You are here

Karen C. Short

Research Ecologist

800 East Beckwith Avenue
Missoula, MT 59801
Contact Karen C. Short

Current Research

My current research is centered around a geospatial fire modeling system (FSim) that is used to map wildfire hazard for risk assessment and other applications ( To support this work I have developed and maintain a spatial database of wildfires in the US, 1992-2015, including 1.88 million records from federal, state, and local wildland fire reporting systems (


  • University of Montana, Missoula, Ph.D., Organismal Biology and Ecology, 2003
  • University of Arizona, Tucson, B.S., Wildlife and Fisheries Science, 1996
  • Featured Publications


    St. Denis, Lise A.; Mietkiewicz, Nathan P.; Short, Karen C.; Buckland, Mollie; Balch, Jennifer K., 2020. All-hazards dataset mined from the US National Incident Management System 1999-2014
    Parisien, Marc-Andre; Ager, Alan; Barros, Ana M.; Dawe, Denyse; Erni, Sandy; Finney, Mark A.; McHugh, Charles W.; Miller, Carol L.; Parks, Sean A.; Riley, Karin; Short, Karen C.; Stockdale, Christopher A.; Wang, Xianli; Whitman, Ellen, 2020. Commentary on the article “Burn probability simulation and subsequent wildland fire activity in Alberta, Canada - Implications for risk assessment and strategic planning” by J. L. Beverly and N. McLoughlin
    Short, Karen C.; Ahrens, Marty; Harris, Sarah; San-Miguel-Ayanz, Jesus, 2020. Fire data
    Haynes, Katharine; Short, Karen C.; Xanthopoulos, Gavriil; Viegas, Domingos; Ribeiro, Luis Mario; Blanchi, Raphaele, 2020. Wildfires and WUI fire fatalities
    Calkin, Dave E.; Short, Karen C.; Traci, Meg, 2019. California wildfires [Chapter 7]
    Ager, Alan; Palaiologou, Palaiologos; Evers, Cody R.; Day, Michelle A.; Ringo, Chris; Short, Karen C., 2019. Wildfire exposure to the wildland urban interface in the western US
    Riley, Karin; Williams, A. Park; Urbanski, Shawn P.; Calkin, Dave E.; Short, Karen C.; O'Connor, Christopher D., 2019. Will landscape fire increase in the future? A systems approach to climate, fire, fuel, and human drivers
    Pioneer Fire in Idaho, night time photo of active fire running up hill
    The USDA Forest Service Rocky Mountain Research Station recently released a new General Technical Report, GTR-392, Cross-boundary Wildfire and Community Exposure: A Framework and Application in the Western US. The publication describes the development and application of a framework to assess cross-boundary wildfire exposure for the Western U.S. with the purpose of mapping potential fire transmission among public and private lands, and identifying areas where ignitions are most likely to expose communities to wildfire.  
    Rocky Mountain Research Station scientists have developed a simulation system designed to estimate wildfire risk for Fire Planning Units (FPUs) across the conterminous United States. This research demonstrates a practical approach to using fire simulations at very broad scales for operational planning and ecological research. Findings are being used in national wildfire decision support applications such as the Forest Service and Department of Interior Hazardous Fuel Prioritization and Allocation System, and to create national maps of wildfire potential. 
    A project led by Rocky Mountain Research Station scientist Karen Short provides one-stop access to mappable information about 22 years of U.S. wildfires from federal, state, and local fire reporting systems.
    The RMRS Wildfire Risk Management Team has been instrumental in the development and maintenance of national fire and vegetation datasets that are foundational to U.S. wildfire risk science. The assessment of contemporary wildfire hazard--a fundamental part of the risk assessment framework--is not possible without a reliable source of historical fire-occurrence data.
    Effective and efficient risk based management requires integrated knowledge, systems and planning tools that explore the interaction of the full range of land and fire management activities. The Wildfire Risk Management Team is working with managers to develop and demonstrate the power of integrating fire-risk science across the full range of fire management activities from local to national scales. Improved linkages between landscape fire potential and land management objectives will have profound effects on the efficiency of the full range of fire management activities. 
    Effective and efficient risk-based management requires integrated knowledge, systems and planning tools that explore the interaction of the full range of land and fire management activities. The Wildfire Risk Management team is working to develop and demonstrate the power of integrating fire-risk science across the full range of fire management activities. This work will include the first pilot study of changes in wildfire risk across time, using the prototype LANDFIRE time series dataset, created specifically for the study landscape.
    There is a wealth of U.S. wildfire activity data available for analyses, but users must be aware of inherent reporting biases, inconsistencies, and uncertainty in the data in. Information is generally acquired from archival summary reports of the federal or interagency fire organizations. This project provides an overview of sources of data for U.S. wildfire activity analyses that highlights major reporting biases, inconsistencies, and uncertainty. 
    The Wildfire Risk Management Team is an interdisciplinary team that explores wildfire management through the lenses of risk analysis, economics, decision science, and landscape ecology to improve the scientific basis for the full range of wildfire management decisions. Primary research topics include integrated spatial risk assessment modeling and planning, econometric modeling of fire management expenditures, effectiveness of suppression resource utilization, organizational structure and managerial incentive systems, and performance measurement.
    This work provides an overview of sources of data for United States wildfire activity analyses and highlights major reporting biases, inconsistencies, and uncertainty within data source.  

    RMRS Science Program Areas: 
    Fire, Fuel and Smoke