Habitat-mediated noise pollution reduction in seagrass meadows
Bibliographic record
Abstract
Despite widespread effects of anthropogenic noise on marine organisms, it is still unclear how the propagation of noise is influenced by habitat degradation. Here, we used field experiments to evaluate habitat-mediated reduction of noise pollution. We conducted habitat characterizations, faunal surveys, and transmission loss measurements at sites in subtropical and tropical seagrass ecosystems, across a range of habitat conditions. We found that recreational boat noise was reduced more at sites with denser habitats. For example, in Belize, a site with almost total coverage of seagrasses and attached macroalgae attenuated noise ~4 dB re 1 μPa more (reducing acoustic energy by ~37 %) over 5 m compared to a site with little habitat structure. Other factors that influenced transmission loss included water depth, dissolved oxygen, and temperature. Neither habitat density, nor any of the other environmental variables that affected transmission loss, influenced the abundance, richness, and composition of seagrass-associated faunal communities. The rich faunal communities found in sparser habitats could thus be disproportionately affected by the increased noise pollution exposure. Our work provides empirical evidence that seagrass habitats play a role in attenuating noise pollution, leading to greater protection for faunal communities and the seagrasses themselves. These findings strengthen our understanding of coastal soundscape-habitat interactions and demonstrate that the ability of seagrasses to dampen noise is a valuable ecosystem function that has so far largely been undervalued. A conceptual visualization of the hypothesized mitigation effects of habitat structure on noise pollution in seagrass ecosystems. • We measured transmission loss in subtropical and tropical seagrass ecosystems. • Denser seagrass habitats dampened boat noise more than sparser habitats. • Other environmental factors, like water depth, also influenced transmission loss. • Habitat-mediated attenuation can help protect faunal communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".