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The spatial, temporal, taxonomic, and ecological scales considered here force some simplifications. For example, all abundance estimates in this study represent indices of near-surface plankton abundance and not absolute values, because the CPR is towed at a depth of ∼10 m and many taxa, especially smaller ones, are caught only semiquantitatively. We calculate abundance rather than biomass time series for each trophic level because neither mass nor length measurements are taken from CPR samples, so biomass estimates would require additional assumptions. Within the coarse trophic categories in this study, members (supporting online text) are deemed to be generalist feeders, so each is considered a functional group. Although the phytoplankton compartment does not include nanoflagellates (they are too delicate to be preserved on CPR silks), we are primarily interested in phytoplankton as food for herbivorous copepods, and these feed preferentially on the larger phytoplankton. The Zooplankton carnivore compartment includes data on siphonophore abundance, but corresponding data for other cnidarians are not available due to damage during sampling. We do not include meroplankton because their dynamics can be heavily influenced by processes independent of the pelagic ecosystem. We also do not include various other functional groups such as picoplankton, fish, birds, or marine mammals because time series are not available at the appropriate scales for our study. Thus, our conclusions can only be applied to groups sampled quantitatively by the CPR and cannot easily be extended to include the entire pelagic ecosystem.
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We do not use wind or hydrographic (current) data because they have differential effects over the study domain. Reliable time series for clouds are rare over the entire study period (1958 to 2002) and domain. We also do not use an integrative environmental index such as the NAO because it does not allow analysis of the direct responses of plankton communities to their local environment, and because the effects of climate change on the NAO are less clearly understood than are those on SST.
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To apply the modified Chelton Method we estimated autocorrelation functions for each time series. Because many were broken, we used a spline smoother to interpolate data for up to two missing years. These interpolated data were used only to determine the number of degrees of freedom to be removed from analyses; in no way were they used to inflate the time series or to alter correlation coefficients.
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We thank A. Lindley and M. Gibbons for helping us assign zooplankton to functional groups, as well as the Hadley Centre, UK Met Office, for providing the SST data (HadISST Version 1.1) at no cost. D.S.S. gratefully acknowledges the funding generously provided for this work by the South African National Research Foundation (GUN 2053579), the Ernest Oppenheimer Memorial Trust, and the University of Port Elizabeth, and A.J.R. acknowledges the financial support of Department of Environment Food and Rural Affairs contract MF0430. The CPR survey would not be possible without the cooperation of the agents, owners, masters, and crews of the vessels that tow the recorders. A funding consortium made up of governmental agencies from Canada, France, Iceland, Ireland, the Netherlands, Portugal, the United Kingdom, and the United States financially supports the survey. CPR data are available freely to the international scientific community for research (see www.sahfos.org).
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