Avaliação cienciométrica em estudos de ecologia alimentar em peixes

• Ano de defesa: 2017
• Autor(a) principal: Lira, Angélica Dorigon
• Orientador(a): Gubiani, Éder André
• Banca de defesa: Gubiani, Éder André , Piana, Pitágoras Augusto , Isaac, Andréia
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual do Oeste do Paraná; Toledo
• Programa de Pós-Graduação: Programa de Pós-Graduação em Recursos Pesqueiros e Engenharia de Pesca
• Departamento: Centro de Engenharias e Ciências Exatas
• País: Brasil
• Palavras-chave em Português: Cienciometria; Avaliação da dieta; Testes estatísticos; Ictiofauna
• Palavras-chave em Inglês: Scientometry; Diet assessment; Statistical tests; Icthyofauna
• Área do conhecimento CNPq: CIENCIAS AGRARIAS::RECURSOS PESQUEIROS E ENGENHARIA DE PESCA
• Link de acesso: http://tede.unioeste.br/handle/tede/3044

Several laboratory procedures and statistical methods were developed to evaluate diet in fish. Thus, through a scientometric approach, we identified patterns in articles on fish feeding ecology. The database used for the survey was Thomson Reuters (ISI Web of Knowledge, apps.webofknowledge.com). In which, we observed a significant increase in the number of articles on feeding ecology of fish over time. Among the 1319 articles evaluated, the most frequent characteristics were: i) publication in the Journal of Fish Biology; ii) Brazilian and American researchers as the main authors; iii) three authors per article; iv) marine environment as more studied; v) population, the most discussed subject; vi) frequency of occurrence, the most used method for analysis of stomach and intestinal contents; vii) index of relative importance, the method most used to evaluate the importance of food items in the diet; viii) the use of the Kolmogorov-Smirnov and Levene statistical tests to evaluate the assumptions of normality and homogeneity of variances, respectively; ix) the use of the univariate analysis of variance hypotheses, the Kruskall-Wallis non-parametric univariate test, the multivariate analysis of permutational variance analysis, and the multivariate analysis of similarity tests; and x) the use of parametric ordering techniques cluster analysis and non-parametric non-metric multidimensional scaling.