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Updated: Sep 6, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
Integrating future grassland degradation risk to improve the spatial targeting efficiency of payment for ecosystem
Yanan Guo1, Ruonan Li2, Yanzheng Yang2
1State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Science, Beijing, 100085, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
Abstract:
Spatial targeting plays a key role in improving the efficiency of payment for ecosystem services (PES). However, the risk of grassland degradation after implementing PES increases uncertainty about the efficiency of PES. Here, we identified the spatial heterogeneity of grassland degradation risk using Future Land Use Simulation (FLUS) model, then incorporated grassland degradation risk as a criterion into PES spatial targeting using cost-benefit analysis and ranking optimization. The framework was applied to a case study of the Three-River-Source National Park, China. We found that grasslands in the study area continued to degrade between 2015 and 2025, and the area of degraded grasslands increased by 26%. Compared with spatial targeting of PES without considering grassland degradation risk, PES spatial targeting that considered grassland degradation risk was significantly different (the overlap area accounted for only 75%, 82%, and 94% of the PES area within 25%, 50%, and 75% of the total protection cost budget). When the grassland degradation risk was considered as a targeting criterion, PES efficiency increased by 154%, 116%, 124%, and 99%, respectively, within 25%, 50%, 75%, and 100% of the total protection cost budget. Our results demonstrate that considering grassland degradation risk in the spatial targeting of PES increases efficiency because it helps to target areas with greater environmental benefits.
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