The Global Distribution and Drivers of Grazing Dynamics Estimated from
Inverse Modelling
- Tyler Weaver Rohr,
- Anthony Richardson,
- Andrew Allan Lenton,
- Matthew A Chamberlain,
- Elizabeth H. Shadwick
Andrew Allan Lenton
Commonwealth Scientific and Industrial Research Organisation (CSIRO) Oceans and Atmosphere
Author ProfileMatthew A Chamberlain
CSIRO Marine and Atmospheric Research
Author ProfileAbstract
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