dc.creatorFrancisco, Cláudia Aparecida Cavalheiro
dc.creatorAlmeida, Ricardo de
dc.creatorSteiner, Maria Teresinha Arns
dc.creatorCoelho, Leandro dos Santos
dc.creatorSteiner Neto, Pedro José
dc.date2020-12-23T12:56:45Z
dc.date2020-12-23T12:56:45Z
dc.date2019
dc.identifierALMEIDA, Ricardo de; STEINER, Maria Teresinha Arns; COELHO, Leandro dos Santos; FRANCISCO, Cláudia Aparecida Cavalheiro; STEINER NETO, Pedro José. 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. Computers & Industrial Engineering, [S.L.], v. 135, p. 1239-1252, set. 2019.Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S0360835218304480?via%3Dihub Acesso em: 15 dez 2020. https://doi.org/10.1016/j.cie.2018.09.032
dc.identifier0360-8352
dc.identifierhttps://repositorio.ufrn.br/handle/123456789/31114
dc.identifier10.1016/j.cie.2018.09.032
dc.descriptionThe 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 Corumbá Reservoir in the State of Goiás, 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
dc.languageen
dc.publisherElsevier
dc.subjectEnvironment sustainability
dc.subjectClustering analysis
dc.subjectTrophic categories of fish
dc.subjectRiver phase
dc.subjectReservoir phase
dc.titleA 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
dc.typearticle


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