Maximum thermal limits of coral reef damselfishes are size-dependent and resilient to near-future ocean acidification
Bibliographic record
Abstract
Theoretical models predict that ocean acidification, caused by increased dissolved CO2, will reduce the maximum thermal limits of fishes, thereby increasing their vulnerability to rising ocean temperatures and transient heatwaves. Here, we test this prediction in three species of damselfishes on the Great Barrier Reef, Australia. Maximum thermal limits were quantified using critical thermal maxima (CTmax) tests following acclimation to either present-day or end-of-century levels of CO2 for coral reef environments (∼500 or ∼1,000 µatm, respectively). While species differed significantly in their thermal limits, whereby Dischistodus perspicillatus exhibited greater CTmax (37.88±0.03oC; N=47) than Dascyllus aruanus (37.68±0.02oC; N=85) and Acanthochromis polyacanthus (36.58±0.02oC; N=63), end-of-century CO2 had no effect (D. aruanus) or a slightly positive effect (increase in CTmax of 0.16oC in D. perspicillatus and 0.21oC in A. polyacanthus) on CTmax. Contrary to expectations, smaller individuals were equally as resilient to CO2 as larger conspecifics, and CTmax was higher at smaller body sizes in two species. These findings suggest that ocean acidification will not impair the maximum thermal limits of reef fishes, and they highlight the critical role of experimental biology in testing predictions of theoretical models forecasting the consequences of environmental change.
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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) | 0.001 | 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".