MétaCan
Menu
Back to cohort

Introgression of domesticated alleles into a wild trout genotype and the impact on seasonal survival in natural lakes

2011· article· en· W1556607378 on OpenAlexaff
Wendy E. Vandersteen, Peter A. Biro, Les N. Harris, Robert H. Devlin

Bibliographic record

VenueEvolutionary Applications · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsOutbreeding depressionDomesticationBiologyIntrogressionTroutRainbow troutHybridPopulationZoologyEcologySelective breedingFish <Actinopterygii>FisheryGeneticsInbreedingDemographyAgronomyGene

Abstract

fetched live from OpenAlex

We tested the fitness consequences of introgression of fast-growing domesticated fish into a wild population. Fry from wild and domesticated rainbow trout (Oncorhynchus mykiss) crosses, F1 hybrids, and first- and second-generation backcrosses were released into two natural lakes. Parentage analysis using microsatellite loci facilitated the identification of survivors, so fitness was estimated in nature from the first-feeding stage. Results indicated that under certain conditions, domesticated fish survived at least as well as wild fish within the same environment. Relative growth and survival of the crosses, however, were highly dependent on environment. During the first summer, fastest-growing crosses had the highest survival, but this trend was reversed after one winter and another summer. Although the F1 hybrids showed evidence of outbreeding depression because of the disruption of local adaptation, there was little evidence of outbreeding depression in the backcrosses, and the second-generation backcrosses exhibited a wild-type phenotype. This information is relevant for assessing the multigenerational risk of escaped or released domesticated fish should they successfully interbreed with wild populations and provides information on how to minimize detrimental impacts of a conservation breeding and/or management programme. These data also further understanding of the selection pressures in nature that maintain submaximal rates of growth.

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 score0.049
Threshold uncertainty score0.299

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 head0.007
GPT teacher head0.237
Teacher spread0.230 · 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

Citations26
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueEvolutionary ApplicationsSame topicFish Ecology and Management StudiesFrench-language works237,207