Hydrogen isotopes (δ<sup>2</sup>H) of polyunsaturated fatty acids track bioconversion by zooplankton
Bibliographic record
Abstract
Abstract Organisms at the base of aquatic food webs synthesize essential nutrients, such as omega‐3 polyunsaturated fatty acids (n‐3 PUFA), which are transferred to consumers at higher trophic levels. Many consumers, requiring n‐3 long‐chain (LC) PUFA, such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), have limited ability to biosynthesize them from the essential dietary precursor α‐linolenic acid (ALA) and thus rely on dietary provision of LC‐PUFA. We investigated LC‐PUFA metabolism in freshwater zooplankton using stable hydrogen isotopes (δ 2 H) of fatty acids as tracers. We conducted feeding experiments with the freshwater keystone grazer Daphnia to quantify changes in the δ 2 H value of body FA in response to the FA composition of their food and the δ 2 H value of the ambient water. The isotopic composition of LC‐PUFA changed in Daphnia , depending on the integration of 2 H from ambient water during de novo synthesis or bioconversion from dietary precursors, allowing us to distinguish dietary from bioconverted EPA in body tissue. We tested the applicability of these laboratory findings in a field setting by analysing δ 2 H values of PUFA in primary producers and consumers in eutrophic ponds to track EPA sources of zooplankton. Multilinear regression models that included conversion of ALA to EPA correlated better with zooplankton δ 2 H EPA than seston δ 2 H EPA at low dietary EPA supply. This study provides evidence that zooplankton can compensate for low dietary EPA supply by activating LC‐PUFA biosynthesis and shows that herbivorous zooplankton play a crucial role in upgrading FA for higher trophic levels during low dietary EPA supply. A free Plain Language Summary can be found within the Supporting Information of this article.
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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) | 0.050 | 0.002 |
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; both teacher heads agree on what is shown here.
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".