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Corpus Systématique Animale

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Long-term variability of meiobenthos: value, synopsis, hypothesis generation and predictive modelling

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Springer (journals)
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Mots-clés d'auteur
  • meiobenthos
  • long-term
  • synopsis
  • hypothesis
  • modelling
Nom du fichier dans la ressource
  • Bruce C. Coull
  • Belle W. Baruch Institute for Marine Biology & Coastal Research, Marine Science Program and Department of Biology, University of South Carolina, 29208, Columbia, SC, USA

Few long-term data sets exist for meiofauna. Such data sets are expensive to collect, sort and identify; continuous meiofauna data for a period of greater than two years are limited to one site in Belgium (7 yrs) and two sites (one mud, one sand) in South Carolina, USA (11 yrs). The Belgian study concentrates on benthic copepod abundances whereas data from South Carolina includes major taxa and benthic copepods as well as 4 years of concurrent macrofauna abundance and 3 years of nematode species abundances. In South Carolina, the variance associated with meiofaunal abundance had 6 or 12 month recurrent cycles. Similar analyses on 4 years of macrofauna from the same 2 sites indicated the same cyclicity: one year. Seasonality of the South Carolina major taxa and the 6 most abundant mud copepod species was pronounced at the mud site, but absent or less pronounced at the sand site. Similar results were also found for the nematode species over three years. Variability in meiofaunal abundance was greater year-to-year than within a year. Many such long-term data sets are analysed and abandoned. Herewith, I use our long-term results to hypothesize the causes of the high temporal variance in mud and the lower temporal variance in sand. Is it because the mud fauna is controlled by seasonal inputs of natant predators while at the hydrodynamically active sand site temporal variability is homogenized by constant physical activity? By appropriate statistical modelling long-term data sets can also be used to assess the appropriateness of the sampling schedule (spatial and temporal) and as a predictor of future trends.

Catégories Science-Metrix
  • 1 - natural sciences
  • 2 - biology
  • 3 - marine biology & hydrobiology
Catégories INIST
  • 1 - sciences appliquees, technologies et medecines
  • 2 - sciences biologiques et medicales
  • 3 - sciences biologiques fondamentales et appliquees. psychologie
Catégories Scopus
  • 1 - Life Sciences ; 2 - Agricultural and Biological Sciences ; 3 - Aquatic Science
Catégories WoS
  • 1 - science ; 2 - marine & freshwater biology
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