Environmental suitability and climate-informed spatial prioritization of Opuntia ficus-indica (L.) MILL. in India using MaxEnt and the analytic hierarchy process
Year: 2026
Type: article
Abstract: Climate-informed diversification of water-limited farming systems requires identifying environmentally suitable areas that remain favorable under future climate conditions. This study assessed the current and future environmental suitability of cactus pear ( Opuntia ficus-indica ) across India and developed a spatial prioritization framework for dryland agricultural planning. MaxEnt models using 138 spatially thinned occurrence records and climatic, soil, and land-use/land-cover predictors were projected to the 2050s and 2070s under four RCP scenarios using the BCC-CSM1-1 global climate model. MaxEnt-derived suitability was integrated with selected soil and land-surface criteria through the Analytic Hierarchy Process (AHP). Future suitability persistence was quantified using the Climate Persistence Index (CPI) and combined with current integrated suitability to derive the Climate-smart Opuntia Priority Index (COPI). Current Moderate-to-Optimum integrated suitability covered approximately 1.085 million km 2 , of which 73.41% (796,315 km 2 ) retained at least Moderate suitability across five or more of eight future scenarios. COPI identified 549,070 km 2 (16.80% of the analyzed area) as High or Very-high priority, primarily in western India, with additional opportunities in peninsular regions. Five independently reported Indian experimental locations corresponded spatially with High or Very-high COPI classes; however, observed differences in survival and productivity demonstrated that model-derived suitability does not directly predict crop performance. The principal limitations include reliance on a single climate model, predefined MaxEnt regularization and AHP weights, static soil and land-use assumptions, and limited field correspondence. Thus, COPI provides a preliminary biophysical decision-support framework for prioritizing genotype evaluation, agronomic trials, and climate-smart dryland diversification rather than direct evidence of cultivation success or agricultural resilience.
Authors: Manish Mathur, Preet Mathur
Language: English
Subfield: Ecological Modeling
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,353
OpenAlex ID: W7225105946