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Mountain Pine Beetle Epidemic: An Interplay of Terpenoids in Host Defense and Insect Pheromones

2022· review· en· W4210902810 on OpenAlexafffund
Christine Chiu, Jöerg Bohlmann

Bibliographic record

VenueAnnual Review of Plant Biology · 2022
Typereview
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaGenome AlbertaGenome British ColumbiaGenome Canada
KeywordsTerpenoidHost (biology)OleoresinBiologyDendroctonusInsectBark beetleBark (sound)Chemical ecologyBotanyDiterpeneGreen leaf volatilesPheromoneChemical defenseAbietic acidEcologyHerbivoreResin acidChemistryBiochemistry

Abstract

fetched live from OpenAlex

The mountain pine beetle epidemic has highlighted the complex interactions of bark beetles with conifer host defenses. In these interactions, oleoresin terpenoids and volatiles, produced and released by the host tree, can be both harmful and beneficial to the beetle's success in colonizing a tree and completing its life cycle. The insect spends almost its entire life, from egg to adult, within the bark and phloem of a pine host, exposed to large quantities of complex mixtures of oleoresin terpenoids. Conifer oleoresin comprises mostly monoterpenes and diterpene resin acids as well as many different sesquiterpenes. It functions as a major chemical and physical defense system. However, the insect has evolved host colonization behavior and enzymes for terpenoid metabolism and detoxification that allow it to overcome some of the terpenoid defenses and, importantly, to co-opt pine monoterpenes as cues for host search and as a precursor for its own pheromone system. The insect-associated microbiome also plays a role in the metabolism of conifer terpenoids.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.025
GPT teacher head0.316
Teacher spread0.291 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations29
Published2022
Admission routes2
Has abstractyes

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