Abstract

The dynamics of agricultural soil organic carbon storage have been considerably influenced by the evolution of crop species, offering promising opportunities for restoring soil organic carbon under elevated temperatures through yield improvements. However, the intricate interplay between climate change and surface erosion processes poses challenges in understanding agricultural soil carbon dynamics in hilly landscapes. This study aimed to address these challenges by assessing the effects of climate change on soil organic carbon dynamics under the Shared Socioeconomic Pathways 245 and 585. We utilized projections from 12 distinct global climate models, covering the period from 2015 to 2100. Additionally, we investigated the potential for improving soybean yields by 100 %, 200 %, and 300 % linearly by 2100 to offset the anticipated soil organic carbon losses. Using a coupled landscape and biogeochemical model, our analysis focused on a soybean field in Nenjiang County, China. Our findings revealed a distinct soil organic carbon profile in deposition areas, characterized by relatively low levels of soil organic carbon in surface layers, attributed to carbon influx from adjacent erosion areas with typically low carbon content. We modeled decreases in soil CO2 fluxes with escalating climate change, corresponding to expected decreases in soil organic carbon levels, despite concurrent rises in soil microbial activity linked to increasing temperatures. Erosion areas emerged as particularly vulnerable zones under elevated temperatures due to their higher proportion of soil CO2 fluxes relative to soil organic carbon levels compared to deposition areas. As a soil organic carbon restoration strategy, improvements in soybean yields showed promise in mitigating soil organic carbon losses through enhanced litter inputs and the cooling effects induced by shading the soil. This study underscored the potential for achieving the dual benefits of food security and soil organic carbon restoration in the coming decades through a unified approach to enhancing soybean yields.

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