Bumble-BEEHAVE: A systems model for exploring multifactorial causes of bumblebee decline at individual, colony, population and community level

Models of bee responses to land use and land cover changes in agricultural landscapes - a review and research agenda

Predictive modelling tools can be used to support the design of agricultural landscapes to promote pollinator biodiversity and pollination services. Despite the proliferation of such modelling tools in recent decades, there remains a gap in synthesising their main characteristics and representation capacities. Here, we reviewed 42 studies that developed non-correlative models to explore the impact of land use and land cover changes on bee populations, and synthesised information about the modelled systems, modelling approaches, and key model characteristics like spatiotemporal extent and resolution. Various modelling approaches are employed to predict the biodiversity of bees and the pollination services they provide, with a prevalence of models focusing on wild populations compared to managed ones. Of these models, landscape indicators and distance decay models are relatively simple, with few parameters. They allow mapping bee visitation probabilities using basic land cover data and considering bee foraging ranges. Conversely, mechanistic or agent-based models delineate, with varying degrees of complexity, a multitude of processes that characterise, among others, the foraging behaviour and population dynamics of bees. The reviewed models collectively encompass 38 ecological, agronomic, and economic processes, producing various outputs including bee abundance, habitat visitation rate, and crop yield. To advance the development of predictive modelling tools aimed at fostering pollinator biodiversity and pollination services in agricultural landscapes, we highlight future avenues for increasing biophysical realism in models predicting the impact of land use and land cover changes on bees. Additionally, we address the challenges associated with balancing model complexity and practical usability.

Chronic cadmium exposure impairs flight behavior by dampening flight muscle carbon metabolism in bumblebees

Cadmium pollution affects the global ecosystem because cadmium can be transferred up the food chain. The bumblebee, Bombus terrestris, is an important insect pollinator. Their foraging activity on flowers exposes them to harmful heavy metals, which damages their health and leads to massive population declines. However, the effects of chronic exposure to heavy metals on the flight performance of bumblebees have not yet been characterized. Here, we studied variation in the flight capacity of bumblebees induced by chronic cadmium exposure at field-realistic concentrations using behavioral, physiological, and molecular approaches. Chronic cadmium exposure caused a significant reduction in the duration, distance, and mean velocity of bumblebee flight. Transcriptome analysis showed that the impairment of carbon metabolism and mitochondrial dysfunction in the flight muscle were the primary causes. Physiological, biochemical, and metabolomic analyses validated disruptions in energy metabolism, and impairments in mitochondrial respiratory chain complexes activities. Histological analysis revealed muscle fiber damage and mitochondrial loss. Exogenous decanoic acid or citric acid partially restored sustained flight ability of bumblebees by mitigating muscle fiber damage and increasing energy generation. These findings provide insights into how long-term cadmium stress affects the flight ability of insects and will aid human muscle or exercise-related disease research.

Pesticide Exposure and Effects on Non-Apis Bees

Bees are essential pollinators of many crops and wild plants, and pesticide exposure is one of the key environmental stressors affecting their health in anthropogenically modified landscapes. Until recently, almost all information on routes and impacts of pesticide exposure came from honey bees, at least partially because they were the only model species required for environmental risk assessments (ERAs) for insect pollinators. Recently, there has been a surge in research activity focusing on pesticide exposure and effects for non-Apis bees, including other social bees (bumble bees and stingless bees) and solitary bees. These taxa vary substantially from honey bees and one another in several important ecological traits, including spatial and temporal activity patterns, foraging and nesting requirements, and degree of sociality. In this article, we review the current evidence base about pesticide exposure pathways and the consequences of exposure for non-Apis bees. We find that the insights into non-Apis bee pesticide exposure and resulting impacts across biological organizations, landscapes, mixtures, and multiple stressors are still in their infancy. The good news is that there are many promising approaches that could be used to advance our understanding, with priority given to informing exposure pathways, extrapolating effects, and determining how well our current insights (limited to very few species and mostly neonicotinoid insecticides under unrealistic conditions) can be generalized to the diversity of species and lifestyles in the global bee community. We conclude that future research to expand our knowledge would also be beneficial for ERAs and wider policy decisions concerning pollinator conservation and pesticide regulation.

