Adaptive environmental management

Adaptive Environmental Management (AEM) refers to the emerging directions which can be seen to be developing through the integration of ecological and participatory research approaches.

Many contemporary research efforts are concentrating on creating new approaches to more closely link science, management and policy at an ecosystem level. At the base, these efforts represent a search for a research and development model and practice which combine the features of:

  • • management-based experimentation and innovation;
  • • natural resource system management on scales larger than individual enterprises and communities;
  • • methods for bringing about capacity for action among multiple agencies and actors (with typically divergent, not to say antagonistic points of view and interests);
  • • facilitation of the social processes and organizational capacity to accomplish these.

AEM focuses on learning and adapting through partnerships of managers, scientists and other stakeholders who learn together how to create and maintain sustainable ecosystems. It helps managers maintain flexibility in their decisions, knowing that uncertainties exist and so provides the latitude to adjust direction to improve progress towards desired outcomes (Fernândez-Giménez et al. 2019; Berkes 2009).

Effective implementation of AEM must therefore involve the active involvement and support of the full set of partners and stakeholders - that is, it must be as collaborative as possible. An inclusive approach is required not only to build understanding, support, credibility and trust among constituent groups, but also to ensure adequate problem-framing and access to the knowledge, experience and skills held by these groups. Because environmental conservation problems are social in origin and potential solutions are framed in a social context, effective management programs must therefore be designed in biophysical and social contexts. These contexts inform stakeholder management priorities and help stakeholders evaluate trade-offs in management decision-making. For example, a local (traditional) management context helps explain why stakeholders would prioritize learning about drought resilience by keeping cattle in a single large herd, rather than splitting them into several smaller herds. This will allow for the development of a drought forage reserve by resting several pastures, even though it will be associated with a reduction in daily livestock gains. This temporal environmental context would influence how stakeholders value learning about drought resilience over potential short-term financial gain from reduced stock density.

Therefore, acknowledging that AEM is shaped by social and environmental contexts at multiple scales may provide a pathway for the application of AEM-produced knowledge. The use of new knowledge depends on its salience, credibility and legitimacy to users (Beier et al. 2017). In multistakeholder collaborations, prolonged engagement and mutual knowledge exchange is often required to develop respect, trust, and ultimately the credibility and legitimacy of co-produced knowledge. A shared culture of learning will contribute to co-produced knowledge driven by stakeholder questions relevant to the local naniral resource management context (Fabricius & Cundill 2014).

 
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