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The Global Distribution and Drivers of Grazing Dynamics Estimated from Inverse Modelling
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  • Tyler Weaver Rohr,
  • Anthony Richardson,
  • Andrew Allan Lenton,
  • Matthew A Chamberlain,
  • Elizabeth H. Shadwick
Tyler Weaver Rohr
University of Tasmania

Corresponding Author:[email protected]

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Anthony Richardson
University of Queensland, Australia
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Andrew Allan Lenton
Commonwealth Scientific and Industrial Research Organisation (CSIRO) Oceans and Atmosphere
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Matthew A Chamberlain
CSIRO Marine and Atmospheric Research
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Elizabeth H. Shadwick
CSIRO Oceans & Atmosphere
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We use inverse modelling to infer the distribution and drivers of community-integrated zooplankton grazing dynamics based on the skill with which different grazing formulations recreate the satellite-observed seasonal cycle in phytoplankton biomass. We find that oligotrophic and eutrophic biomes require more and less efficient grazing dynamics, respectively. This is characteristic of micro- and mesozooplankton, respectively, and leads to a strong sigmoidal relationship between observed mean-annual phytoplankton biomass and the optimal grazing parameterization required to simulate its seasonal cycle. Globally, we find Type III rather than Type II functional response curves consistently exhibit higher skill. These new observationally-based distributions can help constrain, validate and develop next-generation biogeochemical models.
17 May 2023Submitted to ESS Open Archive
25 May 2023Published in ESS Open Archive