[show abstract][hide abstract] ABSTRACT: Species’ potential distribution modelling is the process of building a representation of the fundamental ecological requirements
for a species and extrapolating these requirements into a geographical region. The importance of being able to predict the
distribution of species is currently highlighted by issues like global climate change, public health problems caused by disease
vectors, anthropogenic impacts that can lead to massive species extinction, among other challenges. There are several computational
approaches that can be used to generate potential distribution models, each achieving optimal results under different conditions.
However, the existing software packages available for this purpose typically implement a single algorithm, and each software
package presents a new learning curve to the user. Whenever new software is developed for species’ potential distribution
modelling, significant duplication of effort results because many feature requirements are shared between the different packages.
Additionally, data preparation and comparison between algorithms becomes difficult when using separate software applications,
since each application has different data input and output capabilities. This paper describes a generic approach for building
a single computing framework capable of handling different data formats and multiple algorithms that can be used in potential
distribution modelling. The ideas described in this paper have been implemented in a free and open source software package
called openModeller. The main concepts of species’ potential distribution modelling are also explained and an example use
case illustrates potential distribution maps generated by the framework.