Climate change intensifies the challenge of sustaining forest landscapes that simultaneously deliver timber, carbon sequestration, recreation, and biodiversity conservation. We develop a stochastic network model of forest governance under climate-induced disturbances, combining nonstationary climate drivers, adaptive management, and evolutionary variational inequalities. The framework contrasts monofunctional zoning with multifunctionality, integrating spatial connectivity, adaptive budgets, and governance strategies.
Using Monte Carlo climate scenarios for both high-emission (Business-as-Usual) and low-emission (Net Zero) policy pathways, we quantify welfare, resilience metrics -- including viability probabilities, welfare preservation ratios, conditional value-at-risk (CVaR), and downside risk -- and service synergies. Results show multifunctionality increases median discounted welfare by $14\%$ (Business-as-Usual) and $15\%$ (Net Zero) relative to monofunctional zoning and improves median resilience indicators by up to $30\%$, particularly under high climate variability, though it reduces peak timber output. We identify adaptive budget thresholds and service allocation mixes that jointly maximize welfare and robustness, revealing strong non-linear interactions between spatial connectivity and diversification.
Policy analysis confirms multifunctionality consistently enhances welfare and resilience across climate scenarios, providing a quantitative basis for designing forest governance strategies that balance economic, social, and ecological objectives under climate change.
