This is the authors' abstract. We don't add key points for this paper.
Amid global climate warming, agricultural low-carbon transition is critical for ecological governance. In China’s ecologically fragile contiguous karst areas of Yunnan–Guizhou, intensifying rural population decline poses unique challenges to emission reduction. This study analyzes population and agricultural production data from 25 cities (prefectures) (2013–2022) to quantify rural population decline rates and agricultural carbon emission efficiency. We map their spatiotemporal evolution patterns, apply spatial autocorrelation models to assess spatial dependencies, and investigate mechanisms through a mediation model integrated with agricultural modernization’s three core systems: industrial, production, and management. Key findings reveal (1) divergent trajectories of carbon emission efficiency across regions with varying population decline types; (2) a global Moran’s I of −0.3519, indicating significant negative spatial correlation between population decline intensity and emission efficiency; and (3) dual impact mechanisms where population decline directly alters emission efficiency and indirectly modulates it through interactions with agricultural systems, with mechanism heterogeneity across decline patterns. To reconcile carbon reduction and agricultural growth, region-specific strategies must align population decline gradients with dynamic adjustments to agricultural systems, ensuring synchronized demographic transition and modernization.
No takes yet. Share an insight, caveat, or question.
Chen et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: