Predictive accuracy of post‐fire conifer death declines over time in models based on crown and bole injury

Abstract

A key uncertainty of empirical models of post‐fire tree mortality is understanding the drivers of elevated post‐fire mortality several years following fire, known as delayed mortality. Delayed mortality can represent a substantial fraction of mortality, particularly for large trees that are a conservation focus in western US coniferous forests. Current post‐fire tree mortality models have undergone limited evaluation of how injury level and time since fire interact to influence model accuracy and predictor variable importance. Less severe injuries potentially serve as an indicator for vulnerability to additional stressors such as bark beetle attack or moisture stress. We used a collection of 164,293 individual tree records to examine post‐fire tree mortality in eight western USA conifers: Abies concolor, Abies grandis, Calocedrus decurrens, Larix occidentalis, Pinus contorta, Pinus lambertiana, Pinus ponderosa, and Pseudotsuga menziesii. We evaluated the importance of fire injury predictors on discriminating between surviving trees versus immediate and delayed post‐fire mortality. We fit balanced random forest models for each species using cumulative tree mortality from 1 to 5‐years post‐fire. We compared these results to multi‐class random forest models using first‐year mortality, 2–5‐year mortality, and survival 5‐years post‐fire as a response variable. Crown volume scorched, diameter at breast height, and relative bark char height, were used as predictor variables. The cumulative mortality models all predicted trees that died within 1‐year of fire with high accuracy but failed to predict 2–5‐year mortality. The multi‐class models were an improvement but had lower accuracy for predicting 2–5‐year mortality. Multi‐class model accuracies ranged from 85% to 95% across all species for predicting 1‐year post‐fire mortality, 42%–71% for predicting 2–5‐year mortality, and 64%–85% for predicting trees that lived past 5‐years. Our study highlights the differences in tree species tolerance to fire injury and suggests that including second‐order predictors such as beetle attack or climatic water stress before and after fire will be critical to improve accuracy and better understand the mechanisms and patterns of fire‐caused tree death. Random forest models have potential for management applications such as post‐fire harvesting and simulating future stand dynamics.

Linking crown fire likelihood with post-fire spectral variability in Mediterranean fire-prone ecosystems

“…surface, crown) after wildfire extinction. Such knowledge would be of value, for example, in (1) testing the accuracy of fire behaviour models (Alexander and Cruz 2012), (2) providing insights on pre-fire fuel conditions conducive to extreme fire behaviour and severe ecological impacts (Dimitrakopoulos et al 2007), (3) evaluating fuel treatment effectiveness (Cruz et al 2004;Hu et al 2019), and (4) estimating post-fire ecosystem responses including delayed tree mortality (Shearman et al 2023). Indeed, several authors suggested that physically meaningful variables of actual fire effects that can be used as a proxy for fire type, such as crown fraction burned (CFB), can be more readily translated into management applications (Woolley et al 2012;Hood et al 2018), as opposed to integrative fire severity indices (e.g.…”

Empirical Modelling of Stem Cambium Heating Caused by Prescribed Burning in Mediterranean Pine Forest

“…Stem char height and percentage of bole char height have commonly been used as a proxies for potential cambium damage in post-fire mortality prediction [57,[79][80][81][82]. However, the use of these variables has been criticized due to their frequent poor or inconsistent performance [17,83,84]. Furthermore, stem char height has also been used as a proxy for flame length and fireline intensity [85].…”

“…Bark char severity [86], an indicator of char depth used in mortality prediction studies [16,57,70], has been found to be significantly related to the probability of cambium necrosis [8]. Crown scorch height and percentage of crown volume or length scorched are by far the most commonly used variables to predict post-fire tree mortality [83,87,88], both alone and in combination with stem char height [62,89]. Since crown scorch does not describe the actual amount of crown foliage or buds affected by fire [90], monitoring litterfall biomass [31,91] can also help to determine the level of crown damage and can serve as a proxy for fire severity.…”