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Modern and ancient DNA reveal recent partial replacement of caribou in the southwest Yukon

2010· article· en· W2168936911 on OpenAlexafffundabout
Tyler S. Kuhn, Keri McFarlane, Pamela Groves, Arne Ø. Mooers, Beth Shapiro

Bibliographic record

VenueMolecular Ecology · 2010
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsThe King's UniversitySimon Fraser University
FundersParks Canada
KeywordsBiologyAncient DNAEvolutionary biologyEcologyArchaeologyZoologyDemographyPopulationGeography

Abstract

fetched live from OpenAlex

The long-term persistence of forest-dwelling caribou (Rangifer tarandus caribou) will probably be determined by management and conservation decisions. Understanding the evolutionary relationships between modern caribou herds, and how these relationships have changed through time will provide key information for the design of appropriate management strategies. To explore these relationships, we amplified microsatellite and mitochondrial markers from modern caribou from across the Southern Yukon, Canada, as well as mitochondrial DNA from Holocene specimens recovered from alpine ice patches in the same region. Our analyses identify a genetically distinct group of caribou composed of herds from the Southern Lakes region that may warrant special management consideration. We also identify a partial genetic replacement event occurring 1000 years before present, coincident with the deposition of the White River tephra and the Medieval Warm Period. These results suggest that, in the face of increasing anthropogenic pressures and climate variability, maintaining the ability of caribou herds to expand in numbers and range may be more important than protecting the survival of any individual, isolated sedentary forest-dwelling herd.

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 score0.956
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.333
Teacher spread0.311 · 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

Citations45
Published2010
Admission routes3
Has abstractyes

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