Fig. 5 Redundancy analyses (RDA) using pooling data of bacterial (a) and fungal (b) community and abiotic variables (arrows). The values of Axes 1 and 2 are percentages that the corresponding axis can explain.
Redundancy analysis (RDA) and Monte Carlo permutation test were used to provide a statistical analysis of the microbial community response to changes in different forest ages (p < 0.01) (Fig. 5). According to the RDA results the first two axes explained 52.12% of the total variation in the soil bacterial community (RDA1, 40.89%; RDA2, 11.23%), and HIX, FI, SOC, and SWC were the main factors influencing the structure of the soil bacterial community. The structure of bacteria was significantly correlated with soil FI index (p < 0.01) in 10 years plantations, but was more strongly associated with NO3- and FI index (p< 0.05) in 30 years plantations, then SWC and NH4+ (p < 0.01) had the greatest effect on bacterial community structure in 50 years plantations.
Differences in fungal community composition were mainly determined by SWC (p < 0.01), HIX (p < 0.01), and FI (p < 0.05), with HIX and FI indexes influencing the distribution of fungal communities in 10 years plantations and SWC and NH4+ (p < 0.01) having a greater impact on fungal diversity in 50 years plantations. The first two axes explained 23.7% of the total variation in the soil fungal community (RDA1, 13.34%; RDA2, 10.36%).
Table 2 Mantel tests and partial Mantel tests showing the relationships between dissimilarities of microbial community composition and individual environmental variables after controlling the potential effect of age stand. Mantel statistic r and associated p were determined by partial Mantel tests based on Spearman’s correlation with 9999 permutations