Abstract

Soil available nutrient contents are critical for regulating ecosystem structure and function; therefore, exploring patterns, dynamics, and drivers of soil available nutrient contents is helpful for understanding the geochemical cycle at the regional scale. However, learning the patterns and dynamics of soil available nutrients across a regional scale is quite limited, especially the soil available nitrogen (SAN) and soil available phosphorus (SAP) in alpine grasslands. In this study, we used machine learning (Random Forest) to map the SAN and SAP at a soil depth of 0–30 cm in alpine grasslands across the QingZang Plateau (QZP) in 2015. Our results showed that the current (2015) contents of the SAN and SAP in alpine grasslands on the QZP were 139.96 mg kg−1 and 2.63 mg kg−1, respectively. Compared to the 1980s, the SAN significantly increased by 18.12 mg kg−1 (14.83%, p < 0.05) and the SAP decreased by 1.71 mg kg−1 (39.40%, p < 0.05). The SAN and SAP contents of alpine meadows were higher than those of alpine steppes. The increases in SAN were not significantly (p > 0.05) different between those two grassland types, while the decrease in SAP was significantly (p < 0.05) higher in alpine meadows than in alpine grasslands. Combined with redundancy analysis, we quantified the impact of environmental drivers, and 80% of the spatial variation in SAN and SAP could be explained by environmental factors. Our findings also highlighted that in the context of global change, the increase in SAP and decrease in SAP might lead to weakening of nitrogen limitation and intensification of phosphorus limitation, especially in alpine meadows. In general, this study expanded the knowledge about the patterns and dynamics of SAN and SAP, and deepened the understanding of the driving mechanisms, which provided a basis for sustainable management of grasslands and optimization of ecological security barrier functions on the QZP.

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