Obviously, there are too many species on Earth to know them all, not to say their distributional ranges. To make things even more complicated, a species does not exists physically but consists of individuals, which share characteristics according to a species concept.
This problem is known as the Wallacean shortfall and the reason why we need SDM: we never can sample all individuals of a species (some exeptions of extremely rare species may exist, though) to know the actual distribution of a species, not to mention their dynamics through time.
Applicability of SDM
What can we do once the distribution of a single species or of a set of species is modelled?
There are plenty of opportunities and here are some of them:
- a species’ range can be used for descriptive purposes like assessing and monitoring species numbers and composition in a particular area,
- if we model the distribution from the occurrence of individuals of different steps in time, we can assess changes of distribution ranges through time,
- if we know under which environmental conditions species do occur, we can predict the suitability of habitats that are not occupied yet or find yet unknown populations,
- with SDM, it is possible to predict the occurrence of species under scenarios of climate change, what has direct relevance for nature conservation,
- stacking many predicted species’ distributions together allows us to calculate the number of species - or species richness - that occur in a particular area or grid cell, what is directly relevant for biodiversity research,
- and last but not least, knowing the distribution ranges of species allows researchers to link characteristics of species with characteristics of the environment, what opens up a plethora of possibilities in scientific research to understand better the functional significance of traits of species, to understand better why species occur in some places but not in others, and ultimately to understand a bit better the functional and phylogenetic diversity of life on Earth.
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