Wildfire in Colorado: Understanding the role of social interactions and risk perceptions in shaping households’ mitigation behaviors Katie Dickinson Working with Hannah Brenkert-Smith, Patricia Champ, and Nicholas Flores

Katie Dickinson, environmental economist Research interest: What motivates individual actions that affect environmental, health, and economic outcomes? Past projects: -Sanitation choices in India -Malaria prevention and treatment behaviors in Tanzania -Mosquito control in Wisconsin Current projects at NCAR: -Wildfire mitigation behaviors in Colorado -Cookstove use and meningitis in Ghana -Urban vulnerability to climate change -Hurricane warning information and evacuation decisions in Miami Overarching questions: How do social networks shape behaviors? How can a better understanding of human behaviors inform more effective policies and programs? What benefits and costs do people consider when making decisions in the face of risk? Relevance to NCAR: Understanding the societal impacts of weather and climate requires an understanding of behavioral responses to risk

Background on Wildfire Wildfire as part of the natural regime in CO, but combination of factors affecting frequency and impacts Centralized policies & government action can’t fix the problem… homeowners’ behaviors on private property are key What drives these behaviors?

A Simple Economic Model No FireFire Do not mitigateV0V0 V 0 – D MitigateV 0 – c m V 0 – c m – D m If the perceived probability of having a fire on your property is p f, you will choose to mitigate if: C m < p f (D – D m ) Cost of mitigation < Prob of fire * ∆ in damages We can get more people to mitigate by: -Decreasing mitigation costs (c m ) -Increasing perceived probability of fire (p f ) -Increasing perceived damages from fire (D) and/or perceived effectiveness of mitigation (D – D m )

The Role of Social Interactions Mitigation choices of neighbors and social contacts can affect risk perceptions: – How likely is it that a fire will occur? (p f ) – How bad will it be if it does? (D – D m ) – How much will my actions decrease damages in the event of a fire? (D, D – D m ) But social interactions can also affect costs: – What kinds of mitigation options are available? – How do I go about mitigating? – How much will mitigation decrease the quality of my landscape? – Will I face social costs if I do/don’t mitigate? – Will you help me? C m < p f (D – D m )

The Role of Social Interactions M Fire Mitigation Behaviors effects operating through other social pathways, e.g., learning, norms R Risk Perceptions S Social Interactions effects operating through risk perceptions

Wildfire Study Overview Phase 1: Analysis of 2007 and 2010 Boulder & Larimer County datasets (now – Spring 2012) – What relationships between S, R, and M do we observe in a sample of 700 homeowners? Phase 2: Experimental studies in 3-4 Western Slope communities (site selection and initial interviews Summer 2011, NSF proposal Nov ’11) – If we change S, R, or M for some people, how do others’ behaviors change?

Boulder/Larimer County Analysis M Structural Defensive space (30 ft) Defensive space ( ft) R Fire probability Fire impacts S Physical proximity “Generic” social interactions (participation in community groups) Fire-related interactions (talking about fire, attending fire events) Perceptions of neighbors’ behaviors X County, Age, Gender, Variables: Analyses: Social amplification of risk? R=f(S, X) Determinants of mitigation? M=f(S, X) M=f(R, X) M=f(S, R, X)

Results: Social Amplification of Risk Both formal and informal interactions associated with risk perceptions Fire-related interactions matter more than generic interactions What neighbors do may matter more than what we talk about… actions speak louder than words? Risk Perceptions (r) fireprobfiredestroyhousefiredamageneighb Social interactions (s) close neighbns community group+**ns talk fire+***+*+** fire event+***ns+*** neighb act first-*ns neighb dense veg+***

Results: Mitigation Behaviors StructuralDspace30Dspace100 Social (S) closeneighbns-*-*** comgroupns talkfirens +*** fireeventns+***ns neighbfirstns-*-*** neighbdensveg+**+*** Risk (R) fireprobns+***ns fireimpactindexns Results depend on how mitigation is measured: – Neither S nor R strongly associated with structural – Both S and R associated with dspace30 – Only S associated with dspace100 Evidence for substitution? As neighbors do more, I do less?

Boulder/Larimer Limitations and Opportunities Cross sectional data makes causality very hard to determine Possible solution: 2010 data… Looking at changes in behavior over time An alternative direction… cluster analysis – Are there different types of individuals that show different S-R-M patterns? M R S

Experiments Computer-based experiments: – Participants choose mitigation on parcel – Fire simulated & respondents observe results – Experimental conditions: Collaboration between participants? Decisions simultaneous or in sequence? Aid of wildfire expert? Field experiments – Baseline data includes full census with all social linkages – Incentives randomly provided to community members, then observe how incentives affect own & contacts’ behaviors

Questions or suggestions welcome!