Human reliance on insect pollination services continues to increase even as pollinator populations exhibit global declines. Increased commodity crop prices and federal subsidies for biofuel crops, such as corn and soybeans, have contributed to rapid land-use change in the US Northern Great Plains (NGP), changes that may jeopardize habitat for honey bees in a part of the country that supports >40% of the US colony stock. We investigated changes in biofuel crop production and grassland land covers surrounding ∼18,000 registered commercial apiaries in North and South Dakota from 2006 to 2014. We then developed habitat selection models to identify remotely sensed land-cover and land-use features that influence apiary site selection by Dakota beekeepers. Our study demonstrates a continual increase in biofuel crops, totaling 1.2 Mha, around registered apiary locations in North and South Dakota. Such crops were avoided by commercial beekeepers when selecting apiary sites in this region. Furthermore, our analysis reveals how grasslands that beekeepers target when selecting commercial apiary locations are becoming less common in eastern North and South Dakota, changes that may have lasting impact on pollinator conservation efforts. Our study highlights how land-use change in the NGP is altering the landscape in ways that are seemingly less conducive to beekeeping. Our models can be used to guide future conservation efforts highlighted in the US national pollinator health strategy by identifying areas that support high densities of commercial apiaries and that have exhibited significant land-use changes.apiary selection models | Apis mellifera | land use | land-cover trends | pollinators A nimal pollination service is critical for sustaining ecosystem health and human well-being (1, 2). In many terrestrial systems, plant-pollinator interactions provide the basic framework for all other trophic interactions. Globally, about one-third of crop production depends on animal pollination (3). US agricultural production relies heavily on managed and native insects for pollination services, with an estimated economic value of $15 billion annually (2). Reliance on insects for pollination services is growing even as populations of native and managed pollinators exhibit concurrent declines (4, 5). For example, in 2013−2014, total US honey bee colony losses were 34%, but beekeepers on average lost 51% of their colonies (6). Declines in managed honey bees and native bees put significant pressure on global food supplies, plant-pollinator networks, agricultural producers, and ecosystem function (7,8).Proposed reasons for the declines include parasites, diseases, agro-chemical use, forage availability, and land-use change (9, 10). Much of the research investigating anthropogenic disturbance effects on managed and native pollinators focuses on pesticides and less so on habitat fragmentation, land-use, and loss of forage. Although a paucity of data exists for most parts of the world, recent research indicates that land use influences honey ...

Typha is an iconic wetland plant found worldwide. Hybridization and anthropogenic disturbances have resulted in large increases in Typha abundance in wetland ecosystems throughout North America at a cost to native floral and faunal biodiversity. As demonstrated by three regional case studies, Typha is capable of rapidly colonizing habitats and forming monodominant vegetation stands due to traits such as robust size, rapid growth rate, and rhizomatic expansion. Increased nutrient inputs into wetlands and altered hydrologic regimes are among the principal anthropogenic drivers of Typha invasion. Typha is associated with a wide range of negative ecological impacts to wetland and agricultural systems, but also is linked with a variety of ecosystem services such as bioremediation and provisioning of biomass, as well as an assortment of traditional cultural uses. Numerous physical, chemical, and hydrologic control methods are used to manage invasive Typha, but results are inconsistent and multiple methods and repeated treatments often are required. While this review focuses on invasive Typha in North America, the literature cited comes from research on Typha and other invasive species from around the world. As such, many of the underlying concepts in this review are relevant to invasive species in other wetland ecosystems worldwide.

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.

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Identifying plant taxa that honey bees (Apis mellifera) forage upon is of great apicultural interest, but traditional methods are labor intensive and may lack resolution. Here we evaluate a high-throughput genetic barcoding approach to characterize trap-collected pollen from multiple North Dakota apiaries across multiple years. We used the Illumina MiSeq platform to generate sequence scaffolds from non-overlapping 300-bp paired-end sequencing reads of the ribosomal internal transcribed spacers (ITS). Full-length sequence scaffolds represented ~530 bp of ITS sequence after adapter trimming, drawn from the 5’ of ITS1 and the 3’ of ITS2, while skipping the uninformative 5.8S region. Operational taxonomic units (OTUs) were picked from scaffolds clustered at 97% identity, searched by BLAST against the nt database, and given taxonomic assignments using the paired-read lowest common ancestor approach. Taxonomic assignments and quantitative patterns were consistent with known plant distributions, phenology, and observational reports of pollen foraging, but revealed an unexpected contribution from non-crop graminoids and wetland plants. The mean number of plant species assignments per sample was 23.0 (+/- 5.5) and the mean species diversity (effective number of equally abundant species) was 3.3 (+/- 1.2). Bray-Curtis similarities showed good agreement among samples from the same apiary and sampling date. Rarefaction plots indicated that fewer than 50,000 reads are typically needed to characterize pollen samples of this complexity. Our results show that a pre-compiled, curated reference database is not essential for genus-level assignments, but species-level assignments are hindered by database gaps, reference length variation, and probable errors in the taxonomic assignment, requiring post-hoc evaluation. Although the effective per-sample yield achieved using custom MiSeq amplicon primers was less than the machine maximum, primarily due to lower “read2” quality, further protocol optimization and/or a modest reduction in multiplex scale should offset this difficulty. As small quantities of pollen are sufficient for amplification, our approach might be extendable to other questions or species for which large pollen samples are not available.