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

机译:社会学习:一种知识和能力建设的方法,用于有争议的景观的自适应联合管理

摘要

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.
机译:在自然资源管理领域,人们越来越认识到,要对气候和政策变化进行变革性适应,就需要跨行业的学习和景观领域的合作。这可以通过开发学习模型的系统方法论来支持,以在多样化和冲突的景观管理者之间进行自适应的共同管理。我们在澳大利亚亚热带地区将土地利用改变为硬木人工林的例子说明了社会学习过程的创新实施框架,该框架有助于建立知识和社区能力,以适应性地共同管理动态和共享的景观。行动研究方法学依靠对当地知识,现有和新兴科学发现的审议,从而导致态度上的变化。桥接组织(在此情况下为研究机构)需要流程的协助和调解,以支持跨规模的沟通。反思表明,需要注意管理风险和支持利益相关者分析,特别是在理解有争议的价值以及克服行业和个人利益集团之间的权力差异方面。解决资金问题将需要政府和行业团体更多地考虑其对社区和环境的社会责任;特别是因为这种社会学习模型被认为可以更广泛地用于提供多层次的治理联系,并且可以作为针对干预措施以解决政策空白或失败的基础。

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