A review of logistic regression models used to predict post-fire tree mortality of western North American conifers

Abstract

Logistic regression models used to predict tree mortality are critical to post-fire management, planning prescribed burns and understanding disturbance ecology. We review literature concerning post-fire mortality prediction using logistic regression models for coniferous tree species in the western USA. We include synthesis and review of: methods to develop, evaluate and interpret logistic regression models; explanatory variables in logistic regression models; factors influencing scope of inference and model limitations; model validation; and management applications. Logistic regression is currently the most widely used and available technique for predicting post-fire tree mortality. Over 100 logistic regression models have been developed to predict post-fire tree mortality for 19 coniferous species following wild and prescribed fires. The most widely used explanatory variables in post-fire tree mortality logistic regression models have been measurements of crown (e.g. crown scorch) and stem (e.g. bole char) injury. Prediction of post-fire tree mortality improves when crown and stem variables are used collectively. Logistic regression models that predict post-fire tree mortality are the basis of simple field tools and contribute to larger fire-effects models. Future post-fire tree mortality prediction models should include consistent definition of model variables, model validation and direct incorporation of physiological responses that link to process modelling efforts.

Tree survival scales to community-level effects following mixed-severity fire in a mixed-conifer forest

“…Numerous previous studies have investigated individual tree survival (or mortality) following both wildfire and prescribed fire (Woolley et al, 2012). However, such tree-level studies rarely consider controls on, or effects of, fires at larger spatial extents, making this body of work difficult to integrate with community and landscape fire ecology theory (McKenzie et al, 2011).…”

“…Because individual trees are embedded in communities that experience variable fire intensity and behavior, we also included a remotely-sensed measure of short-term (i.e., first year) burn severity to investigate if long-term survival occurred even in patches of initial high burn severity. A secondary objective was to investigate post-fire tree survival in western larch/mixed-conifer forests, which has been identified in a recent literature review as a high priority for research (Woolley et al, 2012).…”

“…Ecological effects of fire can be characterized by mechanisms that operate across spatial scales that range from <0.0001 to >10,000 hectares (McKenzie et al, 2011). Mixed-severity fires emerge from heterogeneity in patterns of individual tree mortality (Woolley et al, 2012) and large-scale drivers of burn severity, such as topography and climatic variation (Lutz et al, 2009;Cansler and McKenzie, 2014).…”

Survival to prescribed fire of plantation-grown Corsican black pine in northern Portugal

“…Crown scorch metrics describe the immediate loss of photosynthetic capacity and are common to most post fire tree mortality models (Fernandes et al 2008;Woolley et al 2012). Crown scorch data was not acquired in this study.…”

Mortality Assessment of Redwood and Mixed Conifer Forest Types in Santa Cruz County Following Wildfire

“…Landowners and foresters needed a reliable method to predict tree mortality resulting from wildfire for the redwood region. To date, there was only one publication, Finney (1993), that provided a type of logistic regression model to evaluate tree mortality in the redwood region following a prescribed burn (Woolley, 2012). Certain model variables were derived from Finney (1993) and incorporated into the MA model.…”