| Managing ecosystems is challenging due the diversity and high number of stakeholders, institutional fragmentation and mismatch to the temporal and spatial extent of biophysical processes, and a limited understanding of complex ecosystem and societal dynamics. Given these conditions, collaborative governance is well-suited to support the collective action necessary to address threats to sustainability of linked social and ecological systems (SESs). Under this paradigm, an increased understanding of which actors get involved and with whom they collaborate is needed.;In this dissertation, I investigated two cases of environmental network governance. First, I conducted social network analysis (SNA) and Stochastic Actor Oriented Models (SAOMs) and drew on semi-structured stakeholder interviews to describe and analyze the evolution of the comanagement network of stakeholders in the Honduran spiny lobster fishery during a conservation and development initiative. I found a lack of evidence that the initiative built the foundation of a sustainable, functional collaborative governance regime. Instead, network activity coalesced around traditional centers of power and transient donor organizations, and there was a failure to empower traditionally underrepresented stakeholders.;Next, I used Exponential Random Graph Models (ERGMs) to examine how the collaborative environmental governance network around sea-level rise adaptation in the San Francisco Bay Area has evolved over time as a result of actors making decisions about which adaptation venues to participate in. I found that popular actors and venues, embedded social capital, and geographical constraints shaped network evolution.;The results obtained in this collection of studies have implications for the implementation and evaluation of network governance performance, as well as for theories of collaborative governance and institutional evolution. |
