Marine Biology

, Volume 161, Issue 2, pp 447–458 | Cite as

Lower thermal capacity limits of the common brown shrimp (Crangon crangon, L.)

  • Stefan Reiser
  • Jens-Peter Herrmann
  • Thomas Neudecker
  • Axel Temming
Original Paper


Brown shrimp (Crangon crangon, L.) are subjected to a huge annual temperature range, and certain thermal conditions during winter have been identified to affect the brown shrimp population. Despite that, little is known about its thermal biology with regard to critically low temperatures. In the present study, we determined the critical thermal minima (CTmin) and the critical lethal minima (CLmin) of male and female brown shrimp of different body sizes in laboratory-based experiments. For the CTmin trials, shrimp were acclimated to 4.0, 9.0, and 14.0 °C and exposed to a cooling rate of −0.2 °C min−1. In the CLmin trials, brown shrimp were exposed to a cooling rate of −1.0 °C day−1 without prior thermal acclimation. Acclimation temperature significantly affected the temperature tolerance of brown shrimp (p < 0.001). CTmin among the experimental groups just varied slightly, and no clear effect of gender or body size was observed. In the CLmin trials, brown shrimp even tolerated the coldest temperature of −1.7 °C that could be established in the experimental setup. However, we observed a negative relationship between temperature and reactivity within the range of 7.0 and 1.0 °C that was determined by means of the flicking response. This relationship suddenly broke between 1.0 and 0.0 °C where an abrupt drop in the reactivity of the shrimp became apparent. The results of this study revealed that brown shrimp hold a wider thermal range as originally reported and that it can cope with subzero temperatures. Implications of low-temperature tolerance are discussed in the context of the brown shrimp’s ecology as well as stock assessment.


Acclimation Temperature Brown Shrimp Winter Water Temperature Righting Response Dynamic Energy Budget Model 
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 authors thank the crew from the research vessel FFS Solea for providing life brown shrimp for this study. Andre Eckhardt and Jörg Bruhn are thanked for their help in setup construction and assembly. We thank Sven Stäker, Wiebke Bretting, and Paul Haffke for laboratory assistance and their help during the experiments. Marc Hufnagl provided helpful comments on the design of the study. We further thank Klaus Huebert for his advice on segmented regression as well as Bart Verschueren and Yves Verhaegen for their advice on the electric pulse trials. This study was partly funded by the Cluster of Excellence “Integrated Climate System Analysis and Prediction” (CliSAP) of the University of Hamburg. We also acknowledge the constructive comments of two anonymous reviewers on an earlier version of this manuscript.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Stefan Reiser
    • 1
    • 2
  • Jens-Peter Herrmann
    • 1
  • Thomas Neudecker
    • 3
  • Axel Temming
    • 1
  1. 1.Institute for Hydrobiology and Fisheries ScienceUniversity of HamburgHamburgGermany
  2. 2.Thünen-Institute of Fisheries EcologyHamburgGermany
  3. 3.Thünen-Institute of Sea FisheriesHamburgGermany

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