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Modelling the interactions of the hydrothermal mussel Bathymodiolus azoricus with vent fluid

Author

Listed:
  • Husson, Bérengère
  • Sarrazin, Jozée
  • van Oevelen, Dick
  • Sarradin, Pierre-Marie
  • Soetaert, Karline
  • Menesguen, Alain

Abstract

In the 40 years since the discovery of the rich faunal community around hydrothermal vents, many studies have clearly shown that environmental conditions have a strong influence on species distribution in these habitats. Nevertheless, the mechanisms that determine the spatial and temporal dynamics of species’ responses to vent conditions remain elusive. Metabolic studies to assess faunal interactions with vent fluid are particularly difficult to perform in the deep sea and are generally executed in isolation ex situ. Available data mainly concern foundation species, which visually dominate these ecosystems. This work uses a modelling approach to integrate biotic and abiotic data that have been acquired through the years on Eiffel Tower, a large sulphide edifice located on the Lucky Strike vent field on the Mid-Atlantic Ridge, and particularly on its dominant species, Bathymodiolus azoricus. A carbon-flux model was built using seven state variables: the biomass of mussels and their associated thiotrophic (SOX) and methanotrophic (MOX) symbionts and the ambient concentrations of oxygen, dihydrogen sulphide, methane and (particulate and dissolved) organic carbon. Temperature of the surrounding water and mussel density were the forcing variables in the system. Results showed no statistically significant differences between predicted and observed mussel biomass and estimates of energy partitioning within the mussel were in the range of available data.

Suggested Citation

  • Husson, Bérengère & Sarrazin, Jozée & van Oevelen, Dick & Sarradin, Pierre-Marie & Soetaert, Karline & Menesguen, Alain, 2018. "Modelling the interactions of the hydrothermal mussel Bathymodiolus azoricus with vent fluid," Ecological Modelling, Elsevier, vol. 377(C), pages 35-50.
    • Handle: RePEc:eee:ecomod:v:377:y:2018:i:c:p:35-50
    DOI: 10.1016/j.ecolmodel.2018.03.007
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    References listed on IDEAS

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    1. Soetaert, Karline & Petzoldt, Thomas & Setzer, R. Woodrow, 2010. "Solving Differential Equations in R: Package deSolve," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i09).
    2. Collins, Patrick Colman & Croot, Peter & Carlsson, Jens & Colaço, Ana & Grehan, Anthony & Hyeong, Kiseong & Kennedy, Robert & Mohn, Christian & Smith, Samantha & Yamamoto, Hiroyuki & Rowden, Ashley, 2013. "A primer for the Environmental Impact Assessment of mining at seafloor massive sulfide deposits," Marine Policy, Elsevier, vol. 42(C), pages 198-209.
    3. George W. Luther & Tim F. Rozan & Martial Taillefert & Donald B. Nuzzio & Carol Di Meo & Timothy M. Shank & Richard A. Lutz & S. Craig Cary, 2001. "Chemical speciation drives hydrothermal vent ecology," Nature, Nature, vol. 410(6830), pages 813-816, April.
    4. Soetaert, Karline & Petzoldt, Thomas, 2010. "Inverse Modelling, Sensitivity and Monte Carlo Analysis in R Using Package FME," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i03).
    5. Jillian M. Petersen & Frank U. Zielinski & Thomas Pape & Richard Seifert & Cristina Moraru & Rudolf Amann & Stephane Hourdez & Peter R. Girguis & Scott D. Wankel & Valerie Barbe & Eric Pelletier & Den, 2011. "Hydrogen is an energy source for hydrothermal vent symbioses," Nature, Nature, vol. 476(7359), pages 176-180, August.
    6. Martins, Irene & Colaço, Ana & Dando, Paul R. & Martins, Inês & Desbruyères, Daniel & Sarradin, Pierre-Marie & Marques, João Carlos & Serrão-Santos, Ricardo, 2008. "Size-dependent variations on the nutritional pathway of Bathymodiolus azoricus demonstrated by a C-flux model," Ecological Modelling, Elsevier, vol. 217(1), pages 59-71.
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