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An Integrated Framework for Assessing Livestock Ecological Efficiency in Sichuan: Spatiotemporal Dynamics, Drivers, and Projections

Author

Listed:
  • Hongrui Liu

    (Yantai Institute, China Agricultural University, Yantai 264670, China)

  • Baoquan Yin

    (Yantai Institute, China Agricultural University, Yantai 264670, China)

Abstract

The upper reaches of the Yangtze River face the challenge of balancing livestock development and ecological protection. As a significant livestock production region in China, optimizing the livestock ecological efficiency (LEE) of Sichuan Province (SP) is of strategic importance for regional sustainable development. Livestock carbon emissions and related pollution indices were utilized as undesirable output indicators within the super-efficiency SBM model to measure SP’s LEE over the 2010–2022 period. Kernel density estimation was combined with the Theil index to analyze spatiotemporal variation characteristics. A STIRPAT model was constructed to explore the influencing factors of SP’s LEE, and a grey forecasting GM (1,1) model was employed for prediction. Key findings reveal the following: (1) LEE increased by 25.9%, with high-efficiency regions expanding from 19.0% to 57.1%; (2) regional disparities persist, driven by labor redundancy and environmental governance gaps; (3) per capita GDP, industrial agglomeration, and technology advancement significantly promoted efficiency, while government subsidies and carbon intensity suppressed it. Projections show LEE reaching 0.923 by 2035. Key recommendations include the following: (1) implementing region-specific strategies for resource optimization, (2) restructuring agricultural subsidies to incentivize emission reduction, and (3) promoting cross-regional technology diffusion. These provide actionable pathways for sustainable livestock management in ecologically fragile zones.

Suggested Citation

  • Hongrui Liu & Baoquan Yin, 2025. "An Integrated Framework for Assessing Livestock Ecological Efficiency in Sichuan: Spatiotemporal Dynamics, Drivers, and Projections," Sustainability, MDPI, vol. 17(16), pages 1-28, August.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:16:p:7415-:d:1725946
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