Modelling effects of honeybee behaviors on the distribution of pesticide in nectar within a hive and resultant in-hive exposure

This is the author accepted manuscript. The final version is available from the American Chemical Society via the DOI in this record.Recently, the causes of honeybee colony losses have been intensely studied, showing that there are multiple stressors implicated in colony declines, one stressor being the exposure to pesticides. Measuring exposure of individual bees within a hive to pesticide is at least as difficult as assessing the potential exposure of foraging bees to pesticide. We present a model to explore how heterogeneity of pesticide distribution on a comb in the hive can be driven by worker behaviors. The model contains simplified behaviors to capture the extremes of possible heterogeneity of pesticide location/deposition within the hive to compare with exposure levels estimated by averaging values across the comb. When adults feed on nectar containing the average concentration of all pesticide brought into the hive on that particular day it is likely representative of the worst case exposure scenario. However, for larvae, clustering of pesticide in the comb can lead to higher exposure levels than taking an average concentration in some circumstances. The potential for extrapolating the model to risk assessment is discussed.J.R. was funded to do this work on an Industrial CASE PhD studentship funded by the Biology and Biotechnology Sciences Research Council of the UK (BBSRC), and Syngenta. J.O. and M.B. were supported on BBSRC project BB/K014463/1

Interpretable neural architecture search via Bayesian optimisation with Weisfeiler-Lehman kernels

Current neural architecture search (NAS) strategies focus only on finding a single, good, architecture. They offer little insight into why a specific network is performing well, or how we should modify the architecture if we want further improvements. We propose a Bayesian optimisation (BO) approach for NAS that combines the Weisfeiler-Lehman graph kernel with a Gaussian process surrogate. Our method optimises the architecture in a highly data-efficient manner: it is capable of capturing the topological structures of the architectures and is scalable to large graphs, thus making the high-dimensional and graph-like search spaces amenable to BO. More importantly, our method affords interpretability by discovering useful network features and their corresponding impact on the network performance. Indeed, we demonstrate empirically that our surrogate model is capable of identifying useful motifs which can guide the generation of new architectures. We finally show that our method outperforms existing NAS approaches to achieve the state of the art on both closed- and open-domain search spaces

Multiple stressors: using the honeybee model BEEHAVE to explore how spatial and temporal forage stress affects colony resilience

The causes underlying the increased mortality of honeybee colonies (Apis mellifera) observed over the past decade remain unclear. Since so far the evidence for monocausal explanations is equivocal, involvement of multiple stressors is generally assumed. We here focus on various aspects of forage availability, which have received less attention than other stressors because it is virtually impossible to explore them empirically. We applied the colony model BEEHAVE, which links within-hive dynamics and foraging, to stylized landscape settings to explore how foraging distance, forage supply, and “forage gaps”, i.e. periods in which honeybees cannot find any nectar and pollen, affect colony resilience and the mechanisms behind. We found that colony extinction was mainly driven by foraging distance, but the timing of forage gaps had strongest effects on time to extinction. Sensitivity to forage gaps of 15 days was highest in June or July even if otherwise forage availability was sufficient to survive. Forage availability affected colonies via cascading effects on queen's egg-laying rate, reduction of new-emerging brood stages developing into adult workers, pollen debt, lack of workforce for nursing, and reduced foraging activity. Forage gaps in July led to reduction in egg-laying and increased mortality of brood stages at a time when the queen's seasonal egg-laying rate is at its maximum, leading to colony failure over time. Our results demonstrate that badly timed forage gaps interacting with poor overall forage supply reduce honeybee colony resilience. Existing regulation mechanisms which in principle enable colonies to cope with varying forage supply in a given landscape and year, such as a reduction in egg-laying, have only a certain capacity. Our results are hypothetical, as they are obtained from simplified landscape settings, but they are consistent with existing empirical knowledge. They offer ample opportunities for testing the predicted effects of forage stress in controlled experiments

REVIEW: Towards a systems approach for understanding honeybee decline: a stocktaking and synthesis of existing models

Published© 2013 The Authors. Journal of Applied Ecology © 2013 British Ecological Society This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.Summary 1. The health of managed and wild honeybee colonies appears to have declined substantially in Europe and the United States over the last decade. Sustainability of honeybee colonies is important not only for honey production, but also for pollination of crops and wild plants alongside other insect pollinators. A combination of causal factors, including parasites, pathogens, land use changes and pesticide usage, are cited as responsible for the increased colony mortality. 2. However, despite detailed knowledge of the behaviour of honeybees and their colonies, there are no suitable tools to explore the resilience mechanisms of this complex system under stress. Empirically testing all combinations of stressors in a systematic fashion is not feasible. We therefore suggest a cross-level systems approach, based on mechanistic modelling, to investigate the impacts of (and interactions between) colony and land management. 3. We review existing honeybee models that are relevant to examining the effects of different stressors on colony growth and survival. Most of these models describe honeybee colony dynamics, foraging behaviour or honeybee – varroa mite – virus interactions. 4. We found that many, but not all, processes within honeybee colonies, epidemiology and foraging are well understood and described in the models, but there is no model that couples in-hive dynamics and pathology with foraging dynamics in realistic landscapes. 5. Synthesis and applications. We describe how a new integrated model could be built to simulate multifactorial impacts on the honeybee colony system, using building blocks from the reviewed models. The development of such a tool would not only highlight empirical research priorities but also provide an important forecasting tool for policy makers and beekeepers, and we list examples of relevant applications to bee disease and landscape management decisions.Biotechnology and Biological Sciences Research Council (BBSRC

