Ecological niche modeling as an effective tool to predict the distribution of freshwater organisms: The case of the Sabaleta Brycon henni (Eigenmann, 1913)

• Published in: PloS one Vol. 16; no. 3; p. e0247876
• Main Authors: Valencia-Rodríguez, Daniel, Jiménez-Segura, Luz, Rogéliz, Carlos A, Parra, Juan L
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 03-03-2021; Public Library of Science (PLoS)
• Subjects: Biology and Life Sciences; Distribution; Earth Sciences; Ecological research; Ecology and Environmental Sciences; Fishes, Fresh-water; Natural history; Niche (Ecology); Colombia
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0247876

Ecological niche models (ENMs) aim to recreate the relationships between species and the environments where they occur and allow us to identify unexplored areas in geography where these species might be present. These models have been successfully used in terrestrial organisms but their application in aquatic organisms is still scarce. Recent advances in the availability of species occurrences and environmental information particular to aquatic systems allow the evaluation of these models. This study aims to characterize the niche of the Sabaleta Brycon henni Eigenmann 1913, an endemic fish of the Colombian Andes, using ENMs to predict its geographical distribution across the Magdalena Basin. For this purpose, we used a set of environmental variables specific to freshwater systems in addition to the customary bioclimatic variables, and species' occurrence data to model its potential distribution using the Maximum Entropy algorithm (MaxEnt). We evaluate the relative importance between these two sets of variables, the model's performance, and its geographic overlap with the IUCN map. Both on-site (annual precipitation, minimum temperature of coldest month) and upstream variables (open waters, average minimum temperature of the coldest month and average precipitation seasonality) were included in the models with the highest predictive accuracy. With an area under the curve of 90%, 99% of the species occurrences and 68% of absences correctly predicted, our results support the good performance of ENMs to predict the potential distribution of the Sabaleta and the utility of this tool in conservation and decision-making at the national level.