Could future ocean acidification be affecting the energy budgets of marine fish?
Bibliographic record
Abstract
With the unprecedented environmental changes caused by climate change including ocean acidification, it has become crucial to understand the responses and adaptive capacity of fish to better predict directional changes in the ecological landscape of the future. We conducted a systematic literature review to examine if simulated ocean acidification (sOA) could influence growth and reproduction in fish within the dynamic energy budget theory framework. As such, we chose to examine metabolic rate, locomotion, food assimilation and growth in early life stages (i.e. larvae and juvenile) and adults. Our goal was to evaluate if acclimatization to sOA has any directional changes in these traits and to explore potential implications for energetic trade-offs in these for growth and reproduction. We found that sOA had negligible effects on energetic expenditure for maintenance and aerobic metabolism due to the robust physiological capacity regulating acid-base and ion perturbations but substantive effects on locomotion, food assimilation and growth. We demonstrated evidence that sOA significantly reduced growth performance of fish in early life stages, which may have resulted from reduced food intake and digestion efficiency. Also, our results showed that sOA may enhance reproduction with increased numbers of offspring although this may come at the cost of altered reproductive behaviours or offspring fitness. While these results indicate evidence for changes in energy budgets because of physiological acclimatization to sOA, the heterogeneity of results in the literature suggests that physiological and neural mechanisms need to be clearly elucidated in future studies. Lastly, most studies on sOA have been conducted on early life stages, which necessitates that more studies should be conducted on adults to understand reproductive success and thus better predict cohort and population dynamics under ongoing climate 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".