Contribuição relativa de preditores de dispersão simétrica e assimétrica nos modelos de nicho ecológico em ambientes aquáticos - Parreira, Micael Rosa (2022)
Species distribution models are based mainly on environmental (mostly climatic) and species distribution data to predict the potential distribution of species. In this sense, the species dispersal (i.e., movement) is often ignored in their predictions. In freshwater habitats, species dispersal is not restricted only by physical barriers but also by the directional movement of the hydrographic network, which can be considered through spatial predictors. Here, we aim to evaluate the effect of including asymmetrical dispersal predictors in the potential geographic distribution of a freshwater fish in the Tocantins-Araguaia River basin, Brazil. Furthermore, we aim to assess if the predictions using climatic and asymmetrical dispersal vary depending on multiple species occurrence distribution and range, and on the inclusion of hydropower plants as dispersal barriers in the predictions. For this, we built models with seven variable sets representing environmental (climatic) and dispersal models, as well as their interactions. The models’ accuracy metrics were then used to compare the performance of different model sets (e.g., asymmetrical and symmetrical dispersal and environmental predictors), the performance of multiple species models based on their occurrence distribution among sub-basins and range, and the effect of including dispersal barriers into the models. First, we found that the models with higher performance are those built using asymmetrical dispersal predictors, either solo or combined with environmental variables. Second, species more restricted had models with higher performance when modeled using asymmetrical dispersal predictors, especially when distributed in different sub-basins. Third, predictions including the hydropower plants as dispersal barriers showed a higher loss of species richness and composition, especially for the areas with the highest number of dams. Therefore, the inclusion of asymmetrical dispersal variables, taking into account dispersal limitations of species, decreased the overprediction to climatically suitable but disconnected areas through rivers. Furthermore, those models using asymmetrical dispersal better represented restricted species distributed in both sub-basins of the basin and also the effect of dispersal barriers in the fish species richness and composition along the basin. Therefore, future SDM studies, especially those using species groups with asymmetrical dispersal, should consider the inclusion of asymmetrical dispersal predictors to increase the model’s accuracy and ecological reality of predictions.