Riverscape meets underwater soundscape: Acoustic habitat selection by brook char in a small stream
Bibliographic record
Abstract
Stream habitats are characterised by geophysical descriptors such as water temperature, depth, substrate type, and flow speed. So far, few studies have focused on underwater sounds as an important feature of habitat selection by fish. In this study, we described stream habitats at high resolution to evaluate the relative importance of the underwater soundscape and other geophysical descriptors for understanding the distribution of brook char densities. Our results showed the high acoustical heterogeneity of stream habitats (ranging from 40 dB up to 150 dB re 1uPa), which was related to differences in water velocity and depth as expected from theory. Brooks char densities were nevertheless positively related to sound intensities, irrespective of water velocity, depth, or facies type. Our findings showed that underwater sounds integrate the many environmental dimensions of stream and may be used as cues for habitat selection. The positive relationship between brook char densities and sound intensities could be related to the high auditory threshold of Salmonidae.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".