Impacts of neonicotinoids on biodiversity: a critical review

Neonicotinoids are the most widely used class of insecticides in the world, but they have raised numerous concerns regarding their effects on biodiversity. Thus, the objective of this work was to do a critical review of the contamination of the environment (soil, water, air, biota) by neonicotinoids (acetamiprid, clothianidin, imidacloprid, thiacloprid, thiamethoxam) and of their impacts on terrestrial and aquatic biodiversity. Neonicotinoids are very frequently detected in soils and in freshwater, and they are also found in the air. They have only been recently monitored in coastal and marine environments, but some studies already reported the presence of imidacloprid and thiamethoxam in transitional or semi-enclosed ecosystems (lagoons, bays, and estuaries). The contamination of the environment leads to the exposure and to the contamination of non-target organisms and to negative effects on biodiversity. Direct impacts of neonicotinoids are mainly reported on terrestrial invertebrates (e.g., pollinators, natural enemies, earthworms) and vertebrates (e.g., birds) and on aquatic invertebrates (e.g., arthropods). Impacts on aquatic vertebrate populations and communities, as well as on microorganisms, are less documented. In addition to their toxicity to directly exposed organisms, neonicotinoid induce indirect effects via trophic cascades as demonstrated in several species (terrestrial and aquatic invertebrates). However, more data are needed to reach firmer conclusions and to get a clearer picture of such indirect effects. Finally, we identified specific knowledge gaps that need to be filled to better understand the effects of neonicotinoids on terrestrial, freshwater, and marine organisms, as well as on ecosystem services associated with these biotas.

Using physiology to better support wild bee conservation

There is accumulating evidence that wild bees are experiencing a decline in terms of species diversity, abundance or distribution, which leads to major concerns about the sustainability of both pollination services and intrinsic biodiversity. There is therefore an urgent need to better understand the drivers of their decline, as well as design conservation strategies. In this context, the current approach consists of linking observed occurrence and distribution data of species to environmental features. While useful, a highly complementary approach would be the use of new biological metrics that can link individual bee responses to environmental alteration with population-level responses, which could communicate the actual bee sensitivity to environmental changes and act as early warning signals of bee population decline or sustainability. We discuss here through several examples how the measurement of bee physiological traits or performance can play this role not only in better assessing the impact of anthropogenic pressures on bees, but also in guiding conservation practices with the help of the documentation of species' physiological needs. Last but not least, because physiological changes generally occur well in advance of demographic changes, we argue that physiological traits can help in predicting and anticipating future population trends, which would represent a more proactive approach to conservation. In conclusion, we believe that future efforts to combine physiological, ecological and population-level knowledge will provide meaningful contributions to wild bee conservation-based research.

The FloRes Database: A floral resources trait database for pollinator habitat-assessment generated by a multistep workflow

Background

The decline of pollinating insects in agricultural landscapes proceeds due to intensive land use and the associated loss of habitat and food sources. The feeding of those insects depends on the spatial and temporal distribution of nectar and pollen as food resource. Hence, to protect insect biodiversity, a spatio-temporal assessment of food quantity of their habitats is necessary. Therefore, sufficient data on traits of floral resources are required.

New information

As floral resources' traits of plants are important to quantify food availability, we present two databases, the FloRes Database (Floral Resources Database) and the raw database, from where FloRes was derived. Both databases contain the plant traits: (1) flowering period, (2) floral-unit density per day, (3) nectar volume per floral unit per day, (4) sugar content per floral unit, (5) sugar concentration in nectar, (6) pollen mass or volume per floral unit and per day, (7) protein content of pollen and (8) corolla depth. All traits were sampled from literature and online databases. The raw database consists of 702 specified plant species, 138 unspecified species 37 species (spec., sp), 22 species pluralis (spp) and, for 79, only the genus was identified) and two species complexes (agg.). Those 842 taxa belong to 488 genera and 102 families. Finally, only 27 taxa have a complete set of traits, too few for a sufficient assessment of spatio-temporal availability of floral food-resources.As information on floral resources is scattered throughout many publications with different units, we also present our multistep workflow implemented in five consecutive R-scripts. The multistep workflow standardises the trait units of the raw database to comparable entities with identical units and aggregates them on a reasonable taxonomic level into the second application database, the FloRes Database. Finally, the FloRes Database contains aggregated information of traits for 42 taxa and, when corolla depth is excluded, for 72 taxa.This is the first attempt to gather these eight traits from different literature sources into one database with a multistep workflow. The publication of the multistep workflow enables the users to extend the FloRes Database on their own demands with other literature data or newly-gathered data to improve quantification of food resources. Especially, the combination of pollen, nectar and the open flowers per square metre is, as far as we know, a novelty.The FloRes Database can be used to evaluate the quantity of food-resource habitats available for pollinators, for example, to compare seed mixtures of agri-environmental measures, such as flower strips, considering flower phenology on a daily basis.

