Social learning: A knowledge and capacity building approach for adaptive co-management of contested landscapes

There is increasing recognition in the field of natural resource management that transformative adaptation to climate and policy change requires cross industry learning and cooperation at the landscape scale. This can be supported by the development of systematic methodology on learning models for adaptive co-management between diverse and conflicting landscape managers. Our example of land-use change to hardwood plantation forestry in sub-tropical Australia illustrates an innovative implementation framework for a social learning process that helped build knowledge and community capacity for adaptive co-management of dynamic and shared landscapes. The action research methodology relied on deliberation over local knowledge, existing and emergent scientific findings, resulting in attitudinal change. Processes required facilitation and mediation by a bridging organisation, in this case a research institution, to support cross-scale communications. Reflections suggest that attention is required to manage risk and support stakeholder analysis, particularly in understanding contested values and overcoming power differentials between industry and self-interest groups. Resolving funding issues will require greater consideration by governments and industry groups of their social responsibilities to communities and the environment; particularly as this social learning model is posited for more broad-scale use in providing multi-level governance linkages and as a basis for targeting interventions to address policy gaps or failure.

Graphical abstractBuilding knowledge and capacity through cross-scale and multi-level partnerships and learning for adaptive NRM.Figure optionsDownload full-size imageDownload as PowerPoint slideResearch highlights▶ Social learning model within the adaptive co-management framework. ▶Supports community self-organisation through building collective capacity. ▶ Role of research institutions in bridging cross-scale and multi-level governance links. ▶ Systematic methodology for social learning to resolve land-use conflict. ▶ Use of visual modelling techniques for investigating dynamic socio-ecological systems.