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Record W4406885013 · doi:10.1139/cjfr-2024-0303

Comparing outbreak regimes of western spruce budworm at low- and high-elevation sites in Idaho using dendrochronology

2025· article· en· W4406885013 on OpenAlexvenueno aff
Ian Woodruff, Jeffrey A. Hicke, Robert A. Andrus

Bibliographic record

VenueCanadian Journal of Forest Research · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsSpruce budwormDendrochronologyForestryElevation (ballistics)Choristoneura fumiferanaOutbreakAbies balsameaGeographyDendroclimatologyPhysical geographyTortricidaeEnvironmental scienceEcologyLepidoptera genitaliaBalsamBiologyArchaeologyBotany

Abstract

fetched live from OpenAlex

The western spruce budworm ( Choristoneura freemani; WSB) is the most damaging defoliating insect in the Pacific Northwest. Despite general knowledge about climate influences on WSB, few studies have evaluated how outbreak dynamics are affected by local variability in climate. We used dendrochronological techniques to reconstruct WSB activity in Douglas-firs ( Pseudotsuga menziesii) at three low- and three high-elevation sites (representing climate variability) in Idaho, USA. We first tested different thresholds used in an established algorithm for determining WSB activity and found substantial variability in outbreak metrics. We then compared the timing of our reconstructed outbreaks with activity reported by aerial surveys, historical reports, and other reconstructions. Some agreement occurred in non-outbreak periods, but significant disagreement existed in the timing of outbreaks. Our assessment of topo-climatic influences on reconstructed WSB activity revealed that defoliation frequency was lower at low-elevation sites, with some inconsistencies depending on metric and threshold choice. Finally, we examined the influence of interannual variability of drought on outbreak initiation, finding no consistent effects. Our results reveal sensitivity to the choice of threshold of the reconstruction algorithm and suggest that more investigation is needed to better understand the role of climate, given future conditions that will likely be warmer and drier.

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 score0.065
Threshold uncertainty score0.129

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)0.0000.000

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 head0.032
GPT teacher head0.295
Teacher spread0.264 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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