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Ocean biogeochemical response to phytoplankton-light feedback in a global model

By Manfredi Manizza, Corinne Le Quéré, Andrew J. Watson and Erik T. Buitenhuis

Abstract

Oceanic phytoplankton, absorbing solar radiation, can influence the bio-optical properties of seawater and hence upper ocean physics. We include this process in a global ocean general circulation model (OGCM) coupled to a dynamic green ocean model (DGOM) based on multiple plankton functional types (PFT). We not only study the impact of this process on ocean physics but we also explore the biogeochemical response due to this biophysical feedback. The phytoplankton-light feedback (PLF) impacts the dynamics of the upper tropical and subtropical oceans. The change in circulation enhances both the vertical supply in the tropics and the lateral supply of nutrients from the tropics to the subtropics boosting the subtropical productivity by up to 60 gC m(-2) a(-1). Physical changes, due to the PLF, impact on light and nutrient availability causing shifts in the ocean ecosystems. In the extratropics, increased stratification favors calcifiers (by up to similar to 8%) at the expense of mixed phytoplankton. In the Southern Ocean, silicifiers increase their biomass (by up to similar to 10%) because of the combined alleviation of iron and light limitation. The PLF has a small effect globally on air-sea fluxes of carbon dioxide (CO2, 72 TmolC a(-1) outgassing) and oxygen (O-2, 46 TmolO(2) a(-1) ingassing) because changes in biogeochemical processes (primary production, biogenic calcification, and export production) highly vary regionally and can also oppose each other. From our study it emerges that the main impact of the PLF is an amplification of the seasonal cycle of physical and biogeochemical properties of the high-latitude oceans mostly driven by the amplification of the SST seasonal cycle

Topics: Marine Sciences, Meteorology and Climatology, Ecology and Environment
Publisher: American Geophysical Union
Year: 2008
DOI identifier: 10.1029/2007JC004478
OAI identifier: oai:nora.nerc.ac.uk:11563

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