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Exploring future ecosystem service trade-off and key driving factors in the ecologically fragile region, northern China

Author

Listed:
  • Chen, Xueping
  • Zhao, Xueyong
  • Zhao, Yanming
  • Zhu, Xiaowen
  • Bai, Liya
  • Yu, Hongmei

Abstract

Aligning the supply and demand of ecosystem services (ESs) is crucial for achieving sustainable management of the grain-water relationship in arid and semiarid regions. However, research on matching the supply and demand of ESS to advance the sustainability of grain-water systems remains limited, particularly under future scenarios in the ecologically fragile semiarid regions of northern China. This study addressed this gap by analyzing grain production (GP) and water yield (WY) under different Shared Socioeconomic Pathways (SSP) scenarios in Horqin Sandy Land (HQSL), a typical grain production base with water resource scarcity in semiarid China. Markov-PLUS model was employed to predict land use and cover change (LUCC) in 2030, 2040 and 2050 under future SSP126, 245 and 585 scenarios. InVEST model and equation were employed to evaluate the spatial patterns of WY and GP. Key findings include: (1) GP was oversupplied in all scenarios, while WY showed a supply-demand deficit in 2020 and 2040 SSP585 scenario. (2) An increase in cultivated land was associated with a decrease in WY's ESDR and an increase in GP's, and an optimal trade-off was found under the 2030 SSP126 scenario. (3) Precipitation positively influenced both WY and GP, while GDP and population density also exerted significant influences on GP. This study offers insights into ESs dynamics and a framework for sustainable grain-water management in semiarid regions.

Suggested Citation

  • Chen, Xueping & Zhao, Xueyong & Zhao, Yanming & Zhu, Xiaowen & Bai, Liya & Yu, Hongmei, 2026. "Exploring future ecosystem service trade-off and key driving factors in the ecologically fragile region, northern China," Ecological Modelling, Elsevier, vol. 512(C).
    • Handle: RePEc:eee:ecomod:v:512:y:2026:i:c:s0304380025003989
    DOI: 10.1016/j.ecolmodel.2025.111412
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