JOURNAL ARTICLE
Low‐level infection of parasitic copepods on Rainbow Trout does not affect vulnerability to angling or short‐term survival following catch‐and‐release angling.
Published In: North American Journal of Fisheries Management, 2023, v. 43, n. 6. P. 1789 1 of 3
Database: Environment Complete 2 of 3
Authored By: Swain‐Menzel, Hannah N.; Billman, Eric J. 3 of 3
Abstract
This article investigates the effects of the parasitic copepod Salmincola californiensis on the vulnerability of Rainbow Trout (Oncorhynchus mykiss) to recreational angling and their short-term survival after catch-and-release in Birch Creek, Idaho. The study found that low-level infections did not significantly affect the likelihood of trout being caught by anglers nor their survival following a simulated catch-and-release stress event involving air exposure. Infection prevalence and intensity were positively correlated with fish length but did not differ between fish caught by angling and electrofishing, indicating no influence of infection on catchability under the study conditions. The authors suggest that while low-level infections may not impact catch rates or short-term survival, further research is needed at higher infection intensities and with larger fish to fully understand potential effects. They also highlight the importance of public education to maintain angler satisfaction and proper fishery management in the presence of parasitic copepods.
Additional Information
- Source:North American Journal of Fisheries Management. 2023/12, Vol. 43, Issue 6, p1789
- Document Type:Article
- Subject Area:Sports and Leisure
- Publication Date:2023
- ISSN:0275-5947
- DOI:10.1002/nafm.10957
- Accession Number:174780375
- Copyright Statement:Copyright of North American Journal of Fisheries Management is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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