JOURNAL ARTICLE
Interannual variation in survival of wild Atlantic salmon smolts through a dynamic estuarine habitat.
Published In: Fisheries Management & Ecology, 2024, v. 31, n. 6. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Barry, J.; Fitzgerald, C.; Callaghan, J. O.; Kennedy, R.; Rosell, R.; Roche, W. 3 of 3
Abstract
Migration timing is critical for diadromous fish, especially for survival. Migration through fresh water and estuarine transitional waterbodies may be an important early life survival bottleneck through potential exposure to anthropogenic pressures and predators. Monitoring smolt movement and survival through riverine and estuarine habitats is important for identifying causes of smolt mortality and the potential for directing focused, mitigating management actions. Acoustic telemetry was used to track 186 Atlantic salmon smolts during migration from the river Boyne to the Irish Sea on the east coast of Ireland during 2019–2021. Migration success from release to sea entry that ranged from 47% to 81% was linked to biotic (predation) and abiotic effects (water flow and water temperature). Predation was associated with interannual variation in smolt survival, with 5.4% of smolts consumed by marine mammals and 26.3% lost to unknown fates. Our findings contribute to the understanding of predation on smolts and also how water temperature, flow and tidal phase can influence this critical life stage of Atlantic Salmon, a species in decline across its range. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Fisheries Management & Ecology. 2024/12, Vol. 31, Issue 6, p1
- Document Type:Article
- Subject Area:Zoology
- Publication Date:2024
- ISSN:0969-997X
- DOI:10.1111/fme.12685
- Accession Number:180776092
- Copyright Statement:Copyright of Fisheries Management & Ecology is the property of Wiley-Blackwell 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.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.