Spatial estimation of soil carbon, nitrogen and phosphorus stoichiometry in complex terrains: a case study of Schrenk's spruce forest in the Tianshan Mountains

Abstract. Spatial patterns of soil carbon (C), nitrogen (N) and phosphorus (P) and their stoichiometric characteristics (C : N : P) play an important role in nutrient limitations, community dynamics, nutrient use efficiency and biogeochemical cycles, etc. To date, the spatial distributions of soil organic C at various spatial scales have been extensively studied, whereas little is known about the spatial patterns of N and P and C : N : P ratios in various landscapes, especially across complex terrains. To fill this gap, we estimated the spatial patterns of concentrations of C, N and P and C : N : P ratios in Schrenk's spruce (Picea schrenkiana) forest in the Tianshan Mountains using multiple linear regression (MLR) model based on data from soil profiles collected from 2012 to 2017. We found that (1) elevation and climatic variables jointly contributed to concentrations of C, N and P and C : N : P ratios, (2) soil concentrations and stoichiometric ratios demonstrated different but continual spatial patterns in Schrenk's spruce forest, and (3) MLR models could be reliably used to estimate the spatial patterns of soil elemental concentrations and stoichiometric ratios in mountainous terrain. We suggest that more independent variables (including biotic, abiotic and anthropogenic factors) should be considered in future works. Additionally, adjustment of MLR and other models should be used for a better delineation of spatial patterns in the concentrations of soil elements and stoichiometric ratios.