Holly K. Nesbitt

I am an interdisciplinary social scientist studying institutions, governance and collective action in systems experiencing large-scale social-ecological change.

My work is motivated by the complex realities of sustainable and equitable adaptation to global change–including changing climates, land uses, social values, institutions, and governance structures. I focus on questions and contexts that have a cross-scale nature both ecologically and socially, such as the social-ecological implications of fish and wildlife movement, invasive plant encroachment, or wildfire spread and management. Although institutions often focus on a particular scale of society to achieve outcomes for that group (e.g., the institution of private property to maximize individual landowner rights), what happens when social-ecological conditions change? How does society adapt or transform while still being constrained to previous institutional structures and paradigms? Do relatively novel environmental policies that encourage cross-boundary collaboration achieve their intended outcomes? Where and for whom?

 

My research focuses on these types of questions to understand societal adaptation with the intention of informing more equitable and effective environmental policy. I draw on theories of social-ecological system resilience and transformation, institutional development and fit, planned behavior, and social relations to critically examine and inform environmental policy. I use predominantly quantitative social science methods including social network analysis, regression, and dimension reduction to ask questions about societal adaptation and transformation at different, interacting scales. I collect data through surveys, assemble data through publicly available documents, and leverage large datasets that are available publicly or through partnerships.

 

In my postdoc and current role, I lead an interdisciplinary team to understand how social-ecological conditions are related to the emergence and quality of collaborative wildfire planning across the US. We combine surveys, natural language processing of plans and policy, and spatial analysis of demographics and risk with Bayesian time-to-event models, social network analysis, and other spatial statistical analyses.