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Record W2030274869 · doi:10.1139/x07-021

Dendrochronological reconstruction of forest tent caterpillar outbreaks in time and space, western Manitoba, Canada

2007· article· en· W2030274869 on OpenAlexafffundvenueabout
Alanna Sutton, Jacques Tardif

Bibliographic record

VenueCanadian Journal of Forest Research · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsUniversity of Winnipeg
FundersCommon FundCanada Research ChairsManitoba Hydro
KeywordsOutbreakDendrochronologyGeographyForestryYellow birchStand developmentBalsamEcologyBiologyArchaeologyBotanyMaple

Abstract

fetched live from OpenAlex

A tree-ring reconstruction of forest tent caterpillar ( Malacosoma disstria Hubner) outbreaks was conducted in the Duck Mountain Provincial Forest. Trembling aspen ( Populus tremuloides Michx.), balsam poplar ( Populus balsamifera L.), and paper birch ( Betula papyrifera Marsh.) tree-ring chronologies were used to identify periods of outbreaks from approximately 1800 to 2002. The impacts of the major forest tent caterpillar outbreaks of the 20th century were compared among four stand types and two age classes. The presence of white rings and growth suppression were used to identify three important outbreak periods, 1939–1948, 1961–1965, and 1982–1985, with another large-scale outbreak suspected during the 1870s. A roughly 20-year interval was observed between major outbreaks. Few differences were found between stand types, except during the 1960s, when mixed stands with jack pine ( Pinus banksiana Lamb.) registered more growth suppression and white rings. In general, the outbreak signal in the younger sites was variable. The importance of utilizing white rings and growth suppression data together is discussed. The major outbreaks of the 20th century generally started in the north of the Duck Mountain Provincial Forest. The technique was successful at identifying forest tent caterpillar outbreaks during the 20th and late 19th centuries, when no historical surveys were available.

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)0.002
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 score0.049
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.034
GPT teacher head0.257
Teacher spread0.223 · 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

Citations32
Published2007
Admission routes4
Has abstractyes

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