Sensitivity of fish density estimates to standard analytical procedures applied to Great Lakes hydroacoustic data

Journal of Great Lakes Research
By: , and 

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Abstract

Standardized methods of data collection and analysis ensure quality and facilitate comparisons among systems. We evaluated the importance of three recommendations from the Standard Operating Procedure for hydroacoustics in the Laurentian Great Lakes (GLSOP) on density estimates of target species: noise subtraction; setting volume backscattering strength (Sv) thresholds from user-defined minimum target strength (TS) of interest (TS-based Sv threshold); and calculations of an index for multiple targets (Nv index) to identify and remove biased TS values. Eliminating noise had the predictable effect of decreasing density estimates in most lakes. Using the TS-based Sv threshold decreased fish densities in the middle and lower layers in the deepest lakes with abundant invertebrates (e.g., Mysis diluviana). Correcting for biased in situ TS increased measured density up to 86% in the shallower lakes, which had the highest fish densities. The current recommendations by the GLSOP significantly influence acoustic density estimates, but the degree of importance is lake dependent. Applying GLSOP recommendations, whether in the Laurentian Great Lakes or elsewhere, will improve our ability to compare results among lakes. We recommend further development of standards, including minimum TS and analytical cell size, for reducing the effect of biased in situ TS on density estimates.

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Publication type Article
Publication Subtype Journal Article
Title Sensitivity of fish density estimates to standard analytical procedures applied to Great Lakes hydroacoustic data
Series title Journal of Great Lakes Research
DOI 10.1016/j.jglr.2013.09.002
Volume 39
Issue 4
Year Published 2013
Language English
Publisher Elsevier
Contributing office(s) Great Lakes Science Center
Description 8 p.
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Journal of Great Lakes Research
First page 655
Last page 662
Country United States
Other Geospatial Great Lakes
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