Hierarchical Modelling Reveals Local Environmental Metrics as Key Predictors of Fish Stream Assemblage Structure

Environmental factors act at multiple spatial scales, shaping the fish assemblage structure in streams. Understanding catchment-stream relationships through hierarchical classification can aid in the conservation and management of freshwater ecosystems. The main goal of our work was to use the Hierarchical Modelling of Species Communities framework to answer the following questions: Which environmental variables are more important in structuring stream assemblages? Do ecomorphological traits influence species' responses to environmental conditions? What is the pattern of species co-occurrences along the streams? We fitted models with two alternative response datasets: a community matrix (site × species) with presence/absence data (PA) and abundance data (ABU). Species ecomorphological traits were also included in the models. We tested models considering the environmental variables at each scale separately (local and catchment) and considering all variables together. Variables at the local scale explained 57.1% (PA) and 53.3% (ABU) of the overall variance portion partitioning, while catchment variables explained only 36.6% and 23.3%, respectively. Traits explained only 47.9% (PA) and 18.93% (ABU) of the variation. No significant correlation between species co-occurrences was found. Our results suggest that local-scale metrics better predict the structure of fish assemblages in headwater streams from the Chapada Diamantina region of Caatinga.