Nature as a decision-maker agent: a new conceptual framework for climate policy evaluation

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This paper introduces the PATTERN model, a novel agent-based modeling framework designed to assess the impacts of climate and biodiversity policies under conditions of uncertainty, spatial heterogeneity, and systemic feedback. The model captures interactions between heterogeneous human agents—policymakers, producers, and consumers— and natural systems, which are represented as decision-making agents through spatially explicit climate and biodiversity modules. The PATTERN model incorporates behavioral dynamics, legal developments recognizing the agency of nature, and high-resolution spatial information through raster layers that reflect real-world environmental heterogeneity. The framework combines micro-level behavioural responses with macroeconomic dynamics by coupling an Agent-Based Model (ABM) with a Computable General Equilibrium (CGE) model. This hybrid architecture allows environmental feedback, policy responses, and economic adjustments to co-evolve across spatial and institutional scales. Following the ODD (Overview, Design concepts, Details) protocol, the model’s structure, data sources, and sub-models is described highlighting its utility in informing forward-looking, adaptive environmental policy, and its potential to enrich integrated assessment models by agent heterogeneity and environmental feedback To complement the conceptual framework, the paper includes a concise empirical illustration from the agricultural sector, showing how biodiversity indicators and climate variables affect production decisions and policy outcomes within the model.