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Replicated population divergence caused by localized coevolution? A test of three hypotheses in the red crossbill-lodgepole pine system

2006· article· en· W2139626165 on OpenAlexaff
Pim Edelaar, Craig W. Benkman

Bibliographic record

VenueJournal of Evolutionary Biology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBiologyDivergence (linguistics)CoevolutionEvolutionary biologyPopulationDemography

Abstract

fetched live from OpenAlex

Several lines of evidence support the hypothesis that local populations of red crossbills (Loxia curvirostra complex) enter into a predator-prey arms race with lodgepole pine (Pinus contorta latifolia) in the absence of competing pine squirrels (Tamiasciurus hudsonicus). Nevertheless, the alternative hypotheses that neutral evolution or factors other than squirrels have caused crossbill population differentiation have not been thoroughly tested. We compared crossbill and pine cone morphology between island populations where squirrels are absent or present, and mainland sites where squirrels are present, in order to distinguish among these hypotheses. All comparisons supported an effect of squirrel absence, not island status, on crossbill and cone morphology. Hence our results provide further evidence that strong localized coevolutionary interactions in a geographic mosaic have driven adaptive population differentiation. In addition, vocal differentiation of crossbills was related to the absence of squirrels, but not to island status. As morphological and vocal differentiation is correlated with reproductive isolation in crossbills, the geographic mosaic of coevolution also seems to promote ecological speciation.

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)0.005
metaresearch head score (Gemma)0.020
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 score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.250
Teacher spread0.235 · 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

Citations24
Published2006
Admission routes1
Has abstractyes

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