Rethinking governance for the Global Biodiversity Framework: Legal gaps and lessons from Chile

The Kunming-Montreal Global Biodiversity Framework (GBF) calls for transformative governance to halt biodiversity loss and promote equitable, effective conservation. Yet implementation remains challenging in countries with fragmented and unequal governance systems. This Perspective introduces a place-based conceptual framework to assess and improve biodiversity governance under the GBF, integrating governance typologies, structural principles (e.g., polycentricity, resilience), and normative dimensions of good governance (e.g., legitimacy, inclusion, equity). We apply this framework to Chile, a country marked by jurisdictional fragmentation and uneven recognition of diverse governance models. Through a documentary analysis of 15 legal instruments, we examine their alignment with GBF Targets 1, 2, 3, and 22 and assess how good governance principles are formally reflected in national legal frameworks. Our findings reveal partial alignment with structural principles, stronger recognition of legitimacy and effectiveness, and persistent weaknesses in equity and accountability. The proposed framework offers a transferable perspective for identifying regulatory and institutional gaps, allowing for guidance on necessary reforms in the design of more adaptive, plural, and evidence-based conservation strategies. By revealing how legal design can enable or constrain progress, the framework supports institutional learning and highlights the need to promote the integration of community and indigenous governance into national planning. While developed through the Chilean case, the framework may inform similar efforts in other postcolonial settings. The effective implementation of the GBF requires reimagining governance, and design-based legal evaluation is crucial for diagnosing institutional architectures and highlighting where reforms are needed to achieve that dynamic and inclusive process, rooted in both legal mandates and diverse knowledge systems.