Marine Biology

, Volume 162, Issue 1, pp 235–243 | Cite as

Metabolic cold adaptation and aerobic performance of blue mussels (Mytilus edulis) along a temperature gradient into the High Arctic region

  • Jakob ThyrringEmail author
  • Søren Rysgaard
  • Martin E. Blicher
  • Mikael K. Sejr
Original Paper


The blue mussel (Mytilus edulis) has recently expanded its northern distribution in the Arctic and is therefore considered to be a sensitive indicator of climate changes in this region. In this study, we compared aerobic performance of blue mussels from High Arctic, Subarctic and temperate populations at different temperatures. Standard metabolic rates (SMR) and active metabolic rates (AMR) were measured for each population, and absolute (AMR − SMR) and factorial (\(\frac{AMR}{SMR}\)) scopes were calculated. Blue mussels from the temperate population had the lowest Q10 (= 1.8) and the largest thermal window (−1 to 25 °C), whereas Q10 values in the Arctic populations were 1.9 (Subarctic) and 2.3 (High Arctic), with a thermal window of −1 to 21 °C. Aerobic scope increased with rising temperatures, reaching a maximum at 14 °C (temperate) and 7 °C (Subarctic and High Arctic, respectively), after which a decrease was observed at temperatures exceeding 14 °C. At low temperatures (−1 °C), the average SMR of the High Arctic population was 93 % higher than that of the temperate population and 22 % higher than that of the Subarctic population. Combined, our results demonstrate physiological adaptation and plasticity of blue mussels across latitudes spanning from 56 to 77ºN. This indicates that low ocean temperature per se does not constrain metabolic activity of Mytilus in the Arctic; rather, we speculate that maturation of reproductive tissues, larval supply and annual energy budgets are the most relevant factors influencing Mytilus populations near their northern distributional edge in the Arctic.


Blue Mussel Thermal Limit Standard Metabolic Rate Aerobic Performance Temperate Population 
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.



The study was financially supported by the 15 June Foundation. JT was supported by the Commission for Scientific Research in Greenland and Aase og Jørgens Münter’s Foundation. The authors wish to thank Kattegatcentret for providing filtrated seawater. We gratefully acknowledge the contributions of Arctic Research Centre (ARC), Aarhus University. SR was supported by the Canada Excellence Research Chair (CERC). This work is a contribution to the Arctic Science Partnership (ASP)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Jakob Thyrring
    • 1
    Email author
  • Søren Rysgaard
    • 1
    • 2
    • 3
  • Martin E. Blicher
    • 2
  • Mikael K. Sejr
    • 1
    • 2
  1. 1.Department of Bioscience, Arctic Research CentreAarhus UniversityAarhus CDenmark
  2. 2.Greenland Climate Research Centre, Greenland Institute of Natural ResourcesNuukGreenland
  3. 3.Centre for Earth Observation ScienceUniversity of ManitobaWinnipegCanada

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