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Record W4399716336 · doi:10.26786/1920-7603(2024)791

Pollinator effectiveness and pollination dependency of bilberry (Vaccinium myrtillus) in Swedish hemi-boreal forests

2024· article· en· W4399716336 on OpenAlexvenueno aff
Océane Bartholomée, Jacob Björnberg, Henrik G. Smith, Liam Kendall

Bibliographic record

VenueJournal of Pollination Ecology · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
FundersVetenskapsrådet
KeywordsVaccinium myrtillusBilberryPollinatorTaigaPollinationPollenDependency (UML)BiologyBorealEcologyVacciniumBotanyEngineering

Abstract

fetched live from OpenAlex

Intensification of forest management to increase production of biomass has resulted in considerable habitat degradation with negative impacts on insect biodiversity, including beneficial insect groups such as pollinators. Yet, little is known about how reliant forest understory plants, such as bilberry (Vaccinium myrtillus), are on insect pollinators for reproduction. Here, we quantified the structure of the bilberry flower visitor community, compared the pollination effectiveness of the most common pollinators, and experimentally quantified bilberry pollination dependency. The bilberry pollinator community was comprised of several bee and hoverfly taxa. Bumblebees were the most important pollinators due to their high abundance and pollination effectiveness. Other bees, in particular, Andrena spp., and to a smaller extent, hoverflies, were also effective pollinators. Furthermore, bilberry was strongly pollen-limited, with only 40% of open-pollinated flowers setting fruit. Bilberry supports a diverse flower visitor community within hemi-boreal forests, for which it is highly dependent for reproduction. Given the ecological and cultural value of bilberry, the importance of insect pollinators for understory plants should be considered within forest management strategies.

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)0.001
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 score0.146
Threshold uncertainty score0.249

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.016
GPT teacher head0.245
Teacher spread0.229 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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