Interactive effects of temperature and salinity on otolith chemistry: challenges for determining environmental histories of fish
Bibliographic record
Abstract
The concentrations of elements and isotopes in fish otoliths may provide a method of reconstructing movements of fish by differentiating between water bodies of different temperatures and salinities. However, before otoliths can be used to reconstruct environmental histories of fish, it is necessary to assess the effects of seawater temperature and salinity on otolith microchemistry. Using controlled laboratory experiments, juvenile black bream, Acanthopagrus butcheri (family Sparidae), were reared for 50 days in aquaria of varying temperatures and salinities using three experimental designs: temperature × salinity, temperature only, and salinity only. Temperature and salinity interacted to significantly affect the elemental concentration ratios of Sr:Ca and Ba:Ca and the concentrations of isotopes δ 13 C and δ 18 O in otoliths. The single-factor experiments showed that temperature significantly affected the concentration ratios of Sr:Ca and Ba:Ca and the concentrations of δ 13 C and δ 18 O in otoliths, whereas salinity alone did not affect the concentration ratios of any elements but did affect both isotopes. The concentration ratios of Mg:Ca and Mn:Ca varied considerably among fish within the same treatment level and showed little or no effects due to temperature and (or) salinity. The significant interactive effects of temperature and salinity on otolith microchemistry highlight the need for a multifactorial approach to testing hypotheses regarding the environmental histories of fish.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".