Shifts in regional production as a driver of future global ocean production stoichiometry

Abstract

Using a global ocean biogeochemistry model, we examined three drivers of global ocean production C:N:P ratio: flexible phytoplankton stoichiometry, phytoplankton community composition, and regional production shifts. For a middle-of-the-road warming scenario (SSP2), the model predicts a substantial increase in the global export C:P ratio from 113:1 to 119:1 by the year 2100. The most important physiological driver of this stoichiometric change is the effect of the worldwide warming on cyanobacteria, followed by the effect of phosphate depletion on eukaryotes in the Southern Ocean. Also, there is a modest global shift in the phytoplankton community in favor of cyanobacteria at the expense of eukaryotes with a minimal effect on the global production stoichiometry. We find that shifts in the regional production, even in the absence of any change in phytoplankton stoichiometry or taxonomy, can change the global production C:N:P ratio. For example, enhancing the production in the polar waters, which typically have low C:N:P ratios, will have the effect of lowering the global ratio. In our model, the retreat of Antarctic sea ice has this very effect but is offset by production changes downstream and elsewhere. This study thus provides an understanding of how regional production changes can affect the global production C:N:P ratio. However, the current literature indicates substantial uncertainty in the future projections of regional production changes, so it is unclear at this time what their net effect is on the global production C:N:P ratio. Finally, our model predicts that the overall increase in the carbon content of organic matter due to flexible C:N:P ratio helps to stabilize carbon export in the face of reduced nutrient export (i.e. the decrease in C export is ~30% smaller than expected from the decrease in P export by 2100) but has a minimal effect on atmospheric CO _2 uptake (~1%).

Keywords

• ocean carbon cycle
• stoichiometry
• numerical model
• future projection
• biological production