An evaluation of deuterium as a food source tracer in temperate streams of eastern Canada
Bibliographic record
Abstract
Stable H isotope ratios (D/H, expressed as δD) hold promise as an additional tool for elucidating food sources for consumers in aquatic ecosystems. We tested the applicability of δD as a food source tracer in streams of New Brunswick, Canada. First, we analyzed δD and δ13C in biofilm and terrestrial leaves and compared signal-to-noise ratios (variability within sources vs variability between sources) between the 2 elements. Signal-to-noise ratios were roughly similar, and 23 of the 31 sites had isotopically distinct food sources based on δD compared to 20 of 31 based on δ13C. Second, we used mixing models to estimate % aquatic H and % aquatic C for benthic invertebrates at a subset of sites. Of 16 samples, only 1 had δ13C that was outside the range of the 2 food sources (yielding % aquatic C > 100%), but 12 of the 16 samples had δD outside the range of the food sources, a result suggesting confounding effects of water and lipids on total body H content. Last, we analyzed δD in laboratory-reared consumers (brook trout and water striders) and in their diet before and after lipid extraction to estimate diet–tissue fractionation. Large differences between consumer and diet were apparent before lipid extraction, but no significant differences were found after lipid extraction. All of these measures indicate that δD could serve as a complementary, but not alternative, isotopic method for estimating food sources for consumers in streams. Further laboratory trials are needed to explore the influence of lipids on δD values.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".