Using Publicly Available Data to Quantify Plant-Pollinator Interactions and Evaluate Conservation Seeding Mixes in the Northern Great Plains.

Concern over declining pollinators has led to multiple conservation initiatives for improving forage for bees in agroecosystems. Using data available through the Pollinator Library (npwrc.usgs.gov/pollinator/), we summarize plant-pollinator interaction data collected from 2012-2015 on lands managed by the U.S. Fish and Wildlife Service and private lands enrolled in U.S. Department of Agriculture conservation programs in eastern North Dakota (ND). Furthermore, we demonstrate how plant-pollinator interaction data from the Pollinator Library and seed cost information can be used to evaluate hypothetical seeding mixes for pollinator habitat enhancements. We summarize records of 314 wild bee and 849 honey bee (Apis mellifera L.) interactions detected on 63 different plant species. The wild bee observations consisted of 46 species, 15 genera, and 5 families. Over 54% of all wild bee observations were represented by three genera-Bombus, Lassioglossum, and Melissodes. The most commonly visited forbs by wild bees were Monarda fistulosa, Sonchus arvensis, and Zizia aurea. The most commonly visited forbs by A. mellifera were Cirsium arvense, Melilotus officinalis, and Medicago sativa. Among all interactions, 13% of A. mellifera and 77% of wild bee observations were made on plants native to ND. Our seed mix evaluation shows that mixes may often need to be tailored to meet the unique needs of wild bees and managed honey bees in agricultural landscapes. Our evaluation also demonstrates the importance of incorporating both biologic and economic information when attempting to design cost-effective seeding mixes for supporting pollinators in a critically important part of the United States.

A Comparison of Honey Bee-Collected Pollen From Working Agricultural Lands Using Light Microscopy and ITS Metabarcoding.

Taxonomic identification of pollen has historically been accomplished via light microscopy but requires specialized knowledge and reference collections, particularly when identification to lower taxonomic levels is necessary. Recently, next-generation sequencing technology has been used as a cost-effective alternative for identifying bee-collected pollen; however, this novel approach has not been tested on a spatially or temporally robust number of pollen samples. Here, we compare pollen identification results derived from light microscopy and DNA sequencing techniques with samples collected from honey bee colonies embedded within a gradient of intensive agricultural landscapes in the Northern Great Plains throughout the 2010-2011 growing seasons. We demonstrate that at all taxonomic levels, DNA sequencing was able to discern a greater number of taxa, and was particularly useful for the identification of infrequently detected species. Importantly, substantial phenological overlap did occur for commonly detected taxa using either technique, suggesting that DNA sequencing is an appropriate, and enhancing, substitutive technique for accurately capturing the breadth of bee-collected species of pollen present across agricultural landscapes. We also show that honey bees located in high and low intensity agricultural settings forage on dissimilar plants, though with overlap of the most abundantly collected pollen taxa. We highlight practical applications of utilizing sequencing technology, including addressing ecological issues surrounding land use, climate change, importance of taxa relative to abundance, and evaluating the impact of conservation program habitat enhancement efforts.