Modelling post-fire tree mortality: Can random forest improve discrimination of imbalanced data?

[1]  Duncan C. Lutes,et al.  First-Order Fire Effects Model (FOFEM) , 2020, Encyclopedia of Wildfires and Wildland-Urban Interface (WUI) Fires.

[2]  David S. Pilliod,et al.  Cannot see the random forest for the decision trees: selecting predictive models for restoration ecology , 2019, Restoration Ecology.

[3]  Andrew J. Larson,et al.  Multi-scale assessment of post-fire tree mortality models , 2019, International Journal of Wildland Fire.

[4]  C. A. Cansler,et al.  Fire and tree death: understanding and improving modeling of fire-induced tree mortality , 2018, Environmental Research Letters.

[5]  J. Varner,et al.  Advances in Mechanistic Approaches to Quantifying Biophysical Fire Effects , 2018, Current Forestry Reports.

[6]  M. Metz,et al.  Characterizing interactions between fire and other disturbances and their impacts on tree mortality in western U.S. Forests , 2017 .

[7]  S. Hood,et al.  Predicting post-fire tree mortality for 14 conifers in the Pacific Northwest, USA: Model evaluation, development, and thresholds , 2017 .

[8]  Duncan C. Lutes,et al.  Predicting Post-Fire Tree Mortality for 12 Western US Conifers Using the First Order Fire Effects Model (FOFEM) , 2017 .

[9]  J. Kane,et al.  Higher sensitivity and lower specificity in post-fire mortality model validation of 11 western US tree species , 2017 .

[10]  Mortality predictions of fire-injured large Douglas-fir and ponderosa pine in Oregon and Washington, USA , 2017 .

[11]  Brandon M. Greenwell.  pdp: An R Package for Constructing Partial Dependence Plots , 2017, R J..

[12]  Robert J. McGaughey,et al.  Mixed severity fire effects within the Rim fire: Relative importance of local climate, fire weather, topography, and forest structure , 2015 .

[13]  The Discriminatory Ability of Postfire Tree Mortality Logistic Regression Models , 2015 .

[14]  Malcolm P. North,et al.  Water balance and topography predict fire and forest structure patterns , 2015 .

[15]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[16]  Emil Pitkin,et al.  Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation , 2013, 1309.6392.

[17]  J. Morgan Varner,et al.  Prescribed fire in North American forests and woodlands: history, current practice, and challenges , 2013 .

[18]  S. Hood,et al.  Assessing Post-Fire Douglas-Fir Mortality and Douglas-Fir Beetle Attacks in the Northern Rocky Mountains , 2012 .

[19]  L. Ganio,et al.  A review of logistic regression models used to predict post-fire tree mortality of western North American conifers , 2012 .

[20]  Mario Chica-Olmo,et al.  An assessment of the effectiveness of a random forest classifier for land-cover classification , 2012 .

[21]  Xavier Robin,et al.  pROC: an open-source package for R and S+ to analyze and compare ROC curves , 2011, BMC Bioinformatics.

[22]  J. Varner,et al.  Acute Physiological Stress and Mortality Following Fire in a Long-Unburned Longleaf Pine Ecosystem , 2010 .

[23]  Sharon M. Hood,et al.  Predicting mortality for five California conifers following wildfire , 2010 .

[24]  M. Dickinson,et al.  First-Order Fire Effects on Animals: Review and Recommendations , 2010 .

[25]  Max Kuhn,et al.  Building Predictive Models in R Using the caret Package , 2008 .

[26]  Using Bark Char Codes to Predict Post-fire Cambium Mortality , 2008 .

[27]  R. Real,et al.  AUC: a misleading measure of the performance of predictive distribution models , 2008 .

[28]  E. Johnson,et al.  How forest fires kill trees: A review of the fundamental biophysical processes , 2007 .

[29]  D. R. Cutler,et al.  Utah State University From the SelectedWorks of , 2017 .

[30]  F. Putz,et al.  Overstory tree mortality resulting from reintroducing fire to long-unburned longleaf pine forests: the importance of duff moisture , 2007 .

[31]  M. Brock,et al.  The use of “overall accuracy” to evaluate the validity of screening or diagnostic tests , 2004, Journal of General Internal Medicine.

[32]  Charles W. McHugh,et al.  Evaluation of a post-fire tree mortality model for western USA conifers , 2007 .

[33]  Andy Liaw,et al.  Classification and Regression by randomForest , 2007 .

[34]  Jason J. Moghaddas,et al.  Tree mortality patterns following prescribed fires in a mixed conifer forest , 2006 .

[35]  W. Shepperd,et al.  Modeling Postfire Mortality of Ponderosa Pine following a Mixed-Severity Wildfire in the Black Hills: The Role of Tree Morphology and Direct Fire Effects , 2006, Forest Science.

[36]  W. Thies,et al.  Prediction of delayed mortality of fire-damaged ponderosa pine following prescribed fires in eastern Oregon, USA , 2006 .

[37]  A. Prasad,et al.  Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction , 2006, Ecosystems.

[38]  Carl N. Skinner,et al.  Basic principles of forest fuel reduction treatments , 2005 .

[39]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[40]  Chao Chen,et al.  Using Random Forest to Learn Imbalanced Data , 2004 .

[41]  J. Kevin Hiers,et al.  Simple Spatial Modeling Tool for Prioritizing Prescribed Burning Activities at the Landscape Scale , 2003 .

[42]  Robert E. Keane,et al.  Modeling fire effects , 2001 .

[43]  Leo Breiman,et al.  Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author) , 2001 .

[44]  Gary King,et al.  Logistic Regression in Rare Events Data , 2001, Political Analysis.

[45]  G. De’ath,et al.  CLASSIFICATION AND REGRESSION TREES: A POWERFUL YET SIMPLE TECHNIQUE FOR ECOLOGICAL DATA ANALYSIS , 2000 .

[46]  S. Conard,et al.  Modeling Tree Mortality Following Wildfire in Pinus ponderosa Forests in the Central Sierra-Nevada of California , 1993 .

[47]  J. M. Saveland,et al.  A signal detection framework to evaluate models of tree mortality following fire damage. , 1990 .

[48]  D. Hosmer,et al.  Applied Logistic Regression , 1991 .

[49]  K. Ryan,et al.  Predicting postfire mortality of seven western conifers , 1988 .

[50]  D. Peterson.  Crown scorch volume and scorch height: estimates of postfire tree condition , 1985 .

[51]  Martin E. Alexander,et al.  Calculating and interpreting forest fire intensities , 1982 .

[52]  Collin D. Bevins.  Estimating survival and salvage potential of fire-scarred Douglas-fir. , 1980 .