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Record W2969674343 · doi:10.1111/conl.12669

Genetics of century‐old fish scales reveal population patterns of decline

2019· article· en· W2969674343 on OpenAlex
Michael H. H. Price, Brendan Connors, John R. Candy, Brenda McIntosh, Terry D. Beacham, Jonathan W. Moore, John D. Reynolds

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

VenueConservation Letters · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsFisheries and Oceans CanadaSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaW. Garfield Weston Foundation
KeywordsFishingAbundance (ecology)FisheryGeographyFish <Actinopterygii>EcologyBiologyCommercial fishingPopulationWatershedPopulation declineHabitatDemography

Abstract

fetched live from OpenAlex

Abstract Conservation scientists rarely have the information required to understand changes in abundance over more than a few decades, even for important species like Pacific salmon. Such lack of historical information can underestimate the magnitude of decline for depressed populations. We applied genetic tools to a unique collection of 100‐year‐old salmon scales to reveal declines of 56%–99% in wild sockeye populations across Canada's second largest salmon watershed, the Skeena River. These analyses reveal century‐long declines that are much greater than those based on modern era abundance data, which suggested that only 7 of 13 populations declined over the last five decades. Populations of larger‐bodied fish have declined the most in abundance, likely because of size‐selective commercial fisheries. Our findings illustrate how a deep historical perspective can expand our understanding of past abundances to a time before species incurred significant losses from fishing, and help inform conservation for diminished populations.

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 score0.021
Threshold uncertainty score0.425

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 head0.009
GPT teacher head0.210
Teacher spread0.201 · 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