SDM profiling: A tool for assessing the information-content of sampled and unsampled locations for species distribution models

Species distribution models (SDMs) are key tools in biodiversity and conservation, but assessing their reliability unsampled locations is difficult, especially where there sampling biases. We present a spatially-explicit sensitivity analysis for SDMs – SDM profiling which assesses the leverage that have on overall model by exploring interaction between effect variable response curves prevalence of affected environmental conditions. The method adds ‘pseudo-presence’ ‘pseudo-absence’ to locations, re-running each, measuring difference probability surfaces original new SDMs. When standardised values plotted against each other (a ‘profile plot’), point's location can be summarized four measures, calculated as distances corner. explore several applications: visualization certainty; identification optimal redundant existing locations; flagging potentially erroneous occurrence records.