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Record W2888345454 · doi:10.1111/fwb.13166

Bioenergetic consequences of warming rivers to adult Atlantic salmon <i>Salmo salar</i> during their spawning migration

2018· article· en· W2888345454 on OpenAlexafffund
Robert J. Lennox, Erika J. Eliason, Torgeir B. Havn, Martin R. Johansen, Eva B. Thorstad, Steven J. Cooke, Ola H. Diserud, Frederick G. Whoriskey, Anthony P. Farrell, Ingebrigt Uglem

Bibliographic record

VenueFreshwater Biology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of British ColumbiaOcean Tracking NetworkDalhousie UniversityCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsSalmoSalmonidaeBioenergeticsRange (aeronautics)Fish migrationHabitatEnvironmental scienceEcologyFisheryClimate changeEnergeticsEnergy expenditureBiologySmoltificationFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Abstract Climate change poses a challenge to wild fishes, yet little is known about the behavioural use and metabolic consequences of thermally heterogeneous water encountered by wild salmon during their energetically demanding upstream spawning migration. Temperature, body size and activity levels were modelled to predict energy depletion of salmon during their spawning migration in rivers. Archival temperature loggers revealed the thermal habitat of adult migrating Atlantic salmon ( Salmo salar Salmonidae), which we used to apply bioenergetics models that estimated size‐dependent temperature‐driven metabolic expenditures as part of the costs of the migration. Between July 16 and August 19, the mean water temperature experienced by salmon ( t FISH ) ranged from 11.5 to 18.0°C (14.5 ± 1.2 SD °C) and closely followed the ambient surface water temperature ( t RIVER ) of the river (11.5–18.5°C; 14.8 ± 1.4°C) such that the regression equation t FISH = 3.24 + 0.76 ( t RIVER ) was highly correlated with observations ( R 2 = 0.94). Although temperature increases were predicted and confirmed to increase energetic costs, rates of energy depletion were more sensitive to changes in swimming speed and body size than to temperature increases in the range explored for this system. We conclude that warming could contribute to changing life history phenotypes of salmon in some rivers, for example, delayed river entry or reduced probability of iteroparity, with potentially more dire consequences for smaller individuals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.213
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations35
Published2018
Admission routes2
Has abstractyes

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