Using down-scan capabilities from recreational-grade side-scan sonar systems to sample paddlefish and evaluate depth use in a reservoir
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Abstract
Recreational-grade side-scan sonar (SSS) has only recently been applied to estimate abundance of Paddlefish Polyodon spathula, a large pelagic planktivore, in reservoirs. Current recreational-grade SSS units also have a dedicated down-scan channel, which may be useful for detecting Paddlefish in reservoirs because the range of depths they inhabit. We investigated the utility of down-scan images using SSS data from a previously published study of Paddlefish in Keystone Lake, Oklahoma. Two readers counted Paddlefish and estimated the depth of each fish and the water column. We used proximity functions in a geographic information system to find individual Paddlefish that were common between the readers. We further used proximity functions to identify common fish observed from the SSS survey conducted previously as an aid to compare and refine down-scan estimates. Depth of Paddlefish averaged approximately 7 m, but fish were deeper when water was deeper. Density estimates from down-scan were comparable to side-scan, but only after utilizing the side-scan data to adjust for detection-by-distance in a dual-gear approach. Down-scan data thus appear to be useful for not only estimating density of Paddlefish, but also for incorporating depth use, creating a three-dimensional database of locations that can inform managers of optimal depths for sampling gear (e.g., gill nets), improve monitoring efficiency, and facilitate better management of reservoir populations.
Study Area
Publication type | Article |
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Publication Subtype | Journal Article |
Title | Using down-scan capabilities from recreational-grade side-scan sonar systems to sample paddlefish and evaluate depth use in a reservoir |
DOI | 10.1016/j.fishres.2023.106872 |
Volume | 269 |
Year Published | 2024 |
Language | English |
Publisher | Elsevier |
Contributing office(s) | Coop Res Unit Atlanta |
Description | 106872, 8 p. |
Country | United States |
State | Oklahoma |
Other Geospatial | Keystone Lake |
Google Analytic Metrics | Metrics page |