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Record W4399550132 · doi:10.1111/jen.13262

On the deduction and quantification of irruptive dynamics in mountain pine beetle population and proxy data

2024· article· en· W4399550132 on OpenAlexaff
Barry J. Cooke, Chris J.K. MacQuarrie, Allan L. Carroll

Bibliographic record

VenueJournal of Applied Entomology · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsNatural Resources CanadaUniversity of British ColumbiaCanadian Forest Service
Fundersnot available
KeywordsAllee effectPopulationProxy (statistics)Population densityBiologyAerial surveyRange (aeronautics)Sampling (signal processing)EcologyStatisticsGeographyDemographyCartographyMathematicsComputer science

Abstract

fetched live from OpenAlex

Abstract In attempting to develop a coherent description of the irruptive dynamics of mountain pine beetle (MPB) in North America, we examined a range of cases where authors described the dependency of intrinsic population growth rates on population attack levels. In some cases, detailed population data were used, but in most cases, investigators relied on operational aerial detection survey data. We found that study conclusions varied significantly depending on the type of data analysed and the spatial and temporal dimensions of the monitoring program. The ability to detect an intrinsic Allee effect (i.e., positive density‐dependent growth for low and rising population densities) depended on the type and the intensity of the sampling effort and the extent of sampling in space and time. Consequently, not all studies were able to quantify the irruption threshold (i.e., the population density at which endemic populations may transition towards the epidemic state). Notably, in every study where an Allee effect was demonstrated, investigators also identified at least one extrinsic environmental factor (e.g., winter weather, summer drought, microclimatic effect) that was regulating its strength. Our results suggest that population surveys conducted from the ground are a necessary complement to aerial survey data if the goal is to make inferences about the irruptive potential for MPB populations and the role of environmental factors in shaping that irruptive potential.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
Threshold uncertainty score0.117

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 head0.016
GPT teacher head0.266
Teacher spread0.250 · 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 designTheoretical or conceptual
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

Citations3
Published2024
Admission routes1
Has abstractyes

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