地形
土壤碳
比例(比率)
环境科学
固碳
空间生态学
植被(病理学)
环境资源管理
自然地理学
分布(数学)
气候变化
气候学
地理
地图学
土壤科学
生态学
地质学
土壤水分
数学
海洋学
数学分析
医学
病理
二氧化碳
生物
作者
Tianhong Tan,Giulio Genova,G.B.M. Heuvelink,Johannes Lehmann,Laura Poggio,Dominic Woolf,Fengqi You
标识
DOI:10.1021/acs.est.4c01172
摘要
Soil organic carbon (SOC) plays a vital role in global carbon cycling and sequestration, underpinning the need for a comprehensive understanding of its distribution and controls. This study explores the importance of various covariates on SOC spatial distribution at both local (up to 1.25 km) and continental (USA) scales using a deep learning approach. Our findings highlight the significant role of terrain attributes in predicting SOC concentration distribution with terrain, contributing approximately one-third of the overall prediction at the local scale. At the continental scale, climate is only 1.2 times more important than terrain in predicting SOC distribution, whereas at the local scale, the structural pattern of terrain is 14 and 2 times more important than climate and vegetation, respectively. We underscore that terrain attributes, while being integral to the SOC distribution at all scales, are stronger predictors at the local scale with explicit spatial arrangement information. While this observational study does not assess causal mechanisms, our analysis nonetheless presents a nuanced perspective about SOC spatial distribution, which suggests disparate predictors of SOC at local and continental scales. The insights gained from this study have implications for improved SOC mapping, decision support tools, and land management strategies, aiding in the development of effective carbon sequestration initiatives and enhancing climate mitigation efforts.
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