**Introduction**

Geographic Distance is a geographical model that uses the location of known occurrences and predicts that the likelihood of finding a species in an area depends on the distance of that area to a known occurrence point. The predicted values are the inverse linear distance to the nearest known presence point. Distances smaller than or equal to zero are set to 1 (highest score).

This model does not use the input of environmental variables to predict the distribution of a species.

**Advantages **

- Simple and easy to interpret

**Limitations**

- Does not use environmental variables to predict species occurrence

**Assumptions**

N/A

**Requires absence data **

No

Configuration options

EcoCommons allows the user to set model arguments as specified below.

random_seed | Setting a random seed will not impact this model. |

scale | scale (in metres) used to divide the distance from occurrence records before computing the inverse distance. (default = 1000) |

Tails (tails) | The "tails” argument can be used to ignore the left or right tail of the percentile distribution for a variable. I If supplied, tails should be a character vector with a length equal to the number of variables used in the model. Valid values are "both", "low" and "high". (default = NULL) |

References

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