Roshan and collaborators present new observations of dissolved iron and its physical speciation in the South Pacific
Jun / 10 / 2020
Modelling
Silicon isotopes reveal the different Arctic endmembers contributing to the deep water formed in the North Atlantic Ocean
Combining a multiparametric analysis, biogenic and dissolved silicon (Si) isotope data (30Si-bSiO2 and δ30Si-DSi, respectively) in the Arctic Ocean, Liguori and co-workers (2020, see reference below) could unravel the influence of water masses on the δ30Si-DSi distribution within the Arctic Ocean. Any deviation of the δ30Si-DSi signature from pure mixing was attributed to the contribution […]
Apr / 20 / 2020
Particulate fluxes and circulation in a changing Arctic Ocean: tracer data and modeling
A complete review of published and new water column profiles of thorium-230 (230Th) and protactinium-231 (231Pa) concentrations and neodymium (Nd) isotopic compositions collected in the Amerasian Basin of the Arctic Ocean between 1983 and 2015 was performed by Grenier and co-workers (2019, see reference below). This review allowed them to identify regional and temporal variability […]
Mar / 27 / 2020
Is the global primary production at it’s maximum rate?
Lauderdale and co-authors (2020, see reference below) are seriously questioning the paradigm establishing that marine phytoplankton growth is limited by iron on a global scale. Iron availability to marine microbes is facilitated by binding with organic molecules which, in turn, are produced by microbes. The authors hypothesize this forms a reinforcing cycle between biological activity […]
Feb / 25 / 2020
Neural network as tools to replace oceanic data deficiencies
The importance of the cycle and speciation of nitrate and its isotopes (δ15N) in the ocean does not have to be demonstrated anymore. In an attempt to overcome the difficulty to compare the results of N/δ15N cycle models to a sparse set of data, Rafter and co-workers propose an original approach, based on artificial intelligence […]
Dec / 16 / 2019
Artificial intelligence helps investigate the oceanic zinc cycle
What explains the hitherto mysterious correlation between zinc (Zn) and silicon, an element not involved in the Zn cycle? Roshan and co-workers (2018, see reference below) used an artificial neural network (ANN, a machine learning technique inspired by biological neural systems) to produce a global climatology of dissolved Zn concentration, the first such global climatology […]
Jan / 24 / 2019
More realistic oceanic particle field improved the thorium-230 and protactinium-231 modeling
Thorium-230 (230Th) and protactinium-231 (231Pa) are two geochemical tracers extensively used for investigating particle transport in the ocean and reconstructing past ocean circulation. A key feature in reproducing their distributions by modelling is to understand and constrain as good as possible the scavenging processes, which means: 1) having the good adsorption-desorption kinetic rates and 2) describing […]
Dec / 10 / 2018
Influence of particle composition on the rate constants of thorium adsorption
Chemical species are constantly exchanged between seawater (solution, D) and particles (solid material, P). This continuous D-P exchange is a key process determining the chemical composition of the ocean. Particles are heterogeneous materials, made of (i) biological material from the surface ocean, (ii) lithogenic material from external inputs to the ocean, and (iii) authigenic (oxyhydr)oxides […]
Sep / 04 / 2018
Manganese in the west Atlantic Ocean in the context of the first global ocean circulation model of manganese
Marco van Hulten and co-workers (2017, see reference below) ran a global ocean model to understand manganese (Mn), a biologically essential element. The model shows that: (i) in the deep ocean, dissolved [Mn] is mostly homogeneous ~0.10—0.15 nM. The model reproduces this with a threshold on MnO₂ of 25 pM, suggesting a minimal particle concentration […]
Jun / 29 / 2017