The Amazon River imprint on the marine biogeochemistry

Context

  •  The nutrient-rich waters of the Amazon River support a large phytoplankton production
  •  The sinking fuxes resulting from this enhanced primary productivity provide new pathways for carbon sequestration which has been hypothesized to explain the observed anomalously low pCO2 values in the areas influenced by the plume
  •  Fully coupled numerical modeling will allow us to unravel the complex interplay between physical and biogeochemical processes
Methods: a modeling experiment

We use the UCLA-ETH version of the Regional Oceanic Modeling System (ROMS) coupled with the Biogeochemical Elemental Cycling Model (BEC). The setup has a telescopic grid (as seen below) with an eddy-resolving resolution at the mouth of the river while simulating the entire Atlantic Ocean.
                                                   Telescopic grid                                                                                             Surface chlorophyll simulated for one day in May

BEC has 1 zooplankton class and 3 phytoplankton functional types: small phytoplankton (with implicit calcifiers), diatoms and diazotroph (based on Trichodesmium). This version of the code has been augmented with a 4th phytoplankton type: the Diatom-Diazotroph-Assemblages (DDAs) which represent a symbiosis between a diatom and diazotroph. Based on in situ measurements, it has been hypothesized that DDAs play a crucial role in the carbon export within the river plume.

The baseline simulation reproduces quite well the spread of the river plume and the strong blooms within. The total Net Primary Production for the region plotted below is 1.33 Pg C yr-1 when SeaWiFS estimate is 1.59  C yr-1.


Average surface chlorophyll in spring on the left panel and fall on the right panel. Plume limits as <35 PSU in the baseline simulation (solid line) and in satellite data* (dotted line).

* SMAP project (2015-2017 average)


The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovaton programme under the Marie Sklodowska-Curie grant agreement No 643052 (C-CASCADES project).