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The Global Distribution and Drivers of Grazing Dynamics Estimated from Inverse Modelling
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  • Tyler Rohr,
  • Anthony Richardson,
  • Andrew Lenton,
  • Matthew Chamberlain,
  • Elizabeth Shadwick
Tyler Rohr
Institute for Marine and Antarctic Science, University of Tasmania, Hobart, Tasmania, 7000, Australia, Institute for Marine and Antarctic Science, University of Tasmania, Hobart, Tasmania, 7000, Australia

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Anthony Richardson
CSIRO
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Andrew Lenton
CSIRO
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Matthew Chamberlain
CSIRO
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Elizabeth Shadwick
CSIRO Marine and Atmospheric Research
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Abstract

We examine how zooplankton influence phytoplankton bloom phenology from the top-down, then use inverse modelling to infer the distribution and drivers of mean community zooplankton grazing dynamics based on the skill with which different simulated grazing formulations are able to recreate the observed seasonal cycle in phytoplankton biomass. We find that oligotrophic (eutrophic) biomes require more (less) efficient grazing dynamics, characteristic of micro- (meso-) zooplankton, leading to a strong relationship between the observed mean annual phytoplankton concentration in a region and the optimal grazing parameterization required to simulate it’s observed phenology. Across the globe, we found that a type III functional response consistently exhibits more skill than a type II response, suggesting the mean dynamics of a coarse model grid-cell should offer stability and prey refuge at low biomass concentrations. These new observationally-based global distributions will be invaluable to help constrain, validate and develop next generation of biogeochemical models.