Production, distribution, and abundance of long-chain omega-3 polyunsaturated fatty acids: a fundamental dichotomy between freshwater and terrestrial ecosystems
Bibliographic record
Abstract
Long-chain polyunsaturated fatty acids (LC-PUFA) are critical for the health of aquatic and terrestrial organisms; therefore, understanding the production, distribution, and abundance of these compounds is imperative. Although the dynamics of LC-PUFA production and distribution in aquatic environments has been well documented, a systematic and comprehensive comparison to LC-PUFA in terrestrial environments has not been rigorously investigated. Here we use a data synthesis approach to compare and contrast fatty acid profiles of 369 aquatic and terrestrial organisms. Habitat and trophic level were interacting factors that determined the proportion of individual omega-3 (n-3) or omega-6 (n-6) PUFA in aquatic and terrestrial organisms. Higher total n-3 content compared with n-6 PUFA and a strong prevalence of the n-3 PUFA eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) characterized aquatic versus terrestrial organisms. Conversely, terrestrial organisms had higher linoleic acid (LNA) and alpha-linolenic acid (ALA) contents than aquatic organisms; however, the ratio of ALA:LNA was higher in aquatic organisms. The EPA + DHA content was higher in aquatic animals than terrestrial organisms, and increased from algae to invertebrates to vertebrates in the aquatic environment. An analysis of covariance (ANCOVA) revealed that fatty acid composition was highly dependent on the interaction between habitat and trophic level. We conclude that freshwater ecosystems provide an essential service through the production of n-3 LC-PUFA that are required to maintain the health of terrestrial organisms including humans.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".