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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
[Spatio-temporal Simulation of Ecosystem Services, Trade-offs, and Synergies in Jiangxi Province Based on the SD-PLUS
Zhu-An Chen1,2,3,4, Ya-Si Chen1,4, Zi-Qiang Liu5
1School of Geomatics and Spatial Information Engineering, Donghua University of Technology, Nanchang 330013, China.
Abstract:
Ecosystem services (ESs) are fundamental to human well-being. Understanding the spatial and temporal impacts of their trade-offs and synergies, driven by land use and climate change, is essential for ecosystem conservation and sustainable development. This study uses the SSP-RCP scenarios of CMIP6 to couple the system dynamics (SD) model with the patch generation land use (PLUS) model, predicting land use patterns in Jiangxi Province in 2035 under the SSP245, SSP585, and SSP126 scenarios. The ecosystem services evaluation tool (InVEST) is then employed to quantify changes in carbon stock, habitat quality, soil retention, and water yield dynamics, as well as their interactions. The results indicate that from 2000 to 2020, Jiangxi Province experienced a decline in carbon stock by 0.255×108 t, habitat quality by 0.018, soil retention by 0.516×108 t, and water yield by 0.140 ×1010 m3. Under the SSP245 scenario, carbon stock, habitat quality, and soil retention are projected to decline, while water yield increases. In the SSP585 scenario, significant decreases were observed in carbon stock, habitat quality, and soil retention. Conversely, the SSP126 scenario projected increases in carbon stock and water yield. Overall, habitat quality and water yield exhibited trade-offs, whereas other ecosystem services demonstrated synergistic relationships. This study offers a scientific reference for exploring the complex mechanisms underlying ecosystem service interactions and optimizing their management. It further supports ecological conservation and sustainable development efforts in Jiangxi Province.
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