Coping with multiple stressors: physiological mechanisms and strategies in fishes of the Salton Sea
Bibliographic record
Abstract
Saline lakes are found around the world, typically within inland drainage basins that lack outflow. While fish species in these lakes are not numerous, the Salton Sea in southeastern California, USA, supports several species and a substantial recreational fishery. The Salton Sea was formed in 1905, and since its formation, the salinity has varied greatly, and is currently approaching 44 g/l. The Salton Sea presents several environmental challenges to fishes that inhabit it, especially high salinity, large variations in temperature, and high levels of calcium and sulphate. Studies investigating the osmoregulatory ability of the California Mozambique tilapia (Oreochromis mossambicus x O. urolepis hornorum), the dominant species in the Salton Sea, indicate that they can tolerate salinities up to 65 g/l at 25 °C with minimal effects on osmoregulatory status. However, a reduction in temperature to 15 °C or an increase to 35 °C (both within the range of temperature observed in the Salton Sea) greatly reduce the salinity tolerance of this species. These data indicate that the seasonal winter kills of California Mozambique tilapia are likely associated with a direct effect of temperature on salinity tolerance at the current salinity of the Salton Sea. In this review we explore these environmental stressors and their effects on fish, particularly within the context of the Salton Sea fishery, and discuss how euryhalinity may give tilapia an advantage over the other Salton Sea species with respect to surviving the dynamic environment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".