Predation in High CO2 Waters: Prey Fish from High-Risk Environments are Less Susceptible to Ocean Acidification
Bibliographic record
Abstract
SYNOPSIS: Most studies investigating the effects of anthropogenic environmental stressors do so in conditions that are often optimal for their test subjects, ignoring natural stressors such as competition or predation. As such, the quantitative results from such studies may often underestimate the lethality of certain toxic compounds. A well-known example of this concept is illustrated by the marked increase in the lethality of pesticides when larval amphibians are concurrently exposed to the odor of potential predators. Here, we investigated the interaction between background levels of environmental predation risk (high vs. low) and ocean acidification (ambient vs. elevated CO2) in 2 × 2 design. Wild-caught juvenile damselfish, Pomacentrus amboinensis, were exposed in the laboratory to the different risk and CO2 conditions for 4 days and released onto coral reef patches. Using a well-established field assay, we monitored the in situ behavior and mortality of the damselfish for 2 days. We predicted that juvenile fish exposed to elevated CO2 and high-risk conditions would display more severe behavioral impairments and increased mortality compared to fish exposed to elevated CO2 maintained under low-risk conditions. As expected, elevated CO2 exposure led to impaired antipredator responses and increased mortality in low-risk fish compared to ambient CO2 controls. However, we failed to find an effect of elevated CO2 on the behavior and survival of the high-risk fish. We hypothesized that the results may stem from either a behavioral compensation or a physiological response to high risk. Our results provide insights into the interactive nature of environmental and natural stressors and advance our understanding of the predicted effect of ocean acidification on aquatic ecosystems.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".