Abstract
River restoration is one of the most common, expensive, and environmentally influential forms of restoration, but has little post-restoration assessment of social success. In this study, we use social network theory and analysis (SNA), an emerging approach for understanding social dynamics in restoration projects, to examine the social connections, perceptions of project success, and attitudes of stakeholders involved in a river restoration project. We find that positive and negative social network ties have asymmetrical effects on stakeholders’ attitudes and satisfaction with project outcomes. Trust ties positively influence perceptions of public engagement, while avoidance ties negatively influence satisfaction. Trust in leaders positively influences satisfaction and both public engagement and perceived conflict influence the development of that trust. We contribute to the growing body of research using SNA in natural resource contexts through quantitative tests of social networks’ effects on stakeholder satisfaction with project outcomes.
Notes
1 We also ran our analyses with each conflict item separately (see Table S2). The direction and significance of results were virtually identical to the results with the combined scale.
2 Another accepted method to combine matrices is elementwise multiplication (Hanneman and Riddle Citation2005; Zagenczyk et al. Citation2015). As a robustness check, we reran all analyses using this method. The direction and significance of the results were virtually identical. Refer to Table S3 for results.
3 In addition, we ran all analyses using separate variables for cognition-based trust network size and affect-based trust network size. The direction and significance of results were virtually identical. Refer to Table S3 for results.
4 As shown in the map of the avoidance network (), one individual received a disproportionally greater amount of the negative relationship nominations. To examine whether this one individual was the sole cause contributing to our finding, as a robustness check, we re-tested the model with that person removed from the network. The direction and significance of the results were unchanged. Refer to Table S4 for results.