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Marine Biology

, Volume 160, Issue 10, pp 2723–2732 | Cite as

Thermal tolerance of larvae of Pollicipes elegans, a marine species with an antitropical distribution

  • Kathleen WaltherEmail author
  • Samuel E. Crickenberger
  • Sergio Marchant
  • Peter B. Marko
  • Amy L. Moran
Original Paper

Abstract

For the antitropical gooseneck barnacle Pollicipes elegans, population-specific physiological temperature tolerance of larvae may serve as a barrier to larval dispersal across the warmest regions of the tropical Pacific Ocean. Thermal tolerance ranges of larvae of three different populations of P. elegans sampled in 2011 and 2012 (Mexico [MX], El Salvador [ES], and Peru [PE]) were investigated by measuring three indicators of physiological performance: swimming activity, oxygen consumption, and lethality or LT50. The thermal tolerance profiles, which include measurable optimum (maximum aerobic performance), pejus (“getting worse”) and pessimum (worst aerobic performance) ranges, of larvae from the three populations were consistent with their characteristic environmental temperatures. In MX, larvae live close to the upper border of their optimum during warm months and so have a limited capacity to tolerate higher-than-normal temperatures. Larvae from the ES population likewise appear to live within their optimum temperature range, but these larvae lack a detectable pessimum range, suggesting they would be unable to cope with temperatures above their pejus range. Larvae from PE have a broad optimum but no pejus range. Different thermal tolerance ranges provide strong evidence for population-dependent physiological adaptations in P. elegans. For the southern (PE) and northern (MX) P. elegans populations, high tropical temperatures are likely to be a strong direct physiological barrier to larval survival and dispersal, which is in contrast to the more thermally tolerant ES population.

Keywords

Oxygen Consumption Rate Thermal Tolerance Green Crab Rhodomonas Salina Warm Tropical Water 
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.

Notes

Acknowledgements

This work was supported by Clemson University’s Department of Biological Sciences and by the National Science Foundation (OCE-0961996 to PBM and ALM). We thank Carmen Yamashiro from the Marine Invertebrates Research unit of IMARPE in Peru and Enrique Barraza from the Natural Resources and Environmental Department in El Salvador for providing collection permits and logistical support. We also thank L. Plough and C. Genovese for help with collection and technical support.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Kathleen Walther
    • 1
    Email author
  • Samuel E. Crickenberger
    • 1
  • Sergio Marchant
    • 1
  • Peter B. Marko
    • 1
  • Amy L. Moran
    • 1
  1. 1.Department of Biological SciencesClemson UniversityClemsonUSA

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