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Record W4410029574 · doi:10.1111/een.13449

Annual variation across functional traits: The effects of precipitation and land use on four wild bee species

2025· article· en· W4410029574 on OpenAlexafffundabout
Katherine D. Chau, Bita Ghafarifarokhzad, Anthony C. Ayers, Sandra M. Rehan

Bibliographic record

VenueEcological Entomology · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of CanadaMitacsYork University
KeywordsBiologyVariation (astronomy)EcologyPrecipitationZoology

Abstract

fetched live from OpenAlex

Abstract Understanding the impacts of urbanization and climate change on organisms has become increasingly critical in ecology and conservation as these anthropogenic stressors negatively impact wildlife biodiversity, especially pollinators such as bees. We analysed the demographic (abundance and sex ratio) and morphological (body size and wing wear) responses to urbanization and inter‐annual variation of four common wild bee species across an urban gradient in Toronto, Canada. We observed more significant shifts in bee demography with inter‐annual precipitation variation than with urbanization, with diverse patterns depending on species. The drier active season saw a decrease in abundance for Agapostemon virescens and Ceratina calcarata , whereas Bombus impatiens and Xenoglossa pruinosa increased when compared with the previous year. Wetter active seasons resulted in smaller body sizes and greater wing wear for all bee species examined. For larger bees ( A. virescens , B. impatiens and X. pruinosa ), increasing urbanization resulted in significantly larger females only for A. virescens , whereas foraging effort reduced as urban intensity increased. The small, cavity‐nesting bee, C. calcarata exhibited reduced body sizes and increased foraging effort with increasing urbanization. Moderate urbanization better supported most wild bee assemblages and morphology, suggesting that moderate land use intensity provides green spaces and adequate resources for these bee species.

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)0.001
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 score0.374
Threshold uncertainty score0.160

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.030
GPT teacher head0.228
Teacher spread0.198 · 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

Citations1
Published2025
Admission routes3
Has abstractyes

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