Abstract:
Adaptive co-management of natural resources requires a variety of stakeholders across different scales and sectors to communicate and collaborate effectively. Social network theory recognizes that stakeholders interact with each other through networks and that various network characteristics affect the way in which they function. Social relationships can be visualized through network mapping and their patterns systematically analyzed in a process known as social network analysis (SNA). Participatory SNA allows members of the network to be involved in the mapping or analysis process. Participants can then apply their knowledge of these relationships to build, improve, or better utilize their connections to increase desired outcomes. These actions are referred to as network interventions or network weaving. In Bua Province in the Fiji Islands, the Wildlife Conservation Society and other partners are facilitating "ridge to reef" ecosystem-based management planning and are striving to build local capacity for natural resources governance and conservation. This study seeks to determine how participatory SNA might be used as a tool for enhancing community-led natural resources management. First it was necessary to develop methods for conducting participatory SNA research with rural Fijian communities. Network data was then gathered from eight Districts and fifty villages. Social network maps were presented back to community stakeholders for their interpretation and to elicit their ideas for improving their resource governance networks. SNA was used to characterize and map patterns of information exchange and collaboration among stakeholders involved in natural resource management in Bua. Even without complete network data, several patterns emerged. These included: 1) Traditional decision-making networks that were more cohesive than information exchange networks, reflecting the importance of social hierarchies for decision making within rural Fijian communities and the need for resource governance to link into these structures. 2) All the District-level networks had a number of fragmented groups and more ties within than between communities. This highlights the challenge of getting communities to effectively collaborate at the District-level due to issues like distance between villages, conflicts, barriers to communication (e.g. no phone/internet), and clan-based (mataqali) land-ownership system. These issues suggest the need for innovative actions to help bridge these gaps and present an opportunity for network weaving. 3) Actor position analyses (indegree and outdegree) provided a list of opinion leaders and people who are good at reaching out to others. These individuals may be good candidates to receive network weaver trainings. These measures also highlighted individuals and groups that communities would like to work with in the future and who facilitators can help to connect. Overall, these results indicate that SNA can be a valuable tool for better understanding relationships between actors involved in collaborative natural resource management, but its use in rural settings can be limited by the challenges of collecting data in remote villages. The participatory process of evaluating networks with participants was beneficial since it helped communities recognize and discuss the strengths and weaknesses of their resource governance networks. This resulted in a list of recommended capacity-building activities (such as alternative livelihoods projects and special trainings for traditional leaders) based on their self-identified needs. However, the real potential benefits of this process will not be realized until the study results are applied, until network weaving and capacity building actually take place, and the process is evaluated to determine if any positive outcomes resulted for communities or conservation. This will require considerable commitment on the part of a network coordinator(s) to impart network concepts, facilitate network weaving activities, and in due course empower a transformation from the status quo to self-organizing, action-oriented conservation networks.
