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Molecular analysis of honey bee foraging ecology

Richardson, Rodney Trey
http://orcid.org/0000-0002-4443-1705
http://rave.ohiolink.edu/etdc/view?acc_num=osu1543239052414523

Abstract Details

2018, Doctor of Philosophy, Ohio State University, Entomology.
While numerous factors currently impact the health of honey bees and other pollinating Hymenoptera, poor floral resource availability due to habitat loss and land conversion is thought to be important. This issue is particularly salient in the upper Midwest, a location which harbors approximately 60 percent of the US honey bee colonies each summer for honey production. This region has experienced a dramatic expansion in the area devoted to crop production over the past decade. Consequently, understanding how changes to landscape composition affect the diversity, quality and quantity of available floral resources has become an important research goal. Here, I developed molecular methods for the identification of bee-collected pollen by adapting and improving upon the existing amplicon sequencing infrastructure used for microbial community ecology. In thoroughly benchmarking our procedures, I show that a simple and cost-effective three-step PCR-based library preparation protocol in combination with Metaxa2-based hierarchical classification yields an accurate and highly quantitative pollen metabarcoding approach when applied across multiple plant markers. In Chapter 1, I conducted one of the first ever proof-of-concept studies applying amplicon sequencing, or metabarcoding, to the identification of bee-collected pollen. In this work, we used rudimentary laboratory and bioinformatic methods to apply the method to a single nuclear marker, ITS2. In doing so, we found the method to be highly inaccurate with respect to quantitative inference of the relative abundances of different plant taxa represented within our sample. Thus, in Chapter 2 I used the same methods and turned my attention to two alternative chloroplast markers, matK and rbcL, in addition to ITS2. In this study, I found that the chloroplast markers were more useful for quantification of pollen abundance relative to ITS2. With an improved understanding of the behavior of different plant markers, I began optimizing the bioinformatic and laboratory methods used for pollen metabarcoding. In Chapter 3, I conducted in silico cross-validation analyses using three prominent hierarchical amplicon sequence classifiers. Testing the classifiers on data from all five commonly used plant barcoding markers, I found wide variance in the accuracy and sensitivity of the classifiers evaluated, suggesting that the choice of classifier and the optimization of classification procedures is an important area for future methods development. In Chapter 4, I expand on evaluating hierarchical sequence classifiers with finer granularity and apply cross-validation analysis to the Metaxa2 hierarchical DNA sequence classifier. Further, I discuss and implement my perspective upon best practices for reference database curation. These curation procedures are designed for the purposes of hierarchical classification specifically. In Chapter 5, I apply pollen metabarcoding in combination with waggle dance interpretation to investigate the spatial and taxonomic foraging patterns of honey bees in central Ohio agroecosystems. After modifying existing PCR-based library preparation protocols, we applied our methods to target four plant barcode markers, trnL, trnH, rbcL and ITS2, for 32 samples collected across the month of May 2015 from four corn and soybean-dominated agroecosystems. Our results indicated that the vast majority of colony nutrition provided by pollen during this time was provided by three major plant taxa, woody Rosaceae trees, Salix and Trifolium. Inference of spatial foraging patterns through waggle dance analysis revealed a significant preference for wood lots and tree lines relative to herbaceous, residential and crop landcover types. Having worked to optimize and validate molecular methods for pollen analysis, investigations into how floral resource availability mediates honey bee health can be more feasibly conducted at large scales. It is my hope that this approach proves useful for quantifying and maximizing the pollinator floral resource value of managed lands.
Reed Johnson (Advisor)
John Christman (Committee Member)
Mary Gardiner (Committee Member)
Roman Lanno (Committee Member)
166 p.
Agriculture; Bioinformatics; Biology; Ecology; Entomology; Pollen
quantitative metabarcoding; pollen; molecular palynology; hierarchical classification; pollinator nutrition; waggle dance; pollinator foraging

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Citations

  • Richardson, R. T. (2018). Molecular analysis of honey bee foraging ecology [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1543239052414523

    APA Style (7th edition)

  • Richardson, Rodney. Molecular analysis of honey bee foraging ecology. 2018. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1543239052414523.

    MLA Style (8th edition)

  • Richardson, Rodney. "Molecular analysis of honey bee foraging ecology." Doctoral dissertation, Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1543239052414523

    Chicago Manual of Style (17th edition)

osu1543239052414523
545
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