Method Factsheet - Species Distribution Models

Species distribution models (SDMs) (Franklin, 2009) have shown great potential in helping to achieve conservation planning goals by refining our knowledge of species distributions (Jetz et al., 2012). SDMs extrapolate species distribution data in space and time, usually based on a statistical model. These models identify areas that are ecologically suitable for the presence of species (Soberon & Peterson, 2005; Hirzel et al., 2002; Franklin, 2009).

Implementation

Spatial planning

Topics

Biodiversity
Climate change

Constraints

Some species are very hard to model as the factors driving their present-day distributions are unclear. The projections generally reflect the climate, environmental characterisitics and/or habitat niche that a species could potentially use - they do not usually take into consideration other factors such as predation, competition or disease, or changes over time in factors such as habitat distribution.
As with any modelling, some species fit better with the driving variables and produce projections that are more statistically significant than others
Relatively advanced statistical process underly the models

Product requirements

Appropriate species and contextual (or proxy) datasets for the case study area.
In general, SDMs require expertise from the ecology/biodiversity field, but input from non-academic stakeholders can be useful to validate the results
Availability of software depends on the species distribution model in question. Some software is freely available for download, others are embedded in particular institutions. BIOMOD is implemented in R statistical coding landuage and is a freeware, open source, package. SPECIES is implemented as standalone interface

Advantages

Can identify areas where climate and/or habitat is appropriate for a given species
Can be used to explore multiple future scenarios
Spatial outputs produced with accompanying goodness-of-fit statistics.

Links