Abstract

Accurately predicting the mortality of trees that initially survive a fire event is important for management, such as planning post-fire salvage, planting, and prescribed fires. Although crown scorch has been successfully used to predict post-fire mortality (greater than one-year post-fire), it remains unclear whether other first-order fire effect metrics (e.g., stem char) and information on growing conditions can improve such predictions. Droughts can also elevate mortality and may interact, synergistically, with fire effects to influence post-fire tree survival. We used logistic regression to test whether drought exposure, as indicated by summarized monthly Palmer Drought Severity Index (PDSI) over ten-years could improve predictions of delayed mortality (4–9 years post-fire) at the individual tree level in fire-affected forest inventory and analysis (FIA) plots in California (USA). We included crown scorch, bark thickness, stem char, soil char, slope, and aspect in the model as predictors. We selected the six most prevalent species to include in the model: canyon live oak, Douglas-fir, Jeffrey pine, incense-cedar, ponderosa pine, and white fir. Mean delayed mortality, based on tree count, across all FIA plots across all tree species and plots was 17%, and overall accuracy was good (AUC = 79%). Our model performed well, correctly predicting survivor trees (sensitivity of 0.98) but had difficulty correctly predicting the smaller number of mortality trees (specificity of 0.27) at the standard probability=0.5 mortality threshold. Crown scorch was the most influential predictor of tree mortality. Increasing crown scorch was associated with greater risk of delayed mortality for all six species, with trees exhibiting over 75% crown scorch having a probability of dying that exceeded 0.5. Increasing levels of stem char and soil char (first order indicators) were associated with increasing mortality risk but to less effect than crown scorch. We expected that greater drought exposure would increase delayed post-fire mortality, but we found that increasing drought exposure (median and minimum PDSI) was associated with a modest decrease in post-fire mortality. However, we did find that trees with high levels of crown scorch were less likely to survive with increasing drought exposure (median PDSI). Delayed mortality risk decreased as terrain slope increased. Taken together, our results suggest that trees with substantial crown damage may be more vulnerable to delayed mortality if exposed to drought and that crown scorch is an effective post-fire mortality predictor up to 10 years post-fire.

Highlights

  • The 2012–2016, California drought and associated tree mortality [1] brought renewed urgency to concerns that post-fire tree mortality can be exacerbated by drought [2,3]

  • We expected that greater drought exposure would increase delayed post-fire mortality, but we found that increasing drought exposure was associated with a modest decrease in post-fire mortality

  • There was the significant interaction between crown scorch and median Palmer Drought Severity Index (PDSI) (p = 0.0004), which we presented to illustrate the relationship between drought and post-fire mortality

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Summary

Introduction

The 2012–2016, California drought and associated tree mortality [1] brought renewed urgency to concerns that post-fire tree mortality can be exacerbated by drought [2,3]. Forest managers need tools to account for drought effects on tree mortality in everything from planning fuel hazard reduction treatments to post-fire recovery [4]. Post-fire mortality models typically focus on first-order effects such as crown scorch, not second-order factors such as drought [5]. The commonly used Ryan-Amman model is designed to accurately predict immediate post-fire mortality using two first-order metrics: crown scorch and fire resistance (bark thickness). Accounting for drought is important when predicting delayed mortality because trees surviving a wild-fire may be more sensitive to fire-caused injury following episodes of drought-stress and associated hydraulic failure [3,7]. Models that do not incorporate second-order effects such as drought or insect damage might underpredict mortality occurring within the first decade post-fire

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