Fig. 3From: Using machine learning to predict habitat suitability of sloth bears at multiple spatial scalesVariable importance plot for scaled variables used in the multivariate random forest model of sloth bears based on model improvement ratio (MIR). The degraded forest was the most important variable, and the river density was the least important variable. Rest of the variables are listed in order of their relative importance to degraded forests. The X-axis represents the relative additional model improvement with the addition of each successive variable. Variables included are degraded8km, degraded forests; Farmland_9km, farmlands; sal5km, sal-dominated forests; drydec1km, dry deciduous forests; moistdec4km, moist deciduous forests; road1km, road density; and river1km, river density. The numerical value succeeding each variable represents the respective spatial scaleBack to article page