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Updated: Sep 26, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
Coordinated management of ecosystem service Supply-Demand and trade-offs based on nonlinear responses across multiple
Changyan Yin1, Weixiang Cai2, Chenyun Bai2
1College of Natural Resources and Environment, Northwest A&F University, Yangling, Shaanxi, 712100, China; State Key Laboratory of Soil and Water Conservation and Desertification Control, College of Soil and Water Conservation Science and Engineering (Institute of Soil and Water Conservation), Northwest A&F University, Yangling, Shaanxi, 712100, China.
Abstract:
Ecosystem service (ES) supply-demand balance is essential for regional sustainability, yet simultaneously optimizing multiple ESs remains challenging due to inherent trade-offs. This study investigates ES supply-demand patterns, trade-offs and synergies across multiple scales in the Loess Plateau (LP) in 2020, employing Generalized Additive Models (GAMs) to quantify nonlinear responses and identify model-derived breakpoints of socio-ecological drivers affecting both the overall ES supply-demand ratio (CESDR) and trade-offs (EStrade-off). Results showed that CESDR and EStrade-off exhibited a southeast-northwest gradient, with surplus and synergistic areas concentrated in the southeastern LP and deficits and stronger trade-offs in urbanized and northwestern regions. Based on ES supply-demand ratio (ESDR) bundles, the LP was delineated into four, five, and six sub-zones at the city, county, and town scales, respectively. GAM analyses revealed widespread nonlinear responses of CESDR and EStrade-off to socio-ecological drivers, with human activity-related factors exhibiting dominant negative influences. CESDR generally exhibited hump-shaped responses to forest and grassland proportions in most sub-zones, with diminishing or negative responses beyond certain ranges. By integrating multi-scale pattern analysis, ESDR-based zoning, and nonlinear response assessment, this study advances understanding of ES supply-demand dynamics and provides insights for ecological management in the LP.
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