Microzooplankton regulation of surface ocean POC:PON ratios
The elemental composition of particulate organic matter in the surface ocean significantly affects the efficiency of the ocean's store of carbon. Though the elemental composition of primary producers is an important factor, recent observations from the western North Atlantic Ocean revealed that...
Published in: | Global Biogeochemical Cycles |
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Main Authors: | , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
2016
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Subjects: | |
Online Access: | https://eprints.soton.ac.uk/388362/ https://eprints.soton.ac.uk/388362/1/gbc20386.pdf |
Summary: | The elemental composition of particulate organic matter in the surface ocean significantly affects the efficiency of the ocean's store of carbon. Though the elemental composition of primary producers is an important factor, recent observations from the western North Atlantic Ocean revealed that carbon-to-nitrogen ratios (C:N) of phytoplankton were significantly higher than the relatively homeostatic ratio of the total particulate pool (particulate organic carbon:particulate organic nitrogen; POC:PON). Here we use an idealized ecosystem model to show how interactions between primary and secondary producers maintain the mean composition of surface particulates and the difference between primary producers and bulk material. Idealized physiological models of phytoplankton and microzooplankton, constrained by laboratory data, reveal contrasting autotrophic and heterotrophic responses to nitrogen limitation: under nitrogen limitation, phytoplankton accumulate carbon in carbohydrates and lipids while microzooplankton deplete internal C reserves to fuel respiration. Global ecosystem simulations yield hypothetical global distributions of phytoplankton and microzooplankton C:N ratio predicting elevated phytoplankton C:N ratios in the high-light, low-nutrient regions of the ocean despite a lower, homeostatic POC:PON ratio due to respiration of excess carbon in systems subject to top-down control. The model qualitatively captures and provides a simple interpretation for, a global compilation of surface ocean POC:PON data. |
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