High metabolic zinc demand within native Amundsen and Ross Sea phytoplankton communities determined by stable isotope uptake rate measurements
Bibliographic record
Abstract
Abstract. Zinc (Zn) is an essential micronutrient for most eukaryotic phytoplankton. Zn uptake by phytoplankton within the euphotic zone results in nutrient-like dissolved Zn profiles (dZn) with a large dynamic range. The combination of key biochemical uses for Zn and large vertical gradients in dZn implies the potential for rapid rates of Zn removal from the surface ocean. However, due to the ease of contamination at sea, direct measurements of dZn uptake within natural environments have not been previously made. To investigate the demand for dZn and for dissolved cadmium (dCd; a closely related nutrient-like element) within Southern Ocean phytoplankton communities, we conducted 67Zn and 110Cd tracer uptake experiments within the Amundsen Sea, Ross Sea, and Terra Nova Bay into the >3 μm phytoplankton particulate size fraction. The highly productive Amundsen Sea and Ross Sea of Antarctica host large phytoplankton blooms in the austral spring and summer, during which macronutrient and micronutrient surface concentrations become significantly depleted largely due to phytoplankton uptake. In autumn and winter, nutrient levels are “reset” to high concentrations throughout the water column in these environments due to convective overturn, advancing sea ice cover, and darkness. This annual “resetting” of nutrient concentrations makes these Antarctic environments ideal locations to study the seasonal demand for Zn within these productive communities. In this study, variations in metal uptake rates over depth and time and correlations with other oceanic parameters were examined. High total metal uptake rates (ρMetal) of both Zn and Cd were consistent with the observed depletion of dZn and dCd surface concentrations. Our findings suggest that high biomass and low seawater pCO2 exerted primary control over increasing ρZn, which in turn led to increases in ρCd likely through the upregulation of shared transport systems. Overall, we observed a high magnitude of Zn uptake ( > 100 pmol dZn L-1 d-1) into the particulate phase within these Southern Ocean phytoplankton communities, suggesting that even in the Zn-rich waters of the Southern Ocean, high Zn uptake rates can lead to Zn depletion and potential Zn scarcity.
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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 | 0.000 | 0.000 |
| 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".