Key Wildfire Actor Inventory

Fede Holm

Amanda Wheelock

Sophie Daudon

Paige Fischer

Purpose

Identifying the full range of actors with interests in complex environmental governance challenges is important for ensuring that research and policy efforts engage and are responsive to the knowledge needs of diverse parties. However, identifying the full range of actors with interests in complex environmental governance challenges is also a difficult task. Relying on only a single-source approach to identify actors can unintentionally exclude voices that could be important stakeholders in the wildfire governance space. Using both deductive and inductive approaches helps us look beyond our own networks which often constrain us because they can create echo-chambers. 

Approach

We identified key actors through three methods: 1) exploratory search of websites using keywords, 2) “Expert elicitation” from WFFI team members and the wildfire thought leaders and resource people WFFI faculty were aware of, and 3) big data analysis of Twitter, newspaper articles, and Community Wildfire Protection Plans (CWPPs). We then used these data to create lists of relevant actors at various levels and domains, as well as identify areas of overlap or intersection. 

Analysis Pt. 1

We identified a small set of actors at the overlap between datasets, revealing a core group that are at once active, engaged, and influential. This finding indicates that triangulation is useful, as the data sources do indeed provide access to actors with different attributes or roles within the system. Secondly, by assessing actors that appear across datasets, we can retrieve the set of critical actors in the governance system. The overlaps are dominated by a small number of categories strongly associated with formal (institutional) authority and expertise: county governments, fire departments and districts, federal lands (parks or forests), state agencies, environmental NGOs, and individuals occupying authority roles (subject matter experts or authorities). 

Analysis Pt. 2

Our results show how actors can be associated with different numbers of topics, ranging from generalists (actors associated to many topics) to specialists (actors associated to a small subset of topics), adding another element in our understanding of the roles actors have in the system. Automated topic modeling opens the door for identifying groups of actors associated with specific issues in the governance system, and for understanding the most pressing challenges regarding wildfire governance. This approach provides an avenue for refining actor identification when studying intractable or interdependent governance problems. 

 

Key Findings and Recommendations for Practice