MétaCan
Menu
Back to cohort
Record W2892678357 · doi:10.1111/afe.12305

Morphological variation associated with dispersal capacity in a tree‐killing bark beetle <i>Dendroctonus ponderosae</i> Hopkins

2018· article· en· W2892678357 on OpenAlexafffund
Victor A. Shegelski, Maya L. Evenden, Felix A. H. Sperling

Bibliographic record

VenueAgricultural and Forest Entomology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsUniversity of Alberta
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaNational Institutes of Health
KeywordsBiological dispersalBiologyWingDendroctonusMountain pine beetleWing loadingBark beetleEcologyPopulationInsect flightZoologyBark (sound)Demography

Abstract

fetched live from OpenAlex

Abstract Intrinsic factors influencing the dispersal of insect pests during outbreaks are poorly understood, yet these factors need to be quantified to parameterize dispersal in models that predict population spread. The present study related wing and body morphology of female mountain pine beetles ( Dendroctonus ponderosae ) to flight distance, as measured by flight mill bioassays. Beetles that flew long distances (&gt; 11 km) had a greater body weight and larger wings than beetles that flew short distances (&lt; 1 km). These heavier female beetles should also be more capable pioneers because other studies have shown that body weight is positively correlated with lipid content. Wing and body morphology of females are significant predictors of flight distance; heavy beetles with large wings generally flew further than smaller beetles, although this relationship is heteroscedastic. Dispersion of flight distance values increases with wing loading (weight/wing area) as a result of a cohort of ‘lazy’ individuals that fly short distances (&lt; 1 km) regardless of flight phenotype. The observed morphology explained less than 20% of the variation in flight capacity, indicating a substantial contribution from other intrinsic factors that remain to be investigated. The present study may have implications for dispersal modelling, providing estimates of flight capacity using morphological measurements.

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 score0.074
Threshold uncertainty score0.941

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 head0.012
GPT teacher head0.192
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

Citations18
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueAgricultural and Forest EntomologySame topicForest Insect Ecology and ManagementFrench-language works237,207