Abstract
Improved taxonomic methods are needed to quantify declining populations of insect pollinators. This study devises a high-throughput DNA barcoding protocol for a regional fauna (United Kingdom) of bees (Apiformes), consisting of reference library construction, a proof-of-concept monitoring scheme, and the deep barcoding of individuals to assess potential artefacts and organismal associations. A reference database of cytochrome oxidase c subunit 1 (cox1) sequences including 92.4% of 278 bee species known from the UK showed high congruence with morphological taxon concepts, but molecular species delimitations resulted in numerous split and (fewer) lumped entities within the Linnaean species. Double tagging permitted deep Illumina sequencing of 762 separate individuals of bees from a UK-wide survey. Extracting the target barcode from the amplicon mix required a new protocol employing read abundance and phylogenetic position, which revealed 180 molecular entities of Apiformes identifiable to species. An additional 72 entities were ascribed to nuclear pseudogenes based on patterns of read abundance and phylogenetic relatedness to the reference set. Clustering of reads revealed a range of secondary operational taxonomic units (OTUs) in almost all samples, resulting from traces of insect species caught in the same traps, organisms associated with the insects including a known mite parasite of bees, and the common detection of human DNA, besides evidence for low-level cross-contamination in pan traps and laboratory procedures. Custom scripts were generated to conduct critical steps of the bioinformatics protocol. The resources built here will greatly aid DNA-based monitoring to inform management and conservation policies for the protection of pollinators.
Highlights
Widespread declines in pollinator populations are causing concern about the future of global biodiversity and agricultural productivity (Garibaldi et al 2013; Hallmann et al 2017; Lever et al 2014), driven by the combined effects of habitat loss, introduction of non-native and invasive species, pathogens and parasites, and various other factors contributing to environmental change (Vanbergen et al 2013)
A total of 355 bee specimens were newly sequenced for the COI barcode to generate the reference set, representing 165 Linnaean species. These new sequences were compared against 1754 fulllength barcode sequences obtained from the Barcode of Life Database (BOLD) for species known from the UK (Fig. 1A)
High-throughput sequencing can greatly change the approach to monitoring of pollinators, through mass identification of sequence reads against reference databases verified by taxonomic specialists (Tang et al 2015; Ji et al 2013)
Summary
Widespread declines in pollinator populations are causing concern about the future of global biodiversity and agricultural productivity (Garibaldi et al 2013; Hallmann et al 2017; Lever et al 2014), driven by the combined effects of habitat loss, introduction of non-native and invasive species, pathogens and parasites, and various other factors contributing to environmental change (Vanbergen et al 2013). Landscape effects on pollination of crops through agricultural intensification, the use of monoculture crops, have led to significant changes in pollinator communities (Kennedy et al 2013; Ricketts et al 2008), with obvious economic implications for the agricultural sector and pollination services worth hundreds of millions of pounds in the United Kingdom alone (Potts et al 2010). These trends in species distribution and abundance are difficult to quantify, unless solid methodologies for monitoring at regional levels can be implemented. Species identification is usually performed by expert taxonomists, but there is a growing need for alternative methods, in particular because the great species diversity and large quantity of specimens from mass trapping make them challenging and costly to identify (Lebuhn et al 2013)
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