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Record W4406382017 · doi:10.1093/ee/nvae125

Wild bees show local spatial and temporal dynamics in southeastern US blueberry farmscapes

2024· article· en· W4406382017 on OpenAlexaff
Sarah M. Rezende, Svoboda V. Pennisi, Tara D. Gariépy, Marina Querejeta, Michael D. Ulyshen, Jason M. Schmidt

Bibliographic record

VenueEnvironmental Entomology · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsAgriculture and Agri-Food Canada
FundersNatural Resources Conservation ServiceU.S. Department of Agriculture
KeywordsBiologyPollinatorHalictidaeApidaeSpecies richnessEcologyNectarAbundance (ecology)ApoideaHabitatPollinationHymenopteraPollen

Abstract

fetched live from OpenAlex

Wild bee communities are the target of various conservation and ecological restoration programs. Strategic conservation can influence bee communities visiting fields and help mitigate pollinator limitations in fruit production. However, planning compatible conservation strategies and gauging their effectiveness requires understanding how local communities vary across space and time in crops and adjacent semi-natural areas. Here, we assessed the spatiotemporal changes in the composition of wild bee communities in blueberry fields and adjacent forests. In partnership with commercial farms in southeast Georgia, USA, we deployed blue vane traps at the interior and edge of blueberry fields and within adjacent forests of 8 fields, from March to October over 2 yr. We identified 72 wild bee species across 26 genera. The most common were Melissodes communis (Cresson, Hymenoptera: Apidae), Bombus bimaculatus (Cresson, Apidae), Melissodes bimaculatus (Lepeletier), Ceratina floridana (Mitchell, Apidae), Lasioglossum pectorale (Smith, Halictidae), and Lasioglossum nymphale (Smith), which accounted for nearly 60% of the wild bees caught. Bee diversity and richness fluctuated over time, with peaks in all 3 habitat types occurring after the blueberry blooming. Bee abundance in the adjacent forest was relatively constant throughout the season, while in the field interior and edge assemblages, abundance peaked between May and June. We observed dissimilarity in species composition related to month and field location. This difference was explained by fluctuation in the identity and relative abundance of the most abundant species. Together, our study advances foundational knowledge of wild bee community dynamics and species identity in blueberry fields which will help inform and prioritize conservation practices.

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 score0.080
Threshold uncertainty score0.972

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 head0.011
GPT teacher head0.185
Teacher spread0.173 · 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
Published2024
Admission routes1
Has abstractyes

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