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Record W7133278021

Evaluation of potential direct genetic effects of the proposed Atlantic salmon (Salmo salar) aquaculture site expansion in southern Newfoundland

2022· other· en· W7133278021 on OpenAlexaboutno aff
Ian R. Bradbury, Steve Duffy, Sarah Lehnert, Ragnar Johannsson, Fridriksson Jon Hlodver, Marco Castellani, Ingrid Burgetz, Emma Sylvester, Amber Messmer, Nicholas Kelly, Ian Fleming

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsBiological dispersalBayPopulationAquacultureEffective population sizePopulation size
DOInot available

Abstract

fetched live from OpenAlex

In 2019 a proponent applied for aquaculture licenses at various sites located on the south coast of Newfoundland and the request was referred to DFO for siting advice including examination of the potential for genetic interactions with wild Atlantic salmon. Here we examine the potential genetic interactions resulting from the proposed finfish expansion involving thirteen sites (1M individuals/site) in southern Newfoundland using a combination of empirical data, and both individual-based and dispersal modeling. We use an eco-genetic individual-based Atlantic salmon model (IBSEM) parameterized for southern Newfoundland populations, with regional environmental data and field-based estimates of aquaculture parr survival, to explore how the proportion of escapees relative to the size of wild populations influences genetic and demographic change in the wild. Our simulations suggest that both demographic decline and genetic change are predicted when the proportion of escapees relative to wild population size exceeds 10% annually. The occurrence of escapees in southern Newfoundland rivers (estimated population size ~22,000 individuals), both at present and under the proposed expansion scenario were predicted using river and site locations, simple models of dispersal for early and late escapees, and the best available data from Canada and Europe. Model predictions of escapee dispersal suggest that under the present regime, rivers characterized by the largest proportion of escapees relative to wild population size are located in the head of Fortune Bay and Bay d’Espoir (19 rivers total > 10% escapees, max 15.6%) consistent with recent empirical evidence of escapees and hybridization. Under the proposed expansion, the number of escapees in southern Newfoundland rivers is predicted to increase by 49% (1.5X) and the rivers characterized by the greatest proportion of escapees relative to wild population size are predicted to occur in the Bay d’Espoir area (20 rivers total >10% escapees, max 24%).

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)0.001
metaresearch head score (Gemma)0.002
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 score0.516
Threshold uncertainty score0.962

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.226
Teacher spread0.219 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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Same venueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du CanadaFrench-language works237,207