The forest age classes, though some basidiomycetous ECM fungi have been found only inside the young or shared involving the medium along with the old forest age classes (Table S3).Relationships among Fungal Communities and Environmental VariablesNMDS evaluation followed by environmental variable fitting to assess the relationship of individual variables for the ordination plotFungal Community within a Chinese Subtropical ForestPLOS 1 | plosone.orgFungal Community within a Chinese Subtropical ForestFigure two. Distribution of observed richness of ECM fungal communities in the loved ones (a) and OTU amount of the most abundant ECM fungal family members Russulaceae (b) across the three forest age classes visualized by heatmap. doi:ten.1371/journal.pone.0066829.gFigure 3. Non-metric multidimensional scaling (NMDS) ordination in the study plots across three forest age classes (Y: Young, M: Medium, O: Old) depending on fungal communities of (a) kingdom fungi and (b) ectomycorrhizal fungi. In each diagram, soil and plant qualities that showed a significant goodness of match depending on post-hoc correlations (P#0.05) are represented as vectors. Stress values represent percentages. doi:ten.1371/journal.pone.0066829.gPLOS A single | plosone.orgFungal Community in a Chinese Subtropical ForestTable 2. Goodness of fit statistics or squared coefficients of environmental variables fitted for the Nonmetric Multi-dimensional Scaling (NMDS) ordination space of fungal, Ascomycota, Basidiomycota, and ECM fungal communities.Environmental variables Forest age Elevation (m) Herb layer cover ( ) Tree layer cover ( ) Deadwood cover ( ) Bare soil cover ( ) Rock cover ( ) Litter layer (thickness, cm) Herb species richness Tree species richness Herbaceous biomass (g) Woody plant biomass (,1 m) (g) Litter biomass (dry weight, g) Sand ( ) Clay ( ) Soil organic carbon ( ) C/N pHKClFungi 0.378* 0.188 0.052 0.487* 0.123 0.083 0.637* 0.613* 0.209 0.418 0.025 0.685** 0.159 0.741** 0.154 0.841*** 0.382 0.Ascomycota 0.043 0.042 0.004 0.063 0.006 0.244 0.621* 0.312 0.127 0.693** 0.137 0.089 0.055 0.730** 0.566* 0.638** 0.429 0.Basidiomycota 0.626** 0.749** 0.266 0.745** 0.686** 0.242 0.133 0.4-(Dimethylamino)but-2-ynoic acid Purity 288 0.Quinuclidine Chemical name 484 0.PMID:23962101 189 0.374 0.630* 0.103 0.091 0.171 0.184 0.035 0.ECM fungi 0.427* 0.250 0.238 0.651** 0.509* 0.087 0.337 0.494* 0.071 0.307 0.368 0.708** 0.094 0.386 0.405 0.506 0.031 0.*P,0.05, **P,0.01, ***P,0.001, Fungi = Kingdom Fungi. Substantial correlations (Bonferroni corrected P,0.05) are presented in bold. doi:ten.1371/journal.pone.0066829.tindicated that the fungal neighborhood composition was considerably related to forest age and to plant and soil parameters (Table 2, Fig. 3a). In contrast towards the ascomycetous communities the basidiomycetous and ECM fungal community ordinations were influenced by forest age and plant parameters (Table two, Fig. 3b). The dbRDA based model selection, even so, indicated SOC and elevation to be by far the most essential variables shaping the fungal community composition (F = 1.63, P,0.01) (Table 3). Marginal tests also showed that SOC and elevation have been considerably related to the fungal community composition (SOC – F = 1.84, P,0.01; elevation – F = 1.42, P,0.05). We also found a significantinteraction of forest age with SOC and elevation within the fungal (adonis F = 1.37, P,0.05) and ascomycetous (adonis F = two.01, P = 0.002) communities (Table three). These outcomes indicated the role of a particular or particular group of environmental drivers that shape the diversity and composition of fungal communities.Connection be.