Effects of size and diet on stable hydrogen isotope values (δD) in fish: implications for tracing origins of individuals and their food sources
Bibliographic record
Abstract
Recent studies suggest that stable hydrogen isotope ratios (δD) of fish can be used to track their watershed origin and the relative contributions of source material. Both applications assume that there is no metabolic or trophic effect on tissue δD. We studied the local variation of δD values in four fish species of contrasting size and feeding habits in an isotopically homogenous reservoir (Flix, Spain). Other isotopic values (δ 15 N, δ 13 C) and trace metal content were measured as indicators of trophic and bioaccumulation patterns. In addition, isotopic values (δD, δ 15 N, δ 13 C) of other food web components were measured for comparison. Muscle δD values differed greatly among fish species: European catfish, Silurus glanis (–131‰); common carp, Cyprinus carpio (–141‰); rudd, Scardinius erythrophthalmus (–158‰); and roach, Rutilus rutilus (–163‰). The influence of fish size and trophic position affected the fish δD values. Possible mechanisms that drive δD variation among fish might be a metabolic effect and (or) the compounding effect of ambient water δD on exchangeable H at each trophic stage. Our findings showed that size and feeding habits are factors that should be controlled when tracing origins of fish or their dependence on nutrient inputs using δD measurements.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".