Agroclimatic risk of Andean crops under CMIP6 scenarios in Imbabura, Ecuador: A reproducible Random Forest-Bayesian Network pipeline

Complete computational pipeline (22 Python scripts, 10 phases) and all outputs for assessing agroclimatic risk of four Andean crops (potato, maize, bean, quinoa) across 42 parishes of Imbabura Province, Ecuador, under CMIP6 climate scenarios (SSP1-2.6, SSP3-7.0, SSP5-8.5) for 2021-2040, 2041-2060, and 2061-2080. Methodology: Random Forest SDMs on BASD-CMIP6-PE projections + 7-node Bayesian Network (Hazard x Exposure x Vulnerability, IPCC AR6 framework). Outputs: 1,512 Risk Index values, 58 cartographic maps (300 DPI), 42 parish technical sheets. Key results: Garcia Moreno IR=0.689 (highest risk, SSP5-8.5, 2061-2080); Imbaya IR=0.350 (lowest); potato most vulnerable (IR~0.596); quinoa largest relative increase (+46.6% SSP3-7.0, +49.3% SSP5-8.5); bean most climate-stable (DeltaIR <= +0.5%); AUC 0.804-0.871; total agricultural exposure 10,706.1 ha. GitHub: https://github.com/VICTORSIG1985/agroclimatic-risk-imbabura