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Record W2015460338 · doi:10.5558/tfc86766-6

The ecological interaction of the mountain pine beetle and jack pine budworm in the boreal forest

2010· article· en· W2015460338 on OpenAlexafffundvenueabout
Lindsay J. Colgan, Nadir Erbilgin

Bibliographic record

VenueThe Forestry Chronicle · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsMountain pine beetleDendroctonusEcologyPinus contortaTaigaSpruce budwormBiologyRange (aeronautics)SnagBark beetleHabitatLarvaTortricidaeBark (sound)

Abstract

fetched live from OpenAlex

As climate change facilitates the range and host expansion of insect species into new ecosystems, the development of newstrategies for managing and preventing biological invasion is receiving considerable interest. In recent years, the range ofthe mountain pine beetle (Dendroctonus ponderosae Hopkins) has expanded from lodgepole pine-dominated forests eastof the Rocky Mountains into lodgepole x jack pine hybrid forest of western Alberta, and may soon invade jack pine forestsof the boreal. Our understanding of factors contributing colonization of jack pine by mountain pine beetle is far fromcomplete and several factors may limit its spread in these forests, including tree resistance and competitors. Among these,the jack pine budworm (Choristoneura pinus pinus Freeman) is one of the most important insect enemies of jack pine andan outbreak defoliator that potentially weakens jack pine trees, which may make them more susceptible to MPB attacks.To develop effective management strategies in the face of the short-run impacts of climate change, we need an in-depthunderstanding of factors influencing establishment and survival of the beetle in jack pine forests.Key words: Choristoneura pinus pinus, Dendroctonus ponderosae, jack pine, range expansion, invasion biology, climatechange in the boreal forest, conifer-mediated interactions, tree induced defences, tripartite interactions

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.232
Teacher spread0.224 · 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

Citations14
Published2010
Admission routes4
Has abstractyes

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