Variable and spatially explicit response of fish larvae to the playback of local, continuous reef soundscapes
Bibliographic record
Abstract
Understanding the cues that drive larval fish settlement is critical for managing reef systems under stress. Reef sound is increasingly reported to influence fish recruitment, yet the physical and acoustic environment in which larval fish settle varies in space and time. Accordingly, testing potential settlement cues under different conditions is vital for understanding their ecological importance. We conducted 2 sets of field playback experiments in St. John, US Virgin Islands, one nearshore (10 m depth) and the second ‘offshore’ (25 m depth), to assess the effects of reef soundscape playback on settlement rates of multiple reef fish families. In each experiment, nightly currents were quantified and we replicated the diel soundscape cycle using high, low, and control (silent) amplitude recordings from nearby reefs. The first experiment revealed significant current-based, down-stream reduction in larval fish catches in subsurface light traps and a significant effect of increasing amplitude of reef playbacks on larval lizardfish (Synodontidae) catches. In the second, offshore experiment which had no current effect, increasing reef playback amplitude led to a significantly greater catch of parrotfish (Scaridae) larvae and decreased larval pelagic fish catch. Total reef fish larvae only showed attraction to reef playbacks at the most nearshore site. This work demonstrates that while sound can play a role in the settlement of certain reef fishes, responses are influenced by multiple factors, including larger-scale physical processes, underscoring the need to consider the scale of soundscape cues for reef fish settlement within an oceanographic context.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| 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 teacher head, 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".