Energy metabolism and cellular homeostasis trade-offs provide the basis for a new type of sensitivity to ocean acidification in a marine polychaete at a high CO2 vent: adenylate and phosphagen energy pools vs. carbonic anhydrase
Bibliographic record
Abstract
Species distributions and ecology can often be explained by their physiological sensitivity to environmental conditions. Whilst we have a relatively good understanding of how these are shaped by temperature, for other emerging drivers, such as PCO2 we know relatively little. The marine polychaete Sabella spallanzanii increases its metabolic rate when exposed to high PCO2 conditions and remains absent from the CO2 vent of Ischia. To understand new possible pathways of sensitivity to CO2 in marine ectotherms, we examined the metabolic plasticity of S. spallanzanii exposed in situ to elevated PCO2 by measuring fundamental metabolite and carbonic anhydrase concentrations. We show that whilst this species can survive elevated PCO2 conditions in the short term, and exhibits an increase in energy metabolism, this is accompanied by a significant decrease in carbonic anhydrase concentration. These homeostatic changes are unlikely to be sustainable in the longer term, indicating S. spallanzanii may struggle with future high PCO2 conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".