Thirty years of use of multivariate quantitative methods in benthic community ecology of marine and coastal habitats: looking to the past to planning the future

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• 作者：Gilson Correia de Carvalho ; Raymundo José de Sá-Neto ; Francisco Barros
• 关键词：Multivariate quantitative methods ; Statistics ; Benthic ecology ; Machine learning methods
• 刊名：Scientometrics
• 出版年：2015
• 出版时间：October 2015
• 年：2015
• 卷：105
• 期：1
• 页码：593-610
• 全文大小：1,573 KB
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• 作者单位：Gilson Correia de Carvalho (1) (2)
  Raymundo José de Sá-Neto (3)
  Francisco Barros (2)
  
  1. Departamento de Biointera??o, Instituto de Ciências da Saúde, Universidade Federal da Bahia, Campus Canela, Salvador, Bahia, 40110-100, Brazil
  2. Laboratório de Ecologia Bent?nica, PPGEcoBio, Instituto de Biologia, Universidade Federal da Bahia, Campus Ondina, Salvador, Bahia, 40170-290, Brazil
  3. Laboratório de Biodiversidade do Semiárido, Departamento de Ciências Naturais, Universidade Estadual do Sudoeste da Bahia, Itapetinga, Bahia, Brazil
  
• 刊物主题：Information Storage and Retrieval; Library Science; Interdisciplinary Studies;
• 出版者：Springer Netherlands
• ISSN：1588-2861

文摘

The benthic community ecology of marine and coastal habitats has recently been faced with the challenge of needing a predictive model to anticipate the responses of these natural communities to environmental impacts. This challenge forces the use of quantitative methods to conduct more predictive science. This work is focused on multivariate quantitative methods applied to community ecological problems. A survey was conducted in the Science Citation Index using combined keywords that reflects multivariate quantitative methods, benthic assemblages and marine and coastal habitats. There has been analytical inertia in this research field, as the most commonly used methods have not changed over the years, and novel methods that have been developed inside and outside of ecology have not been included in the analytical tools of marine benthic ecologists. Methods that are increasing the predictive power of freshwater benthic ecology, such as machine learning, have not been used for the benthic community ecology of marine and coastal habitats. Keywords Multivariate quantitative methods Statistics Benthic ecology Machine learning methods