Abstract

Exploring the resource limitation of soil microbial metabolism is essential to understand ecosystem functions and processes. However, the spatially divergent patterns and drivers of soil microbial nutrient limitation cha-racteristics in montane ecosystems at small scales, especially at the slope aspect scale, are still unclear. In this study, we measured soil enzyme activities involved in carbon (C), nitrogen (N) and phosphorus (P) cycle and quantified the microbial nutrient limitations by enzyme stoichiometry in two representative mountain sites in subalpine region of western Sichuan, including the sunny and shady slopes with different vegetation types (shrubland and forest, respectively) in Miyaluo of Lixian County, and with the same vegetation type (shrubland) in Yakexia of Heishui County. The results showed that soil enzyme activities and their stoichiometric ratios were significantly different between slope aspects in Miyaluo, while the differences were not significant in Yakexia. The stoichiometry ratio of C-, N- and P-acquiring enzymes on the sunny slope of Miyaluo was 1:0.96:0.92, approaching the 1:1:1 ratio at the global scale, but deviated from 1:1:1 on the shady slope of Miyaluo (1:1.39:0.75) and the different slopes of Yakexia (1:1.09:1.35). There was no significant difference in vector length between slope aspects at both sites, indicating no significant effect of slope aspect on the microbial C limitation. The vector angle was significantly higher on the sunny slope (43.6°) than that on the shady slope (28.7°) in Miyaluo, suggesting that the microorganisms were mainly N-limited. Partial least squares path model showed that the vector angle was mainly directly influenced by the soil nutrient ratios. The vector angle ranged from 50.3° to 51.4°, and did not differ between slope aspects in Yakexia. Therefore, differences in vegetation types between slope aspects drove variations in soil enzyme activity and microbial nutrient limitation through soil properties. It would provide a scientific basis for predicting the spatial pattern of soil enzyme activity and microbial nutrient limitation.

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