Abstract
The ecological productivity of the Robinia pseudoacacia L. (RP) widely cultivated on the Loess hilly region has been widely questioned with its aging. Soil microbial biomass (SMB) plays a key role in soil nutrient dynamics and productivity of the ecosystems. Understanding the main ecological drivers of SMB is supposed to be of importance for ecosystem functioning of RP in the Loess hilly region. In this study, we identified the most influential factors affecting SMB at 2 layers (0–10 cm and 10–30 cm) using forward selection in terms of plant characteristics (forest age, tree height, diameter at breast height, tree canopy, crown base height, herb height, herb number, herb coverage, herb ground diameter and herb diversity), soil physiochemical characteristics (soil bulk density, pH, water content, soil organ carbon, soil total and available nutrient content) and topographical properties (elevation, aspect and slope). We also analyzed individual and interactive effects (plant–soil, plant–topography, soil–topography, plant–soil–topography) using general linear model (GLM) analysis. Among all plant variables, tree canopy and understory richness had the greatest impact on SMB. The soil variables with the greatest impact on SMB were bulk density and available phosphorus. Elevation was the most important topographic factor affecting SMB. When we considered the interactive effects among plant, soil physicochemical and topographical variables on SMB, a significant interaction effect occurred at a depth of 10–30 cm soil layer. We concluded that individual effects of abiotic and biotic factors significantly affect SMB at 0–10 cm, while the interaction of these factors mainly played roles at 10–30 cm. These results provide a basis for maintaining soil health and productivity using efficient SMB by providing suitable abiotic and biotic habitats.
Highlights
IntroductionBelowground soil microbes are important for forest ecosystem sustainability and functioning [1,2]
The reduced models for soil microbial biomass (SMB) containing the most significant variables at different soil depth were constructed by forward selection
These models were acceptable because: (1) these models contain the least amount of explanatory variables, but the R2 is equal to R2 of the model containing all explanatory variables, indicating that the quality of the model can be improved by reducing the explanatory variables; (2) the variance inflation factor (VIF) value of each explanatory variable in the reduced model is less than 10, indicating that there is no significant collinearity between the explanatory variables
Summary
Belowground soil microbes are important for forest ecosystem sustainability and functioning [1,2]. They take parts in carbon and nutrient turnover, nutrient mobilization/immobilization, humification, and maintenance of the soil structure [3,4,5]. Among the various microbial characteristics, soil microbial biomass (SMB) is regarded as the most satisfactory index to estimate ecosystem productivity [6,7], which is the major reservoir of available nutrients [8] and the balance between the release and sequestration of soil carbon [9]. Identifying the main drivers of SMB is important to better understand the function of soil microorganisms in regulating ecosystem structure, process and functioning
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