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Advancing effects analysis for integrated, large-scale wildfire risk assessment

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Abstract

In this article, we describe the design and development of a quantitative, geospatial risk assessment tool intended to facilitate monitoring trends in wildfire risk over time and to provide information useful in prioritizing fuels treatments and mitigation measures. The research effort is designed to develop, from a strategic view, a first approximation of how both fire likelihood and intensity influence risk to social, economic, and ecological values at regional and national scales. Three main components are required to generate wildfire risk outputs: (1) burn probability maps generated from wildfire simulations, (2) spatially identified highly valued resources (HVRs), and (3) response functions that describe the effects of fire (beneficial or detrimental) on the HVR. Analyzing fire effects has to date presented a major challenge to integrated risk assessments, due to a limited understanding of the type and magnitude of changes wrought by wildfire to ecological and other nonmarket values. This work advances wildfire effects analysis, recognizing knowledge uncertainty and appropriately managing it through the use of an expert systems approach. Specifically, this work entailed consultation with 10 fire and fuels program management officials from federal agencies with fire management responsibilities in order to define quantitative resource response relationships as a function of fire intensity. Here, we demonstrate a proof-of-concept application of the wildland fire risk assessment tool, using the state of Oregon as a case study.

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References

  • Ager, A. A., Finney, M. A., Kerns, B. K., & Maffei, H. (2007). Modeling wildfire risk to northern spotted owl (Strix occidentalis caurina) habitat in Central Oregon, USA. Forest Ecology and Management, 246(1), 45–56.

    Article  Google Scholar 

  • Ager, A. A., Valliant, N. M., & Finney, M. A. (2010a). Analyzing management tradeoffs between forest restoration and wildfire mitigation in a wildland urban interface. Forest Ecology and Management, 259, 1556–1570.

    Article  Google Scholar 

  • Ager, A. A., Finney, M. A., & McMahan, A. (2010b). Measuring the effect of fuel treatments on forest carbon using landscape risk analysis. Natural Hazards and Earth Systems Science (in press).

  • Alho, J. M., & Kangas, J. (1997). Analyzing uncertainties in experts’ opinions of forest plan performance. Forest Science, 43(4), 521–528.

    Google Scholar 

  • Amacher, G. S., Malik, A. S., & Haight, R. G. (2005). Forest landowner decisions and the value of information under fire risk. Canadian Journal of Forest Research, 35(11), 2603–2615.

    Article  Google Scholar 

  • Andrews, P., Finney, M., & Fischetti, M. (2007). Predicting wildfires. Scientific American, August, 47–55.

  • Ascough, J. C. II, Maier, H. R., Ravalico, J. K., & Strudley, M. W. (2008). Future research challenges for incorporation of uncertainty in environmental and ecological decision-making. Ecological Modelling, 219(3–4), 383–399.

    Article  Google Scholar 

  • Bailey, R. G., McNab, W. H., Avers, P. E., & King, T. (1994). Ecoregions and subregions of the United States (Lower 48): USDA Forest Service, Washington, DC. Data available at: http://www.fs.fed.us/rm/ecoregions/products/map-ecoregions-united-states. Last Accessed 16 Sept 2010.

  • Bonazountas, M., Kallidromitou, D., Kassomenosc, P., & Passas, N. (2007). A decision support system for managing forest fire casualties. Journal of Environmental Management, 84, 412–418.

    Article  Google Scholar 

  • Braga, J., & Starmer, C. (2005). Preference anomalies, preference elicitation, and the discovered preference hypothesis. Environmental and Resource Economics, 32, 55–89.

    Article  Google Scholar 

  • Brillinger, D. R., Autrey, B. S., & Cattaneo, M. D. (2009). Probabilistic risk modeling at the wildland urban interface: The 2003 Cedar Fire. Environmetrics, 20, 607–620.

    Article  Google Scholar 

  • Brown, T. C., Kingsley, D., Peterson, G. L., Flores, N. E., Clarke, A., & Birjulin, A. (2008). Reliability of individual valuations of public and private goods: Choice consistency, response time, and preference refinement. Journal of Public Economics, 92, 1595–1606.

    Article  Google Scholar 

  • Calkin, D., Ager, A. A., Gilbertson-Day, J., Scott, J. H., Finney, M. A., Schrader-Patton, C., et al. (2010). Wildland fire risk and hazard: Procedures for the first approximation (p. 62). Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, RMRS-GTR-235.

