- Pollination is an essential ecosystem service that sustains functioning ecosystems and aids in food production. In response to recent, widespread declines of managed and native bee populations, many land managers have shown interest in developing conservation and restoration plans for enhancing native bee habitat. However, there is a lack of data on which plant species serve as important food sources for native bees. Traditional methods for describing plant-bee interactions (e.g., bee foraging observations, microscopy) are time consuming, require specialized expertise, and often result in low taxonomic resolution. DNA metabarcoding of bee-collected pollen has been introduced as a more effective tool for describing the relationship between bees and flowering plants. However, there are still some concerns with this relatively new technique that need to be examined and resolved before pollinator researchers can be confident in the results that it produces. My thesis examines the strengths and some limitations of using DNA metabarcoding of bee pollen to describe plant-bee interactions.
Chapter 1 provides an introduction to the topic of native bees and their ecological and societal importance. I identify current knowledge gaps, and I introduce the topic of DNA metabarcoding, its many uses, and its potential limitations. This chapter provides background knowledge and introduces the questions that are addressed in the following chapters.
Chapter 2 addresses some unresolved questions that exist in the field of pollen metabarcoding, including which type of sequence count removal threshold is most appropriate for studying plant-pollinator interactions, the quantitative abilities of pollen metabarcoding, the ability of pollen metabarcoding to detect rare flower visits by bees, and the potential role of environmental contamination in mischaracterizing bee foraging behavior. We collected pollen from five plant species, created pollen mixtures in the laboratory that varied in species richness and evenness, and used metabarcoding of the ITS2 region to identify the plant species in the mixtures. We analyzed the sequencing data using two different sequence count removal threshold protocols: one liberal and one conservative. We were able to correctly identify all plant species in the mixtures, confirming the qualitative abilities of ITS2 pollen metabarcoding. When using the liberal threshold, six additional plant species that were not used to create the pollen mixtures were detected in the single-species samples. When using the conservative threshold, no additional species were detected in the single-species mixtures, but some species used to create the pollen mixtures were not detected above the sequence count removal threshold in mixtures 2-5, resulting in false negatives. We compared the proportion of pollen by mass to the proportion of sequencing reads produced for each plant species in the mixtures. Regardless of the threshold used, the proportion of pollen and sequencing reads were not significantly related for two of the four mixtures, and certain species were consistently over and underrepresented. We examined each plant species separately, and the proportion of pollen and sequencing reads was significantly and positively related, but proportions of the over and underrepresented species varied strongly from a one-to-one relationship.
In Chapter 3, we examine the strengths and limitations of using pollen metabarcoding to study plant-native bee interactions in three different habitat types. We sampled 403 native bees from three different habitat types in eastern Oregon. We documented foraging observations for each bee, and we used DNA metabarcoding of the ITS2 region and rbcL gene to identify the plant species present in each bee’s pollen load. We compared plant-pollinator networks created from bee foraging observations with networks created from plant species assignments obtained using DNA metabarcoding to determine whether these data are consistent or if DNA metabarcoding provides additional information on bee foraging behavior. We also compared plant species assignments produced by DNA metabarcoding when using a larger, “regional” reference database to those produced using a site specific, “local” reference database. Plant-pollinator networks produced using data derived from DNA metabarcoding had significantly higher connectance, linkage density, and bee generality and significantly lower specialization when compared to networks based on bee foraging observations. Approximately 15% more plant species were assigned when using the regional database than when using the local database. Using a local reference database reduced the possibility of erroneous taxonomic assignments.
Chapter 4 provides a summary of the key findings from Chapters 2 and 3. I make some suggestions for researchers that wish to use DNA metabarcoding to study interactions between bees and plants and identify some areas for future research. Ultimately, the results of this thesis show that DNA metabarcoding of bee pollen is a promising technique which provides additional information on bee foraging behavior that cannot easily be discovered using bee foraging observations or microscopy. Although ITS2 sequence reads cannot be used to determine the amount of a plant species in a pollen sample, ITS2 metabarcoding provides accurate species identification and does not appear to overestimate the number of plant species on which bees forage when using our more conservative sequence count removal threshold. The results obtained from studies such as these can be used to create bee species- and region-specific plant lists that can inform restoration and conservation plans to increase native bee habitat quantity and quality in any location.