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Record W2114765564 · doi:10.4039/tce.2013.1

Seasonal dynamics of three coexisting aphid species: implications for estimating population variability

2013· article· en· W2114765564 on OpenAlexaff
Robert J. Lamb, Patricia A. MacKay, Andrei Alyokhin

Bibliographic record

VenueThe Canadian Entomologist · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAbundance (ecology)AphidBiologyMacrosiphum euphorbiaeAphididaeMyzus persicaePopulationEcologyContext (archaeology)HorticultureHomopteraDemographyPEST analysis

Abstract

fetched live from OpenAlex

Abstract Seasonal patterns of abundance and population variability were determined for Macrosiphum euphorbiae (Thomas), Myzus persicae (Sulzer), and Aphis nasturtii (Kaltenbach) (Hemiptera: Aphididae) in potato plots from weekly samples for 28 years. All species showed a single annual peak, but arrived and reached peak abundance at different times. Population variability (PV, a proportion between 0 and 1) for the week of peak abundance was close to that of other sample weeks and mean seasonal abundance. Based on mid-season abundance, PV of 0.76 for M. persicae differed significantly from 0.80 for A. nasturtii , as well as from 0.59 for M. euphorbiae . A weekly time scale for abundance, initiated at an early stage of plant growth, produced slightly different estimates of PV early and late in the season than a scale centred on peak abundance for each species. PV at the time of invasion differed from estimates for the rest of the summer. The annual abundance used to estimate PV was best determined in the context of aphid life history. Nevertheless, PV provided a robust and precise metric for comparing population variability among the three species, regardless of their seasonal patterns of abundance.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.459
Threshold uncertainty score0.521

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)0.0000.000

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 head0.035
GPT teacher head0.249
Teacher spread0.214 · 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

Citations7
Published2013
Admission routes1
Has abstractyes

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