Introduction

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.

Advantages

• Simple and easy to interpret
• Presence only model, no absence data needed

Limitations

• Does not use environmental variables to predict species occurrence

Assumptions

N/A

Requires absence data

No

Configuration options

BCCVL uses the ‘dismo’ package. Currently there are no configuration options for this algorithm in the BCCVL.

References

• Hijmans RJ, Elith J (2015) Species distribution modeling with R.