Metabolic response of Arctic pteropods to ocean acidification and warming during the polar night/twilight phase in Kongsfjord (Spitsbergen)
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Thecosome pteropods are considered highly sensitive to ocean acidification. During the Arctic winter, increased solubility of CO2 in cold waters intensifies ocean acidification and food sources are limited. Ocean warming is also particularly pronounced in the Arctic. Here, we present the first data on metabolic rates of two pteropod species (Limacina helicina, Limacina retroversa) during the Arctic winter at 79°N (polar night/twilight phase). Routine oxygen consumption rates and the metabolic response [oxygen consumption (MO2), ammonia excretion (NH3), overall metabolic balance (O:N)] to elevated levels of pCO2 and temperature were examined. Our results suggest lower routine MO2 rates for both Limacina species in winter than in summer. In an 18-h experiment, both pCO2 and temperature affected MO2 of L. helicina and L. retroversa. After a 9-day experiment with L. helicina all three metabolic response variables were affected by the two factors with interactive effects in case of NH3 and O:N. The response resembled a “hormesis-type” pattern with up-regulation at intermediate pCO2 and the highest temperature level. For L. retroversa, NH3 excretion was affected by both factors and O:N only by temperature. No significant effects of pCO2 or temperature on MO2 were detected. Metabolic up-regulation will entail higher energetic costs that may not be covered during periods of food limitation such as the Arctic winter and compel pteropods to utilize storage compounds to a greater extent than usual. This may reduce the fitness and survival of overwintering pteropods and negatively impact their reproductive success in the following summer.
KeywordsPteropods Arctic Winter Ocean acidification Ocean warming Metabolic response
The AWIPEV station and Kings Bay AS in Ny Ålesund and the Institute for Polar Ecology in Kiel are acknowledged for logistical support. M. Marquardt assisted with the field and laboratory work. Thanks are also due to J. Büdenbender and K. Schulz for help with the CO2-system perturbation/calculation, as well as D. Hellemann, A. Ludwig, J. Meyer and I. Schaub for DIC and alkalinity analyses. Constructive comments of three anonymous reviewers helped improve the final manuscript. A. Paul is gratefully acknowledged for English proof reading. PreSens (Regensburg, Germany) provided the SensorDish Reader. This work contributes to the German BMBF (Federal Ministry for Education and Research) funded project Biological Impacts of Ocean Acidification (BIOACID, Grant Number 03F0608A).
- ACIA (2004) Artic climate impact assessment. Impacts of a warming Arctic: Arctic climate impact assessment. Cambridge University Press, CambridgeGoogle Scholar
- Cummings V, Hewitt J, Van Rooyen A, Currie K, Beard S, Thrush S, Norkko J, Barr N, Heath P, Halliday NJ, Sedcole R, Gomez A, McGraw C, Metcalf V (2011) Ocean acidification at high latitudes: potential effects on functioning of the Antarctic bivalve Laternula elliptica. PLoS ONE 6:e16069CrossRefPubMedPubMedCentralGoogle Scholar
- Dickson AG, Sabine CL, Christian JR (2007) Guide to the best practices for ocean CO2 measurements. PICES Special Publication 3Google Scholar
- Ikeda T (1970) Relationship between respiration rate and body size in marine plankton animals as a function of the temperature of habitat. Bull Fac Fish 21:91–112Google Scholar
- IPCC (2013) Climate Change 2013: the physical science basis. In: Contribution of working group I to the fifth assessment report of the intergovernmental panel on Climate Change. Cambridge University Press, Cambridge, New YorkGoogle Scholar
- Koroleff F, Grasshoff K (1983) Determination of nutrients. In: Grasshoff K, Ehrhardt M, Kremling K (eds) Methods of seawater analysis. Verlag Chemie, WeinheimGoogle Scholar
- Lalli CM, Gilmer RW (1989) Pelagic snails: the biology of holoplanktonic gastropod molluscs. Stanford University Press, StanfordGoogle Scholar
- Meehl GA, Stocker TF, Collins WD, Friedlingstein P, Gaye AT, Gregory JM, Kitoh A, Knutti R, Murphy JM, Noda A, Raper SCB, Watterson IG, Weaver AJ, Zaoh C-Z (2007) Global Climate Projections. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate Change 2007: The physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
- Pierrot DEL, Wallace DWR (2006) MS Excel program developed for CO2 system calculations. ORNL/CDIAC-105, Oak Ridge, Tennessee, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of EnergyGoogle Scholar
- R Development Core Team (2012) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. http://www.R-project.org/. ISBN 3-900051-07-0