Tissue‐specific turnover and diet‐tissue discrimination factors of carbon and nitrogen isotopes of a common forage fish held at two temperatures
Bibliographic record
Abstract
Rationale The application of stable isotopes to foraging ecology is dependent on understanding life‐history and environmental factors unrelated to diet that may influence isotopic composition. Diet‐tissue discrimination factors (DTDFs) and turnover rates will increase the accuracy of isotope‐based studies. Furthermore, little consideration has been given to the effects of temperature or life‐history stage on isotopic ratios despite the prevalence of variation in temperature and growth rates throughout life. Methods We measured δ 13 C and δ 15 N values with an elemental analyzer coupled to a continuous flow isotope ratio mass spectrometer. These values were used to estimate turnover and DTDFs for Emerald Shiners ( Notropis atherinoides ), a common North American freshwater forage fish. Fish were assigned to a temperature treatment, either 10°C (Low) or 20°C (High), and provided one of three diets (commercial pellet, Artemia salina , or Hemimysis anomala ). At regular intervals fish were sampled and the isotopic compositions of whole body and liver tissues were determined. Results Tissue turnover rates for fish fed Artemia were faster for liver than for whole body, but were also influenced by temperature. Turnover occurred faster at higher temperatures for body and liver δ 15 N values, but not for δ 13 C values. The pellet and Hemimysis treatments were in isotopic equilibrium from the start of the experiment and estimated DTDFs based on these treatments were lower than assumed for Δ 15 N (+0.6 to 2.7‰) and variable, but within expected ranges for Δ 13 C (−1.9 to +1.5‰). Conclusions The results for Emerald Shiners differed from commonly made assumptions for applying stable isotopes to ecological questions, possibly related to a bias in the use of juveniles in studies of turnover and DTDFs and assumptions regarding thermal‐independence of isotopic relationships. The species‐specific DTDF and tissue turnover estimates provided here will inform interpretations of stable isotope data for smaller fish species and improve food‐web studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".