Design and testing of a national pollinator and pollination monitoring framework

Final summary report to the Department for Environment, Food and Rural Affairs (Defra), Scottish Government and Welsh Government: Project WC1101

Livestock-associated Methicillin-Resistant Staphylococcus aureus Sequence Type 398 in Humans, Canada

Recent emergence of infections resulting from this strain is of public health concern

Pollinator monitoring more than pays for itself

1. Resilient pollination services depend on sufficient abundance of pollinating insects over time. Currently, however, most knowledge about the status and trends of pollinators is based on changes in pollinator species richness and distribution only. 2. Systematic, long‐term monitoring of pollinators is urgently needed to provide baseline information on their status, to identify the drivers of declines and to inform suitable response measures. 3. Power analysis was used to determine the number of sites required to detect a 30% change in pollinator populations over 10 years. We then evaluated the full economic costs of implementing four national monitoring schemes in the UK: (a) professional pollinator monitoring, (b) professional pollination service monitoring, (c) volunteer collected pan traps and (d) volunteer focal floral observations. These costs were compared to (a) the costs of implementing separate, expert‐designed research and monitoring networks and (b) the economic benefits of pollination services threatened by pollinator loss. 4. Estimated scheme costs ranged from £6,159/year for a 75‐site volunteer focal flower observation scheme to £2.7 M/year for an 800‐site professional pollination service monitoring network. The estimated research costs saved using the site network as research infrastructure range from £1.46–4.17 M/year. The economic value of UK crop yield lost following a 30% decline in pollinators was estimated at ~£188 M/year. 5. Synthesis and applications. We evaluated the full costs of running pollinator monitoring schemes against the economic benefits to research and society they provide. The annual costs of monitoring are <0.02% of the economic value of pollination services that would be lost after a 30% decline in pollination services. Furthermore, by providing high‐quality scientific data, monitoring schemes would save at least £1.5 on data collection per £1 spent. Our findings demonstrate that long‐term systematic monitoring can be a cost‐effective tool for both answering key research questions and setting action points for policymakers. Careful consideration must be given to scheme design, the logistics of national‐scale implementation and resulting data quality when selecting the most appropriate combination of surveyors, methods and site networks to deliver a successful scheme

Communications Biophysics

Contains reports on four research projects.National Institutes of Health (Grant 5 P01 NS13126-02)National Institutes of Health (Grant 5 K04 NS00113-03)National Institutes of Health (Grant 2 ROI NS11153-02A1)National Science Foundation (Grant BNS77-16861)National Institutes of Health (Grant 5 RO1 NS10916-03)National Institutes of Health (Fellowship 1 F32 NS05327)National Institutes of Health (Grant 5 ROI NS12846-02)National Institutes of Health (Fellowship 1 F32 NS05266)Edith E. Sturgis FoundationNational Institutes of Health (Grant 1 R01 NS11680-01)National Institutes of Health (Grant 2 RO1 NS11080-04)National Institutes of Health (Grant 5 T32 GIM107301-03)National Institutes of Health (Grant 5 TOI GM01555-10

Communications Biophysics

Contains reports on nine research projects split into four sections.National Institutes of Health (Grant 5 PO1 NS13126)National Institutes of Health (Grant 5 KO4 NS00113)National Institutes of Health (Training Grant 5 T32 NS07047)National Institutes of Health (Training Grant 1 T32 NS07099)National Science Foundation (Grant BNS77-16861)National Institutes of Health (Grant 5 ROI NS10916)National Institutes of Health (Grant 5 RO1 NS12846)National Science Foundation (Grant BNS77-21751)National Institutes of Health (Grant 1 RO1 NS14092)Edith E. Sturgis FoundationHealth Sciences FundNational Institutes of Health (Grant 2 R01 NS11680)National Institutes of Health (Fellowship 5 F32 NS05327)National Institutes of Health (Grant 2 ROI NS11080)National Institutes of Health (Training Grant 5 T32 GM07301

Communications Biophysics

Contains reports on nine research projects split into four sections.National Institutes of Health (Grant 5 P01 NS13126)National Institutes of Health (Grant 5 K04 NS00113)National Institutes of Health (Training Grant 5 T32 NS07047)National Institutes of Health (Grant 5 ROl NS11153-03)National Institutes of Health (Fellowship 1 T32 NS07099-01)National Science Foundation (Grant BNS77-16861)National Institutes of Health (Grant 5 ROl NS10916)National Institutes of Health (Grant 5 ROl NS12846)National Science Foundation (Grant BNS77-21751)National Institutes of Health (Grant 1 RO1 NS14092)Health Sciences FundNational Institutes of Health (Grant 2 R01 NS11680)National Institutes of Health (Grant 2 RO1 NS11080)National Institutes of Health (Training Grant 5 T32 GM07301

Target Region Selection Is a Critical Determinant of Community Fingerprints Generated by 16S Pyrosequencing

