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Record W2604563406

Analyses of environmental factors for the persistence of Myrmica rubra (Hymenoptera: Formicidae) in green spaces of the Greater Toronto Area and applications of ecological niche/species distribution models

2014· article· en· W2604563406 on OpenAlexaboutno aff
Naokazu Ito

Bibliographic record

VenueYork University Digital Library (York University) · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
Fundersnot available
KeywordsHymenopteraEcologyPersistence (discontinuity)NicheDistribution (mathematics)GeographyBiologyMathematicsEngineering
DOInot available

Abstract

fetched live from OpenAlex

Palearctic native European fire ant Myrmica rubra have been sighted frequently across the Greater Toronto Area (GTA) in recent years. Although their populations in the GTA are fragmented, this non native invasive ant species has potential to expand well beyond their current habitats. In order to ascertain the ecological conditions for the persistence of M. rubra, an extensive study was conducted at conservation areas across the GTA.
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\nBased on some of the ecological factors required for M. rubra, ecological niche models (ENMs)/species distribution models (SDMs) were constructed on 3 different scales using occurrence data for better mitigation and prevention of this invasive species and to predict their future potential geographic distributions in the face of climate change.
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\nFrom an array of regression analyses, it was found that soil surface moisture level (p = 0.005, odds ratio = 1.04), soil surface temperature (p = 0.001, Odds ratio = 1.14), and altitude (p = 0.001, odds ratio = 0.99) are essential for M. rubra to persist. It was also found that M. rubra does displace other ant species as well as arthropods, and this is in agreement with the results from other publications. Based on the ENMs/SDMs, this non native invasive species has potential to spread beyond the current distribution range, and susceptible areas should be monitored for future invasion and expansion.

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 score0.074
Threshold uncertainty score0.658

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.184
Teacher spread0.150 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

Explore more

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