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Colonization history and taxonomy of moose Alces alces in southeastern Alaska inferred from mtDNA variation

2006· article· en· W2043248163 on OpenAlexaboutno aff
Kris J. Hundertmark, R. Terry Bowyer, Gerald F. Shields, Charles C. Schwartz, Michael H. Smith

Bibliographic record

VenueWildlife Biology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
FundersUniversity of GeorgiaU.S. Department of EnergyNational Science Foundation
KeywordsSubspeciesPhylogeographyGeographyHaplotypeColonizationEcologyBiologyPhylogenetic treeGenotype

Abstract

fetched live from OpenAlex

We assessed phylogeographic history of moose Alces alces in southeastern Alaska, USA, by determining their genetic affinity to surrounding populations thereby clarifying their origin and uncertain taxonomic status. Moose from central and southern regions of the southeastern Alaska panhandle were characterized by two mitochondrial haplotypes that were highly divergent from those in the remainder of the state; overlap with other haplotypes occurred only in the northernmost area of the panhandle. Moose inhabiting areas of British Columbia, Canada, immediately adjacent to Alaska's panhandle showed high haplotype diversity. A small proportion of those moose shared haplotypes with moose in southeastern and interior Alaska, but most possessed haplotypes that were restricted to that region. Association between geographic distribution and phylogenetic structure of haplotypes indicated spatial separation of moose lineages in the past. Our results indicate that there were two separate entries of moose into the region during colonization, likely from different geographic areas. Coastal populations of moose living south of 58°45′N latitude in southeastern Alaska should be classified as A. a. andersoni rather than as A. a. gigas. Behavioural and morphological differences between A. a. gigas and other forest-dwelling subspecies in North America indicate a need to examine moose management strategies and objectives in southeastern Alaska.

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)0.000
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 score0.015
Threshold uncertainty score0.591

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 head0.014
GPT teacher head0.194
Teacher spread0.180 · 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

Citations9
Published2006
Admission routes1
Has abstractyes

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