Predicting honeybee colony failure: using the BEEHAVE model to simulate colony responses to pesticides

PublishedJournal ArticleResearch Support, Non-U.S. Gov'tTo simulate effects of pesticides on different honeybee (Apis mellifera L.) life stages, we used the BEEHAVE model to explore how increased mortalities of larvae, in-hive workers, and foragers, as well as reduced egg-laying rate, could impact colony dynamics over multiple years. Stresses were applied for 30 days, both as multiples of the modeled control mortality and as set percentage daily mortalities to assess the sensitivity of the modeled colony both to small fluctuations in mortality and periods of low to very high daily mortality. These stresses simulate stylized exposure of the different life stages to nectar and pollen contaminated with pesticide for 30 days. Increasing adult bee mortality had a much greater impact on colony survival than mortality of bee larvae or reduction in egg laying rate. Importantly, the seasonal timing of the imposed mortality affected the magnitude of the impact at colony level. In line with the LD50, we propose a new index of "lethal imposed stress": the LIS50 which indicates the level of stress on individuals that results in 50% colony mortality. This (or any LISx) is a comparative index for exploring the effects of different stressors at colony level in model simulations. While colony failure is not an acceptable protection goal, this index could be used to inform the setting of future regulatory protection goals.J.R. was funded to do this work on an Industrial CASE PhD studentship funded by the Biology and Biotechnology Sciences Research Council of the UK (BBSRC), and Syngenta. J.O., M.B., and P.K. were supported on BBSRC project BB/K014463/

Bombus terrestris in a mass‐flowering pollinator‐dependent crop: A mutualistic relationship? (article)

This is the final version. Available on open access from Wiley via the DOI in this recordThe dataset associated with this article is in ORE at https://doi.org/10.24378/exe.823Bumblebees (Bombus spp.) rely on an abundant and diverse selection of floral resources to meet their nutritional requirements. In farmed landscapes, mass‐flowering crops can provide an important forage resource for bumblebees, with increased visitation from bumblebees into mass‐flowering crops having an additional benefit to growers who require pollination services. This study explores the mutualistic relationship between Bombus terrestris L. (buff‐tailed bumblebee), a common species in European farmland, and the mass‐flowering crop courgette (Cucurbita pepo L.) to see how effective B. terrestris is at pollinating courgette and in return how courgette may affect B. terrestris colony dynamics. By combining empirical data on nectar and pollen availability with model simulations using the novel bumblebee model Bumble‐BEEHAVE, we were able to quantify and simulate for the first time, the importance of courgette as a mass‐flowering forage resource for bumblebees. Courgette provides vast quantities of nectar to ensure a high visitation rate, which combined with abundant pollen grains, enables B. terrestris to have a high pollination potential. While B. terrestris showed a strong fidelity to courgette flowers for nectar, courgette pollen was not found in any pollen loads from returning foragers. Nonetheless, model simulations showed that early season courgette (nectar) increased the number of hibernating queens, colonies, and adult workers in the modeled landscapes. Synthesis and applications. Courgette has the potential to improve bumblebee population dynamics; however, the lack of evidence of the bees collecting courgette pollen in this study suggests that bees can only benefit from this transient nectar source if alternative floral resources, particularly pollen, are also available to fulfill bees’ nutritional requirements in space and time. Therefore, providing additional forage resources could simultaneously improve pollination services and bumblebee populations.Natural Environment Research Council (NERC)Agriculture and Horticulture Development Boar

BEEHAVE: A systems model of honeybee colony dynamics and foraging to explore multifactorial causes of colony failure

