composition.
**Fig. S1** Study site, design, and sampling strategy.

**Fig. S2** Fungal richness across the tree diversity levels.

**Fig. S3** Fungal Shannon diversity across the tree diversity levels.

**Table S1** List of Tree species and their mycorrhizal types.

**Table S2** Two-way-ANOVA on fungal richness and diversity.

**Table S3** Alpha diversity at genus, species, and ASV levels.

**Table S4** Community compositional variations at genus, species, and ASV levels.

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