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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/30773
Title: Gear‐Type Influences on Fish Catch and a Wetland Fish Index in Georgian Bay Wetlands
Authors: Cvetkovic M
Kostuk K
Chow‐Fraser P
Department: Biology
Keywords: 30 Agricultural, Veterinary and Food Sciences;3005 Fisheries Sciences
Publication Date: Apr-2012
Publisher: Wiley
Abstract: The Laurentian Great Lakes are managed by many jurisdictions that use a variety of survey methods and gear types to monitor fish assemblages in coastal marshes. Lack of standardization in these methods makes it difficult for organizations to compare data because of inherent biases in gear types. Of equal concern is the uncertainty of the effect of gear bias on fish-related index scores for ecosystem health. Our first objective was to investigate whether there were differences in catch data between two commonly used sampling gears: fyke nets (FN) and boat electrofishing (EF). Secondly, we investigated whether catch differences in data associated with gear biases can lead to significant differences when these data are used to generate scores for biotic indices such as the published Wetland Fish Index (WFI). We sampled 26 coastal wetlands in Georgian Bay (Lake Huron) in the summers of 2004 and 2005. A majority (73%) of the more than 10,000 fish were caught by FN; this gear also captured a greater number of species and functional taxa and selected for larger piscivores. By comparison, EF captured larger invertivores. Fyke nets were more selective for individuals from the Centrarchidae, Cyprinidae, and Ictaluridae families, while EF was more effective for darters (e.g., the Iowa darter Etheostoma exile and johnny darter E. nigrum) and white suckers Catostomus commersonii. Despite these biases in catch data, we obtained statistically similar WFI scores with both gear types. Therefore, although the fish abundance and species composition information collected from FN and EF are not directly comparable, when necessary they can be used interchangeably to generate a fish-based index of ecosystem health. © 2012 American Fisheries Society.
URI: http://hdl.handle.net/11375/30773
metadata.dc.identifier.doi: https://doi.org/10.1080/02755947.2012.678560
ISSN: 0275-5947
1548-8675
Appears in Collections:Biology Publications

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