Increased food supply mitigates ocean acidification effects on calcification but exacerbates effects on growth
Bibliographic record
Abstract
Abstract Because many of the negative effects of ocean acidification on marine life may result from underlying energetic short-falls associated with increased metabolic demands, several studies have hypothesized that negative responses to high CO 2 could be reduced by energy input. Although this hypothesis was supported by a recent meta-analysis, we believe that the meta-analytic calculation used was not appropriate to test the stated hypothesis. Here, we first clarify the hypothesis put forward, the crux being that the effects of increased food supply and CO 2 interact statistically. We then test this hypothesis by examining the available data in a more appropriate analytical framework. Using factorial meta-analysis, we confirm that food addition has a positive effect and CO 2 has a negative effect on both growth and calcification. For calcification, food addition did indeed reduce CO 2 impacts. Surprisingly, however, we found that food addition actually exacerbated the effects of acidification on growth, perhaps due to increased scope upon which CO 2 effects can act in food-replete situations. These interactive effects were undetectable using a multilevel meta-analytic approach. Ongoing changes in food supply and carbonate chemistry, coupled with under-described, poorly understood, and potentially surprising interactive outcomes for these two variables, suggest that the role of food should remain a priority in ocean acidification research. Arising from: L. Ramajo et al., Sci. Rep. 6: 19374 (2016).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".