Journal Article© 2014 The Authors. Journal of Applied Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly citedSummary: A notable increase in failure of managed European honeybee Apis mellifera L. colonies has been reported in various regions in recent years. Although the underlying causes remain unclear, it is likely that a combination of stressors act together, particularly varroa mites and other pathogens, forage availability and potentially pesticides. It is experimentally challenging to address causality at the colony scale when multiple factors interact. In silico experiments offer a fast and cost-effective way to begin to address these challenges and inform experiments. However, none of the published bee models combine colony dynamics with foraging patterns and varroa dynamics. We have developed a honeybee model, BEEHAVE, which integrates colony dynamics, population dynamics of the varroa mite, epidemiology of varroa-transmitted viruses and allows foragers in an agent-based foraging model to collect food from a representation of a spatially explicit landscape. We describe the model, which is freely available online (www.beehave-model.net). Extensive sensitivity analyses and tests illustrate the model's robustness and realism. Simulation experiments with various combinations of stressors demonstrate, in simplified landscape settings, the model's potential: predicting colony dynamics and potential losses with and without varroa mites under different foraging conditions and under pesticide application. We also show how mitigation measures can be tested. Synthesis and applications. BEEHAVE offers a valuable tool for researchers to design and focus field experiments, for regulators to explore the relative importance of stressors to devise management and policy advice and for beekeepers to understand and predict varroa dynamics and effects of management interventions. We expect that scientists and stakeholders will find a variety of applications for BEEHAVE, stimulating further model development and the possible inclusion of other stressors of potential importance to honeybee colony dynamics. © 2014 The Authors. Journal of Applied Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.Biotechnology and Biological Sciences Research Council (BBSRC

Approximate rogue wave solutions of the forced and damped Nonlinear Schr\"odinger equation for water waves

We consider the effect of the wind and the dissipation on the nonlinear stages of the modulational instability. By applying a suitable transformation, we map the forced/damped Nonlinear Schr\"odinger (NLS) equation into the standard NLS with constant coefficients. The transformation is valid as long as |{\Gamma}t| \ll 1, with {\Gamma} the growth/damping rate of the waves due to the wind/dissipation. Approximate rogue wave solutions of the equation are presented and discussed. The results shed some lights on the effects of wind and dissipation on the formation of rogue waves.Comment: 10 pages, 3 figure

BEESCOUT: A model of bee scouting behaviour and a software tool for characterizing nectar/pollen landscapes for BEEHAVE.

PublishedJournal ArticleThis is the final version of the article. Available from Elsevier via the DOI in this record.Social bees are central place foragers collecting floral resources from the surrounding landscape, but little is known about the probability of a scouting bee finding a particular flower patch. We therefore developed a software tool, BEESCOUT, to theoretically examine how bees might explore a landscape and distribute their scouting activities over time and space. An image file can be imported, which is interpreted by the model as a "forage map" with certain colours representing certain crops or habitat types as specified by the user. BEESCOUT calculates the size and location of these potential food sources in that landscape relative to a bee colony. An individual-based model then determines the detection probabilities of the food patches by bees, based on parameter values gathered from the flight patterns of radar-tracked honeybees and bumblebees. Various "search modes" describe hypothetical search strategies for the long-range exploration of scouting bees. The resulting detection probabilities of forage patches can be used as input for the recently developed honeybee model BEEHAVE, to explore realistic scenarios of colony growth and death in response to different stressors. In example simulations, we find that detection probabilities for food sources close to the colony fit empirical data reasonably well. However, for food sources further away no empirical data are available to validate model output. The simulated detection probabilities depend largely on the bees' search mode, and whether they exchange information about food source locations. Nevertheless, we show that landscape structure and connectivity of food sources can have a strong impact on the results. We believe that BEESCOUT is a valuable tool to better understand how landscape configurations and searching behaviour of bees affect detection probabilities of food sources. It can also guide the collection of relevant data and the design of experiments to close knowledge gaps, and provides a useful extension to the BEEHAVE honeybee model, enabling future users to explore how landscape structure and food availability affect the foraging decisions and patch visitation rates of the bees and, in consequence, to predict colony development and survival.We thank Peter Kennedy and Emma Wright for their contributions to the development of BEESCOUT and its publication. This work was funded by the Biotechnology and Biological Sciences Research Council of the UK [BB/J014915/1]

Anomalous anisotropic cross-correlations between WMAP CMB maps and SDSS galaxy distribution and implications on the dark flow scenario

We search for the dark flow induced diffuse kinetic Sunyaev Zel'dovich (kSZ) effect through CMB-galaxy cross correlation. Such angular correlation is anisotropic, with a unique $cos(theta_DF)$ angular dependence and hence can be distinguished from other components. Here, $theta_DF$ is the angle between the opposite dark flow direction and the direction of the sky where the correlation is measured. We analyze the KIAS-VAGC galaxy catalog of SDSS-DR7 and the WMAP seven-year temperature maps, applying an unbiased optimal weighting scheme to eliminate any statistically isotropic components and to enhance the dark flow detection signal. Non-zero weighted cross correlations are detected at 3.5 sigma for the redshift bin z<0.1 and at 3 sigma for the bin 0.1<z<0.2, implying the existence of statistically anisotropic components in CMB. However, further analysis does not support the dark flow explanation. The observed directional dependence deviates from the $\propto cos(theta_DF)$ relation expected, and hence can not be explained by the presence of a single dark flow, and if the observed cross correlation is generated by the dark flow induced kSZ effect, the velocity would be too high (> 6000 km/s). We report this work as the first attempt to search for dark flow through weighted CMB-galaxy cross correlation and to draw the attention on the sources of the detected anomalous CMB-galaxy cross correlation.Comment: 8 pages, 8 figures, ApJ accepte