Streams are globally important natural resources embedded in watersheds representing complex socio-ecological systems that provide environmental, economic, and social benefits. Streams, however, are highly vulnerable to anthropocentric impacts and are all too often in need of restoration. The primary objective of ecological restoration in general, and stream restoration in particular, is to bring back healthy and sustainable ecological functions. To achieve this end, recent studies suggest a growing global trend towards establishing collaborative and adaptive natural resource governance systems as opposed to traditional government and less effective top-down approaches. These governance systems are built on social networks underpinning cooperation, collective action, and co-management. However, there is a lack of empirical evidence on how these social networks emerge and evolve over time as well as how measurable network structure and character dynamics relate to adaptive governance system effectiveness. In the case of stream restoration in the Upper Shavers Fork of West Virginia, USA, social network analysis was used to investigate the emergence and evolution of collaborative and adaptive governance structures. Furthermore, in this case, research confirms that social network structure and character are linked to natural resource governance effectiveness, and perhaps more importantly, studying network structural dynamics yields greater insights than merely performing analysis at a single period in time. This research also exposes the persistence of core-periphery and polycentric network structures through time providing practical insights for future network development and ecological restoration efforts in West Virginia, and beyond.