A critical review of effect modeling for ecological risk assessment of plant protection products

A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment. Graphical Abstract Combination of the keyword lists composing the first bibliographic query. Columns were joined together with the logical operator AND. All keyword lists are available in Supplementary Information at https://doi.org/10.5281/zenodo.5775038 (Larras et al. 2021).

Agricultural buffer zone thresholds to safeguard functional bee diversity: Insights from a community modeling approach

Wild bee species are important pollinators in agricultural landscapes. However, population decline was reported over the last decades and is still ongoing. While agricultural intensification is a major driver of the rapid loss of pollinating species, transition zones between arable fields and forest or grassland patches, i.e., agricultural buffer zones, are frequently mentioned as suitable mitigation measures to support wild bee populations and other pollinator species. Despite the reported general positive effect, it remains unclear which amount of buffer zones is needed to ensure a sustainable and permanent impact for enhancing bee diversity and abundance. To address this question at a pollinator community level, we implemented a process-based, spatially explicit simulation model of functional bee diversity dynamics in an agricultural landscape. More specifically, we introduced a variable amount of agricultural buffer zones (ABZs) at the transition of arable to grassland, or arable to forest patches to analyze the impact on bee functional diversity and functional richness. We focused our study on solitary bees in a typical agricultural area in the Northeast of Germany. Our results showed positive effects with at least 25% of virtually implemented agricultural buffer zones. However, higher amounts of ABZs of at least 75% should be considered to ensure a sufficient increase in Shannon diversity and decrease in quasi-extinction risks. These high amounts of ABZs represent effective conservation measures to safeguard the stability of pollination services provided by solitary bee species. As the model structure can be easily adapted to other mobile species in agricultural landscapes, our community approach offers the chance to compare the effectiveness of conservation measures also for other pollinator communities in future.

Bayesian Multi-Targets Strategy to Track Apis mellifera Movements at Colony Level

Simple Summary

The number of honey bee, Apis mellifera L., colonies has reduced around the globe, and one potential cause is their unintended exposure to sublethal stressors such as agricultural pesticides. The quantification of such effects at colony level is a very complex task due to the innumerable collective activities done by the individual within colonies. Here, we present a Bayesian and computational approach capable of tracking the movements of bees within colonies, which allows the comparison of the collective activities of colonies that received bees previously exposed to uncontaminated diets or to diets containing sublethal concentrations of an agricultural pesticide (a commercial formulation containing the synthetic fungicides thiophanate-methyl and chlorothalonil). Our Bayesian tracking technique proved successful and superior to comparable algorithms, allowing the estimation of dynamical parameters such as entropy and kinetic energy. Our efforts demonstrated that fungicide-contaminated colonies behaved differently from uncontaminated colonies, as the former exhibited anticipated collective activities in peripheral hive areas and had reduced swarm entropy and kinetic energies. Such findings may facilitate the electronic monitoring of potential unintended effects in social pollinators, at colony level, mediated by environmental stressors (e.g., pesticides, electromagnetic fields, noise, and light intensities) alone or in combination.

