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Record W2412082700 · doi:10.1111/nrm.12123

A periodic matrix population model for monarch butterflies

2017· article· en· W2412082700 on OpenAlexaboutno aff
Eric Hunt, Anthony Tongen

Bibliographic record

VenueNatural Resource Modeling · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
FundersDivision of Mathematical SciencesUS-UK Fulbright CommissionJames Madison UniversityNational Science Foundation
KeywordsMonarch butterflyDanausButterflyGeographyPopulationDeforestation (computer science)Term (time)EcologyDemographyBiologyLepidoptera genitalia

Abstract

fetched live from OpenAlex

Abstract The migration pattern of the eastern monarch butterfly (Danaus plexippus) consists of a sequence of generations of butterflies that originate in Mexico each spring, travel as far north as Southern Canada, and ultimately return to the original location in Mexico the following fall. Estimates of monarch populations in the Oyamel firs in Mexico have caused concern within the scientific community about the long‐term stability of this phenomenon. We use periodic population matrices to model the life cycle of the eastern monarch butterfly and find that, under this linear model, this migration is not currently at risk. We extend the model to address the three primary obstacles for the long‐term survival of this migratory pattern: deforestation in Mexico, increased extreme weather patterns, and milkweed decline. Incorporating these obstacles into the model shows that there is a definite need to take action to alleviate the aforementioned obstacles.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.093
GPT teacher head0.290
Teacher spread0.197 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations7
Published2017
Admission routes1
Has abstractyes

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