361 research outputs found

    Checking the Checks: A Survey of Guest-Check Accuracy

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    Inaccurate guest checks represent lost revenue. And the frequency of check errors is higher than many restaurateurs might think

    Management and drivers of change of pollinating insects and pollination services. National Pollinator Strategy: for bees and other pollinators in England, Evidence statements and Summary of Evidence

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    These Evidence Statements provide up-to-date information on what is known (and not known) about the status, values, drivers of change, and responses to management of UK insect pollinators (as was September 2018). This document has been produced to inform the development of England pollinator policy, and provide insight into the evidence that underpins policy decision-making. This document sits alongside a more detailed Summary of Evidence (Annex I) document written by pollinator experts. For information on the development of the statements, and confidence ratings assigned to them, please see section ?Generation of the statements? below. Citations for these statements are contained in the Summary of Evidence document

    Spatial ecology of a range-expanding bumble bee pollinator

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    Molecular methods have greatly increased our understanding of the previously cryptic spatial ecology of bumble bees (Bombus spp.), with knowledge of the spatial ecology of these bees being central to conserving their essential pollination services. Bombus hypnorum, the Tree Bumble Bee, is unusual in that it has recently rapidly expanded its range, having colonized much of the UK mainland since 2001. However, the spatial ecology of B. hypnorum has not previously been investigated. To address this issue, and to investigate whether specific features of the spatial ecology of B. hypnorum are associated with its rapid range expansion, we used 14 microsatellite markers to estimate worker foraging distance, nest density, between‐year lineage survival rate and isolation by distance in a representative UK B. hypnorum population. After assigning workers to colonies based on full or half sibship, we estimated the mean colony‐specific worker foraging distance as 103.6 m, considerably less than values reported from most other bumble bee populations. Estimated nest density was notably high (2.56 and 0.72 colonies ha−1 in 2014 and 2015, respectively), estimated between‐year lineage survival rate was 0.07, and there was no evidence of fine‐scale isolation by distance. In addition, genotyping stored sperm dissected from sampled queens confirmed polyandry in this population (mean minimum mating frequency of 1.7 males per queen). Overall, our findings establish critical spatial ecological parameters and the mating system of this unusual bumble bee population and suggest that short worker foraging distances and high nest densities are associated with its rapid range expansion

    Increasing flower species richness in agricultural landscapes alters insect pollinator networks: Implications for bee health and competition

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    Ecological restoration programs are established to reverse land degradation, mitigate biodiversity loss, and reinstate ecosystem services. Following recent agricultural intensification that led to a decrease in flower diversity and density in rural areas and subsequently to the decline of many insects, conservation measures targeted at pollinators have been established, including sown wildflower strips (WFS) along field margins. Historically successful in establishing a high density of generalist bees and increasing pollinator diversity, the impact of enhanced flower provision on wider ecological interactions and the structure of pollinator networks has been rarely investigated. Here, we tested the effects of increasing flower species richness and flower density in agricultural landscapes on bee‐plant interaction networks. We measured plant species richness and flower density and surveyed honeybee and bumblebee visits on flowers across a range of field margins on 10 UK farms that applied different pollinator conservation measures. We found that both flower species richness and flower density significantly increased bee abundance, in early and late summer, respectively. At the network level, we found that higher flower species richness did not significantly alter bee species' generality indices, but significantly reduced network connectance and marginally reduced niche overlap across honeybees and bumblebee species, a proxy for insect competition. While higher connectance and niche overlap is believed to strengthen network robustness and often is the aim for the restoration of pollinator networks, we argue that carefully designed WFS may benefit bees by partitioning their foraging niche, limiting competition for resources and the potential for disease transmission via shared floral use. We also discuss the need to extend WFS and their positive effects into spring when wild bee populations are established

    occAssess: an R package for assessing potential biases in species occurrence data

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    Species occurrence records from a variety of sources are increasingly aggregated into heterogeneous databases and made available to ecologists for immediate analytical use. However, these data are typically biased, i.e. they are not a probability sample of the target population of interest, meaning that the information they provide may not be an accurate reflection of reality. It is therefore crucial that species occurrence data are properly scrutinised before they are used for research. In this article, we introduce occAssess, an R package that enables straightforward screening of species occurrence data for potential biases. The package contains a number of discrete functions, each of which returns a measure of the potential for bias in one or more of the taxonomic, temporal, spatial, and environmental dimensions. Users can opt to provide a set of time periods into which the data will be split; in this case separate outputs will be provided for each period, making the package particularly useful for assessing the suitability of a dataset for estimating temporal trends in species' distributions. The outputs are provided visually (as ggplot2 objects) and do not include a formal recommendation as to whether data are of sufficient quality for any given inferential use. Instead, they should be used as ancillary information and viewed in the context of the question that is being asked, and the methods that are being used to answer it. We demonstrate the utility of occAssess by applying it to data on two key pollinator taxa in South America: leaf-nosed bats (Phyllostomidae) and hoverflies (Syrphidae). In this worked example, we briefly assess the degree to which various aspects of data coverage appear to have changed over time. We then discuss additional applications of the package, highlight its limitations, and point to future development opportunities

    Mapping with Sparse Local Sensors and Strong Hierarchical Priors

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    The paradigm case for robotic mapping assumes large quantities of sensory information which allow the use of relatively weak priors. In contrast, the present study considers the mapping problem in environments where only sparse, local sensory information is available. To compensate for these weak likelihoods, we make use of strong hierarchical object priors. Hierarchical models were popular in classical blackboard systems but are here applied in a Bayesian setting and novelly deployed as a mapping algorithm. We give proof of concept results, intended to demonstrate the algorithm’s applicability as a part of a tactile SLAM module for the whiskered SCRATCHbot mobile robot platform
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