Environmental Variability and Plankton Community Dynamics in the English Channel

Temporal environmental variation plays a key role in shaping plankton community structure and dynamics. In some cases, these ecological changes may be abrupt and long-lived, and constitute a significant change in overall ecosystem structure and function. The “Double Integration Hypothesis”, posed recently by Di Lorenzo and Ohman to help explain these complex biophysical linkages, holds that atmospheric variability is filtered first through the ocean surface before secondarily imprinting on plankton communities. In this perspective, physical properties of the surface ocean, such as sea surface temperature (SST), integrate atmospheric white noise, resulting in a time series that is smoother and has more low than high frequency variability (red noise). Secondarily, long-lived zooplankton integrate over oceanographic conditions and further redden the power spectra. We test the generality of this hypothesis with extensive environmental and ecological data from the L4 station in the Western English Channel (1988-present), calculating power spectral slopes from anomaly time series for atmospheric forcing (wind stress and net heat fluxes), surface ocean conditions (SST and macronutrients), and the biomasses of well over 100 phytoplankton and zooplankton taxa. As expected, we find that SST and macronutrient concentrations are redder in character than white noise atmospheric forcing. However, we find that power spectral slopes for phytoplankton and zooplankton are generally not significantly less than found for oceanographic conditions. Moreover, we find a considerable range in power spectral slopes within the phytoplankton and zooplankton, reflecting the diversity of body sizes, traits, life histories, and predator-prey interactions. We interpret these findings using an idealized trait-based model with a single phytoplankton prey and zooplankton predator, configured to capture essential oceanographic properties at the L4 station, and discuss how changes in power spectral slope seen in the L4 time series are linked to predator-prey body size and generation length differences.