Multiple-frequency moored sonar for continuous observations of zooplankton and fish
Bibliographic record
Abstract
Moored, internally-recording acoustic instruments can acquire continuous profiles of echoes throughout the water column, thus providing a low-cost method to study the behavior and abundance of fish and zooplankton in oceans and lakes. Calibrated sonars with several frequencies allow some information about species composition and abundance to be deduced from acoustic backscatter data. The same instrument can be configured to look up from the bottom, down from the surface or horizontally from a CTD cage. In this presentation we describe an improved low power, battery-operated multi-frequency sonar capable of autonomously collecting data at high temporal and spatial resolution for periods of up to a year. The AZFP instrument (Acoustic Zooplankton and Fish Profiler) supports up to four frequencies in a single housing. The available operating frequencies are 38, 125, 200, 455 and 770 kHz. The transducers are co-located, with the same nominal beam widths of 7° or 8°, except at 38 kHz, where the beam width is 12°. The standard AZFP can be moored at depths up to 300m, and with modified transducers as deep as 600m. The recent improvements to the instrument include replacement of the signal detector with a wide dynamic range logarithmic receiver. The linearity of the receiver response has been improved, its instantaneous dynamic range has been increased to over 80 dB, and the requirement to pre-select one of four time-varying gain settings is no longer necessary, as the expanded dynamic range eliminated the need for a time-varying gain function. Additional noise reduction methods have also been implemented. The procedures used to calibrate acoustic performance of these instruments will be discussed. Typical minimum detectable volume backscatter strengths are −100dB at 20m range to −80dB at 100m range for the 125 and 200 kHz channels, and −80dB at 20m range for the 770 kHz channel. Sixteen GigaBytes (GB) of data storage is provided using a compact flash disk, which allows high temporal sampling rates (maximum 1 Hz) to be performed for shorter deployments. For longer periods, true arithmetic averaging can be done internally in both range and time to reduce the data storage space required. Low power consumption allows the instrument to collect data on four channels out to 100m range, pinging at 0.5 Hz for 150 days on a standard 200 Ampère-hours (A-Hr) battery pack. To illustrate the potential of such observations, preliminary results from several deployments in Saanich Inlet, BC are discussed. The effects of seasonal and year-to-year variations in this area are shown in a segment of a six-year time series collected by a 200 kHz sonar mounted on the VENUS cabled observatory, with the data organized as depth-time ‘cubes’ to facilitate handling of such long time series. Data from recent nearby deployments of multiple-frequency instruments (125, 200, 455 and 770 kHz) shows examples of the additional information that can be obtained from simultaneous measurements at several frequencies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".