Relationship between soil microbial communities and nutrient
parameters
The results of the Mantel test based on Spearman’s rank correlation
revealed that the diversity of bacterial communities in invaded plots
along the altitudinal gradient were influenced by all the environmental
variables (p <0.05) except SAL, Zn and Temp
(p >0.05), whereas in uninvaded plots only three
parameters viz. SAL, Zn and Temp determine the bacterial community
diversity (p <0.05) (Table 2). The most influential
variable explaining community composition is TOC (rho =0.97,p < 0.001) in invaded plots and SAL in uninvaded plots
(rho = - 0.81, p < 0.001) (Table 2).
Similarly, the fungal community composition in invaded plots was
influenced by all the environmental variables except SAL and Zn
(p > 0.05), whereas in uninvaded plots EC, K, Zn,
Temp and Alt did not show any significant correlation (p> 0.05). WC in invaded plots (rho = 0.92, p< 0.001) and Mn in uninvaded plots (rho =0.93, p< 0.001) were most significantly correlated with fungal
community composition (Table 2).
Further, Canonical Correspondence analysis (CCA) was used to analyze the
relationship between microbial community structure and environmental
variables along the elevation gradient (Fig. 6). Based on Variance
Inflation Factors (VIF) values obtained, it was observed that among the
15 environmental variables only five (pH, EC, K, Fe and temperature)
were more significant (p <0.001) in determining the
bacterial and fungal diversity among the plots along the altitudinal
gradient. All the five environmental variables were found to be
statistically significant based on Monte Carlo permutation F test
(Appendix S3: Table S4). Constrained inertia or variance explained by
the environmental variables in bacteria and fungi was found to be 1.039
and 1.605 respectively.
In bacteria, first two axes explained 70.9% of the variation (Axis
1~ 41.5% and Axis 2~ 29.4%). Axis 1
was positively related with pH and negatively associated with Fe. Axis 2
was positively correlated with EC and Temp and negatively correlated
with K. The relative abundance of bacteria at the KZ_IN and KD_IN were
related with pH and negatively associated with Fe. However, the
bacterial communities of uninvaded plots at KZ and TM showed a positive
relation with EC and Temp, whereas KD_UN were correlated with K. TM and
KU sites were positively related with Fe (Fig. 6a). In fungi, first two
axes explained 93.33%of variation (Axis 1~ 49.98% and
Axis 2~ 43.35%). Axis 1 was positively correlated with
EC and Temp and negatively associated with K. Axis 2 showed positive
relation with pH and negatively related to Fe. The relative abundance of
fungi in both plots at KZ site was correlated with EC and Temp, whereas
both plots of KD site along with KU_IN were associated with K. Both
plots of TM and KU_UN plot were positively related with Fe and
negatively associated with pH (Fig. 6b). Our results revealed that there
is a significant effect of soil physicochemical properties on the
bacterial and fungal community abundance along the altitudinal gradient.