Skip to main content

Advertisement

Table 5 Best predictor variables for species richness, alpha diversity, and green cover across climate, burn severity, and topographic gradients for wildfire sites in Montana, Idaho, and Washington, USA, that burned in July and August between 2003 and 2007. Abbreviations for predictor variables are: ffp = length of frost-free period, cc = canopy cover, sprp = spring precipitation, dNBR = burn severity index, mat = mean annual temperature, map = mean annual precipitation. xR2 is the cross-validated R2. Bootstrap xR2 is the average fit of 100 models run with the selected predictors and associated standard error (SE). N is the average number of sites contributing to the model estimate at each point on the modeled surface. Tolerance is a smoothing parameter that indicates how broadly a given point estimate is influenced by the surrounding sample space. The tolerance value is reported in the original scale of the predictor variable. A low percent tolerance means that the response variable is sensitive to a change in the predictor variable. Sensitivity ranges from 0 to 1 and indicates the relative importance of each predictor in the model

From: Does burn severity affect plant community diversity and composition in mixed conifer forests of the United States Intermountain West one decade post fire?

Response variablePlots(n)xR2Bootstrap xR2 (SE)NPredictorSensitivityTolerance
Species richness890.3020.480(±0.007)4.7mat0.5854.34 (5%)
dNBR0.195182.8 (15%)
map0.043139.0 (40%)
Species diversity890.3150.552(±0.010)4.5ffp0.25811.14 (10%)
cc0.1000.197 (20%)
sprp0.08111.40 (25%)
dNBR0.058304.8 (25%)
Green cover890.3360.521(±0.009)6.8elevation0.66773.8 (5.0%)
mat0.2988.67 (10.0%)
ffp0.18611.14 (10.0%)