To brood or not to brood: Are marine invertebrates that protect their offspring more resilient to ocean acidification?
Bibliographic record
Abstract
Anthropogenic atmospheric carbon dioxide (CO2) is being absorbed by seawater resulting in increasingly acidic oceans, a process known as ocean acidification (OA). OA is thought to have largely deleterious effects on marine invertebrates, primarily impacting early life stages and consequently, their recruitment and species' survival. Most research in this field has been limited to short-term, single-species and single-life stage studies, making it difficult to determine which taxa will be evolutionarily successful under OA conditions. We circumvent these limitations by relating the dominance and distribution of the known polychaete worm species living in a naturally acidic seawater vent system to their life history strategies. These data are coupled with breeding experiments, showing all dominant species in this natural system exhibit parental care. Our results provide evidence supporting the idea that long-term survival of marine species in acidic conditions is related to life history strategies where eggs are kept in protected maternal environments (brooders) or where larvae have no free swimming phases (direct developers). Our findings are the first to formally validate the hypothesis that species with life history strategies linked to parental care are more protected in an acidifying ocean compared to their relatives employing broadcast spawning and pelagic larval development.
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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 | 0.000 | 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) | 0.002 | 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".