Dataset Information

Analyzing the Dietary Diary of Bumble Bee.

ABSTRACT: Bumble bees are important crop pollinators and provide important pollination services to their respective ecosystems. Their pollen diet and thus food preferences can be characterized through nucleic acid sequence analysis. We present ITS2 amplicon sequence data from pollen collected by bumble bees. The pollen was collected from six different bumble bee colonies that were placed in independent agricultural landscapes. We compared next-generation (Illumina), i.e., short-read, and third-generation (Nanopore), i.e., MinION, sequencing techniques. MinION data were preprocessed using traditional and Nanopore specific tools for comparative analysis and were evaluated in comparison to short-read sequence data with conventional processing. Based on the results, the dietary diary of bumble bee in the studied landscapes can be identified. It is known that short reads generated by next-generation sequencers have the advantage of higher quality scores while Nanopore yields longer read lengths. We show that assignments to taxonomic units yield comparable results when querying against an ITS2-specific sequence database. Thus, lower sequence quality is compensated by longer read lengths. However, the Nanopore technology is improving in terms of data quality, much cheaper, and suitable for portable applications. With respect to the studied agricultural landscapes we found that bumble bees require higher plant diversity than only crops to fulfill their foraging requirements.

SUBMITTER: Leidenfrost RM

PROVIDER: S-EPMC7109327 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Analyzing the Dietary Diary of Bumble Bee.

Leidenfrost Robert M RM Bänsch Svenja S Prudnikow Lisa L Brenig Bertram B Westphal Catrin C Wünschiers Röbbe R

Frontiers in plant science 20200325

Bumble bees are important crop pollinators and provide important pollination services to their respective ecosystems. Their pollen diet and thus food preferences can be characterized through nucleic acid sequence analysis. We present ITS2 amplicon sequence data from pollen collected by bumble bees. The pollen was collected from six different bumble bee colonies that were placed in independent agricultural landscapes. We compared next-generation (Illumina), i.e., short-read, and third-generation ...[more]

PMID: 32269580

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Project description: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.

Dataset Information

Analyzing the Dietary Diary of Bumble Bee.

Publications

Analyzing the Dietary Diary of Bumble Bee.

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