A framework for assessing collaborative capacity in community-based public forest management.
Community-based collaborative groups involved in public natural resource management are assuming greater roles in planning, project implementation, and monitoring. This entails the capacity of collaborative groups to develop and sustain new organizational structures, processes, and strategies, yet there is a lack of understanding what constitutes collaborative capacity. In this paper, we present a framework for assessing collaborative capacities associated with community-based public forest management in the US. The framework is inductively derived from case study research and observations of 30 federal forest-related collaborative efforts. Categories were cross-referenced with literature on collaboration across a variety of contexts. The framework focuses on six arenas of collaborative action: (1) organizing, (2) learning, (3) deciding, (4) acting, (5) evaluating, and (6) legitimizing. Within each arena are capacities expressed through three levels of social agency: individuals, the collaborative group itself, and participating or external organizations. The framework provides a language and set of organizing principles for understanding and assessing collaborative capacity in the context of community-based public forest management. The framework allows groups to assess what capacities they already have and what more is needed. It also provides a way for organizations supporting collaboratives to target investments in building and sustaining their collaborative capacities. The framework can be used by researchers as a set of independent variables against which to measure collaborative outcomes across a large population of collaborative efforts.
Department of Forest & Rangeland Stewardship, Colorado State University, Fort Collins, CO, USA. tony.cheng@colostate.edu
Antony S
AS
Cheng
Victoria E
VE
Sturtevant
D003256:Community Participation; D003247:Conservation of Natural Resources / Q000379:methods*; D003299:Cooperative Behavior; D003661:Decision Support Techniques; D017753:Ecosystem; D016468:Forestry / Q000379:methods*; D014481:United States