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A Signal Detection Framework to Evaluate Models of Tree Mortality Following Fire Damage

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Abstract:

Signal detection theory provides an appropriate framework to evaluate the performance of various individual tree mortality models. Receiver operating characteristic (ROC) curves show the tradeoffs that are possible by varying the decision criteria, show predictive performance with respect to chance, and show the difference between various models. Two ROC curves were generated to predict ponderosa pine mortality following fall prescribed fires in northern Idaho. One ROC curve was developed from rules of thumb using percent crown scorch. A second ROC curve was developed from a logistic mortality model using diameter at breast height and scorch height. Overall, percent crown scorch is a better predictor of mortality than scorch height, and thus should be used to plan and conduct salvage operations in ponderosa pine following a fire. Because of the difficulties involved in predicting percent crown scorch before a fire, the logistic model based on scorch height can be used to plan understory prescribed fires. For. Sci. 36(1):66-76.

Keywords: Fire effects; logistic regression; ponderosa pine; prescribed fire

Document Type: Journal Article

Affiliations: Associate Dean of Research, College of Forestry, Wildlife, and Range Sciences, University of Idaho, Moscow, ID 83843

Publication date: 1990-03-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2015 2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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