Synchrony and multimodality in the timing of Atlantic salmon smolt migration in two Norwegian fjords

The timing of the smolt migration of Atlantic salmon (Salmo salar) is a phenological trait increasingly important to the fitness of this species. Understanding when and how smolts migrate to the sea is crucial to understanding how salmon populations will be affected by both climate change and the el...

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Bibliographic Details
Published in:Scientific Reports
Main Authors: Bjerck, Helge B., Urke, Henning A., Haugen, Thrond O., Alfredsen, Jo Arve, Ulvund, John Birger, Kristensen, Torstein
Format: Text
Language:English
Published: Nature Publishing Group UK 2021
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Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985142/
http://www.ncbi.nlm.nih.gov/pubmed/33753812
https://doi.org/10.1038/s41598-021-85941-9
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Summary:The timing of the smolt migration of Atlantic salmon (Salmo salar) is a phenological trait increasingly important to the fitness of this species. Understanding when and how smolts migrate to the sea is crucial to understanding how salmon populations will be affected by both climate change and the elevated salmon lice concentrations produced by salmon farms. Here, acoustic telemetry was used to monitor the fjord migration of wild post-smolts from four rivers across two fjord systems in western Norway. Smolts began their migration throughout the month of May in all populations. Within-population, the timing of migration was multimodal with peaks in migration determined by the timing of spring floods. As a result, migrations were synchronized across populations with similar hydrology. There was little indication that the timing of migration had an impact on survival from the river mouth to the outer fjord. However, populations with longer fjord migrations experienced lower survival rates and had higher variance in fjord residency times. Explicit consideration of the multimodality inherent to the timing of smolt migration in these populations may help predict when smolts are in the fjord, as these modes seem predictable from available environmental data.