Quantifying stakeholder learning in climate change adaptation across multiple relational and participatory networks

Abstract

Responding to accelerating climate change impacts requires broad and effective engagement with stakeholders, at multiple geographic and governance levels. Stakeholder participation has been hailed as a facilitated approach in climate change adaptation that supports social learning, depolarization of perceptions, and fosters collective action. But stakeholder participation remains loosely interpreted and evaluating measures are limited. This study employs social network analysis (SNA) to investigate how social relations among stakeholders, which emerge as a result of participation, are associated with stakeholder learning, as changes in perceptions of climate change. We hypothesized that reciprocal ties of understanding, respect, and influence can predict changes in perceptions of climate change. This approach was applied to a case study in Deal Island Peninsula, Maryland (USA) where local residents, scientists, and government officials met from 2016 to 2018 to collaboratively manage the impacts of sea-level rise in their communities. We found that social relations based on mutual understanding, respect,and influence are positively associated with perceptions of climate change. We provide a detailed conceptualization and implementation of a network-based approach that may serve as a potential quantitative performance measure of stakeholder participation processes in climate change adaptation. Overall, this study provides empirical evidence of the role that emerging social relations have on enhancing or constraining social learning among stakeholders in the Deal Island Peninsula project.