文章基本信息

标题：Agricultural management explains historic changes in regional soil carbon stocks
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作者：Bas van Wesemael ; Keith Paustian ; Jeroen Meersmans 等
期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2010
卷号：107
期号：33
页码：14926-14930
DOI：10.1073/pnas.1002592107
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：Agriculture is considered to be among the economic sectors having the greatest greenhouse gas mitigation potential, largely via soil organic carbon (SOC) sequestration. However, it remains a challenge to accurately quantify SOC stock changes at regional to national scales. SOC stock changes resulting from SOC inventory systems are only available for a few countries and the trends vary widely between studies. Process-based models can provide insight in the drivers of SOC changes, but accurate input data are currently not available at these spatial scales. Here we use measurements from a soil inventory dating from the 1960s and resampled in 2006 covering the major soil types and agricultural regions in Belgium together with region-specific land use and management data and a process-based model. The largest decreases in SOC stocks occurred in poorly drained grassland soils (clays and floodplain soils), consistent with drainage improvements since 1960. Large increases in SOC in well drained grassland soils appear to be a legacy effect of widespread conversion of cropland to grassland before 1960. SOC in cropland increased only in sandy lowland soils, driven by increasing manure additions. Modeled land use and management impacts accounted for more than 70% of the variation in observed SOC changes, and no bias could be demonstrated. There was no significant effect of climate trends since 1960 on observed SOC changes. SOC monitoring networks are being established in many countries. Our results demonstrate that detailed and long-term land management data are crucial to explain the observed SOC changes for such networks.
关键词：regional inventories ; soil organic carbon dynamics modeling ; land use history