Molecular Diversity of Ectomycorrhizal Fungi in Relation to the Diversity of Neighboring Plant Species

Abstract

(1) Background: Plant diversity has long been assumed to predict soil microbial diversity. The mutualistic symbiosis between forest trees and ectomycorrhizal (EM) fungi favors strong correlations of EM fungal diversity with host density in terrestrial ecosystems. Nevertheless, in contrast with host tree effects, neighboring plant effects are less well studied. (2) Methods: In the study presented herein, we examined the α-diversity, community composition, and co-occurrence patterns of EM fungi in Quercus acutissima across different forest types (pure forests, mixed forests with Pinus tabuliformis, and mixed forests with other broadleaved species) to ascertain how the EM fungi of focal trees are related to their neighboring plants and to identify the underlying mechanisms that contribute to this relationship. (3) Results: The EM fungal community exhibited an overall modest but positive correlation with neighboring plant richness, with the associations being more pronounced in mixed forests. This neighboring effect was mediated by altered abiotic (i.e., SOC, TN, LC, and LP) and biotic (i.e., bacterial community) factors in rhizosphere soil. Further analysis revealed that Tomentella_badia, Tomentella_galzinii, and Sebacina_incrustans exhibited the most significant correlations with plant and EM fungal diversity. These keystone taxa featured low relative abundance and clear habitat preferences and shared similar physiological traits that promote nutrient uptake through contact, short-distance and medium-distance smooth contact-based exploration types, thereby enhancing the potential correlations between EM fungi and the neighboring plant community. (4) Conclusions: Our findings contribute to the comprehension of the effect of neighboring plants on the EM fungal community of focal trees of different forest communities and the biodiversity sensitivity to environmental change.

Keywords: bacterial community; ectomycorrhizal fungi; natural secondary forests; neighboring effects; plant diversity.

Figure 1

Responses of EM fungal α-diversity (a), β- diversity (b), and network topological parameters (c) to forest types. Response ratios calculated by differences between the variable value in pure forests and those in mixed forests, presented as the means (±SE) of six replicate samples. Statistical significance denoted as * p < 0.05, ** p < 0.01. (d) Visualization of the EM fungal networks for each forest type. Nodes in the constructed network denote individual ASVs colored by genus. Edges represent robust and significant correlations (Spearman’s r > 0.6, p < 0.001), divided into positive (green) or negative (orange) edges. QBF, mixed forest of Q. acutissima with broad-leaved tree species; QPF, mixed forest of Q. acutissima with P. tabulaeformis.

Figure 2

Relationships between neighboring plant diversity and diversity of EM fungal (a) Shannon index, (b) Simpson index, (c) community dissimilarity values and (d) community dissimilarity values. The fitted linear models are shown as solid lines, with shading representing 95% confidence intervals. QBF, mixed forest of Q. acutissima with broad-leaved tree species; QPF, mixed forest of Q. acutissima with P. tabulaeformis; PF, pure forest of Q. acutissima.

Figure 3

Contributions of biotic and abiotic variables to plant–EM fungal diversity relationships based on the random forest model. Abiotic factors included soil organic C, soil total N, litter organic C, and litter total P. Biotic factors were the topological properties of soil bacterial and cross-kingdom species associations including average distance, eigenvector centrality, and node assortativity coefficients. Significance of the random forest models labelled as * p < 0.05, ** p < 0.01.

Figure 4

PLS-PM analysis disentangling the mediation effects of abiotic and biotic factors on plant–EM fungal diversity relationships. Solid arrows denote significant relationships, blue arrows signify positive relationships, and brown arrows indicate negative relationships. The numbers are the path coefficients that correspond to the direct effects. R² indicates the proportion of variance explained by the variables. GoF represents the proportion of variance accounted for by the model. Plant diversity is community richness including trees, shrubs, and herbs. EM diversity includes α (Richness, Shannon, Simpson, ACE, and Chao1), β (the first two principal co-ordinate components of the Bray–Curtis matrix), and microbial network topology (node number, edge number, betweenness centrality, and multi-complexity index). Significance of the path coefficient denoted with * p < 0.05, ** p < 0.01, and *** p < 0.001.

Figure 5

The keystone EM fungal taxa significantly associated with neighboring plant and EM fungal community diversity. (a) Zi (within-module connectivity)–Pi (among-module connectivity) plots to identify keystone ASVs within the EM fungal networks. (b) Phylogenetic distributions for the keystone taxa. The phylogenetic tree was constructed using the neighbor-joining method. The heatmap of the correlations between keystone ASVs’ abundance and EM fungal diversity, and the bar plot shows the correlations between keystone ASVs and neighboring plant diversity. Values show Spearman’s coefficient and significance levels denoted with * p < 0.05, ** p < 0.01.