Ocean acidification and responses to predators: can sensory redundancy reduce the apparent impacts of elevated <scp>CO</scp><sub>2</sub> on fish?
Bibliographic record
Abstract
Carbon dioxide (CO2) levels in the atmosphere and surface ocean are rising at an unprecedented rate due to sustained and accelerating anthropogenic CO2 emissions. Previous studies have documented that exposure to elevated CO2 causes impaired antipredator behavior by coral reef fish in response to chemical cues associated with predation. However, whether ocean acidification will impair visual recognition of common predators is currently unknown. This study examined whether sensory compensation in the presence of multiple sensory cues could reduce the impacts of ocean acidification on antipredator responses. When exposed to seawater enriched with levels of CO2 predicted for the end of this century (880 μatm CO2), prey fish completely lost their response to conspecific alarm cues. While the visual response to a predator was also affected by high CO2, it was not entirely lost. Fish exposed to elevated CO2, spent less time in shelter than current-day controls and did not exhibit antipredator signaling behavior (bobbing) when multiple predator cues were present. They did, however, reduce feeding rate and activity levels to the same level as controls. The results suggest that the response of fish to visual cues may partially compensate for the lack of response to chemical cues. Fish subjected to elevated CO2 levels, and exposed to chemical and visual predation cues simultaneously, responded with the same intensity as controls exposed to visual cues alone. However, these responses were still less than control fish simultaneously exposed to chemical and visual predation cues. Consequently, visual cues improve antipredator behavior of CO2 exposed fish, but do not fully compensate for the loss of response to chemical cues. The reduced ability to correctly respond to a predator will have ramifications for survival in encounters with predators in the field, which could have repercussions for population replenishment in acidified oceans.
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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) | 0.001 | 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".