Evidence map›Paper›PMID 28591213›Full record

ArticlePloS one2017

Flight of the bumble bee: Buzzes predict pollination services.

Nicole E Miller-Struttmann, David Heise, Johannes Schul, Jennifer C Geib, Candace Galen

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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  4. Science Literacy: Using Multimodal STEM Text Sets to Help Students With Disabilities Engage in Argumentation.Learning disability quarterly : journal of the Division for Children with Learning Disabilities · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Nicole E Miller-StruttmannBiological Sciences Department, Webster University, St. Louis, Missouri, United States of America.ORCID http://orcid.org/0000-0002-4799-4802
David HeiseDepartment of Computer Science, Technology & Mathematics, Lincoln University, Jefferson City, Missouri, United States of America.
Johannes SchulDivision of Biological Sciences, University of Missouri, Columbia, Missouri, United States of America.
Jennifer C GeibDepartment of Biology, Appalachian State University, Boone, North Carolina, United States of America.
Candace GalenDivision of Biological Sciences, University of Missouri, Columbia, Missouri, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple interacting factors drive recent declines in wild and managed bees, threatening their pollination services. Widespread and intensive monitoring could lead to more effective management of wild and managed bees. However, tracking their dynamic populations is costly. We tested the effectiveness of an inexpensive, noninvasive and passive acoustic survey technique for monitoring bumble bee behavior and pollination services. First, we assessed the relationship between the first harmonic of the flight buzz (characteristic frequency) and pollinator functional traits that influence pollination success using flight cage experiments and a literature search. We analyzed passive acoustic survey data from three locations on Pennsylvania Mountain, Colorado to estimate bumble bee activity. We developed an algorithm based on Computational Auditory Scene Analysis that identified and quantified the number of buzzes recorded in each location. We then compared visual and acoustic estimates of bumble bee activity. Using pollinator exclusion experiments, we tested the power of buzz density to predict pollination services at the landscape scale for two bumble bee pollinated alpine forbs (Trifolium dasyphyllum and T. parryi). We found that the characteristic frequency was correlated with traits known to affect pollination efficacy, explaining 30-52% of variation in body size and tongue length. Buzz density was highly correlated with visual estimates of bumble bee density (r = 0.97), indicating that acoustic signals are predictive of bumble bee activity. Buzz density predicted seed set in two alpine forbs when bumble bees were permitted access to the flowers, but not when they were excluded from visiting. Our results indicate that acoustic signatures of flight can be deciphered to monitor bee activity and pollination services to bumble bee pollinated plants. We propose that applications of this technique could assist scientists and farmers in rapidly detecting and responding to bee population declines.

Indexed as

AnimalsBeesColoradoEcosystemFlight, AnimalFlowersPollinationTrifoliumVocalization, Animal

Identifiers

PMID28591213
PMCPMC5462477

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.