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Record W1995797713 · doi:10.1073/pnas.1009573108

Relationship of farm salmon, sea lice, and wild salmon populations

2010· article· en· W1995797713 on OpenAlexaffabout
Gary D. Marty, Sonja Saksida, Terrance J. Quinn

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsBC Centre for Aquatic Health Sciences
Fundersnot available
KeywordsSpawn (biology)BiologySalmoOncorhynchusFisheryLepeophtheirusAquacultureJuvenileFish farmingPopulationProductivityFish <Actinopterygii>EcologyDemography

Abstract

fetched live from OpenAlex

Increased farm salmon production has heightened concerns about the association between disease on farm and wild fish. The controversy is particularly evident in the Broughton Archipelago of Western Canada, where a high prevalence of sea lice (ectoparasitic copepods) was first reported on juvenile wild pink salmon (Oncorhynchus gorbuscha) in 2001. Exposure to sea lice from farmed Atlantic salmon (Salmo salar) was thought to be the cause of the 97% population decline before these fish returned to spawn in 2002, although no diagnostic investigation was done to rule out other causes of mortality. To address the concern that sea lice from fish farms would cause population extinction of wild salmon, we analyzed 10-20 y of fish farm data and 60 y of pink salmon data. We show that the number of pink salmon returning to spawn in the fall predicts the number of female sea lice on farm fish the next spring, which, in turn, accounts for 98% of the annual variability in the prevalence of sea lice on outmigrating wild juvenile salmon. However, productivity of wild salmon is not negatively associated with either farm lice numbers or farm fish production, and all published field and laboratory data support the conclusion that something other than sea lice caused the population decline in 2002. We conclude that separating farm salmon from wild salmon--proposed through coordinated fallowing or closed containment--will not increase wild salmon productivity and that medical analysis can improve our understanding of complex issues related to aquaculture sustainability.

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)0.001
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 score0.165
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.049
GPT teacher head0.355
Teacher spread0.306 · 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

Citations116
Published2010
Admission routes2
Has abstractyes

Explore more

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