BioModelos: A collaborative online system to map species distributions.

• Main Authors: Jorge Velásquez-Tibatá, María H Olaya-Rodríguez, Daniel López-Lozano, César Gutiérrez, Iván González, María C Londoño-Murcia
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2019-01-01
• Series: PLoS ONE
• Online Access: https://doi.org/10.1371/journal.pone.0214522

Information on species distribution is recognized as a crucial input for biodiversity conservation and management. To that end, considerable resources have been dedicated towards increasing the quantity and availability of species occurrence data, boosting their use in species distribution modeling and online platforms for their dissemination. Currently, those platforms face the challenge of bringing biology into modeling by making informed decisions that result in meaningful models, based on limited occurrence and ecological data. Here we describe BioModelos, a modeling approach supported by an online system and a core team of modelers, whereby a network of experts contributes to the development of species distribution models by assessing the quality of occurrence data, identifying potentially limiting environmental variables, establishing species' accessible areas and validating modeling predictions qualitatively. Models developed through BioModelos become freely and publicly available once validated by experts, furthering their use in conservation applications. Our approach has been implemented in Colombia since 2013 and it currently consist of a network of nearly 500 experts that collaboratively contribute to enhance the knowledge on the distribution of a growing number of species and it has aided the development of several decision support products such as national risk assessments and biodiversity compensation manuals. BioModelos is an example of operationalization of an essential biodiversity variable at a national level through the implementation of a research infrastructure that enhances the value of open access species data.