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