DOI: 10.3390/f17101140 ISSN: 1999-4907

Soil C:N Stoichiometry and pH Are Associated with PLFA-Based Microbial Community Structure Across Forest Types

Mengjun Hu, Mingxing Zhong, Dong Wang, Bin Hu, Tengxu Zhang, Zhenxing Zhou

Forest types are associated with differences in soil properties and microbial communities, but the environmental correlates of microbial variation across soil depths remain poorly resolved. We examined whether PLFA-derived microbial community structure was more closely associated with bulk soil carbon (C) concentrations or with variation in soil C stoichiometry across five representative subtropical forest types in central China. Soil physicochemical properties and phospholipid fatty acid (PLFA) profiles were assessed in surface (0–10 cm) and subsurface (10–30 cm) soils. Forest types were associated with differences in soil moisture, pH, inorganic nitrogen, available phosphorus, total C (TC), total N (TN), and C ratio, accompanied by distinct patterns of PLFA-derived microbial characteristics. Oak forest had the highest TC and TN concentrations but the lowest total PLFA abundance, whereas dawn redwood forest had relatively high microbial biomass despite comparatively low TC and TN concentrations. RDA showed that soil C ratio was the strongest environmental variable associated with PLFA-based microbial community variation in both soil layers, followed by pH and NO3−, while SWC showed an additional association in the surface soil. At the microbial-group level, soil C ratio was negatively associated with bacterial and actinomycete biomarkers, whereas soil pH showed positive associations with fungal and arbuscular mycorrhizal fungal PLFAs. These results indicate that variation in PLFA-derived microbial characteristics among the sampled forest types was more closely associated with bulk soil C stoichiometry and other soil environmental conditions than with TC concentration alone. Overall, bulk soil C stoichiometry provides an informative correlate of below-ground microbial variation across the sampled forest types, although these associations do not establish causal effects of forest type.