Models based on species distributions are widely used and serve important purposes
in ecology, biogeography and conservation. Their continuous predictions
of environmental suitability are commonly converted into a binary classification
of predicted (or potential) presences and absences, whose accuracy is then evaluated
through a number of measures that have been the subject of recent
reviews. We propose four additional measures that analyse observation-prediction
mismatch from a different angle – namely, from the perspective of the
predicted rather than the observed area – and add to the existing toolset of
model evaluation methods. We explain how these measures can complete the
view provided by the existing measures, allowing further insights into distribution
model predictions. We also describe how they can be particularly useful
when using models to forecast the spread of diseases or of invasive species and
to predict modifications in species’ distributions under climate and land-use
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