Abstract

Interactive movements of bees facilitate the division and organization of collective tasks, notably when they need to face internal or external environmental challenges. Here, we present a Bayesian and computational approach to track the movement of several honey bee, Apis mellifera, workers at colony level. We applied algorithms that combined tracking and Kernel Density Estimation (KDE), allowing measurements of entropy and Probability Distribution Function (PDF) of the motion of tracked organisms. We placed approximately 200 recently emerged and labeled bees inside an experimental colony, which consists of a mated queen, approximately 1000 bees, and a naturally occurring beehive background. Before release, labeled bees were fed for one hour with uncontaminated diets or diets containing a commercial mixture of synthetic fungicides (thiophanate-methyl and chlorothalonil). The colonies were filmed (12 min) at the 1st hour, 5th and 10th days after the bees’ release. Our results revealed that the algorithm tracked the labeled bees with great accuracy. Pesticide-contaminated colonies showed anticipated collective activities in peripheral hive areas, far from the brood area, and exhibited reduced swarm entropy and energy values when compared to uncontaminated colonies. Collectively, our approach opens novel possibilities to quantify and predict potential alterations mediated by pollutants (e.g., pesticides) at the bee colony-level.

Memory-guided foraging and landscape design interact to determine ecosystem services

Many studies examine how the landscape affects memory-informed movement patterns, but very few examine how memory-informed foragers influence the landscape. This reverse relationship is an important factor in preventing the continued decline of many ecosystem services. We investigate this question in the context of crop pollination services by wild bees, a critical ecosystem service that is in steep decline. Many studies suggest that adding wild flower patches near crops can result in higher crop pollination services, but specific advice pertaining to the optimal location and density of these wild flower patches is lacking, as well as any estimate of the expected change in crop pollination services. In this work, we seek to understand what is the optimal placement of a flower patch relative to a single crop field, during crop bloom and considering spatial factors alone. We develop an individual based model of memory-based foraging by bumble bees to simulate bee movement from a single nest while the crop is in bloom, and measure the resulting crop pollination services. We consider a single crop field enhanced with a wild flower patch in a variable location, and measure crop flower visitation over the course of a single day. We analyze the pollination intensity and spatial distribution of flower visits to determine optimal wild flower patch placement for an isolated crop field. We find that the spatial arrangement of crop and wild flower patch have a significant effect on the number of crop flower visits, and that these effects arise from the memory-informed foraging pattern. The most effective planting locations are either in the centre of the crop field or on the far side of the crop field, away from the single bumble bee nest.

Pollen Source Richness May Be a Poor Predictor of Bumblebee (Bombus terrestris) Colony Growth

Agricultural intensification has drastically altered foraging landscapes for bees, with large-scale crop monocultures associated with floral diversity loss. Research on bumblebees and honeybees has shown individuals feeding on pollen from a low richness of floral sources can experience negative impacts on health and longevity relative to higher pollen source richness of similar protein concentrations. Florally rich landscapes are thus generally assumed to better support social bees. Yet, little is known about whether the effects of reduced pollen source richness can be mitigated by feeding on pollen with higher crude protein concentration, and importantly how variation in diet affects whole colony growth, rearing decisions and sexual production. Studying queen-right bumblebee (Bombus terrestris) colonies, we monitored colony development under a polyfloral pollen diet or a monofloral pollen diet with 1.5-1.8 times higher crude protein concentration. Over 6 weeks, we found monofloral colonies performed better for all measures, with no apparent long-term effects on colony mass or worker production, and a higher number of pupae in monofloral colonies at the end of the experiment. Unexpectedly, polyfloral colonies showed higher mortality, and little evidence of any strategy to counteract the effects of reduced protein; with fewer and lower mass workers being reared, and males showing a similar trend. Our findings (i) provide well-needed daily growth dynamics of queenright colonies under varied diets, and (ii) support the view that pollen protein content in the foraging landscape rather than floral species richness per se is likely a key driver of colony health and success.

