Soil organic carbon and nitrogen (SOC-N) dynamics are indicative of the human-induced disturbances of the terrestrial ecosystems the quantification of which provides insights into interactions among drivers, pressures, states, impacts, and responses in a changing environment. In this study, a process-based model was developed to simulate the eight monthly outputs of net primary productivity (NPP), SOC-N pools, soil C:N ratio, soil respiration, total N emission, and sediment C-N transport effluxes for cropland, grassland, and forest on a hectare basis. The interaction effect of the climate change drivers of aridity, CO2 fertilization, land-use and land-cover change, and best management practices was simulated on high altitude ecosystems from 2018 to 2070. The best management practices were developed into a spatiotemporally composite index based on SOC-N stock saturation, 4/1000 initiative, and RUCLE-C factor. Our model predictions differed from the remotely sensed data in the range of - 64% (underestimation) for the cropland NPP to 142% (overestimation) for the grassland SOC pool as well as from the global mean values in the range of - 97% for the sediment C and N effluxes to 60% for the total N emission from the grassland. The interaction exerted the greatest negative impact on the monthly sediment N efflux, total N emission, and soil respiration from forest by - 90.5, - 82.7, and - 80.3% and the greatest positive impact on the monthly sediment C effluxes from cropland, grassland, and forest by 139.3, 137.1, and 133.3%, respectively, relative to the currently prevailing conditions.
Keywords: Best management practices; Carbon and nitrogen cycles; Ecosystem biogeochemistry; STELLA model simulation.