JPR Advance Access originally published online on August 22, 2006
Journal of Plankton Research 2006 28(11):1039-1046; doi:10.1093/plankt/fbl037
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Zooplankton and the North Atlantic Oscillation: a basin-scale analysis
1 Institute of Biology of the Southern Seas, Sevastopol, 99011 Crimea, Ukraine, 2 Marine Sciences Research Center, Stony Brook University, Stony Brook, NY 11794, USA, 3 National Marine Fisheries Service—NOAA, 1315 East-West Highway, Silver Spring, MD 20910, USA, 4 Laboratorio di Biologia Marina, University of Trieste, Trieste 34010, Italy, 5 Institute of Fishery, Almaty 480060, Kazakhstan, 6 Institute of Zoology, Almaty 480060, Kazakhstan and 7 Caspian Biological Station, Institute of Zoology, Baku 370073, Azerbaijan
* Corresponding Author: spiontkovski{at}notes.cc.sunysb.edu
Received March 13, 2006; accepted in principle July 10, 2006; accepted for publication August 17, 2006; published online August 22, 2006
Communicating editor: R.P. Harris
This study examines multiple, long-term zooplankton time series across the Atlantic region and its inland seas. Across a broad range of geographic regions and ecological environments, the impact of the North Atlantic Oscillation (NAO) on interannual changes in the zooplankton populations was evident. Across the mid-Atlantic, a correlation between the NAO and zooplankton abundance was present and remained positive from the northwestern Atlantic through the enclosed seas of the far eastern Atlantic. Following high NAO years, these regions experienced higher total zooplankton abundance or biomass. Following low NAO years, this trend was reversed. A time lag in the zooplankton response to the NAO was also evident, influenced more by the scale of the water basin than by latitudinal or longitudinal location. For some regions, the correlation between zooplankton and the NAO was higher when the NAO was substituted with its sub-components: the Azores High (AH) and the Icelandic Low (IL) atmospheric pressure systems. This suggests that decomposition of the NAO into its components might enhance the sensitivity of the analysis of biological time series with regard to climate change.
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