Low cobalt inventories in the Amundsen and Ross seas driven by high demand for labile cobalt uptake among native phytoplankton communities
Bibliographic record
Abstract
Abstract. Cobalt (Co) is a scarce but essential micronutrient for marine plankton in the Southern Ocean and coastal Antarctic seas, where dissolved cobalt (dCo) concentrations can be extremely low. This study presents total dCo and labile dCo distributions measured via shipboard voltammetry in the Amundsen Sea, the Ross Sea and Terra Nova Bay during the CICLOPS (Cobalamin and Iron Co-Limitation of Phytoplankton Species) expedition. A significantly smaller dCo inventory was observed during the 2017/2018 CICLOPS expedition compared to two 2005/2006 expeditions to the Ross Sea conducted over a decade earlier. The dCo inventory loss (∼ 10–20 pM) was present in both the surface and deep ocean and was attributed to the loss of labile dCo, resulting in the near-complete complexation of dCo by strong ligands in the photic zone. A changing dCo inventory in Antarctic coastal seas could be driven by the alleviation of iron (Fe) limitation in coastal areas, where the flux of Fe-rich sediments from melting ice shelves and deep sediment resuspension may have shifted the region towards vitamin B12 and/or zinc (Zn) limitation, both of which are likely to increase the demand for Co among marine plankton. High demand for Zn by phytoplankton can result in increased Co and cadmium (Cd) uptake because these metals often share the same metal uptake transporters. This study compared the magnitudes and ratios of Zn, Cd and Co uptake (ρ) across upper-ocean profiles and the observed order-of-magnitude uptake trends (ρZn > ρCd > ρCo) that paralleled the trace metal concentrations in seawater. High rates of Co and Zn uptake were observed throughout the region, and the speciation of available Co and Zn appeared to influence trends in dissolved metal : phosphate stoichiometry and uptake rates over depth. Multi-year loss of the dCo inventory throughout the water column may be explained by an increase in Co uptake into particulate organic matter and subsequently an increased flux of Co into sediments via sinking and burial. This perturbation of the Southern Ocean Co biogeochemical cycle could signal changes in the nutrient limitation regimes, phytoplankton bloom composition and carbon sequestration sink of the Southern Ocean.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".