Adaptive Co-management Networks: a Comparative Analysis of Two Fishery Conservation Areas in Sweden
Annica Sandström, Division of Social Science/Political Science Unit, Luleå University of Technology, Sweden
Carl Rova, Division of Social Science/Political Science Unit, Luleå University of Technology, Sweden
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Co-management constitutes a certain type of institutional arrangement that has gained increased attention among both policy makers and researchers involved in the field of natural resource management. Yet the concept of co-management is broad, and our knowledge about how different kinds of management structures affect the ability to deal with challenges pertinent to the commons is limited. One of these challenges is to foster an adaptive management process, i.e., a process in which rules are continuously revised and changed according to what is known about the ecological system. We aim to address the relationship between different kinds of co-management structures and adaptive management. To this end, we conducted a comparative case study of two Fishery Conservation Areas in Sweden. The concept of networks and the formal method of social network analysis are applied as theoretical and methodological devices. Building on previous research, we propose that adaptive management processes occur in co-management networks consisting of a heterogeneous set of actors that are centrally and densely integrated. Networks of this kind are believed to promote a management process in which actors with disparate perspectives and resources formulate a common view regarding the condition of the ecosystem, the basic problem to be solved, and what measures to adopt. The empirical findings support the existence of such a relationship. Nonetheless, the restricted empirical material, an inability to control for hidden variables, and a lack of success in determining causality among variables are all factors that call for more research.
adaptive management, co-management, governance, natural resource management, social networks, social network analysis, SNA
Ecology and Society. ISSN: 1708-3087