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Seabed mapping in the southern Irish Sea: predicting benthic biological communities based on sediment characteristics
McBreen, F.; Wilson, J.G.; Mackie, A.S.Y.; Nic Aonghusa, C. (2008). Seabed mapping in the southern Irish Sea: predicting benthic biological communities based on sediment characteristics. Hydrobiologia 597(1): 93-103. dx.doi.org/10.1007/s10750-008-9341-0
In: Hydrobiologia. Springer: The Hague. ISSN 0018-8158, more
Peer reviewed article  

Also published as
  • McBreen, F.; Wilson, J.G.; Mackie, A.S.Y.; Nic Aonghusa, C. (2008). Seabed mapping in the southern Irish Sea: predicting benthic biological communities based on sediment characteristics, in: Davenport, J. et al. (Ed.) Challenges to Marine Ecosystems: Proceedings of the 41st European Marine Biology Symposium, held in Cork, Ireland, 4-8 September 2005. Developments in Hydrobiology, 202: pp. 93-103, more

Available in  Authors 
Document type: Conference paper

Keywords
    Benthos; Community composition; Nitrogen; Nutrient availability; Oceanography; Organic carbon; Particle size; Prediction; Seabed habitats; Seafloor mapping; Sediment chemistry; Sediments; ANE, Irish Sea [Marine Regions]; Marine

Authors  Top 
  • McBreen, F., more
  • Wilson, J.G.
  • Mackie, A.S.Y.
  • Nic Aonghusa, C.

Abstract
    Marine habitat mapping is necessary to comply with European legislation (92/43/EEC, 79/409/EEC and 2001/60/EEC), with international obligations to organizations such as ICES and with agreements such as the OSPAR Convention. Clearly defined habitats are needed before conservation and management practices can be implemented. The BIOMÔ R, SWISS and HABMAP projects have used sediment particle size, organic matter, organic carbon and nitrogen along with benthic macrofaunal species and abundance to define habitats in the southern Irish Sea. The sea floor of the southern Irish Sea is predominantly sandy gravel, grading down through sand to mud in the deeper parts of the Celtic Sea and similarly in the shallower northern basin beyond Anglesey. The physical gradient in particle size is correlated with organic content and also with biological communities. Nevertheless, there are marked discrepancies between boundaries defined by the Folk sediment characterization trigon, by the chemical characteristics of the sediments and by biological communities. The validity of using continuous physical and chemical sediment characteristics to more accurately predict categorical biological assemblages was tested with use of stepwise backward elimination Binary Logistic Regression (BLR). This method could be used as a tool to predict biological assemblages where there is a paucity of biological data. It lends support to the idea that benthic habitat mapping will have to take more account of biological structuring and system function.

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