MESOSCALE EDDIES INFLUENCE ZOOPLANKTON DISTRIBUTION AND GRAZING IN THE GULF OF MEXICO

Abstract

Carbon biomass and net primary productivity, for two size classes of phytoplankton in the Gulf of Mexico (GoM), are calculated from ocean color remote sensing data. Combining these estimates with mechanistic ecosystem model equations allows for analysis of how changes in phytoplankton biomass and community structure propagate through the food web to zooplankton. Biomass and grazing rates are calculated for three size classes of zooplankton (small, large, and predatory) by solving equations from the NEMURO model describing the growth of small and large phytoplankton and zooplankton using the remote sensing net primary productivity, biomass, temperature, and mixed layer depth. The ecosystem model and approach are validated for the GoM and used to assess error propagation. An eddy detection algorithm, tuned for the GoM, is used to calculate the phytoplankton and zooplankton biomass within eddy centers, around eddy edges, and in the immediate surroundings of the eddy to determine the impact of cyclonic and anticyclonic eddies and submesoscale edge effects on patterns of trophic transfer variability. Cyclonic eddy centers increase biomass and anticyclonic eddy centers decrease biomass in the oligotrophic GoM. Eddy edges contribute to variability in biomass but to a lesser extent than eddy centers. Zooplankton grazing varies in a similar pattern as biomass, and in this oligotrophic region, most grazing is on the largest size class of prey available. Nutrient injection stimulated by eddy dynamics more strongly projects onto biomass in zooplankton trophic levels and their associated grazing which suggests many eddies in the oligotrophic GoM experience top-down control. An understanding of mesoscale eddy impacts on zooplankton dynamics may explain variations in larval fish growth. Advances in remote sensing that allow the discrimination of phytoplankton functional types, such as the new PACE satellite, will be useful for providing a more complete base of the food web and thus enhance estimation of zooplankton biomass.