| Description: |
Avocado ( Persea americana Mill.), a nutrient-rich tropical fruit, is gaining prominence in India due to rising domestic demand and export potential. However, its cultivation remains fragmented, largely confined to southern states, with limited knowledge of ecological requirements under diverse agro-climatic zones and climate change scenarios. This study aimed to identify key bioclimatic and non-bioclimatic factors influencing avocado suitability, model its current and future distribution using ensemble species distribution modelling (ESDM), assess niche dynamics under four Representative Concentration Pathways (RCPs 2.6, 4.5, 6.0, and 8.5) for 2050 and 2070, and evaluate implications for climate-resilient agroforestry planning. Using 35 spatially thinned occurrence records and high-resolution environmental predictors, ESDM integrating eight machine learning algorithms was applied. Model performance was robust (AUC: 0.86–0.91), with Random Forest and Maxent performing best. Critical predictors included isothermality, minimum temperature of the coldest month, precipitation in the coldest quarter, urbanization, and forest cover. Current suitability hotspots were concentrated in Kerala and Tamil Nadu. Future projections under RCPs 2.6 and 6.0 indicated northward and altitudinal expansion into the Western Ghats, northeastern hills, and eastern India, whereas RCP 8.5 suggested increased fragmentation and instability. Niche analysis revealed ecological breadth expansion under low to moderate emissions, but contraction and displacement under high-emission conditions. These findings highlight scope for expanding avocado cultivation under low to moderate emissions, provided thermal and precipitation stability is maintained. The study offers a geospatial foundation for climate-smart avocado production, conservation, and policy, emphasizing the protection of climatic refugia in southern India and adaptive agroecological strategies for long-term sustainability. |