Abstract
Modelers of global ocean biogeochemistry are beginning to represent a phenomenon that biologists have long observed in laboratory and field settings: that the elemental stoichiometry of phytoplankton is quite flexible. Today, it is well recog-nized that the C:N:P ratio in phytoplankton and particulate organic matter can vary substantially on ocean basin scales. Recent data show that, compared to the traditional Redfield ratio C:N:P = 106:16:1, the ratio is much higher in the oligotrophic subtropical gyres (~195:28:1) and much lower in eutrophic polar waters (~78:13:1). This pattern of variability, informed by results from phytoplankton incubation experiments, indicates that environmental factors such as nutrient availability and temperature are import-ant drivers. Our model simulations of the global ocean carbon cycle under global warming and glacial conditions suggest that phytoplankton physiology and community composition control global C:N:P export. Model results also indicate the import-ant role that Southern Ocean sea ice plays in determining the global export stoichi-ometry by altering the proportional contribution of Southern Ocean phytoplankton to global production. Sea ice retreat under warming and expansion under glaciation, while opposite in sign, can both elevate the global export C:N:P ratio by altering phyto-plankton physiology and community composition in contrasting ways between each scenario. The global mean export C:N:P ratio increases from 113:16:1 in the control run to 119:17:1 by the year 2100 in the future run and to 140:16:1 in the glacial run. The impact of higher export C:N:P ratios is to strongly buffer carbon export against change for both scenarios.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 44-52 |
| Number of pages | 9 |
| Journal | Oceanography |
| Volume | 33 |
| Issue number | 2 |
| DOIs | |
| State | Published - 2020 |
Bibliographical note
Funding Information:This work was funded by the US National Science Foundation (OCE-1827948). KM was supported by the Leverhulme Trust Visiting Professorship at the University of Oxford. RR acknowledges support from ERC Consolidator Grant APPELS: ERC-2015-COG-681746 and a Wolfson Research Merit Award. Numerical modeling and analysis were carried out using resources at the University of Minnesota Supercomputing Institute. Guest editor P. Delaney asked probing questions that motivated us to think deeper about the lowest C:N:P point. All model results presented here are archived at the Biological & Chemical Oceanography Data Management Office and freely accessible (https://doi.org/10.26008/1912/ bco-dmo.810368.1 for the global warming results and https://doi.org/10.26008/1912/bco-dmo.784634.1 for the glacial results).
Publisher Copyright:
© 2020, Oceanography Society. All rights reserved.
