The resilience of soil erosion rates under historical land use change in agroecosystems of Southern Spain

SCIENCE OF THE TOTAL ENVIRONMENT(2022)

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摘要
Land use change (LUC) is identified as one of the main drivers of soil erosion in the Mediterranean. However, very little information exists regarding the relationship between land use and erosion over longer time periods and on regional scales. We quantified the LUC in Southern Spain between 1956 and 2018, examining its effect on soil erosion and assessing the mitigation role of the permanent grassland (PG). The land use influence on erosion is represented by the RUSLE's C-factor, which was modelled using the Monte Carlo Method (MCM) based on historical LUC. Moreover, future LUC scenarios by 2038 were developed by binary logistic model (scFS) and by a complete conversion of PG to cropland (scPC), permanent crop (scPP) and forest and natural (scFP). Historically, Southern Spain has experienced an impressive intensification of its agricultural system. While soil loss variation is noted within the classes, no big variation is observed in cumulative erosion on a regional scale. The underlying reasons for this resilience are multifold, but mainly attributed to the fact that a small fraction of the total surface (20%), dominates total erosion (67%). The Cfactor decrease in this area displays a LUC towards forest and natural area, suggesting an agriculture abandonment. On the other hand, the agricultural intensification that has taken place in the remainder of the area, contributes much less to overall soil erosion. Future LUC scenarios illustrate the importance of PG for erosion mitigation. scFS scenario does not project major changes. However, scCP and scPP, show an abrupt increase in regional erosion by 13% and 14%, while scFP shows a negligible reduction of erosion close to 0%. This allows to quantify the erosion mitigation offered by maintaining the PG and should be taken into account for future agricultural policy.
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关键词
Erosion, Land use, Permanent grassland, Remote sensing, Historical erosion
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