Tests of size and growth effects on Arctic charr ( <scp> <i>Salvelinus alpinus</i> </scp> ) otolith δ <sup>18</sup> O and δ <sup>13</sup> C values
Bibliographic record
Abstract
Rationale Otolith δ 18 O and δ 13 C values have been used extensively to reconstruct thermal and diet histories. Researchers have suggested that individual growth rate and size may have an effect on otolith isotope ratios and subsequently confound otolith‐based thermal and diet reconstructions. As few explicit tests of the effect on fish in freshwater environments exist, here we determine experimentally the potential for related growth rate and size effects on otolith δ 18 O and δ 13 C values. Methods Fifty Arctic charr were raised in identical conditions for two years after which their otoliths were removed and analyzed for their δ 18 O and δ 13 C values. The potential effects of final length and the Thermal Growth Coefficient (TGC) on otolith isotope ratios were tested using correlation and regression analysis to determine if significant effects were present and to quantify effects when present. Results The analyses indicated that TGC and size had significant and similar positive non‐linear relationships with δ 13 C values and explained 35% and 42% of the variability, respectively. Conversely, both TGC and size were found to have no significant correlation with otolith δ 18 O values. There was no significant correlation between δ 18 O and δ 13 C values. Conclusions The investigation indicated the presence of linked growth rate and size effects on otolith δ 13 C values, the nature of which requires further study. Otolith δ 18 O values were unaffected by individual growth rate and size, confirming the applicability of these values to thermal reconstructions of fish habitat.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".