Local differences in robustness to ocean acidification
Bibliographic record
Abstract
Ocean acidification (OA) caused by increased atmospheric carbon dioxide is affecting marine systems globally and is more extreme in coastal waters. A wealth of research to determine how species will be affected by OA, now and in the future, is emerging. Most studies are discrete and generally do not include the full life cycle of animals. Studies that include the potential for adaptation responses of animals from areas with different environmental conditions and the most vulnerable life stages are needed. Therefore, we conducted experiments with the widely distributed blue mussel, Mytilus edulis, from populations regularly exposed to different OA conditions. Mussels experienced experimental conditions prior to spawning, through embryonic and larval development, both highly vulnerable stages. Survivorship to metamorphosis of larvae from all populations was negatively affected by extreme OA conditions (pH 7.3, Ωar, 0.39, pCO2 2479.74), but, surprisingly, responses to mid OA (pH 7.6, Ωar 0.77, pCO21167.13) and low OA (pH 7.9, Ωar 1.53, pCO2 514.50) varied among populations. Two populations were robust and showed no effect of OA on survivorship in this range. One population displayed the expected negative effect on survivorship with increased OA. Unexpectedly, survivorship in the fourth population was highest under mid OA conditions. There were also significant differences in development time among populations that were unaffected by OA. These results suggest that adaptation to OA may already be present in some populations and emphasizes the importance of testing animals from different populations to see the potential for adaptation to OA.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".