Metabolomic responses to shipping noise in early life stages of blue mussels, <i>Mytilus edulis</i>
Bibliographic record
Abstract
Anthropogenic ocean noise from shipping is steadily increasing, with a predicted doubling every 11.5 years, raising growing global concern about its potential effects on wildlife. There is evidence that anthropogenic noise can affect the behaviour and physiology of many species, but few examples of experiments that show how they may be affected. Here, we used metabolomics analyses to investigate the effects of shipping noise during the crucial early life stage of embryogenesis on a key ecosystem reporter species in the marine benthic system, the blue mussel, Mytilus edulis. We found that exposure to shipping noise provokes stress-induced inflammation, a metabolic imbalance or cellular stress as a result of increased energy demand, leading to disruption of glycolysis and increased oxidative stress response. The noise generated by cargo ships has a direct impact on the first developmental stage of mussel larvae, altering their metabolic pathways including those related to energy. Our study of an ecologically and socio-economically important taxon shows that anthropogenic noise can impair the individual performance of juvenile bivalve invertebrates. This impairment could have a significant cascading effect on population dynamics and resilience, with potential implications for community structure and function.
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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".