Experimental assessment of egg mat gear retention and collection efficacy
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Abstract
Assessment of egg deposition is widely used to provide an index of spawning efforts for lithophilic spawning fishes. However, little is known about the collection efficacy and bias of fish egg collection methods. We conducted a two-phased study consisting of a simulated-river flume study (two-part design), and a field study (an egg drift comparison with capture on mats) to assess egg collection methods and evaluate egg retention and capture on egg mats. Lake whitefish Coregonus clupeaformis egg retention on seeded mats decreased with increasing velocity and walleye Sander vitreus egg retention was variable as velocity increased. Fewer lake whitefish eggs were collected on egg mats when limestone reef rock was present in the flume study during the simulated spawned trials, but the inverse was true for walleye. Similarly, during field collections more lake whitefish eggs were collected in benthic D-shaped frame (D-frame) drift nets set near a known spawning reef compared to egg mats set on the reef, indicating lake whitefish eggs were drifting downstream along the river bottom. In contrast, fewer walleye eggs were observed in D-frame drift nets compared to number of eggs captured on the egg mats. Therefore, egg mats are an informative tool for evaluating walleye egg deposition in an immediate area but may underestimate egg deposition of lake whitefish, especially in lotic systems. Compared to other egg collection methods in the current literature, our study indicates that egg mats are useful for assessing egg deposition by lithophilic spawning fishes, but that the collection and retention efficacy and bias of this gear may vary between species and habitat types.
Publication type | Article |
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Publication Subtype | Journal Article |
Title | Experimental assessment of egg mat gear retention and collection efficacy |
Series title | Journal of Fish and Wildlife Management |
DOI | 10.3996/JFWM-23-018 |
Volume | 15 |
Issue | 1 |
Year Published | 2024 |
Language | English |
Publisher | Allen Press |
Contributing office(s) | Great Lakes Science Center |
Description | 11 p. |
First page | 289 |
Last page | 299 |
Google Analytic Metrics | Metrics page |