A diatom extension to the cGEnIE Earth system model – EcoGEnIE 1.1

We extend the ecological component (ECOGEM) of the carbon-centric Grid-Enabled Integrated Earth system model (cGEnIE) to include a diatom functional group. ECOGEM represents plankton community dynamics via a spectrum of ecophysiological traits originally based on size and plankton food web (phyto- and zooplankton; EcoGEnIE 1.0), which we developed here to account for a diatom functional group (EcoGEnIE 1.1). We tuned EcoGEnIE 1.1, exploring a range of ecophysiological parameter values specific to phytoplankton, including diatom growth and survival (18 parameters over 550 runs) to achieve best fits to observations of diatom biogeography and size class distribution as well as to global ocean nutrient and dissolved oxygen distributions. This, in conjunction with a previously developed representation of opal dissolution and an updated representation of the ocean iron cycle in the water column, resulted in an improved distribution of dissolved oxygen in the water column relative to the previous EcoGEnIE 1.0, with global export production (7.4 Gt C yr−1) now closer to previous estimates. Simulated diatom biogeography is characterised by larger size classes dominating at high latitudes, notably in the Southern Ocean, and smaller size classes dominating at lower latitudes. Overall, diatom biological productivity accounts for ∼20 % of global carbon biomass in the model, with diatoms outcompeting other phytoplankton functional groups when dissolved silica is available due to their faster maximum photosynthetic rates and reduced palatability to grazers. Adding a diatom functional group provides the cGEnIE Earth system model with an extended capability to explore ecological dynamics and their influence on ocean biogeochemistry.


Publication status:
Authors: Naidoo-Bagwell, Aaron A., Monteiro, Fanny M., Hendry, Katharine R. ORCIDORCID record for Katharine R. Hendry, Burgan, Scott, Wilson, Jamie D., Ward, Ben A., Ridgwell, Andy, Conley, Daniel J.

On this site: Kate Hendry
27 February, 2024
Geoscientific Model Development / 17