Travis B. PaveglioUniversity of Montana

Washington State University

Forest Community Vulnerability and Adaptive Capacity Workshop

November, 7 2011

Simulating Future Vulnerability

and Adaptive CapacityPerspectives from projects on wildfire

and climate change

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 management

decisions that influence wildfire risk in WUI, such as subdivision regulations, building materials, fuels treatment, etc.

Data collected about existing management actions, change over time

A Simplified Illustration

Adaptive Capacity and 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”

The line between flexibility and vagueness

Operating at scales of influence

Building Better Assessments

Questions?

travis.paveglio@cfc.umt.edu