  • Calkin, D. E., Hummel, S. S., & Agee, J. K. (2005). Modeling trade-offs between fire threat reduction and late-seral forest structure. Canadian Journal of Forest Resources, 35(11), 2562–2574.

    Article  Google Scholar 

  • Diaz-Balteiro, L., & Romero, C. (2008). Making forestry decisions with multiple criteria: A review and an assessment. Forest Ecology and Management, 255, 3222–3241.

    Article  Google Scholar 

  • Fairbrother, A., & Turnley, J. G. (2005). Predicting risks of uncharacteristic wildfires: Application of the risk assessment process. Forest Ecology and Management, 211, 28–35.

    Article  Google Scholar 

  • Finney, M. A. (2002). Fire growth using minimum travel time methods. Canadian Journal of Forest Research, 32(8), 1420–1424.

    Article  Google Scholar 

  • Finney, M. A. (2005). The challenge of quantitative risk analysis for wildland fire. Forest Ecology and Management, 211, 97–108.

    Article  Google Scholar 

  • Finney, M. A., Seli, R. C., McHugh, C. W., Ager, A. A., Bahro, B., & Agee, J. K. (2007). Simulation of long-term landscape-level fuel treatment effects on large wildfires. International Journal of Wildland Fire, 16, 712–727.

    Article  Google Scholar 

  • González, J. R., Kolehmainen, O., & Pukkala, T. (2007). Using expert knowledge to model forest stand vulnerability to fire. Computers and Electronics in Agriculture, 55, 107–114.

    Article  Google Scholar 

  • Government Accountability Office (2007). Lack of clear goals or a strategy hinders federal agencies’ efforts to contain the costs of fighting fires. Government Accountability Office, Technical Report GAO-07–655. Washington, DC. Available: http://www.gao.gov/new.items/d07655.pdf. Last Accessed 03 May 2010.

  • Government Accountability Office (2009). Actions by federal agencies and Congress could mitigate rising fire costs and their effects on other agency programs. Government Accountability Office, Technical Report GAO-09–444T. Washington, DC. Available: http://www.gao.gov/new.items/d09444t.pdf. Last Accessed 03 May 2010.

  • Hessburg, P. F., Reynolds, K. M., Keane, R. E., James, K. M., & Salter, R. B. (2007). Evaluating wildland fire danger and prioritizing vegetation and fuel treatments. Forest Ecology and Management, 247, 1–17.

    Article  Google Scholar 

  • Hirsch, K. G., Corey, P. N., & Martell, D. L. (1998). Using expert judgment to model initial attack fire crew effectiveness. Forest Science, 44(1), 539–549.

    Google Scholar 

  • Hirsch, K. G., Podur, J. A., Jansen, R. D., McAlpine, R. D., & Martell, D. L. (2004). Productivity of Ontario initial attack fire crews: Results of an expert-judgment elicitation study. Canadian Journal of Forest Resources, 34, 705–715.

    Article  Google Scholar 

  • Holmes, T. P., & Boyle, K. J. (2005). Dynamic learning and context-dependence in sequential, attribute-based, stated-preference valuation questions. Land Economics, 81(1), 114–126.

    Google Scholar 

  • Hyde, K., Woods, S. W., & Donahue, J. (2007). Predicting gully rejuvenation after wildfire using remotely sensed burn severity data. Geomorphology, 86(3–4), 496–511.

    Article  Google Scholar 

  • Kaloudis, S., Tocatlidou, A., Lorentzos, N. A., Sideridis, A. B., & Karteris, M. (2005). Assessing wildfire destruction danger: A decision support system incorporating uncertainty. Ecological Modelling, 181, 25–38.

    Article  Google Scholar 

  • Kangas, A. S., & Kangas, J. (2004). Probability, possibility, and evidence: Approaches to consider risk and uncertainty in forestry decision analysis. Forest Policy and Economics, 6, 169–188.

    Article  Google Scholar 

  • Keane, R. E., Agee, J. K., Fulé, P., Keeley, J. E., Key, C., Kitchen, S. G., et al. (2008). Ecological effects of large fires on US landscapes: Benefit or catastrophe? International Journal of Wildland Fire, 17(6), 696–712.

    Article  Google Scholar 

  • Kennedy, P. L., & Fontaine, J. B. (2009). Synthesis of knowledge on the effects of fire and fire surrogates on wildlife in U.S. Dry Forests. Oregon State University Agricultural Experiment Station Special Report 1096. Available at: http://ir.library.oregonstate.edu/jspui/bitstream/1957/12625/1/SR1096.pdf. Last Accessed 03 May 2010.

