A case study on environmental sustainability: A study of the trophic changes in fish species as a result of the damming of rivers through clustering analysis

The damming of rivers has been long used for electricity generation and is among the most used sources of renewable energy. However, building dams may cause several transformations in the environment, being changes in fish assemblage one important consequence, especially when there are communities that rely on fishing as a source of income. The aim of the present study is to analyze the trophic changes in fish species caused by the damming of rivers. Trophic data (stomach content) on fish from the Corumba Reservoir in the State of Goias, Brazil, which was collected prior (River phase) and after (Reservoir phase) the building of the dam, were used to carry out the study using Clustering techniques. The methodology used was composed of data exploratory analysis, followed by the assignment of clusters for the later implementation of knowledge. The definition of the number of clusters, the usage of different types of clustering distances and the use validation indexes are discussed. A modified version of the Teitz & Bart algorithm, originally used for facilities location problems, was introduced for Clustering problems and the results were compared with three well-known Clustering algorithms from literature. The clustering approaches were applied separately in both phases and in both cases, five large clusters of fish were determined: generalists, insectivores, herbivores, piscivores, and detritivores. With this evaluation, could be used by biologists in order to evaluate environmental effects and managers can develop strategies to address the social and economic impacts caused to the communities that depend on fishing.