Abstract

Accurate identification of soil erosion hot spots across catchments of different sizes and agro-ecologies through the use of conventional tracing techniques has proven challenging. Since this problem hinders implementation of precise soil conservation measures by land managers and decision-making bodies, novel evidence-based techniques are needed. To meet this need, the International Atomic Energy Agency (IAEA, Vienna, Austria) initiated the Coordinated Research Project entitled “Integrated Isotopic Approaches for an Area-wide Precision Conservation to Control the Impacts of Agricultural Practices on Land Degradation and Soil Erosion – D1.20.11” in 2008. This project emphasized the application of isotopic approaches to identify hot spots of land degradation in agricultural catchments to develop effective soil conservation measures. As one key outcome of this project, we present here an aligned protocol to explore the potential of compound-specific stable isotope (CSSI) analysis of individual fatty acids (FA) combined with Bayesian statistics to discriminate sediment sources across six catchments of different sizes and agro-ecologies. The global applicability of the CSSI approach was first tested on the basis of major land use categories (i.e., forest, cultivated and non-cultivated land) as potential sediment sources in the studied catchments. These land use categories were then further resolved into specific land use types (e.g., cassava and maize fields, orchards) to assess the potential resolution threshold of the CSSI technique. In a final step, the influence of miscellaneous sources (e.g., roads, channel banks) that had the potential to distort proportional contributions to sediment deposition was assessed. The introduced aligned protocol of the CSSI technique was applied to discriminate individual erosion sources based on land use types of tested catchments. Merging catchment-specific land use types with broader land use categories made it possible to determine inter-catchment comparisons of isotopic signatures due to significant differences in δ13C values of fatty acids when cultivated land was present. Notably, no correlations were found between different catchment sizes, agro-ecologies, number and type of land use types, or soil organic carbon concentrations and the number of significant δ13C fatty acid values of the various land use types. Thus, we propose that the presented CSSI technique has the potential to identify soil erosion hot spots in contrasting catchments of different sizes and agro-ecologies.

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