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Record W2947602890 · doi:10.1093/ee/nvz051

A Phenology Model for Asian Gypsy Moth Egg Hatch

2019· article· en· W2947602890 on OpenAlexaff
David R. Gray, Melody A. Keena

Bibliographic record

VenueEnvironmental Entomology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsNatural Resources CanadaCanadian Forest Service
Fundersnot available
KeywordsGypsy mothLymantria disparPhenologyBiologyPEST analysisSubspeciesLepidoptera genitaliaRange (aeronautics)EcologyPopulationInvasive speciesAdaptation (eye)ZoologyBotanyDemography

Abstract

fetched live from OpenAlex

Phenology models are useful tools in pest management interventions, biosecurity operations targeting alien invaders, and answering questions regarding the potential for range expansion/shift. The Gypsy Moth Life Stage model (GLS) has been used to predict the invasive range of the North American gypsy moth (Lymantria dispar dispar Linnaeus [Lepidoptera: Erebidae]) in North America and New Zealand. It has been used to examine the role of supra-optimal temperatures in range expansion/stasis/retraction. However, GLS has also been used where the target organism is the Asian subspecies L. d. asiatica Vnukovskij, despite observed differences between the predominant phenotypes of the two subspecies in the temperature requirements for egg hatch and the absence of egg phenology model parameters specific to the Asian phenotype. Here we describe the results of temperature and exposure duration on the timing of Asian gypsy moth egg hatch, and we present phenology model parameters for the Asian phenotype. Sum of squared differences (observed minus predicted day of median egg hatch) was reduced from 7,818 d2 (North American parameters) to 178 d2. Days of simulated median egg hatch differed from the observed days by 0-7 d (x¯=0.2; SD=3.1). The pattern of simulated egg hatch closely mimicked the irregular pattern of observed egg hatch from the temperature regimes of our experiment. Egg hatch is arguably the most important life cycle event in gypsy moth population suppression/eradication interventions and in estimating their potential invasive range. The model parameters described here produce accurate predictions of Asian gypsy moth egg hatch.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.994

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)0.0140.007

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 head0.210
Teacher spread0.203 · 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; both teacher heads agree on what is shown here.

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

Citations6
Published2019
Admission routes1
Has abstractyes

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