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Simulating Future Vulnerability and Adaptive Capacity. Perspectives from projects on wildfire and climate change. Travis B. Paveglio University of Montana Washington State University Forest Community Vulnerability and Adaptive Capacity Workshop November, 7 2011. The FIRECLIM Project.
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Simulating Future Vulnerability and Adaptive Capacity Perspectives from projects on wildfire and climate change Travis B. Paveglio University of Montana Washington State University Forest Community Vulnerability and Adaptive Capacity Workshop November, 7 2011
The FIRECLIM Project Simulate how various factors interact to influence future wildfire risk in the Flathead County WUI Actions and outputs are simulated at small scales and aggregated to different levels
Uncertainty and Action • Positing “alternative futures” to explore uncertain future impacts… • Climate change • Wildfire intensity • Growth and development rates • …and potential human behaviors/actions • Forest treatments • Land use planning regulations • Homeowner mitigations
Simulating Influences • Three primary sub-models • Land use change model (RECID2) • Climate, fire and vegetation models (Fire-BGCv2/FSIM) • Agent-Based Model (ABM)
Measuring Vulnerabilities • Risk measures account for both the expected losses and expected benefits of wildfires • “Risk” varies among the three agents • Expected residential losses from wildfire (E[RLW]) • Historical range of variability (HRV) • Costs to implement new regulations, mitigations or forest management • Commercial timber losses
Simulating Adaptive Actions Local agents make iterative managementdecisions that influence wildfire risk in WUI, such as subdivision regulations, building materials, fuels treatment, etc. Data collected about existing management actions, change over time
Adaptive Capacityand Adaptive Actions(ABM) • Three types of human decision makers or agents acting at different scales: • Land and wildland fire management agencies (6) • Community and regional planners (1) • Homeowners/residents (20,000) • But how to integrate adaptive capacity?
Assessing the “Intangibles” Characteristics that facilitate future potential for adaptation Focus groups (3) with local key informants Ratings become weighted consideration in ABM decision rules
Decision rules use probability cutoffs or multi-criterion decision making methods
Building Better Assessments Systematically documenting the outcomes of interacting factors Integrating dynamic simulations and contextual approaches Building better data, especially for the “intangibles”
Building Better Assessments The line between flexibility andvagueness Operating at scales of influence
Questions? travis.paveglio@cfc.umt.edu