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Assessing ecological health in areas with limited data by using biological traits.
Hewitt, Judi; Gammal, Johanna; Ellis, Joanne.
Afiliação
  • Hewitt J; National Institute of Water and Atmospheric Research Ltd NZ (NIWA), Gate 10 Silverdale Rd, Hamilton 3240, New Zealand. Electronic address: judi.hewitt@auckland.ac.nz.
  • Gammal J; National Institute of Water and Atmospheric Research Ltd NZ (NIWA), Gate 10 Silverdale Rd, Hamilton 3240, New Zealand; The University of Waikato-Te Whare Wananga o Waikato, Gate 1, Knighton Road, Hamilton 3240, New Zealand.
  • Ellis J; The University of Waikato-Te Whare Wananga o Waikato, 101-121 Durham Street, Tauranga 3110, New Zealand.
Mar Pollut Bull ; 181: 113900, 2022 Aug.
Article em En | MEDLINE | ID: mdl-35810647
ABSTRACT
A multitude of biotic indices that represent environmental status have been developed over the past decades making status comparisons difficult. However, transferring an existing index to a new region can be problematic due to differing stressors, ecosystem components and lack of knowledge on regional species sensitivities. Here we assess whether calculating species sensitivities to specific stressors based on biological traits offers a solution. We use biological traits of macrofaunal species to assess sensitivity to suspended sediment concentrations and calculated the Benthic Quality Index (BQI) at 47 sites across a suspended sediment gradient. This trait-based modification of the BQI was well correlated (0.82) to suspended sediment. Problems previously highlighted, relating to trait plasticity and differential weightings of indifferent and beneficial species, were investigated but did not strongly affect results. A trait-based approach has the additional benefit that the data could be easily converted to evaluate ecosystem function.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental / Ecossistema Tipo de estudo: Diagnostic_studies Limite: Animals Idioma: En Revista: Mar Pollut Bull Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental / Ecossistema Tipo de estudo: Diagnostic_studies Limite: Animals Idioma: En Revista: Mar Pollut Bull Ano de publicação: 2022 Tipo de documento: Article