Fig. 4
Model results for the Pinus ponderosa Ryan and Amman (R-A) model. (A) Map shows locations of fires occurring from 1981 to 2016 within the USA from which data to evaluate the model were sampled. Fire locations are plotted over the species’ range (green polygons). P. ponderosa was incredibly well sampled across its geographic range in the US, with data used to evaluate the R-A model from 43 140 trees and 226 fires. BTcoef = specific specific bark thickness coefficient. (B) The bi-plot shows where the observations used to evaluate models (orange points) fall within the species’ bioclimatic niche space (black points) in terms of temperature (x-axis) and precipitation (y-axis). (C) Model evaluation summary statistics including the AUC (area under the receiver operator characteristic curve) at 0.5 threshold for determining mortality, and confidence intervals (CI) around the AUC. Model evaluation statistics include accuracy, sensitivity (Sens.), specificity (Spec.), positive predicted values (PPV), and negative predictive values (NPV), summarized over a range of probability thresholds (0.1 to 0.9; rows), with the commonly used threshold of 0.5 shown in bold. Warmer colors indicate greater values. The top three bold rows show model performance metrics for the “best” threshold, which optimizes sensitivity and specificity, the best threshold with sensitivity >0.8, and the best threshold with specificity >0.8. This model showed higher sensitivity than specificity, but performed well overall (AUC = 0.887). (D) The distributions of defense (diameter at breast height [DBH], as an interpretable representation of bark thickness) and injury (crown volume scorch) variables used in the model are shown with bi-plots. Box plots in the margins of D show median (bar), interquartile range (IQR; box; 25th and 75th percentiles), and whiskers show the minimum and maximum values that do not exceed a 1.5 × IQR. The scatter plot shows that trees that survived and died after fire were sampled across the ranges of percentage crown volume scorched (CVS) and diameter at breast height (DBH). (E) and (F) Assessment of species-level error comparing the predicted probability of mortality using a 0.5 threshold (Pm; orange points show values and shading shows range) and the observed proportion of trees or stems killed (gray points) within binned observations of the primary injury variables (E), and the DBH F. (E) The model over-predicted mortality at middle to high values of CVS, and (F) under-predicted mortality for the small sample of very large trees. Qualitative ratings of data quality, model performance, and direction or error in model predictions are listed at the bottom of the figure. This model had excellent data quality, but did not qualified as having outstanding data quality because samples were only from within the US and did not cover the species’ full climatic range (Additional file 5)