Environmental control of marine phytoplankton stoichiometry in the North Atlantic Ocean
The stoichiometric coupling of carbon to limiting nutrients in marine phytoplankton regulates the magnitude of biological carbon sequestration in the ocean. While clear links between plankton C:N ratios and environmental drivers have been identified, the nature and direction of these links, as well...
| Published in: | Proceedings of the National Academy of Sciences |
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| Main Authors: | , |
| Format: | Text |
| Language: | English |
| Published: |
National Academy of Sciences
2021
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| Subjects: | |
| Online Access: | http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740720/ http://www.ncbi.nlm.nih.gov/pubmed/34949718 https://doi.org/10.1073/pnas.2114602118 |
| Summary: | The stoichiometric coupling of carbon to limiting nutrients in marine phytoplankton regulates the magnitude of biological carbon sequestration in the ocean. While clear links between plankton C:N ratios and environmental drivers have been identified, the nature and direction of these links, as well as their underlying physiological and ecological controls, remain uncertain. We show, with a well-constrained mechanistic model of plankton ecophysiology, that while nitrogen availability and temperature emerge as the main drivers of phytoplankton C:N stoichiometry in the North Atlantic, the biological mechanisms involved vary depending on the spatiotemporal scale and region considered. We find that phytoplankton C:N stoichiometry is overall controlled by nitrogen availability below 40° N, predominantly driven by ecoevolutionary shifts in the functional composition of the phytoplankton communities, while phytoplankton stoichiometric plasticity in response to dropping temperatures and increased grazing pressure dominates at higher latitudes. Our findings highlight the potential of “organisms-to-ecosystems” modeling approaches based on mechanistic models of plankton biology accounting for physiology, ecology, and trait evolution to explore and explain complex observational data and ultimately improve the predictions of global ocean models. |
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