Revealing the full ocean migration of individual Atlantic salmon

Abstract

Background: Knowledge of the complete horizontal migration and vertical movements of Atlantic salmon (Salmo salar L.) during the marine phase is important for understanding the link between individual processes and population recruitment. We studied the detailed migration behaviour of six post-spawned adult Atlantic salmon from a North Norwegian river, during the entire ocean migration, by using high-resolution light-based geolocation archival tags. Results:The fish performed long-distance migrations and utilized Arctic areas from the eastern Barents Sea, to areas of Jan Mayen Island, and north to Svalbard. Four of six individuals exhibited a strong fidelity towards Jan Mayen Island, particularly during winter, which may suggest that the ecological conditions in these waters may be important for overwintering. One fish displayed exclusive utilization of the Barents Sea, indicating that growth and survival of some individuals are entirely dependent on these waters. The fish displayed a pelagic behaviour and all individuals spent more than 83% of the time in the uppermost 10 m of the water column. There was a strong seasonal trend in diving intensity, with the number of dives increasing with day length, independent of individuals' spatial distribution. Diving depth was positively correlated with the depth of the mixed layer. Conclusions:The Atlantic salmon displayed large individual variation in horizontal migrations, utilizing different ocean areas north of the Arctic Circle. This means that, despite the overall fidelity towards northern latitudes, individuals from the same population may experience highly different ecological conditions, potentially contributing to within-population variation in growth and survival. The seasonal correlation between diving intensity and day length, and spatial correlation between diving depth and depth of the mixed layer, indicate that the overall depth use of the Atlantic salmon depends on both spatially independent seasonal factors, and dynamic oceanographic conditions that facilitate food aggregations. This is the first study of Atlantic salmon to present detailed information about individuals' continuous horizontal migration and simultaneous vertical movements during the entire ocean migration, thus providing novel information on how habitat use change throughout the ocean residency.

Thermal habitat of adult Atlantic salmon Salmo salar in a warming ocean

“…In 2006–2007, tags equipped with a temperature sensor were attached externally, while in 2008–2015, tags recording temperature and depth were implanted into the body cavity of the fish (for details, see Rikardsen & Thorstad ; Strøm et al . ). Tags deployed in 2006 and 2007 failed to log data during the last months at sea, due limited battery capacity (Table ).…”

“…() and Strøm et al . (): (a) September 2010, (b) December 2010, (c) September 2011 and (d) December 2011. , Location of the Alta River…”

“…All the recaptured fish had left the river shortly after tagging, with date of ocean entry ranging from May 9–July 5. In previous analyses using parts of this data set, the spatial distribution (Chittenden et al ., ; Strøm et al ., ) and depth use (Hedger et al ., ) of these individuals have been described (Table ). Individual migration routes were reconstructed for six salmon tagged in 2013–2015, because they were fitted with tags that recorded light data, thus enabling light‐based geolocation (Strøm et al .…”

Natural Behavior Learning for Developing an Innovation of Computational Intelligence Applied to a Technical Quadratic Problem

“…This behavior is used to survive and stand for continuing activities and participation during living in the community. During the migration, Salmon swims a great distance to find their home which is shared in natural behavior learning for existing a community in huge migrating routes [5]. Naturally, Salmon face some predators and obstacles to keep a life cycle while migrating for surviving the life on the migrating ways [6], [7].…”

“…As in many previous works, the behavior learning presents natural mechanisms for searching suitable models and understanding the phenomena [5], [8], [9]. Many behaviors of entities or species have been selected as inspirations for developing certain approaches based on mechanisms of processes.…”