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The Global Distribution and Drivers of Grazing Dynamics Estimated from Inverse Modelling 
  • +2
  • Tyler Rohr,
  • Anthony Richardson,
  • Andrew Lenton,
  • Matt Chamberlain,
  • Elizabeth Shadwick
Tyler Rohr
Australian Antarctic Partnership Program, Institute for Marine and Antarctic Science, University of Tasmania

Corresponding Author:[email protected]

Author Profile
Anthony Richardson
Commonwealth Scientific and Industrial Research Organisation (CSIRO) Oceans and Atmosphere, 8 BioSciences Precinct (QBP), School of Mathematics and Physics, The University of Queensland
Andrew Lenton
Commonwealth Scientific and Industrial Research Organisation (CSIRO) Oceans and Atmosphere
Matt Chamberlain
Commonwealth Scientific and Industrial Research Organisation (CSIRO) Oceans and Atmosphere, School of Mathematics and Physics, The University of Queensland
Elizabeth Shadwick
Commonwealth Scientific and Industrial Research Organisation (CSIRO) Oceans and Atmosphere, Commonwealth Scientific and Industrial Research Organisation (CSIRO) Oceans and Atmosphere, 8 BioSciences Precinct (QBP), Australian Antarctic Partnership Program, Institute for Marine and Antarctic Science, University of Tasmania

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.
06 Dec 2022Submitted to ESS Open Archive
07 Dec 2022Published in ESS Open Archive