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Record W2945141121 · doi:10.3390/f10050448

Positive Results of an Early Intervention Strategy to Suppress a Spruce Budworm Outbreak after Five Years of Trials

2019· article· en· W2945141121 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueForests · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsCanadian Forest ServiceForest Protection Limited (Canada)Government of New BrunswickUniversity of New Brunswick
FundersNatural Resources CanadaAtlantic Canada Opportunities Agency
KeywordsSpruce budwormAbies balsameaChoristoneura fumiferanaPopulationBalsamOverwinteringContext (archaeology)ForestryBiologyGeographyEcologyMedicineHorticultureLarvaEnvironmental healthTortricidae

Abstract

fetched live from OpenAlex

Spruce budworm (Choristoneura fumiferana Clem.; SBW) outbreaks are one of the dominant natural disturbances in North America, having killed balsam fir (Abies balsamea (L.) Mill.) and spruce (Picea sp.) trees over tens of millions of hectares. Responses to past SBW outbreaks have included the aerial application of insecticides to limit defoliation and keep trees alive, salvage harvesting of dead and dying trees, or doing nothing and accepting the resulting timber losses. We tested a new ‘early intervention strategy’ (EIS) focused on suppressing rising SBW populations before major defoliation occurs, from 2014 to 2018 in New Brunswick, Canada. The EIS approach included: (1) intensive monitoring of overwintering SBW to detect ‘hot spots’ of low but rising populations; (2) targeted insecticide treatment to prevent spread; and (3) proactive public communications and engagement on project activities and results. This is the first attempt of area-wide (all areas within the jurisdiction of the province of New Brunswick) management of a native forest insect population. The project was conducted by a consortium of government, forest industry, researchers, and other partners. We developed a treatment priority and blocking model to optimize planning and efficacy of EIS SBW insecticide treatment programs. Following 5 years of over 420,000 ha of EIS treatments of low but increasing SBW populations, second instar larvae (L2) SBW levels across northern New Brunswick were found to be considerably lower than populations in adjacent Québec. Treatments increased from 4500 ha in 2014, to 56,600 ha in 2016, and to 199,000 ha in 2018. SBW populations in blocks treated with Bacillus thuringiensis or tebufenozide insecticide were consistently reduced, and generally did not require treatment in the subsequent year. Areas requiring treatment increased up to 2018, but SBW L2 populations showed over 90% reductions in that year. Although this may be a temporary annual decline in SBW population increases, it is counter to continued increases in Québec. Following 5 years of tests, the EIS appears to be effective in reducing the SBW outbreak.

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.

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)0.001
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 score0.229
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.010
GPT teacher head0.265
Teacher spread0.254 · 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