Multi‐generational responses of a marine polychaete to a rapid change in seawater <i>p</i><scp>CO</scp><sub>2</sub>
Bibliographic record
Abstract
Abstract Little is known of the capacity that marine metazoans have to evolve under rapid pCO2 changes. Consequently, we reared a marine polychaete, Ophryotrocha labronica, previously cultured for approximately 33 generations under a low/variable pH regime, under elevated and low pCO2 for six generations. The strain used was found to be tolerant to elevated pCO2 conditions. In generations F1 and F2 females’ fecundity was significantly lower in the low pCO2 treatment. However, from generation F3 onwards there were no differences between pCO2 treatments, indicating that trans‐generational effects enabled the restoration and maintenance of reproductive output. Whilst the initial fitness recovery was likely driven by trans‐generational plasticity (TGP), the results from reciprocal transplant assays, performed using F7 individuals, made it difficult to disentangle between whether TGP had persisted across multiple generations, or if evolutionary adaptation had occurred. Nonetheless, both are important mechanisms for persistence under climate change. Overall, our study highlights the importance of multi‐generational experiments in more accurately determining marine metazoans’ responses to changes in pCO2, and strengthens the case for exploring their use in conservation, by creating specific pCO2 tolerant strains of keystone ecosystem 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 | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".