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Abstract
Introduction: Freshwater ecosystems are some of the most threatened globally, including their ichthyofauna. To understand the factors that affect species composition and distribution of fish communities in rivers, it is important to include different assessment scales. Gradients of natural and anthropic origin converge in the Garagoa River, an ideal condition for the study of impact of multi-scale variables on freshwater ichthyofauna. Objective: evaluate the influence of variables at a local and landscape scale on the fish communities of the Garagoa River basin, through the analysis of beta diversity partitioned into the turnover and nesting components. Methods: Sampling was carried out in 36 transects of 100 m, between February and July 2021. The collection was carried out using electrofishing and trawl nets and physical, chemical and morphological characteristics of the section (local variables) were recorded. Using secondary information, information on land use, geomorphological and bioclimatic characteristics (landscape variables) was obtained. Beta diversity was calculated and the influence of local and landscape variables on this component was analyzed, using Principal Component Analysis PCA and Distance-Based Redundancy Analysis dbRDA. Results: We recorded 22 species from 10 families and five orders. The dissimilarity in species composition was high (93 %), 81 % explained by species turnover. These components were related to local variables, land use, geomorphological and bioclimatic characteristics. Conclusions: The species composition in the Garagoa River basin is distributed according to the elevation gradient and is affected by a set of variables at the local and landscape scale that include natural characteristics and conditions generated by human activities. The most relevant are the physicochemical characteristics of the water, the morphology of the channel, the quality of the riverside vegetation, the characteristics of the relief, as well as the distribution of areas with natural cover and areas affected by agricultural, livestock, mining or urban processes.
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