LEARNFORCLIMATE

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Abstract:
LEARNFORCLIMATE supports learning that enables concurrent achievement of multiple forest-related objectives while responding to constraining and enabling effects of climate-change related stress and disturbances. The project advanced understanding of how these pressures shape forest governance, owners’ and manager’s decisions and ecosystem-service outcomes. Disturbances, such as fires and storms, now influence forest policy development, often incremental but substantial under high disturbance pressure. Yet outcomes depend on national institutions, property rights and actor coalitions. The project identified coherence gaps in national legislation and between national and EU policies, contributing to uneven national implementation of EU ambitions. Understanding historical policy trajectories and actor coalition dynamics is needed to anticipate windows for learning and change. The project clarified what drives forest owners’ and managers’ responses to climate change, disturbance and policy demands. While perceptions differed, actors consistently emphasized economic and environmental influences, e.g. incentives, climate-induced disturbances, and adapted practices, and identified policy coherence as the key political driver. It confirmed the existence of theoretically derived forest-owner types with varying motivations and decision rationalities. Therefore, context-adapted instrument mixes tailored to fit different owner types and national settings are needed. The project also improved understanding of how policy and forest owners’ decisions affect biodiversity and ecosystem services, including trade-offs and synergies. Results confirm recurring timber–biodiversity trade-offs and potential carbon–biodiversity synergies, for example via broadleaves, while water responses were weaker at the studied scale. Modelling shows that substantial shifts in forest systems and ecosystem services require major management changes, and that additional adaptation beyond what is already implemented or planned should not be expected without changes in social, technological, economic, environmental or political conditions. Finally, the project operationalized “learning” for policy and practice through measures of learning propensity: when and how learning is likely. Disturbances and crises can trigger learning, but it is selective and strategic and does not automatically resolve conflicts. Outcomes tend to reflect actors’ coalitions, power relations and strategic use of learning. Effective collaborative learning requires engaging key actors, targeting tractable belief differences, providing relevant knowledge and embedding dialogue in policy processes. The project generated tools and recommendations to promote learning in contested forest policy arenas, complex forest management contexts and polarized collaborative settings. It shows that strong path dependencies exist, and that additional evidence alone is insufficient to induce change.

LEARNFORCLIMATE has advanced forest research by combining policy analysis, behavioral insights and ecosystem-service modelling across Europe. We show how climate disturbances drive policy change and turn learning into practical tools for science–policy dialogue. The results strengthen the evidence base for more substantial climate and biodiversity action and support more effective and legitimate implementation of EU forest policy.