A large database supports the use of simple models of post-fire tree mortality for thick-barked conifers, with less support for other species

C. Alina Cansler, Sharon M. Hood, Phillip J. van Mantgem, J. Morgan Varner

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Predictive models of post-fire tree and stem mortality are vital for management planning and understanding fire effects. Post-fire tree and stem mortality have been traditionally modeled as a simple empirical function of tree defenses (e.g., bark thickness) and fire injury (e.g., crown scorch). We used the Fire and Tree Mortality database (FTM)—which includes observations of tree mortality in obligate seeders and stem mortality in basal resprouting species from across the USA—to evaluate the accuracy of post-fire mortality models used in the First Order Fire Effects Model (FOFEM) software system. The basic model in FOFEM, the Ryan and Amman (R-A) model, uses bark thickness and percentage of crown volume scorched to predict post-fire mortality and can be applied to any species for which bark thickness can be calculated (184 species-level coefficients are included in the program). FOFEM (v6.7) also includes 38 species-specific tree mortality models (26 for gymnosperms, 12 for angiosperms), with unique predictors and coefficients. We assessed accuracy of the R-A model for 44 tree species and accuracy of 24 species-specific models for 13 species, using data from 93 438 tree-level observations and 351 fires that occurred from 1981 to 2016. Results: For each model, we calculated performance statistics and provided an assessment of the representativeness of the evaluation data. We identified probability thresholds for which the model performed best, and the best thresholds with either ≥80% sensitivity or specificity. Of the 68 models evaluated, 43 had Area Under the Receiver Operating Characteristic Curve (AUC) values ≥0.80, indicating excellent performance, and 14 had AUCs
Original languageAmerican English
JournalFire Ecology
Volume16
Issue number1
DOIs
StatePublished - Jan 2020

Keywords

  • AUC
  • ROC analysis
  • bark thickness
  • crown scorch
  • decision support system
  • model evaluation
  • prescribed fire
  • sensitivity
  • specificity
  • threshold
  • top-kill
  • wildland fire

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