How chronic anthropogenic noise can affect wildlife communities
Bibliographic record
Abstract
Anthropogenic noise is a major pollutant in terrestrial and aquatic ecosystems. Since the industrial revolution, human activities have become increasingly noisy, leading to both acute and chronic disturbance of a wide variety of animals. Chronic noise exposure can affect animals over their lifespan, leading to changes in species interactions and likely altering communities. However, the community-level impacts of chronic noise are not well-understood, which impairs our ability for effective mitigation. In this review, we address the effects of chronic noise exposure on communities and explore possible mechanisms underlying these effects. The limited studies on this topic suggest that noise can affect communities by changing the behavior and/or physiology of species in a community, which results in direct or knock-on consequences for other species in the ecosystem. Major knowledge gaps remain due to the logistically complex and financially expensive nature of the long-term studies needed to address these questions. By identifying these gaps and suggesting approaches to answer them, we provide a road map toward mitigating the effects of a noisy world.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".