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Record W2179267854 · doi:10.1603/0022-0493-99.2.443

Commercial Bumble Bee <I>Bombus impatiens</I> (Hymenoptera: Apidae) as a Pollinator in Lowbush Blueberry (Ericale: Ericaceae) Fields

2006· article· en· W2179267854 on OpenAlexaffabout
Ève-Catherine Desjardins, D. de Oliveira

Bibliographic record

VenueJournal of Economic Entomology · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsBiologyBerryImpatiensEricaceaeVacciniumHorticultureBotanyPollinatorPollinationApidaeApoideaPollenHymenopteraCultivar

Abstract

fetched live from OpenAlex

Here, we evaluate the potential of the bumble bee Bombus impatiens Cresson, obtained from commercial colonies, as a pollen vector for lowbush blueberry, Vaccinium augustifolium Aiton. We wanted to gain insight into the relationships between pollination by introduced bumble bees, the categories of seeds produced, and the weight and the maturity of the blueberries. The effect of B. impatiens foraging in blueberry stands was measured quantitatively through fruit set and seed set analysis. We created a density gradient of B. impatiens by clustering 72 small hives at the southern extremity of blueberry fields located in Girardville (49 degrees 00' N, 72 degrees 33' W), Quebec, Canada. Observers recorded plant and insect data in 52 plots of 1 by 10 m, distributed at distances ranging from 25 to 1,500 m from the hives. From these data, we evaluated the fruit set rate, the weight and maturity of the berries, and the number of seed structures per berry, including true seeds of large, medium, and small size, pseudo-seeds, and ovules. Positive correlations were found between the density of B. impatiens and fruit set as well as the number of large seeds per berry. Large seeds influenced the weight and maturity of berries. B. impatiens acted as a "near-nest central forager" and increased fruit set and seed production up to 100 and 150 m respectively, from the hives.

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 score0.280
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.018
GPT teacher head0.226
Teacher spread0.207 · 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

Citations45
Published2006
Admission routes2
Has abstractyes

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