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Metabolic traits of westslope cutthroat trout, introduced rainbow trout and their hybrids in an ecotonal hybrid zone along an elevation gradient

2011· article· en· W1748076794 on OpenAlexafffundabout
Joseph B. Rasmussen, Michael D. Robinson, Alice Hontela, Daniel D. Heath

Bibliographic record

VenueBiological Journal of the Linnean Society · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of WindsorUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Conservation Association
KeywordsRainbow troutBiologyTroutHybridOncorhynchusEcologyZoologyFisheryFish <Actinopterygii>Botany

Abstract

fetched live from OpenAlex

In the Upper Oldman River, Alberta, introduced non-native hatchery rainbow trout (Oncorhynchus mykiss) hybridize with native westslope cutthroat trout (O. clarkii), resulting in a hybrid swarm. Rainbow trout dominate at low elevations (< 1250 m) in the river mainstem, cutthroat in high-elevation tributaries (> 1400 m), and hybrids are numerically dominant in the mid-elevation range. We hypothesized that metabolism of rainbow trout would exceed that of cutthroat trout, and that the elevation gradient in genetic makeup would be mirrored by a gradient in metabolic traits, with intermediate traits in the hybrid-dominated ecotone. Metabolic traits were measured and regressed against the genetic makeup of individuals and elevation. Rainbow trout had higher oxygen consumption rates (OCRs), higher white muscle lactate dehydrogenase (LDH), and citrate synthase (CS) activity, and higher plasma acetylcholinesterase (AchE) than cutthroat trout. Hybrids had intermediate OCRs and AchE, but LDH activity as high as rainbow trout. While hybrid zones are usually modelled as a balance between cross species mating and selection against hybrids, ecotonal hybrid zones, where hybrids proliferate in intermediate habitats and have traits that appear well suited to ecotonal conditions, have been proposed for some plants and animals, and may have important implications for resource management and conservation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.115
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.032
GPT teacher head0.223
Teacher spread0.191 · 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 source (direct Gemma or distilled Codex), 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

Citations41
Published2011
Admission routes3
Has abstractyes

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