Review on mathematical modeling of honeybee population dynamics

Honeybees have an irreplaceable position in agricultural production and the stabilization of natural ecosystems. Unfortunately, honeybee populations have been declining globally. Parasites, diseases, poor nutrition, pesticides, and climate changes contribute greatly to the global crisis of honeybee colony losses. Mathematical models have been used to provide useful insights on potential factors and important processes for improving the survival rate of colonies. In this review, we present various mathematical tractable models from different aspects: 1) simple bee-only models with features such as age segmentation, food collection, and nutrient absorption; 2) models of bees with other species such as parasites and/or pathogens; and 3) models of bees affected by pesticide exposure. We aim to review those mathematical models to emphasize the power of mathematical modeling in helping us understand honeybee population dynamics and its related ecological communities. We also provide a review of computational models such as VARROAPOP and BEEHAVE that describe the bee population dynamics in environments that include factors such as temperature, rainfall, light, distance and quality of food, and their effects on colony growth and survival. In addition, we propose a future outlook on important directions regarding mathematical modeling of honeybees. We particularly encourage collaborations between mathematicians and biologists so that mathematical models could be more useful through validation with experimental data.

Modeling scale up of anthropogenic impacts from individual pollinator behavior to pollination systems

Understanding how anthropogenic disturbances affect plant-pollinator systems has important implications for the conservation of biodiversity and ecosystem functioning. Previous laboratory studies show that pesticides and pathogens, which have been implicated in the rapid global decline of pollinators over recent years, can impair behavioral processes needed for pollinators to adaptively exploit floral resources and effectively transfer pollen among plants. However, the potential for these sublethal stressor effects on pollinator-plant interactions at the individual level to scale up into changes to the dynamics of wild plant and pollinator populations at the system level remains unclear. We developed an empirically parameterized agent-based model of a bumblebee pollination system called SimBee to test for effects of stressor-induced decreases in the memory capacity and information processing speed of individual foragers on bee abundance (scenario 1), plant diversity (scenario 2), and bee-plant system stability (scenario 3) over 20 virtual seasons. Modeling of a simple pollination network of a bumblebee and four co-flowering bee-pollinated plant species indicated that bee decline and plant species extinction events could occur when only 25% of the forager population showed cognitive impairment. Higher percentages of impairment caused 50% bee loss in just five virtual seasons and system-wide extinction events in less than 20 virtual seasons under some conditions. Plant species extinctions occurred regardless of bee population size, indicating that stressor-induced changes to pollinator behavior alone could drive species loss from plant communities. These findings indicate that sublethal stressor effects on pollinator behavioral mechanisms, although seemingly insignificant at the level of individuals, have the cumulative potential in principle to degrade plant-pollinator species interactions at the system level. Our work highlights the importance of an agent-based modeling approach for the identification and mitigation of anthropogenic impacts on plant-pollinator systems.

A model of resource partitioning between foraging bees based on learning

Central place foraging pollinators tend to develop multi-destination routes (traplines) to exploit patchily distributed plant resources. While the formation of traplines by individual pollinators has been studied in detail, how populations of foragers use resources in a common area is an open question, difficult to address experimentally. We explored conditions for the emergence of resource partitioning among traplining bees using agent-based models built from experimental data of bumblebees foraging on artificial flowers. In the models, bees learn to develop routes as a consequence of feedback loops that change their probabilities of moving between flowers. While a positive reinforcement of movements leading to rewarding flowers is sufficient for the emergence of resource partitioning when flowers are evenly distributed, the addition of a negative reinforcement of movements leading to unrewarding flowers is necessary when flowers are patchily distributed. In environments with more complex spatial structures, the negative experiences of individual bees on flowers favour spatial segregation and efficient collective foraging. Our study fills a major gap in modelling pollinator behaviour and constitutes a unique tool to guide future experimental programs.

Pathways for Novel Epidemiology: Plant-Pollinator-Pathogen Networks and Global Change

Multiple global change pressures, and their interplay, cause plant-pollinator extinctions and modify species assemblages and interactions. This may alter the risks of pathogen host shifts, intra- or interspecific pathogen spread, and emergence of novel population or community epidemics. Flowers are hubs for pathogen transmission. Consequently, the structure of plant-pollinator interaction networks may be pivotal in pathogen host shifts and modulating disease dynamics. Traits of plants, pollinators, and pathogens may also govern the interspecific spread of pathogens. Pathogen spillover-spillback between managed and wild pollinators risks driving the evolution of virulence and community epidemics. Understanding this interplay between host-pathogen dynamics and global change will be crucial to predicting impacts on pollinators and pollination underpinning ecosystems and human wellbeing.

