Explaining isotope trophic‐step fractionation: why herbivorous fish are different
Bibliographic record
Abstract
Summary An assumed constant trophic fractionation of 15N/14N between consumer and diet (usually 3·4 for diet–muscle tissue differences) allows inferences to be made about feeding interactions and trophic level in food web studies. However, considerable variability surrounds this constant, which may conceal subtle differences about the trophodynamics of consumers. The feeding ecologies of herbivores and carnivores differ in terms of diet quality (in C : N terms) and food processing mechanisms, which may affect fractionation. We present a new model that explores how consumer feeding rates, excretion rates and diet quality determine the 15N/14N ratios in the consumer's tissues and hence influence the magnitude of trophic fractionation. Three herbivorous reef fish Acanthurus sohal, Zebrasoma xanthurum and Pomacentrus arabicus were chosen as study organisms. Empirical estimates of diet–tissue stable isotope fractionation were made in the field, and model parameters were derived from feeding observations and literature data. The trophic fractionation values of A. sohal, Z. xanthurum and P. arabicus were 4·69, 4·47 and 5·25, respectively, by empirical measurement, and 4·41, 4·30 and 5·68, respectively, by model, indicating that herbivores have a higher trophic fractionation than the currently accepted value of 3·4. The model was most sensitive to the excretion rate, which may differ between herbivores and carnivorous animals. This model is the first to determine stable isotope signatures of a consumer's diet mixture without applying a constant fractionation value.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".