Quantifying Rates of Evolutionary Adaptation in Response to Ocean Acidification
Bibliographic record
Abstract
The global acidification of the earth's oceans is predicted to impact biodiversity via physiological effects impacting growth, survival, reproduction, and immunology, leading to changes in species abundances and global distributions. However, the degree to which these changes will play out critically depends on the evolutionary rate at which populations will respond to natural selection imposed by ocean acidification, which remains largely unquantified. Here we measure the potential for an evolutionary response to ocean acidification in larval development rate in two coastal invertebrates using a full-factorial breeding design. We show that the sea urchin species Strongylocentrotus franciscanus has vastly greater levels of phenotypic and genetic variation for larval size in future CO(2) conditions compared to the mussel species Mytilus trossulus. Using these measures we demonstrate that S. franciscanus may have faster evolutionary responses within 50 years of the onset of predicted year-2100 CO(2) conditions despite having lower population turnover rates. Our comparisons suggest that information on genetic variation, phenotypic variation, and key demographic parameters, may lend valuable insight into relative evolutionary potentials across a large number of species.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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".