openModeller: a generic approach to species' potential distribution modelling

Authors:
Mauro Enrique Souza Muñoz;Renato Giovanni;Marinez Ferreira Siqueira;Tim Sutton;Peter Brewer;Ricardo Scachetti Pereira;Dora Ann Canhos;Vanderlei Perez Canhos
Affiliations:
Centro de Referência em Informação Ambiental, Campinas, Brazil;Centro de Referência em Informação Ambiental, Campinas, Brazil;Centro de Referência em Informação Ambiental, Campinas, Brazil;, Lanseria, South Africa 1748;Malcolm and Carolyn Wiener Laboratory for Aegean and Near Eastern Dendrochronology, B-48 Goldwin Smith Hall, Cornell University, Ithaca, USA 14853-3201;Centro de Referência em Informação Ambiental, Campinas, Brazil;Centro de Referência em Informação Ambiental, Campinas, Brazil;Centro de Referência em Informação Ambiental, Campinas, Brazil
Venue:
Geoinformatica
Year:
2011

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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.