Omega-3 fatty acids-critical for the marine food web and for seabird productivity
Bibliographic record
Abstract
Abstract Seabird reproductive success in northern latitudes is often linked with prey abundance, availability, size, or species. Causes are often broadly explained as changes in ocean currents/temperatures, or diets. Few studies trace diets down the food web to primary producers, thus missing what I propose as an underlying cause of seabird colony failure, dietary abundance of essential omega-3 polyunsaturated fatty acids (PUFA). PUFA differ from other nutrients because they are, in part, ligands—critical for reproduction and other physiological processes for the entire marine food web, not just for seabirds. Diatoms are one of the few life forms that can produce PUFA de novo, and a lack of PUFA in zooplankton and fish reduces their abundance and productivity, with consequences up the food web. Since the mid-1980s, historical prey of breeding seabirds has decreased, and frequency of colony failures has increased. In years of failure, prey often had less fat than historically preferred species. Likewise, proportions of alternate species’ PUFA, from published papers, show lower values than in historical prey. Production of PUFA by diatoms is depressed in warmer and more acidic environments, and I hypothesize that these warmer and more acidic seas have affected production of PUFA over the past 3–4 decades. Assuming this is true, I propose that these lower amounts of PUFA have negatively impacted the breeding success of all members of the marine food web, not just seabirds.
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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 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".