Climate resilient rubber cultivation zoning via species distribution and spatial optimization

Climate change is reshaping the geographic envelope of rubber cultivation in China, creating risks of maladaptation from ill-informed expansion or abandonment of viable regions. We compared five species distribution models (GLM, RF, BRT, MaxNet, and MaxEnt) under identical samples and spatial cross-validation, then projected suitability to 2100 under CMIP6 scenarios. MaxEnt demonstrated the highest accuracy and transferability (AUC 0.973, TSS > 0.90) and was retained for final projections. Isothermality and dry-season precipitation emerged as primary limiting factors. Under moderate emissions (SSP245), highly suitable areas expand by 153% by 2100 with a northward shift, whereas extreme warming (SSP585) triggers heat and drought stresses that limit expansion. Integrating MaxEnt outputs with Marxan spatial optimization identified 480 priority planning units covering 1.9% of the national territory at minimal cost. This workflow translates climate-sensitive suitability into actionable spatial priorities, supporting resilient development of China's rubber sector under uncertainty.