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

Forest ecosystems in Kenya are increasingly positioned at the confluence of climate variability, agricultural expansion and food security policy, yet the thresholds beyond which these socio-ecological systems lose their capacity to buffer environmental shocks remain poorly characterised. Rather than reporting empirical results, the analysis is presented as a methodological and conceptual contribution that integrates ecological resilience theory with spatial risk assessment and hierarchical Bayesian inference. The framework treats forest resilience as a latent, scale-dependent property that emerges from interactions among vegetation condition, hydrological regulation and land-use pressure, and it specifies threshold parameters whose posterior distributions would permit probabilistic statements about system vulnerability. A composite spatial index, incorporating slope, drainage density, rainfall intensity, land cover, soil permeability, elevation and distance to channels, is proposed as the principal covariate structure for identifying high-risk zones. The article argues that conventional single-indicator approaches mis-specify the causal pathway from climate hazard to food insecurity and that a hierarchical, threshold-based model offers a more defensible basis for early warning and adaptive governance in Kenyan forest landscapes.