Content, composition, and transfer of polyunsaturated fatty acids in an Arctic lake food web
Bibliographic record
Abstract
Abstract Freshwater fish production depends on the production and use of polyunsaturated fatty acids (n‐3 and n‐6 PUFA) from lower trophic levels. Here, we aimed to identify the main trophic pathways that support PUFA content in different fish species (mean 39.7 mg/g dry weight) used in the subsistence fishery of the Inuit community in Greiner Lake near Cambridge Bay (Nunavut, Canada). We used stable isotope and taxon‐specific PUFA stocks, to show that the lake food web was divided into distinctive pelagic and littoral benthic food webs and that different fish species obtained their PUFA from different sources within those food webs. The most concentrated fish in n‐3 PUFA was Arctic char ( Salvelinus alpinus ) that obtained nutritionally valuable PUFA compounds by feeding on pelagic zooplankton rich in the essential fatty acids EPA and DHA and on littoral prey with lower PUFA content. The pelagic consumer, lake whitefish ( Coregonus clupeaformis ), that fed on mysids and zooplankton was also rich in n‐3 PUFA. The least concentrated in n‐3 PUFA was lake trout ( Salvelinus namaycush ) that obtained PUFA from low n‐3 PUFA sticklebacks ( Pungitius pungitius ) and macroinvertebrates and from n‐3 PUFA‐rich littoral mysids. The benthic PUFA were entirely made of n‐6 fatty acids and no n‐3 PUFA were detected. We further quantified that from the mean daily phytoplankton production of 319 mg C·m −2 ·d −1 , 2.9% was assimilated by zooplankton (9.4 mg C·m −2 ·d −1 ) and thereby made available to pelagic fish. The food webs to which fish belonged were supported by PUFA produced in the pelagic and benthic zones but likely complemented by inputs from the watershed. The description of the main PUFA pathways of the Greiner Lake food webs explains for the first time the trophic interactions and underlying mechanisms responsible for the health of the fish community in a high‐Arctic lake.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.020 | 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 teacher head, 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".