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Record W1500185615 · doi:10.22621/cfn.v128i2.1580

Activity and diet of bats in conventional versus organic apple orchards in southern Michigan

2014· article· en· W1500185615 on OpenAlexvenueno aff
Brenna L. Long, Allen Kurta

Bibliographic record

VenueThe Canadian Field-Naturalist · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsnot available
FundersEastern Michigan UniversityOrganic Farming Research Foundation
KeywordsEptesicus fuscusInsectivoreBiologyForagingOrchardEcologyMyotis lucifugusPredation

Abstract

fetched live from OpenAlex

Organic farming practices have been suggested as a conservation strategy that can provide productive foraging sites for insectivorous bats in agricultural areas. We tested the hypothesis that the number and diversity of insects captured and the resulting activity and diet of bats would differ between organic and conventional apple orchards. During the summer of 2009 and 2010, we captured 131 Big Brown Bats (Eptesicus fuscus) and five Eastern Red Bats (Lasiurus borealis) by mist netting in four organic and four conventional orchards in Michigan. Acoustic monitoring revealed that most calls (59%) were produced by Big Brown Bats, followed by Hoary Bats (L. cinereus), Eastern Red Bats, and unidentified species of Myotis. Most insects (96%) captured in light traps were Coleoptera, Diptera, Hemiptera, Lepidoptera, and Trichoptera; fecal analysis indicated that Coleoptera dominated the diet of Big Brown Bats (79% by volume), followed by Diptera (14%). There were no significant differences between organic and conventional orchards in number of insects captured with light traps, bats captured with mist nets, acoustic recordings of bats, or proportion of Coleoptera and Diptera consumed by the bats. However, the taxonomic composition of captured insects and acoustic recordings was not homogenous among orchards in either group, suggesting that factors other than farming practices were more important in determining which insects and bats were found in the small orchards typical of southern Michigan.

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 score0.798
Threshold uncertainty score0.811

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 head0.017
GPT teacher head0.213
Teacher spread0.196 · 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

Citations13
Published2014
Admission routes1
Has abstractyes

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