Managing Natural Resources at the Intersection of Economy, Ecology and Policy

Persistent natural resource problems induce research on management approaches. Analyzing natural resource management policies involves recognizing the complex interactions within and between social and ecological systems. Both problems and solutions arise from the relationships between social-ecological factors, such as the resource and its system characteristics, political setting and governance, and the characteristics of resource users and of others with a stake in management. Social- ecological systems (SES) research seeks to understand the many factors influencing these users and stakeholders to collectively manage natural resources in various social and ecological settings. This SES research involved iterations of conducting an economic and policy analysis of intertidal shellfish management and involving stakeholders. Using institutional theory, we estimated regression models to explain the variation of policy structure types, in order to gain understanding of patterns in local intertidal shellfish management policies. We involved stakeholders in this SES research to help link generated knowledge with management improvements. During scoping research with stakeholders, we discovered several types of policy structures for local intertidal shellfish management, allowing us to compare simple models of the presence or absence of management policies to more complex models that explain variation in policies. Using the Institutional Analysis and Development framework, we identified social-ecological factors relevant to local intertidal shellfish management and developed these regression models. With involved stakeholders, we focused research questions on how the differences among resource users, managers and other stakeholders (social heterogeneity) influence management policies. Stakeholder interviews helped inform our specification of regression models. Additionally by conducting interviews, we solicited information about management activities implemented by communities. After we obtained regression results, we conducted a second round of interviews to help interpret results. This round of interviews also allowed us to assess communication channels and preferred media for sharing research results. By focusing on social heterogeneity we learned about resource users and others with a stake in management. The regression models improved our understanding of the variation in policy structure types. We found that social-ecological factors, including the threat to the resource, resource users and our measure of social norms in the community, explain local policy choices. While categorizing policy structures did not significantly improve results relative to a simple presence or absence model, we did find evidence that some factors have influence on different structure types. This research can be compared to others that use models to understand what influences policy decisions. Our more complex model provides another way for learning about complex social-ecological systems. We found that involving stakeholders in a SES study required more time than expected; however, such work aims to improve communication of generated knowledge to those taking actions. We communicated with stakeholders on their terms, so we were able to make common goals and decide on how to communicate research results. We co- identified research outputs, allowing us to communicate results directly to stakeholders. Our iterative research approach holds promise for achieving a greater comprehension of complex social-ecological systems occurring around natural resource management. In addition to contributing to the field of sustainability science, this approach to SES research deepens our understanding of the social-ecological factors influencing natural resource management policies