Predicting Post-Fire Tree Mortality for 12 Western US Conifers Using the First Order Fire Effects Model (FOFEM)

Hood, Sharon M.; Lutes, Duncan C.

doi:10.4996/fireecology.130290243

Cited by 25 publications

(32 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We do not presume that the variables used in this study represent all of the potential influences on individual post‐fire tree mortality. Factors affecting post‐fire conditions (e.g., post‐fire climate, bark beetle attack) may be useful for specifically describing tree mortality but not predicting fire effects (Hood and Lutes ). For example, nearly all of our trees that were dead at the time of our field observations showed symptoms of bark beetle activity, although we cannot be certain if these symptoms were present when trees were originally determined to be dead.…”

Section: Discussionmentioning

confidence: 99%

“…). The relatively few accuracy assessments of empirical model predictions have been mostly favorable, but additional variables can increase model accuracy (e.g., cambial kill, bark beetle attack; Hood and Lutes ). As with any empirical model, the accuracy of post‐fire tree mortality models are likely to suffer when circumstances depart from conditions under which the models were developed.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Pre‐fire drought and competition mediate post‐fire conifer mortality in western U.S. National Parks

Mantgem

Falk

Williams

et al. 2018

Ecological Applications

View full text Add to dashboard Cite

Tree mortality is an important outcome of many forest fires. Extensive tree injuries from fire may lead directly to mortality, but environmental and biological stressors may also contribute to tree death. However, there is little evidence showing how the combined effects of two common stressors, drought and competition, influence post-fire mortality. Geographically broad observations of three common western coniferous trees subjected to prescribed fire showed the likelihood of post-fire mortality was related to intermediate-term (10 yr) pre-fire average radial growth, an important component of tree vigor. Path analysis showed that indices of competition and drought stress prior to fire can be described in terms of joint effects on growth, indirectly affecting post-fire mortality. Our results suggest that the conditions that govern the relationship between growth and mortality in unburned stands may also apply to post-fire environments. Thus, biotic and abiotic changes that affect growth negatively (e.g., drought stress) or positively (e.g., growth releases following thinning treatments) prior to fire may influence expressed fire severity, independent of fire intensity (e.g., heat flux, residence time). These relationships suggest that tree mortality may increase under stressful climatic or stand conditions even if fire behavior remains constant.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Pre‐fire drought and competition mediate post‐fire conifer mortality in western U.S. National Parks

Mantgem

Falk

Williams

et al. 2018

Ecological Applications

View full text Add to dashboard Cite

show abstract

“…(Parker et al 2006, Kane et al 2017b. Several post-fire mortality models include beetle attacks(Woolley et al 2012, Hood andLutes 2017). Because bark beetles require living trees with healthy phloem to reproduce, trees killed immediately by fire are not suitable hosts.…”

mentioning

confidence: 99%

Fire and tree death: understanding and improving modeling of fire-induced tree mortality

Hood

Varner

Mantgem

et al. 2018

Environ. Res. Lett.

178

169

View full text Add to dashboard Cite

Each year wildland fires kill and injure trees on millions of forested hectares globally, affecting plant and animal biodiversity, carbon storage, hydrologic processes, and ecosystem services. The underlying mechanisms of fire-caused tree mortality remain poorly understood, however, limiting the ability to accurately predict mortality and develop robust modeling applications, especially under novel future climates. Virtually all post-fire tree mortality prediction systems are based on the same underlying empirical model described in Ryan and Reinhardt (1988 Can. J. For. Res. 18 1291-7), which was developed from a limited number of species, stretching model assumptions beyond intended limits. We review the current understanding of the mechanisms of fire-induced tree mortality, provide recommended standardized terminology, describe model applications and limitations, and conclude with key knowledge gaps and future directions for research. We suggest a two-pronged approach to future research: (1) continued improvements and evaluations of empirical models to quantify uncertainty and incorporate new regions and species and (2) acceleration of basic, physiological research on the proximate and ultimate causes of fire-induced tree mortality to incorporate processes of tree death into models. Advances in both empirical and process fire-induced tree modeling will allow creation of hybrid models that could advance understanding of how fire injures and kills trees, while improving prediction accuracy of fire-driven feedbacks on ecosystems and landscapes, particularly under novel future conditions.

show abstract

“…Bark thickness appears to be a good predictor of first-order mortality, but the assumed linear relationship between bark thickness and tree diameter is not always correct [55]. Zeibig-Kichas [57] found FVS-FFE tended to under-predict bark thickness in California conifers, which would lead to over-prediction of mortality [1,56], but empirical evidence for this effect is lacking given limited data on bark thickness.…”

Section: The Role Of Ra Equation and Tree Species Effectsmentioning

confidence: 99%

“…Accurate predictions of tree mortality in forests affected by fire are important to land managers and policy-makers charged with planning fuel treatments and assessing risk to life and property if wildfire occurs [1,2]. Estimates of the likelihood of trees dying during, or following, a wildfire can influence decisions about when and how to implement mechanical thinning or other fuel reduction treatments.…”

Section: Introductionmentioning

confidence: 99%

Evaluating Model Predictions of Fire Induced Tree Mortality Using Wildfire-Affected Forest Inventory Measurements

Barker

Fried

Gray

2019

Forests

View full text Add to dashboard Cite

Forest land managers rely on predictions of tree mortality generated from fire behavior models to identify stands for post-fire salvage and to design fuel reduction treatments that reduce mortality. A key challenge in improving the accuracy of these predictions is selecting appropriate wind and fuel moisture inputs. Our objective was to evaluate postfire mortality predictions using the Forest Vegetation Simulator Fire and Fuels Extension (FVS-FFE) to determine if using representative fire-weather data would improve prediction accuracy over two default weather scenarios. We used pre- and post-fire measurements from 342 stands on forest inventory plots, representing a wide range of vegetation types affected by wildfire in California, Oregon, and Washington. Our representative weather scenarios were created by using data from local weather stations for the time each stand was believed to have burned. The accuracy of predicted mortality (percent basal area) with different weather scenarios was evaluated for all stands, by forest type group, and by major tree species using mean error, mean absolute error (MAE), and root mean square error (RMSE). One of the representative weather scenarios, Mean Wind, had the lowest mean error (4%) in predicted mortality, but performed poorly in some forest types, which contributed to a relatively high RMSE of 48% across all stands. Driven in large part by over-prediction of modelled flame length on steeper slopes, the greatest over-prediction mortality errors arose in the scenarios with higher winds and lower fuel moisture. Our results also indicated that fuel moisture was a stronger influence on post-fire mortality than wind speed. Our results suggest that using representative weather can improve accuracy of mortality predictions when attempting to model over a wide range of forest types. Focusing simulations exclusively on extreme conditions, especially with regard to wind speed, may lead to over-prediction of tree mortality from fire.

show abstract

Predicting Post-Fire Tree Mortality for 12 Western US Conifers Using the First Order Fire Effects Model (FOFEM)

Cited by 25 publications

References 42 publications

Pre‐fire drought and competition mediate post‐fire conifer mortality in western U.S. National Parks

Pre‐fire drought and competition mediate post‐fire conifer mortality in western U.S. National Parks

Fire and tree death: understanding and improving modeling of fire-induced tree mortality

Evaluating Model Predictions of Fire Induced Tree Mortality Using Wildfire-Affected Forest Inventory Measurements

Contact Info

Product

Resources

About