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Record W2515396391 · doi:10.4039/tce.2016.5

Population dynamics and epidemiology of four species of<i>Dendroctonus</i>(Coleoptera: Curculionidae): 100 years since J.M. Swaine

2016· article· en· W2515396391 on OpenAlexafffundabout
Brian H. Aukema, Fraser R. McKee, Debra L. Wytrykush, Allan L. Carroll

Bibliographic record

VenueThe Canadian Entomologist · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsUniversity of British Columbia
FundersCanadian Forest ServiceU.S. Forest ServiceUniversity of Minnesota
KeywordsDendroctonusCurculionidaeBark beetlePopulationBark (sound)EcologyPicea engelmanniiLarchSalamandraMountain pine beetleGeographyBiologyPinus contortaDemographyLarvaSociology

Abstract

fetched live from OpenAlex

Abstract Almost 100 years have passed since J.M. Swaine, the assistant entomologist in charge of Forest Insect Investigations, wrote, “Canadian bark-beetles: a preliminary classification, with an account of the habits and means of control”. The goal was to “put into the hands of practical foresters information of inestimable practical value… to prevent the continued loss of timber now being destroyed” by “the most insidious enemies of the forest”. In this paper, we celebrate Swaine’s pioneering work by summarising the foundational aspects of his early treatise of 1918: the “general habits” of bark beetles, classifications of their behaviour, causes of population increase, and mitigation tactics. In the founding text, Swaine identified all majorDendroctonusErichson (Coleoptera: Curculionidae) bark beetles found in Canada, although details on life histories were scarce. We summarise current knowledge of the life histories and population dynamics of the spruce beetle,D.rufipennisKirby; the Douglas-fir beetle,D. pseudotsugaeHopkins; the eastern larch beetle,D. simplex; and address the current range expansion of mountain pine beetle,D. ponderosaeHopkins. We review how aspects of global change, such as invasive species, have altered the population dynamics of certain bark beetles. Finally, we conclude with lessons from two of the many past contributors to bark beetle ecology in Canada, J.M. Swaine and H.A. Richmond.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.104
Threshold uncertainty score0.206

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.236
Teacher spread0.215 · 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

Citations26
Published2016
Admission routes3
Has abstractyes

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