Effects of end-of-the-century ocean acidification on Atlantic cod larvae of different populations in terms of survival, growth and recruitment to the fished stocks
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.The effect of climate change on fish populations and fisheries is poorly understood. While fish may respond to increased temperatures with range shifts, they cannot escape ocean acidification, an inevitable consequence of increasing carbon dioxide concentrations in the oceans and in the atmosphere. Here, we tested the effect of ocean acidification (OA) on larvae of Atlantic cod of two different populations, from the Barents Sea and the Western Baltic Sea. Survival and growth was measured during the first weeks of development post-hatching. Mortality rates doubled in both populations in ocean acidification conditions as they are expected for the end of the century. When these results were included in a Ricker-type recruitment model, the recruitment collapsed. Furthermore the experimental results show an increase in larval size after seven weeks post-hatching. These results highlight the importance of including the effect of ocean acidification on vulnerable early life stages into fisheries models and management.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".