The Microbial Carbon Pump: Quantifying the Dynamics of Dissolved Organic Carbon and its Impact on Atmospheric CO2

The exchange of carbon dioxide (CO₂) between the ocean and atmosphere is strongly mediated by the fate of organic carbon produced by phytoplankton. The existence of a relatively large (662 Pg C), well-mixed pool of dissolved organic carbon (DOC), characterized by radiocarbon ages of between 4000 and 6000 years, has recently led to the conceptualization of the Microbial Carbon Pump (MCP): a pump that sequesters atmospheric CO₂ in the ocean on millennial timescales by maintaining a gradient in reactivity due to formation of recalcitrant DOC (RDOC) from the bacterial degradation of labile DOC. The MCP can be considered as an extension of the Biological Pump but with different dynamics. Changes in the production and/or the degradation of RDOC are predicted for the future ocean with impacts on atmospheric CO₂. However, the precise mechanisms of change are still uncertain and their impacts on atmospheric CO₂ are currently unquantified.

Here I quantify the potential impact of the Microbial Carbon Pump on atmospheric CO₂ and marine biogeochemistry using the Earth system model cGEnIE. The model represents two pools of DOC: one rapidly cycled labile pool and one long-lived recalcitrant pool, calibrated against observed DOC concentrations and carbon isotopes. I test a series of idealized scenarios in RDOC production and degradation to quantify the sensitivity of atmospheric CO₂ and ocean biogeochemistry with changes in this system. In particular, I test changes in 1) partitioning of POC and RDOC in export production; 2) partitioning between RDOC and labile DOC; 3) non-Redfield stoichiometry of RDOC, and 4) whether degradation is determined by reactivity or concentration. Model results show that atmospheric CO₂ is most sensitive to assumptions about RDOC degradation and to non-Redfield stoichiometry. Much of this sensitivity arises from interactions between the Biological Pump and RDOC with implications for long-term climate.