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Quantifying changes in soil organic carbon density from 1982 to 2020 in Chinese grasslands using a random forest model. | LitMetric

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Article Abstract

China has the second-largest grassland area in the world. Soil organic carbon storage (SOCS) in grasslands plays a critical role in maintaining carbon balance and mitigating climate change, both nationally and globally. Soil organic carbon density (SOCD) is an important indicator of SOCS. Exploring the spatiotemporal dynamics of SOCD enables policymakers to develop strategies to reduce carbon emissions, thus meeting the goals of "emission peak" in 2030 and "carbon neutrality" in 2060 proposed by the Chinese government. The objective of this study was to quantify the dynamics of SOCD (0-100 cm) in Chinese grasslands from 1982 to 2020 and identify the dominant drivers of SOCD change using a random forest model. The results showed that the mean SOCD in Chinese grasslands was 7.791 kg C m in 1982 and 8.525 kg C m in 2020, with a net increase of 0.734 kg C m across China. The areas with increased SOCD were mainly distributed in the southern (0.411 kg C m), northwestern (1.439 kg C m), and Qinghai-Tibetan (0.915 kg C m) regions, while those with decreased SOCD were mainly found in the northern (0.172 kg C m) region. Temperature, normalized difference vegetation index, elevation, and wind speed were the dominant factors driving grassland SOCD change, explaining 73.23% of total variation in SOCD. During the study period, grassland SOCS increased in the northwestern region but decreased in the other three regions. Overall, SOCS of Chinese grasslands in 2020 was 22.623 Pg, with a net decrease of 1.158 Pg since 1982. Over the past few decades, the reduction in SOCS caused by grassland degradation may have contributed to soil organic carbon loss and created a negative impact on climate. The results highlight the urgency of strengthening soil carbon management in these grasslands and improving SOCS towards a positive climate impact.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10316965PMC
http://dx.doi.org/10.3389/fpls.2023.1076902DOI Listing

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