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Record W2765511909 · doi:10.1111/eva.12566

Predicting the genetic impact of stocking in Brook Charr (<i>Salvelinus fontinalis</i>) by combining <scp>RAD</scp> sequencing and modeling of explanatory variables

2017· article· en· W2765511909 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEvolutionary Applications · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsUniversité de SherbrookeUniversité Laval
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsStockingBiologySalvelinusPopulationGenetic variationEcologyPopulation geneticsOverfishingPopulation sizeFisheryFishingTroutDemographyGenetics

Abstract

fetched live from OpenAlex

Abstract In fisheries management, intensive stocking programs are commonly used to enhance population abundance and maintain stock productivity. However, such practices are increasingly raising concerns as multiple studies documented adverse genetic and evolutionary impacts of stocking on wild populations. Improvement of stocking management relies on a better understanding of the dynamic of introgressive hybridization between wild and domestic population and on assessment of the genetic state of wild populations after stocking cessation. In Québec, Canada, over five million captive‐reared Brook Charr ( Salvelinus fontinalis ) are stocked every year to support recreational fishing activities. Here, we investigated how variation in stocking history and environmental variables, including water temperature, pH , and dissolved oxygen, may influence the impact of stocking practices on the genetic integrity of wild Brook Charr populations. We collected DNA samples ( n = 862, average of 30 individuals per lake) from 29 lakes that underwent different stocking intensity through time and also collected environmental parameters for each sampled lake. An average of 4,580 high‐quality filtered SNP s was obtained for each population using genotyping by sequencing ( GBS ), which were then used to quantify the mean domestic membership of each sampled population. An exhaustive process of model selection was conducted to obtain a best‐fitted model that explained 56% of the variance observed in mean domestic genetic membership. The number of years since the mean year of stocking was the best explanatory variable to predict variation in mean domestic genetic membership whereas environmental characteristics had little influence on observed patterns of admixture. Our model predictions also revealed that each sampled wild population could potentially return to a wild genetic state (absence of domestic genetic background) after stocking cessation. Overall, our study provides new insights on factors determining level of introgressive hybridization and suggests that stocking impacts could be reversible with time.

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.

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 score0.203
Threshold uncertainty score0.387

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 studies0.0000.000
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 head0.017
GPT teacher head0.256
Teacher spread0.240 · 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