Pyrosequencing of 16S rRNA genes allows for in-depth characterization of complex microbial communities. Although it is known that primer selection can influence the profile of a community generated by sequencing, the extent and severity of this bias on deep-sequencing methodologies is not well elucidated. We tested the hypothesis that the hypervariable region targeted for sequencing and primer degeneracy play important roles in influencing the composition of 16S pyrotag communities. Subgingival plaque from deep sites of current smokers with chronic periodontitis was analyzed using Sanger sequencing and pyrosequencing using 4 primer pairs. Greater numbers of species were detected by pyrosequencing than by Sanger sequencing. Rare taxa constituted nearly 6% of each pyrotag community and less than 1% of the Sanger sequencing community. However, the different target regions selected for pyrosequencing did not demonstrate a significant difference in the number of rare and abundant taxa detected. The genera Prevotella, Fusobacterium, Streptococcus, Granulicatella, Bacteroides, Porphyromonas and Treponema were abundant when the V1–V3 region was targeted, while Streptococcus, Treponema, Prevotella, Eubacterium, Porphyromonas, Campylobacer and Enterococcus predominated in the community generated by V4–V6 primers, and the most numerous genera in the V7–V9 community were Veillonella, Streptococcus, Eubacterium, Enterococcus, Treponema, Catonella and Selenomonas. Targeting the V4–V6 region failed to detect the genus Fusobacterium, while the taxa Selenomonas, TM7 and Mycoplasma were not detected by the V7–V9 primer pairs. The communities generated by degenerate and non-degenerate primers did not demonstrate significant differences. Averaging the community fingerprints generated by V1–V3 and V7–V9 primers providesd results similar to Sanger sequencing, while allowing a significantly greater depth of coverage than is possible with Sanger sequencing. It is therefore important to use primers targeted to these two regions of the 16S rRNA gene in all deep-sequencing efforts to obtain representational characterization of complex microbial communities

Rapid assessment of insect pollination services to inform decision-making.

Pollinator declines have prompted efforts to assess how land-use change affects insect pollinators and pollination services in agricultural landscapes. Yet many tools to measure insect pollination services require substantial landscape-scale data and technical expertise. In expert workshops, 3 straightforward methods (desk-based method, field survey, and empirical manipulation with exclusion experiments) for rapid insect pollination assessment at site scale were developed to provide an adaptable framework that is accessible to nonspecialist with limited resources. These methods were designed for TESSA (Toolkit for Ecosystem Service Site-Based Assessment) and allow comparative assessment of pollination services at a site of conservation interest and in its most plausible alternative state (e.g., converted to agricultural land). We applied the methods at a nature reserve in the United Kingdom to estimate the value of insect pollination services provided by the reserve. The economic value of pollination services provided by the reserve ranged from US$6163 to US$11,546/year. The conversion of the reserve to arable land would provide no insect pollination services and a net annual benefit from insect-pollinated crop production of approximately $1542/year (US$24∙ha-1 ∙year-1 ). The methods had wide applicability and were readily adapted to different insect-pollinated crops: rape (Brassica napus) and beans (Vicia faba) crops. All methods were rapidly employed under a low budget. The relatively less robust methods that required fewer resources yielded higher estimates of annual insect pollination benefit

Monitoring insect pollinators and flower visitation: the effectiveness and feasibility of different survey methods

1. The status of pollinating insects is of international concern, but knowledge of the magnitude and extent of declines is limited by a lack of systematic monitoring. Standardized protocols are urgently needed, alongside a better understanding of how different methods and recorders (data collectors) influence estimates of pollinator abundance and diversity. 2. We compared two common methods for sampling wild pollinating insects (solitary bees, bumblebees and hoverflies), pan traps and transects, in surveys of 1 km countryside squares (agricultural and semi‐natural habitats) and flowering crop fields across Great Britain, including the influence of local floral resources (nectar sugar availability or crop flower density) on the insects sampled. Further, we compared the performance of recorders with differing expertise (non‐specialist research staff, taxonomic experts and non‐expert volunteers) in applying methods. 3. Pan traps and transects produced compositionally distinct samples of pollinator communities. In the wider countryside, pan traps sampled more species of solitary bee and hoverfly. In flowering crops, transects recorded a greater number of individual bumblebees, but fewer species. 4. Across all taxonomic groups and countryside and crop samples, transects generally had lower rates of species accumulation per individual collected than pan traps. This demonstrates that differences between methods in estimating richness are not due to sampling effort alone. However, recorders possessing greater taxonomic expertise can produce species accumulation data from transects that are almost commensurate with pan trapping. 5. The abundance and species richness of pollinators (except solitary bees) on transects in the wider countryside was positively related to the availability of estimated nectar sugar. In crops, pollinator abundance responses to flower densities were idiosyncratic according to crop type, but overall the response was positive and negative for transects and pan traps, respectively. 6. Given these taxonomic and context‐specific differences in method performance, we assess their suitability for monitoring pollinating insect communities and pollination services. We discuss the relevance of these findings within the context of achieving standardized, large‐scale monitoring of pollinating insects