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dc.contributor.authorVollset, Knut
dc.contributor.authorLennox, Robert J.
dc.contributor.authorLamberg, Anders
dc.contributor.authorSkaala, Øystein
dc.contributor.authorSandvik, Anne Dagrun
dc.contributor.authorSægrov, Harald
dc.contributor.authorKvingedal, Eli
dc.contributor.authorKristensen, Torstein
dc.contributor.authorJensen, Arne Johan
dc.contributor.authorHaraldstad, Tormod
dc.contributor.authorBarlaup, Bjørn Torgeir
dc.contributor.authorUgedal, Ola
dc.date.accessioned2021-09-02T07:59:50Z
dc.date.available2021-09-02T07:59:50Z
dc.date.created2021-08-02T09:58:11Z
dc.date.issued2021
dc.identifier.citationDiversity and Distributions: A journal of biological invasions and biodiversity. 2021, 27 (8), 1383-1392.en_US
dc.identifier.issn1366-9516
dc.identifier.urihttps://hdl.handle.net/11250/2772384
dc.description.abstractAim Accurate predictions about transition timing of salmon smolts between freshwater and marine environments are key to effective management. We aimed to use available data on Atlantic salmon smolt migration to predict the emigration timing in rivers throughout Norway. Location In this study, we used outmigration timing data of Atlantic salmon (Salmo salar) smolts from 41 rivers collected from 1984 to 2018 to make a predictive model for the timing of out-migrating salmon smolts along 12 degrees latitude. Methods Smolt migration data were collated from rivers where smolts are monitored with traps, video and tagging and matched to river-specific metadata. Using a mixed-effects generalized additive model, we tested for the effects of spatial location, air temperature, river flow and counting methods on the timing of 25% smolt emigration from rivers. Results After accounting for spatial effects and repeated measures (across years and among rivers), air temperature and counting method were significant drivers of the estimated timing of smolt emigration. In-sample predictions yielded strong correlation with observed values, as did 10-fold cross-validation. Out-of-sample predictions suggested that the previous national estimates underestimated the migration timing in southern populations (linear model intercept = 39.73 days). Conclusion Model-derived estimates of run timing can be used to more accurately predict the timing of outmigration in order to better calibrate environmental flows and regulate management of marine industries such as aquaculture that may affect migration success at this particularly sensitive life stage.en_US
dc.language.isoengen_US
dc.publisherWileyen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titlePredicting the nationwide outmigration timing of Atlantic salmon (Salmo salar) smolts along 12 degrees of latitude in Norwayen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber1383-1392en_US
dc.source.volume27en_US
dc.source.journalDiversity and Distributions: A journal of biological invasions and biodiversityen_US
dc.source.issue8en_US
dc.identifier.doi10.1111/ddi.13285
dc.identifier.cristin1923312
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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