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Record W3154661951 · doi:10.1139/as-2019-0036

Life history variation in Arctic charr (<i>Salvelinus alpinus</i>) and the effects of diet and migration on the growth, condition, and body morphology of two Arctic charr populations in Cumberland Sound, Nunavut, Canada

2021· article· en· W3154661951 on OpenAlexaffvenueabout
Angela L. Young, R. F. Tallman, Derek H. Ogle

Bibliographic record

VenueArctic Science · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsFisheries and Oceans CanadaGovernment of NunavutGovernment of Canada
Fundersnot available
KeywordsSalvelinusArcticFish migrationLandlocked countryBiologyEcologyPopulationFisheryHabitatZoologyFish <Actinopterygii>DemographyTrout

Abstract

fetched live from OpenAlex

Arctic charr (Salvelinus alpinus (Linnaeus, 1758)) are phenotypically plastic with multiple dietary–morphological relationships observed throughout their circumpolar range. Feeding strategies often differ between Arctic charr life histories and can impact size-at-age and morphological attributes. We examined growth, condition, and body morphology for two High Arctic populations of Arctic charr with anadromous and landlocked life histories. Anadromous Arctic charr had higher growth rates, achieving mean lengths two times those of landlocked Arctic charr by age 10 and had higher overall condition, particularly in the fall. Ontogenetic shifts in diet were suspected in both populations, with an abrupt shift to marine feeding in the anadromous population and a gradual shift to piscivory in the landlocked population. Morphological differences between life histories manifested most predominantly in larger eye diameter, longer pectoral and pelvic fins, and longer upper jaws of landlocked Arctic charr, suggestive of piscivorous feeding specialization of landlocked fish &gt;350 mm. Our findings emphasize the benefits that marine feeding can have for growth and condition of freshwater fishes in Arctic environments and also convey the necessity of adaptive feeding strategies to optimize growth and condition in fishes inhabiting low-production lacustrine habitats.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.415
Threshold uncertainty score0.854

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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

Citations14
Published2021
Admission routes3
Has abstractyes

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