Determining drivers of phytoplankton carbon to chlorophyll ratio at Atlantic Basin scale

FRONTIERS IN MARINE SCIENCE(2023)

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摘要
We demonstrate the ability of flow cytometry to determine species specific cellular carbon and chlorophyll content in vivo by using laboratory cultures of phytoplankton encompassing a wide range of cell sizes. When applied to the large Atlantic Meridional Transect flow cytometry dataset, we reveal patterns in the species-specific phytoplankton carbon (C), chlorophyll (Chl) and C:Chl ratio. For Prochlorococcus the range of C:Chl is between 2 - 604; for Synechococcus 0.5 - 558. Using a Random Forest machine learning approach, we show that predictability of phytoplankton C:Chl, dominated by the prevalence of Prochlorococcus, is largely driven by silicate and nitrite concentration in the Atlantic Ocean.
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关键词
flow cytometry, carbon, chlorophyll, machine learning, random forests, Atlantic Ocean, phytoplankton, physiology
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