Meta-analysis reveals taxon- and life stage-dependent effects of ocean acidification on marine calcifier feeding performance
Bibliographic record
Abstract
Abstract While ocean acidification is considered among the greatest threats to marine ecosystems, its effects on the feeding performance of marine calcifiers remain uncertain. I conducted a meta-analysis of effect sizes (LnRR) assessing the impacts of acidification on the feeding ability of three groups of marine calcifiers - molluscs, arthropods, and echinoderms. Results suggested taxon-dependent effects of acidification on calcifier feeding performance, with depressed feeding observed for molluscs, echinoderms, and when all taxa were considered. However, ocean acidification had no effect on feeding performance in marine arthropods and larval feeding performance appeared more vulnerable than that of juveniles and adults. Feeding performance was not related to acclimation time nor p CO 2 level. This study suggests that the feeding performance of molluscs and early life-stage echinoderms may be depressed in a more acidic ocean, but that arthropod feeding performance is unlikely to suffer. Such changes in feeding performance could contribute to slower growth and development in the early life stages of these organisms and could potentially contribute to changes in community and ecosystem structure where these organisms coexist. Finally, feeding performance could, at least in part, moderate the degree to which molluscs and echinoderms can use food to overcome acidification effects early in life.
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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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.019 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".