Sparse targets in hydroacoustic surveys: Balancing quantity and quality of in situ target strength data
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Abstract
Hydroacoustic sampling of low-density fish in shallow water can lead to low sample sizes of naturally variable target strength (TS) estimates, resulting in both sparse and variable data. Increasing maximum beam compensation (BC) beyond conventional values (i.e., 3 dB beam width) can recover more targets during data analysis; however, data quality decreases near the acoustic beam edges. We identified the optimal balance between data quantity and quality with increasing BC using a standard sphere calibration, and we quantified the effect of BC on fish track variability, size structure, and density estimates of Lake Erie walleye (Sander vitreus). Standard sphere mean TS estimates were consistent with theoretical values (−39.6 dB) up to 18-dB BC, while estimates decreased at greater BC values. Natural sources (i.e., residual and mean TS) dominated total fish track variation, while contributions from measurement related error (i.e., number of single echo detections (SEDs) and BC) were proportionally low. Increasing BC led to more fish encounters and SEDs per fish, while stability in size structure and density were observed at intermediate values (e.g., 18 dB). Detection of medium to large fish (i.e., age-2+ walleye) benefited most from increasing BC, as proportional changes in size structure and density were greatest in these size categories. Therefore, when TS data are sparse and variable, increasing BC to an optimal value (here 18 dB) will maximize the TS data quantity while limiting lower-quality data near the beam edges.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Sparse targets in hydroacoustic surveys: Balancing quantity and quality of in situ target strength data |
| Series title | Fisheries Research |
| DOI | 10.1016/j.fishres.2016.12.020 |
| Volume | 188 |
| Year Published | 2017 |
| Language | English |
| Publisher | Elsevier |
| Contributing office(s) | Great Lakes Science Center |
| Description | 10 p. |
| First page | 173 |
| Last page | 182 |
| Country | United States |
| State | Ohio |
| Other Geospatial | Lake Erie |
| Google Analytic Metrics | Metrics page |