Factors controlling the variation in organic carbon stocks in agricultural soils of Germany
Tóm tắt
This study gives an overview of soil organic carbon (SOC) stocks in Germany's agricultural soils, and quantifies and explains the influence of explanatory variables such as land use and management, soil type and climate. Over 2500 agricultural sites were sampled and their SOC stocks determined, together with other soil properties. Machine‐learning algorithms were used to identify the most important variables. Land use, land‐use history, clay content and electrical conductivity were the main predictors in the topsoil, whereas bedrock material, relief and electrical conductivity governed the variation in subsoil carbon stocks. We found that 32% of all soil profiles were anthropogenically transformed. The influence of climate variables was surprisingly small, whereas site variables, in particular in the subsoil, explained a large proportion of the variation in soil carbon. The understanding of SOC dynamics at the regional scale requires a thorough description of the spatial variation in soil properties. The effect of agronomic management on SOC stocks was important near the soil surface, but was mainly attributable to land use (grassland or arable and not to other management factors.
Factors affecting spatial variation of soil organic carbon stocks are largely unknown. More than 200 possible predictors for this variation were assessed for over 2500 sites. Land use (history), texture, electrical conductivity, bedrock and relief were main controlling factors of carbon stock variation. Aggregation and carbon storage capacity of soil determine much of the spatial variation in carbon stocks.
Từ khóa
Tài liệu tham khảo
Greenwell B. Boehmke B. Cunningham J.& GBM Developers (2019).gbm: Generalized Boosted Regression Models. R package version 2.1.5. Retrieved fromhttps://CRAN.R-project.org/package=gbm.
IUSS Working Group WRB, 2006, World Reference Base for Soil Resources 2006
Liaw A., 2002, Classification and regression by random forest, R News, 2, 18
R Core Team, 2013, R: A Language and Environment for Statistical Computing
Sponagel H., 2005, Bodenkundliche Kartieranleitung (German Manual of Soil Mapping, KA5)
West T. O., 2001, Soil organic carbon sequestration rates by tillage and crop rotation, Soil Science Society of America Journal, 66, 1930, 10.2136/sssaj2002.1930