Omega‐3 <scp>PUFA</scp> profoundly affect neural, physiological, and behavioural competences – implications for systemic changes in trophic interactions
Bibliographic record
Abstract
In recent decades, much conceptual thinking in trophic ecology has been guided by theories of nutrient limitation and the flow of elements, such as carbon and nitrogen, within and among ecosystems. More recently, ecologists have also turned their attention to examining the value of specific dietary nutrients, in particular polyunsaturated fatty acids (PUFA), among which the omega-3 PUFA, especially eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) play a central role as essential components of neuronal cell membranes in many organisms. This review focuses on a new neuro-ecological approach stemming from the biochemical (mechanistic) and physiological (functional) role of DHA in neuronal cell membranes, in particular in conjunction with G-protein coupled receptors (GPCRs). We link the co-evolution of these neurological functions to metabolic dependency on dietary omega-3 PUFA. We outline ways in which deficiencies in dietary DHA supply may affect, cognition, vision, and behaviour, and ultimately, the biological fitness of consumers. We then review emerging evidence that changes in access to dietary omega-3 PUFA may ultimately have profound impacts on trophic interactions leading to potential changes in community structure and ecosystem functioning that, in turn, may affect the supply of DHA within and across ecosystems, including the supply for human 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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".