To investigate changes at different spatial scales environmental scientists often use statistical models to extrapolate environmental data in space. Species distribution models (SDM), also called ecological niche models or habitat suitability models, utilize relationships between environmental variables and species observations to find environmental conditions where these species of interest could potentially occur. In other words SDMs extrapolates species distribution data in space and time, usually based on a statistical model.
The idea of modelling species distribution has its origin in ecological gradient analysis, biogeography, remote sensing and geographic information science. In the last decades SDM became increasingly important in scientific literature and the opportunities of how to use SDM has been greatly enhanced by digital databases that make species occurrence data available. Not at least environmental data is available more and more because of the trend to make data open for everyone.
Possible SDM use cases are to test ecological or biogeographical hypotheses, like environmental or climate change, but there are also applied purposes in wildlife and resource management, conservation planning or restoration ecology. Modelling species distribution could also be an advantage to find species in the field.
SDM is often portrayed as a kind of fortune-telling and therefore the models should always be evaluated for “ecological realism” and should base on a reasoned conceptual model.