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Record W2059823276 · doi:10.1073/pnas.0705511104

Encroaching forests decouple alpine butterfly population dynamics

2007· article· en· W2059823276 on OpenAlexaffabout
Jens Roland, Stephen F. Matter

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsButterflyBiological dispersalEcologyForest dynamicsExtinction (optical mineralogy)PopulationHabitatGeographyLocal extinctionBiology

Abstract

fetched live from OpenAlex

Over the past 50 years, the rising tree line along Jumpingpound Ridge in the Rocky Mountains of Alberta, Canada, has reduced the area of alpine meadows and isolated populations that reside within them. By analyzing an 11-year data set of butterfly population sizes for 17 subpopulations along the ridge, we show that forest habitat separating alpine meadows decouples the dynamics of populations of the alpine butterfly Parnassius smintheus. Although the distance between populations is often negatively correlated with synchrony of dynamics, here we show that distance through forest, not Euclidean distance, determines the degree of synchrony. This effect is consistent with previous results demonstrating that encroaching forest reduces dispersal among populations and reduces gene flow. Decoupling dynamics produces more smaller independent populations, each with greater risk of local extinction, but decoupling may produce a lower risk of regional extinction in this capricious environment.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.055
GPT teacher head0.275
Teacher spread0.219 · 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

Citations56
Published2007
Admission routes2
Has abstractyes

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