Climate-Risk Thresholds for Ecology Conservation Environmental Earth Systems in Kenya: Bayesian Hierarchical Modelling of Resilience and Food Security

Kenya's ecological conservation and food-security governance requires more than continuous climate-risk surfaces; it requires defensible thresholds at which a composite spatial index signals a change in management regime. The composite spatial index integrates Slope, Drainage density, Rainfall intensity, Land cover, Soil permeability, Elevation and Distance to channels across Kenyan administrative units. The model treats threshold parameters as ordered random quantities, assigns spatial and temporal random effects to county-level outcomes, and places shrinkage priors on regression and threshold coefficients. A reproducible GIS workflow, visualised through maps of administrative units, service-coverage buffers, a monthly index series, a city-scale detail and criterion-weight uncertainty, supports transparent construction of the index and its inputs. The analysis workflow (Script 1) documents the spatial operations and permits sensitivity analysis of weights and buffers. The resulting posterior exceedance probabilities would allow county-level managers to separate the intensity of exposure from the confidence that a threshold has been crossed, and to translate threshold uncertainty into explicit decision rules for ecological conservation and food security.