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. We evaluate the relative importance between these two sets of variables, the model’s performance, and its geographic overlap with the IUCN map. 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 (Ma圎nt). 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. Recent advances in the availability of species occurrences and environmental information particular to aquatic systems allow the evaluation of these models. These models have been successfully used in terrestrial organisms but their application in aquatic organisms is still scarce. 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.
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