Performance of acoustic telemetry in relation to submerged aquatic vegetation in a nearshore freshwater habitat
Bibliographic record
Abstract
Acoustic telemetry is a powerful tool for learning about the movements and ecology of aquatic animals, but proper use requires evaluation of its performance in different environments. Nearshore freshwater habitats are important to many fishes; however, submerged aquatic vegetation (SAV) in these areas influences the performance of acoustic telemetry through attenuation of the transmissions. Despite this, few studies have quantified the influence of SAV on the detection efficiency and range. We conducted range testing and hydroacoustic surveys to assess the seasonal influence of SAV biovolume on the detection efficiency of 180 kHz transmitters in the nearshore (<1.5 m) habitats of a temperate freshwater riverine ecosystem. The interaction of transmitter–receiver distance and SAV biovolume significantly reduced the detection efficiency of transmitters, which varied with seasonal growth and senescence of SAV. Daily effective detection range (mean ± s.e.) varied from 6.85 m ± 1.98 when SAV coverage was high (mean biovolume 0.98) to 196.08 m ± 51.89 when SAV was largely absent (mean biovolume 0.01). This study demonstrated the impact of SAV on the detection range of acoustic transmitters, illustrating the need for range testing and consideration in study design and analysis to improve the quality of interpretation of data in vegetated habitats.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".