  • Kim, Y., Bettinger, P., & Finney, M. (2009). Spatial optimization of the pattern of fuel management activities and subsequent effects on simulated wildfires. European Journal of Operational Research, 197, 253–265.

    Article  Google Scholar 

  • Konoshima, M., Montgomery, C. A., Albers, H. J., & Arthur, J. L. (2008). Spatial-Endogenous fire risk and efficient fuel management and timber harvest. Land Economics, 84(3), 449–468.

    Google Scholar 

  • Kurtilla, M., Muinonen, E., Leskinen, P., Kilpeläinen, H., & Pykäläinen, J. (2009). An approach for examining the effects of preferential uncertainty on the contents of forest management plan at stand and holding level. European Journal of Forest Research, 128(1), 37–50.

    Article  Google Scholar 

  • Mendoza, G. A., & Martins, H. (2006). Multi-criteria decision analysis in natural resource management: A critical review of methods and new modeling paradigms. Forest Ecology and Management, 230, 1–22.

    Article  Google Scholar 

  • Miller, C., Parisien, M.-A., Ager, A. A., & Finney, M. A. (2008). Evaluating spatially-explicit burn probabilities for strategic fire management planning. WIT Transactions on Ecology and the Environment, 119, 245–252.

    Article  Google Scholar 

  • Moody, J. A., & Martin, D. A. (2009). Synthesis of sediment yields after wildland fire in different rainfall regimes in the western United States. International Journal of Wildland Fire, 18, 96–115.

    Article  Google Scholar 

  • Nadeau, L. B., & Englefield, P. (2006). Fine-Resolution mapping of wildfire fuel types for Canada: Fuzzy logic modeling for an alberta pilot area. Environmental Monitoring and Assessment, 120, 127–152.

    Article  CAS  Google Scholar 

  • Rideout, D. B., Ziesler, P. S., Kling, R., Loomis, J. B., & Botti, S. J. (2008). Estimating rates of substitution for protecting values at risk for initial attack planning and budgeting. Forest Policy and Economics, 10, 205–219.

    Article  Google Scholar 

  • Sikder, I. U., Mal-Sarkar, S., & Mal, T. K. (2006). Knowledge-based risk assessment under uncertainty for species invasion. Risk Analysis, 26(1), 239–252.

    Article  Google Scholar 

  • U.S. Environmental Protection Agency (U.S. EPA) (1998). Guidelines for ecological risk assessment. US Environmental Protection Agency, Washington, DC, EPA/630/R-95/002F, http://oaspub.epa.gov/eims/eimscomm.getfile?p_download_id=36512. Last Accessed 23 Feb 2010.

  • USDA Office of Inspector General (2006). Audit report: Forest service large fire suppression costs. United States Department of Agriculture, Office of Inspector General, Report No. 08601–44-SF. (Washington, DC).

  • Vadrevu, K. P., Eaturu, A., & Badarinath, K. V. S. (2009). Fire risk evaluation using multicriteria analysis—a case study. Environmental Modeling and Assessment, 166(1–4), 223–239. doi:10.1007/s10661-009-0997-3.

    Google Scholar 

  • Venn, T. J., & Calkin, D. E. (2010). Accommodating non-market values in evaluation of wildfire management in the United States: Challenges and opportunities. International Journal of Wildland Fire (in press).

  • Wei, Y., Rideout, D., & Kirsch, A. (2008). An optimization model for locating fuel treatments across a landscape to reduce expected fire losses. Canadian Journal of Forest Research, 38, 868–877.

    Article  Google Scholar 

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Authors and Affiliations

  1. Rocky Mountain Research Station, USDA Forest Service, Missoula, MT, USA

    Matthew P. Thompson & David E. Calkin

  2. College of Forestry and Conservation, University of Montana, Missoula, MT, USA

    Julie W. Gilbertson-Day

  3. Western Wildland Environmental Threat Assessment Center, USDA Forest Service, Prineville, OR, USA

    Alan A. Ager

Authors
  1. Matthew P. Thompson
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  2. David E. Calkin
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  3. Julie W. Gilbertson-Day
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  4. Alan A. Ager
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Correspondence to Matthew P. Thompson.

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Thompson, M.P., Calkin, D.E., Gilbertson-Day, J.W. et al. Advancing effects analysis for integrated, large-scale wildfire risk assessment. Environ Monit Assess 179, 217–239 (2011). https://doi.org/10.1007/s10661-010-1731-x

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