Freshwater fish otoliths record signals from both water and physiological processes: new insights from Sr/Ca and Ba/Ca ratios
Bibliographic record
Abstract
Using strontium (Sr) and barium (Ba) in otoliths to determine natal origins and understand patterns of fish movements is based on the fundamental assumption that otoliths record water chemistry signals without any major alterations. Although prior studies highlighted that fish physiology can modify the water signal in otoliths, studies for freshwater fish are scarce. We exposed different groups of Atlantic salmon parr Salmo salar to different scenarios of ambient-level variations in Sr/Ca and Ba/Ca ratios and then combined otolith chemical profiles with environmental data (water chemistry and temperature), Fulton's index, and otolith growth rates to assess what factors explain/influence the elemental ratios of Sr and Ba in otoliths. Generalized additive mixed models (GAMMs) using water-based otolith composition, temperature, Fulton's index, and “individual” as explanatory variables allow to demonstrate that water chemistry alone cannot fully explain measured ratios in otoliths, except in scenarios involving significant changes in water chemistry. Other factors (physiological effects) should be accounted for reproducing short and minimal seasonal variations in water composition, considering that inter-individual variability contributes quite significantly in most scenarios.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".