Manganese and iron deficiency in Southern Ocean Phaeocystis antarctica populations revealed through taxon-specific protein indicators
Bibliographic record
Abstract
Iron and light are recognized as limiting factors controlling Southern Ocean phytoplankton growth. Recent field-based evidence suggests, however, that manganese availability may also play a role. Here we examine the influence of iron and manganese on protein expression and physiology in Phaeocystis antarctica, a key Antarctic primary producer. We provide taxon-specific proteomic evidence to show that in-situ Southern Ocean Phaeocystis populations regularly experience stress due to combined low manganese and iron availability. In culture, combined low iron and manganese induce large-scale changes in the Phaeocystis proteome and result in reorganization of the photosynthetic apparatus. Natural Phaeocystis populations produce protein signatures indicating late-season manganese and iron stress, consistent with concurrently observed stimulation of chlorophyll production upon additions of manganese or iron. These results implicate manganese as an important driver of Southern Ocean productivity and demonstrate the utility of peptide mass spectrometry for identifying drivers of incomplete macronutrient consumption.
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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".