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Spatial synchrony of the two‐year cycle budworm outbreaks in central British Columbia, Canada

2003· article· en· W2169669287 on OpenAlexfundaboutno aff
Qi‐Bin Zhang, René I. Alfaro

Bibliographic record

VenueOikos · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
FundersMinistry of Forests, Lands and Natural Resource Operations
KeywordsOutbreakSpruce budwormGeographyEcologyAbies balsameaSpatial ecologyCanopyBiologyLepidoptera genitaliaForestryBalsamTortricidaeBotany

Abstract

fetched live from OpenAlex

Outbreaks of forest defoliating insects are usually synchronized over a large spatial scale. Observed records of past outbreaks are usually short and incomplete, therefore long proxy data are useful for better understanding of the spatial synchrony. In this study, we developed tree‐ring proxy records of two‐year cycle spruce budworm ( Choristoneura biennis Freeman) outbreaks in central British Columbia, Canada, and examined the spatial patterns of past outbreaks. This budworm is a major defoliating insect of the interior spruce ( Picea engelmannii Parry× P. glauca Moench) and subalpine fir ( Abies lasiocarpa [Hook.] Nutt.) forests in the Prince George Region of British Columbia. Four outbreaks occurred in relatively close synchrony over the entire region in the period 1880–1999, however, the initiation year, the intensity and extent of outbreaks varied spatially and from one outbreak to another. In some instances, the occurrence of outbreaks was restricted to only one area. The general synchrony of outbreaks suggested that a large‐scale extrinsic factor, such as weather, was at play. However, the imperfect synchrony of outbreaks suggested that local stand characteristics, such as canopy structure, composition of tree species and host plant quality, probably played a major role in preconditioning outbreaks. Dispersal might play a role in synchronizing outbreaks, but the extent to which it contributed to the synchrony was limited in this mountainous region.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.997

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)0.0040.000

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 head0.004
GPT teacher head0.188
Teacher spread0.184 · 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.

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

Citations39
Published2003
Admission routes2
Has abstractyes

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