Marine Biology

, Volume 101, Issue 2, pp 235–247 | Cite as

Gulf of Mexico hydrocarbon seep communities

II. Spatial distribution of seep organisms and hydrocarbons at Bush Hill
  • I. R. MacDonald
  • G. S. Boland
  • J. S. Baker
  • J. M. Brooks
  • M. C. KennicuttII
  • R. R. Bidigare


Sediment and water samples were collected by submersible in September 1986 at 16 locations on the carbonate cap overlying a conical diapir, which was formed by the upward migration of oil and gas through a subsurface fault on the continental slope off Louisiana, USA (27°47′N; 91°30.4′W). The biological community at the site was photographed quantitatively with still and video cameras. Rigorous spatial sampling indices were maintained so that variation in chemical parameters and in the abundance of photographed organisms could be estimated within the bounds of the study site. Concentrations of extractable organic material (EOM) ranged from 0.24 to 119.26‰ in the sediment samples, while methane concentrations in the water samples were from 0.037 to 66.474 μM. The visible biological community was predominantly composed of the chemosynthetic tube worms (Vestimentifera) Lamellibrachia sp. and Escarpia sp., and an undescribed, methane-oxidizing mussel (Mytilidae: Bathymodiolus-like), as well as diverse non-chemosynthetic organisms. The ranked abundance of tube worms was significantly correlated (p<0.05) with the concentration of EOM in the sediment samples, while the abundance of mussels was significantly correlated (p<0.05) with the concentration of methane in the water samples. Tube worms and mussels both occurred in dense clusters; however, the clusters of mussels had a more restricted distribution within the study site than did clusters of tube worms. Both organisms were most abundant in the vicinity of the subsurface fault.


Hydrocarbon Water Sample Sediment Sample Continental Slope Methane Concentration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag 1989

Authors and Affiliations

  • I. R. MacDonald
    • 1
  • G. S. Boland
    • 1
  • J. S. Baker
    • 2
  • J. M. Brooks
    • 3
  • M. C. KennicuttII
    • 3
  • R. R. Bidigare
    • 3
  1. 1.Department of OceanographyTexas A&M UniversityCollege StationUSA
  2. 2.Glaxo Co., IncorporatedResearch Triangle ParkUSA
  3. 3.Geochemical and Environmental Research GroupTexas A&M UniversityCollege StationUSA

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