Circles is a geographical model that uses the location of known occurrences and predicts that a species can be present within a circle with a given radius around these occurrence points. This model does not use the input of environmental variables to predict the distribution of a species.
The radius is by default computed from the mean of all distances between points. This can be a really large distance for example if your are modelling a marine species that occurs across the globe. In this case some circles might overlap and the algorithm tries to merge these circles which might result in a fail. The solution is to rerun the experiment with a fixed distance for the radius.
- Simple and easy to interpret
- Presence only model, no absence data needed
Does not use environmental variables to predict species occurrence
Requires absence data
BCCVL uses the ‘dismo’ package. Currently there are no configuration options for this algorithm in the BCCVL.
- Hijmans RJ, Elith J (2015) Species distribution modeling with R.