| one publication added to basket [57944] | The temporal variation in the meiobenthos along a bathymetrical gradient (‘Hausgarten’, Arctica’): impact of climate oscillations
Hoste, E.; Soltwedel, T.; Vanhove, S.; Vanreusel, A. (2004). The temporal variation in the meiobenthos along a bathymetrical gradient (‘Hausgarten’, Arctica’): impact of climate oscillations, in: Mees, J. et al. VLIZ Young Scientists' Day, Brugge, Belgium 5 March 2004: book of abstracts. VLIZ Special Publication, 17: pp. 55
In: Mees, J.; Seys, J. (Ed.) (2004). VLIZ Young Scientists' Day, Brugge, Belgium 5 March 2004: book of abstracts. VLIZ Special Publication, 17. Vlaams Instituut voor de Zee (VLIZ): Oostende. X, 148 pp., more
In: VLIZ Special Publication. Vlaams Instituut voor de Zee (VLIZ): Oostende. ISSN 1377-0950, more
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Document type: Summary
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| Keywords |
Aquatic communities > Benthos > Meiobenthos
Climatic changes
Models
Oscillations
Radiations > Electromagnetic radiation > Solar radiation
Temporal variations
Marine/Coastal |
| Abstract |
In 1999 the Alfred-Wegener institute started a long term (10 years) sampling campaign of the ‘Hausgarten’ site 79°N, North Pole. Meiobenthos samples are taken between 1000 and 5500m depth and the samples of the first five years will be analysed in this study. The aim is to make a statistical model that allows predictions of the changes in the meiobenthos ecosystem in relation to variation in environmental parameters linked to climate oscillations (e.g. NAO, ENSO) and global warming. Models will be adjusted according to the answers to following questions: 1. Are there annual differences in meiobenthos composition in the Arctic region and can these differences be linked to changes in physical and biological environmental parameters, such as oxygen concentration, temperature food supply? 2. Is there a relation between changes in meiofauna community structure and environmental parameters along the bathymetrical gradient? Emphasis will be on nematodes and copepods, the most abundant meiofauna taxa, which will be identified up to species level. Density, biomass and productivity, diversity (-,- -diversity) will be assessed. These data will be analysed using variance analysis, correlation and regression analysis and multivariate techniques. |
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