The Importance of Brokers in Collaborative Marine Ecosystem-Based Management of Social Ecological Systems

Abstract

Practitioners play a critical yet largely unexamined role in translating collaborative, ecosystem-based management (EBM) for social-ecological systems from theory to practice. We paired mental models and social network analytical methods and applied them to two cases of marine EBM in Rhode Island and New York, focusing on practitioners themselves, to understand the relationship between practitioners’ mental models of marine ecosystems and the extent and nature of collaboration within each network. Mental models analysis was used to assess the comprehensiveness and balance of practitioners’ mental models, and social network analysis was used to assess the role and influence of practitioners within each network. A comparative statistical analysis was then performed to understand the relationship between mental models and network measures. Research revealed a statistically significant correlation between practitioners’ mental model comprehensiveness and practitioners’ influence within the network. In other words, practitioners with comprehensive mental models of the ecosystem for which they were planning were found to act as “brokers,” connecting those who were not otherwise connected, bridging jurisdictions, sectors, and disciplines. Results underscore the importance of brokers in achieving the collaborative and integrated goals of EBM and suggest the need for greater attention to practitioners’ role in EBM implementation.

Keywords:

• brokers
• collaboration
• ecosystem-based management
• mental models
• social-ecological systems
• social networks

Acknowledgments

The author thanks the 41 RI and NY practitioners who contributed their time, input, and expertise to this research.

Disclosure statement

The views expressed in this manuscript are those of the authors and do not represent the official policy or position of the U.S. Coast Guard, the Department of Homeland Security, or the U.S. Government.

Notes

1 While our data were collected in 2011, nothing has transpired with the case studies that would alter our interpretation of the data. Further, nothing has been published that combines social network analysis and mental models analysis to better understand how EBM might be successfully implemented.

2 41 practitioners participated in mental models interviews conducted for this study while an additional 6 practitioners (total of 47) participated in the social network analysis interviews. As this paper reports on the comparative analysis between the two, our analysis includes only the 41 practitioners who participated in both study components. For further details on the mental models study see Smythe and Thompson 2015 and for further details on the SNA study see Smythe, Thompson and Garcia-Quijano 2014.

3 Regarding the NY sample (n = 13), results should be interpreted with caution because this sample is too small for any correlation method to provide much insight.

4 Broad network summaries reported here include all actors identified by study participants as part of the network, thus including individuals that were neither interviewed nor surveyed.

5 Normalized degree and betweenness centrality are calculated by dividing raw scores by maximum possible scores and expressed as percentages. This is done to facilitate communication between networks.

6 Average degree and betweenness centrality scores are calculated based on the 41 study participants who participated in both interviews and surveys, consistent with this study’s focus on these 41 participants. These averages exclude centrality measures for actors who were neither interviewed nor surveyed.

Additional information

Funding

This research was supported in part by NSF IGERT grant DGE-0504103 to the University of Rhode Island Coastal Institute.