Marine Ecology Progress Series · 2020 · 19 citations · 77 references
Life SciencesEcologyOceanographyMarine EcologyPhysical OceanographyPlankton EcologyMarine Ecosystem DynamicsMarine Population DynamicsOcean EcologyPlankton BloomsPlankton Life CyclesZooplankton EcologyOceanographic ForcingPlankton Bloom DynamicsPlankton Population DynamicsSeasonal Bloom DynamicsSeasonal Plankton DynamicsSeasonal VariationTemporal Environmental VariationWhite Noise
Theory and observations suggest that low frequency variation in marine plankton populations, or red noise, may arise through cumulative integration of white noise atmospheric forcing by the ocean and its amplification within food webs. Here, we revisit evidence for the integration of stochastic atmospheric variations by comparing the power spectra of time series of atmospheric and oceanographic conditions to the population dynamics of 150 plankton taxa at Station L4 in the Western English Channel. The power spectra of oceanographic conditions (sea surface temperature, surface nitrate) are redder than those of atmospheric forcing (surface wind stress, net heat fluxes) at Station L4. However, plankton populations have power spectral slopes across trophic levels and body sizes that are redder than atmospheric forcing but whiter than oceanographic conditions. While zooplankton have redder spectral slopes than phytoplankton, there is no significant relationship between power spectral slope and body size or generation length. Using a predator-prey model, we show that the whitening of plankton time series relative to oceanographic conditions arises from noisy plankton bloom dynamics in this strongly seasonal system. The model indicates that, for typical predator-prey interactions, where the predator is on average 10 times longer than the prey, grazing leads to a modest reddening of phytoplankton variability by their larger and longer lived zooplankton consumers. Our findings suggest that, beyond extrinsic forcing by the environment, predator-prey interactions play a role in influencing the power spectra of time series of plankton populations.
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