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Record W2521529852 · doi:10.1093/ee/nvw121

Flight Period of Mountain Pine Beetle (Coleoptera: Curculionidae) in its Recently Expanded Range

2016· article· en· W2521529852 on OpenAlexafffundabout
Katherine P. Bleiker, Brian H. Van Hezewijk

Bibliographic record

VenueEnvironmental Entomology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsNatural Resources CanadaCanadian Forest Service
FundersNatural Resources CanadaMinistry of Forests, Lands and Natural Resource Operations
KeywordsCurculionidaeMountain pine beetleRange (aeronautics)DendroctonusBiological dispersalBiologyPhenologyLatitudeBark beetleEcologyPeriod (music)Pheromone trapGeographyPheromoneDemography

Abstract

fetched live from OpenAlex

The ability to predict key phenological events, such as the timing of flight periods, is useful for the monitoring and management of insect pests. We used empirical data to describe the flight period of mountain pine beetle, Dendroctonus ponderosae Hopkins, in its recently expanded range east of the Rocky Mountains in Canada and developed a degree-day model based on the number of trapped beetles. Data were collected over four degrees of latitude and six years. The main flight period, when the middle 70% of the total number of beetles were caught, started during the second or third week of July, lasted 26 d, and peaked within 2 wk of starting. The best model accounted for 89% of the variation in the data. Mountain pine beetle's flight tended to start later and be more contracted at higher latitudes. The synchrony of mountain pine beetle's flight period in the expanded range appears to be comparable to the limited reports from the historic range, although it may start earlier. This suggests that conditions in the new range are suitable for a coordinated dispersal flight, which is critical for the beetle's strategy of overwhelming tree defenses by attacking en masse. Forest managers can use the model to support operational decisions, e.g., when to impose hauling restrictions to reduce the risk of spread through the transport of infested material, or the time frame for control programs. Understanding the flight period may also improve our ability to assess the response of mountain pine beetle to novel and changing climates in the future.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.999

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)0.0200.002

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 head0.007
GPT teacher head0.210
Teacher spread0.203 · 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; both teacher heads agree on what is shown here.

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

Citations16
Published2016
Admission routes3
Has abstractyes

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