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


Requirements

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.