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Record W2538581601 · doi:10.1139/cjfas-2015-0558

Harbour seals target juvenile salmon of conservation concern

2016· article· en· W2538581601 on OpenAlexaffvenueabout
Austen C. Thomas, Benjamin W. Nelson, Monique M. Lance, Bruce E. Deagle, Andrew W. Trites

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental DNA in Biodiversity Studies
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsOncorhynchusChinook windPhocaPredationJuvenileFisheryBiologyHarbourEcologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Knowing the species and life stages of prey that predators consume is important for understanding the impacts that predation may have on prey populations, but traditional methods for determining diets often cannot provide sufficient detail. We combined data from two methods of scat analysis (DNA metabarcoding and morphological prey ID) to quantify the species and life stages of salmon (Oncorhynchus spp.) consumed by harbour seals (Phoca vitulina) in the Strait of Georgia, Canada, where juvenile Chinook (Oncorhynchus tshawytscha) and coho (Oncorhynchus kisutch) salmon survival is poor. Harbour seals primarily consumed adult salmon of lesser conservation concern in the fall (August–November): chum (Oncorhynchus keta: 18.4%), pink (Oncorhynchus gorbuscha: 12.6%), sockeye (Oncorhynchus nerka: 7.4%), Chinook (7.1%), and coho (1.8%). However, the opposite species trend occurred during the spring when seals preferred juvenile salmon of greater conservation concern (April–July): coho (2.9%), Chinook (2.9%), sockeye (2.5%), pink (1.4%), and chum (0.8%) — percentages that can equate to many individuals consumed. Our data suggest that harbour seals select juveniles of salmon species that out-migrate at ages >1 year and provide evidence of a potential causal relationship between harbour seal predation and juvenile salmon survival trends.

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)0.001
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 score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.025
GPT teacher head0.206
Teacher spread0.181 · 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

Citations102
Published2016
Admission routes3
Has abstractyes

Explore more

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