Copper requirements for iron acquisition and growth of coastal and oceanic diatoms
Bibliographic record
Abstract
Centric diatoms isolated from open ocean environments require higher concentrations of Cu for growth than their coastal counterparts. In artificial seawater medium containing <1 nmol L™1 Cu, three coastal species maintained near maximum rates of growth, but the oceanic clones were unable to survive. Copper limitation was more severe in the diatoms grown in low- than in high-Fe seawater, suggesting that Cu and Fe were interacting essential resources. The interactive effect was in part the result of a Cu requirement for Fe transport. Thalassiosira weissflogii and Thalassiosira oceanica had lower Fe quotas and slower rates of Fe uptake when [Cu] was reduced in the medium. Brief exposure of Cu-limited cells to 10 nmol L−1 Cu increased the instantaneous Fe uptake rate by 1.5 times in T. oceanica. Steady-state uptake rates of both species at high, growth-saturating concentrations of Fe were also Cu dependent. Oceanic species appeared to have an additional Cu requirement that was independent of Fe acquisition and likely responsible for their higher requirements compared to coastal species. Evidence for the importance of Cu in natural communities of phytoplankton was obtained from an incubation experiment performed in the Fe-limited basin of the Bering Sea. Addition of 2 nmol L−1 Cu doubled the phytoplankton net growth rate compared to the untreated controls and, in the presence of extra Fe, increased the growth rate compared to the samples amended with Fe alone. The results suggest that Cu may be an important micronutrient for phytoplankton growth in low-Fe regions of the sea because of its role in Fe acquisition. Paradoxically, oceanic diatoms may be more susceptible to the effects of low Cu concentrations than coastal species.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".