The Distribution of Nickel in the West-Atlantic Ocean, Its Relationship With Phosphate and a Comparison to Cadmium and Zinc
Bibliographic record
Abstract
Nickel (Ni) is a bio-essential element required for the growth of phytoplankton. It is the least studied bio-essential element, mainly because surface ocean Ni concentrations are never fully depleted and Ni is not generally considered to be a limiting factor. However, stimulation of growth after Ni addition has been observed in past experiments when seemingly ample ambient dissolved Ni was present, suggesting not all dissolved Ni is bio-available. This study details the distribution of Ni along the GEOTRACES GA02 Atlantic Meridional section. Concentrations of Ni were lowest in the surface ocean and the lowest observed concentration of 1.7 nmol kg-1 was found in the northern hemisphere. The generally lower surface concentrations in the northern hemisphere subtropical gyre compared to the southern hemisphere, might be related to a greater Ni uptake by nitrogen fixers that are stimulated by iron deposition. The distribution of Ni resembles the distribution of cadmium (Cd) and also features a so called kink (change in the steepness of slope) in the Ni-PO4 relationship. Like for Cd, this is caused by the mixing of Nordic and Antarctic origin water masses. The overall distribution of Ni is driven by mixing with an influence of regional remineralisation. This influence of remineralisation is, with a maximum remineralisation contribution of 13% of the highest observed concentration, smaller than for Cd (30%), but larger than for zinc (Zn; 6%). The uptake pattern in the formation regions of Antarctic origin water masses is suggested to be more similar to Zn than to Cd, however, the surface concentrations of Ni are never fully depleted. This results in a North Atlantic concentration distribution of Ni where the trends of increasing and decreasing concentrations between water masses are similar to those observed for Cd, but the actual concentrations as well as the uptake and remineralisation patterns are different between these elements.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".