High sensitivity to ocean acidification in wild out‐migrating juvenile Pacific salmon is not impacted by feeding success
Bibliographic record
Abstract
Abstract Salmon populations are declining worldwide, with high mortality rates during juvenile marine migration presenting a bottleneck to recruitment. The ocean conditions along the main migratory route of juvenile salmon in British Columbia are characterized by high variability in CO 2 , with the amplitude, duration, and frequency of ocean acidification events exacerbated by climate change. Similarly, the variability in ocean conditions affects the abundance and diversity of plankton prey, leading to areas of food paucity for juvenile salmon. We investigated the combined effects of ocean acidification (control and 3200 μatm CO 2 ) and food limitation (ad libitum, ½ ration, and food deprived) on the survival, condition, and gene expression profiles of juvenile Chum salmon ( Oncorhynchus keta ) to develop predictive biomarkers for CO 2 exposure and food deprivation. Ocean acidification caused a direct 3‐fold increase in mortality over 25 days of exposure, which was unaffected by food availability but differentially affected smaller fish. CO 2 exposure induced transcriptomic changes in a suite of genes associated with ion regulation, while food deprivation was associated with a differential expression of stress, immune, and mortality markers, as well as reduced condition factor. Our data indicate that CO 2 directly impairs ionoregulatory capacity to the point of failure in juvenile Chum salmon and that these effects cannot be compensated through increased energy from food. Applying our gene panels as biomarkers to a subset of fish with known exposure, we were able to accurately predict exposure to CO 2 and food deprivation (74% and 90%, respectively). By combining these gene panels with previously established biomarkers for other environmental stressors, the recent environmental stress history of wild fish can be determined and can be used in models to predict salmon returns, informing fisheries management and conservation efforts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".