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Record W1976072127 · doi:10.5558/tfc82579-4

Evaluation of the push-pull tactic against the mountain pine beetle using verbenone and non-host volatiles in combination with pheromone-baited trees

2006· article· en· W1976072127 on OpenAlexafffundvenue
John H. Borden, Anna L Birmingham, Jennifer S Burleigh

Bibliographic record

VenueThe Forestry Chronicle · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsPrince Albert Grand CouncilRealNetworks (Canada)
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMountain pine beetlePheromoneDendroctonusPinus contortaHorticultureBotanyHost (biology)BiologyEcologyBark beetleCurculionidae

Abstract

fetched live from OpenAlex

Experiments were conducted near Williams Lake and Quesnel, BC in 2003 to evaluate the effectiveness of the anti-aggregation pheromone verbenone and a three-component non-host volatile (NHV) blend (E-2- and Z-3-hexen-1-ol and benzyl alcohol) in deterring attack of lodgepole pines, Pinus contorta var. latifolia Engelmann, by the mountain pine beetle, Dendroctonus ponderosae Hopkins. In 0.16-ha square plots, with a pheromone-baited tree in the centre and 16 release points at 10-m centres, either verbenone (in a polyurethane gel inside plastic membrane pouches, released at ca. 100 mg/day) or the NHVs (released from separate bubble caps at ca. 1.2 mg/day) deterred attack, but efficacy was not increased by combining them. When deployed from 25 release points at 10-m centres in 0.25-ha square plots, verbenone plus NHVs were effective in deterring attack in some (but not all) cases, when compared to attack in a 25-m wide band around the treated zone. In a test of the push-pull tactic, verbenone plus the NHV blend were tested in a 10-replicate experiment with 100, 44.4 or 25 release points/ha at 10-, 15- or 20-m centres, respectively, in a 1-ha square central zone surrounded by a 3-ha, 50-m-wide band containing 12 pheromone-baited lodgepole pines 50 m apart. Other treatments were pheromonebaited trees alone, and an untreated control. In the three push-pull treatments (but not the bait only or control treatments), 28 of 30 replicates had significantly more mass-attacked trees in the pheromone-baited outer 3 ha than in the inner ha treated with verbenone plus NHVs. The percentage of available trees ≥ 17.5 cm diameter at breast height (dbh) that were mass-attacked was < 10% in 5, 4 and 3 of 10 replicates when verbenone plus NHVs were deployed at 10-, 15- and 20-m centres, respectively, and was < 10% in two each of the bait only and control replicates. The mean ratios of newly-attacked green trees in 2003 to red trees killed in 2002 were significantly lower in the inner ha of the 10-m and 15-m centre treatments (2.6 and 2.7, respectively) than 5.9 in the untreated control. Also the pooled percentages of attacked trees that were not mass-attacked were significantly higher in the inner ha of the treatments with centres at 15 m (24.7%) and 10 m (17.6%) than in the other three treatments (all between 12% and 13%). Despite the apparent efficacy in 10-m and 15-m centre treatments, some replicates failed spectacularly. Failure was not significantly related to the incidence of red trees, but was negatively related to density/ha of available trees and positively related to mean dbh. We recommend operational implementation of the push-pull tactic at 10-m or 15-m centres when the density of available lodgepole pines is > 400/ha, the mean dbh is ≤ 25 cm, current attack is ≤ 15%, and the tactic is part of an integrated pest management program that includes sanitation harvesting. Using verbenone alone at 15-m centres would cost $380/ha (CAD), excluding labour. Key words: mountain pine beetle, Dendroctonus ponderosae, lodgepole pine, Pinus contorta var. latifolia, pheromones, semiochemicals, pest management

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.457
Threshold uncertainty score0.996

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)0.0000.000

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 head0.231
Teacher spread0.220 · 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

Citations58
Published2006
Admission routes3
Has abstractyes

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