Evaluating Collaborative Adaptive Management in Sierra Nevada Forests by Exploring Public Meeting Dialogues Using Self-Organizing Maps

Abstract

Collaborative adaptive management (CAM) is an appropriate management regime for social–ecological systems because it aims to reduce management uncertainties and fosters collaboration among diverse stakeholders. We evaluate the effectiveness of CAM in fostering collaboration among contentious multiparty environmental stakeholders based on the Sierra Nevada Adaptive Management Project (SNAMP). Our evaluation focuses on facilitated public multiparty discussions (2005–2012). Self-organizing maps (SOM), an unsupervised machine-learning method, were used to process, organize, and visualize the public meeting notes. We found that public discussion remained focused on the project content, yet the more contentious and critical issues dominated the discussions through time. Integration across topics could be improved. These results suggest that SNAMP collaborative adaptive management seems to have helped participants focus on the key issues, as well as advancing their discussions over time. Given the effectiveness of SOMs in analyzing text, we provide suggestions on how natural resource managers might use SOM.

Keywords:

• collaborative adaptive management
• participation
• self-organizing map
• SNAMP
• SOM

Acknowledgment

This is SNAMP Publication number 36.