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Record W2949180046 · doi:10.3390/f10060503

Influence of a Foliar Endophyte and Budburst Phenology on Survival of Wild and Laboratory-Reared Eastern Spruce Budworm, Choristoneura fumiferana on White Spruce (Picea glauca)

2019· article· en· W2949180046 on OpenAlexaff
Dan T. Quiring, G. W. Adams, Leah Flaherty, Andrew McCartney, J. David Miller, Sara Edwards

Bibliographic record

VenueForests · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and fungal interactions
Canadian institutionsCarleton UniversityJ. D. Irving (Canada)Innovation MaritimeUniversity of New Brunswick
Fundersnot available
KeywordsSpruce budwormChoristoneura fumiferanaBiologyEndophytePopulationTortricidaeBotanyPEST analysisAbies balsameaAgronomyBalsam

Abstract

fetched live from OpenAlex

A manipulative field study was carried out to determine whether the foliar endophyte fungus, Phialocephala scopiformis DAOM 229536, decreased the performance of eastern spruce budworm, Choristoneura fumiferana larvae developing on white spruce trees. Overwintered second-instar budworm larvae from a laboratory colony or from a wild population were placed on endophyte positive or negative trees one or two weeks before budburst. The presence of the endophyte in the needles reduced the survival of C. fumiferana from both a wild population and a laboratory colony. Survival for budworm juveniles up to pupation and to adult emergence was 13% and 17% lower, respectively, on endophyte positive trees. The endophyte did not influence the size or sex of survivors and budworm survival was not influenced by any two- or three-way interactions. Budworm survival was higher for wild than for laboratory-reared budworm and for budworm placed on trees a week before budburst. This may be the first field study to demonstrate the efficacy of an endophytic fungus against wild individuals of a major forest insect pest. The efficacy of the endophyte at low larval densities suggests that it could be a useful tactic to limit spruce budworm population growth in the context of an early intervention strategy.

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 score0.159
Threshold uncertainty score0.272

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 head0.011
GPT teacher head0.220
Teacher spread0.209 · 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

Citations10
Published2019
Admission routes1
Has abstractyes

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