Data analysis
To evaluate the differences in land-use type among groups, land-use data
were visualized by principal coordinates analysis (PCoA) based on
Bray-Curtis distances. Pearson’s
correlation coefficients were used to evaluate the impacts of different
land-use types on the environmental factors. Both analyses were
performed using the “vegan ” package in R software (versions
4.1.2) (R Core Team, 2021).
Microbial alpha diversity was calculated using the “vegan ”
package in R software (versions
4.1.2) (R Core Team, 2021). The phylogenetic tree was constructed using
the unweighted pair group method with arithmetic mean (UPGMA) based on
Bray-Curtis distances with the “ggtree ” package in R software
(versions 4.1.2) (R Core Team, 2021) and visualized with iTOL(versions
6) (https://itol.embl.de). Microbial community composition was
visualized using the nonmetric multidimensional scaling ordination
(NMDS) method based on Bray-Curtis dissimilarities. Analysis of
Similarities (ANOSIM) was used to evaluate the degree of separation in
microbial communities between groups. Furthermore, a regression analysis
was used to determine the Bray-Curtis dissimilarity of microbial
communities between sample pairs; subsequently, the environmental
factors and land-use types were plotted against the community
dissimilarity. The impacts of land-use type and environmental factors on
the Bray-Curtis dissimilarity were evaluated using the Mantel’s test and
Pearson’s rank correlation.
Microbial functional groups were
predicted using the FAPROTAX
database (Louca et al., 2016), which is suitable for functional
annotation prediction of biogeochemical cycle processes (especially the
carbon [C], hydrogen [H2], N, P, sulfur [S]
cycles, and other element cycles) in environmental samples (e.g., oceans
and lakes). The FAPROTAX database was established based on published and
validated literature (Sansupa et al., 2021). The relative abundances of
predicted functional groups were subjected to heatmap analysis using the
“pheatmap ” package in R software (versions 4.1.2) (R Core Team,
2021). To assess the impacts of environmental factors and land-use types
on microbial functional groups, the heatmap and Pearson’s rank
correlation were visualized based on Bray-Curtis dissimilarities. Linear
discriminant analysis (LDA) effect size (LEFSe) analysis was conducted
on the functional groups to identify biomarkers of anthropogenic
disturbance.