Impacts of Neonicotinoids on the Bumble Bees Bombus terrestris and Bombus impatiens Examined through the Lens of an Adverse Outcome Pathway Framework

Bumble bees (Bombus sp.) are important pollinators for agricultural systems and natural landscapes and have faced population declines globally in recent decades. Neonicotinoid pesticides have been implicated as one of the reasons for the population reductions in bumble bees and other pollinators due to their widespread use, specificity to the invertebrate nervous system, and toxicity to bees. Adverse outcome pathways (AOPs) are used to describe the mechanism of action of a toxicant through sequential levels of biological organization to understand the key events that occur for a given adverse outcome. We used the AOP framework to organize and present the current literature available on the impacts of neonicotinoids on bumble bees. The present review focuses on Bombus terrestris and B. impatiens, the 2 most commonly studied bumble bees due to their commercial availability. Our review does not seek to describe an AOP for the molecular initiating event shared by neonicotinoids, but rather aims to summarize the current literature and determine data gaps for the Bombus research community to address. Overall, we highlight a great need for additional studies, especially those examining cellular and organ responses in bumble bees exposed to neonicotinoids. Environ Toxicol Chem 2021;40:309-322. © 2020 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Overview of the testing and assessment of effects of microbial pesticides on bees: strengths, challenges and perspectives

Currently, there is a growing interest in developing biopesticides and increasing their share in the plant protection market as sustainable tools in integrated pest management (IPM). Therefore, it is important that regulatory requirements are consistent and thorough in consideration of biopesticides' unique properties. While microbial pesticides generally have a lower risk profile, they present special challenges in non-target organism testing and risk assessment since, in contrast to chemical pesticides, their modes of action include infectivity and pathogenicity rather than toxicity alone. For this reason, non-target organism testing guidelines designed for conventional chemical pesticides are not necessarily directly applicable to microbial pesticides. Many stakeholders have recognised the need for improvements in the guidance available for testing microbial pesticides with honey bees, particularly given the increasing interest in development and registration of microbial pesticides and concerns over risks to pollinators. This paper provides an overview of the challenges with testing and assessment of the effects of microbial pesticides on honey bees (Apis mellifera), which have served as a surrogate for both Apis and non-Apis bees, and provides a foundation toward developing improved testing methods.

Honey bee colony performance affected by crop diversity and farmland structure: a modeling framework

Forage availability has been suggested as one driver of the observed decline in honey bees. However, little is known about the effects of its spatiotemporal variation on colony success. We present a modeling framework for assessing honey bee colony viability in cropping systems. Based on two real farmland structures, we developed a landscape generator to design cropping systems varying in crop species identity, diversity, and relative abundance. The landscape scenarios generated were evaluated using the existing honey bee colony model BEEHAVE, which links foraging to in-hive dynamics. We thereby explored how different cropping systems determine spatiotemporal forage availability and, in turn, honey bee colony viability (e.g., time to extinction, TTE) and resilience (indicated by, e.g., brood mortality). To assess overall colony viability, we developed metrics, P_H and P_P, which quantified how much nectar and pollen provided by a cropping system per year was converted into a colony's adult worker population. Both crop species identity and diversity determined the temporal continuity in nectar and pollen supply and thus colony viability. Overall farmland structure and relative crop abundance were less important, but details mattered. For monocultures and for four-crop species systems composed of cereals, oilseed rape, maize, and sunflower, P_H and P_P were below the viability threshold. Such cropping systems showed frequent, badly timed, and prolonged forage gaps leading to detrimental cascading effects on life stages and in-hive work force, which critically reduced colony resilience. Four-crop systems composed of rye-grass-dandelion pasture, trefoil-grass pasture, sunflower, and phacelia ensured continuous nectar and pollen supply resulting in TTE > 5 yr, and P_H (269.5 kg) and P_P (108 kg) being above viability thresholds for 5 yr. Overall, trefoil-grass pasture, oilseed rape, buckwheat, and phacelia improved the temporal continuity in forage supply and colony's viability. Our results are hypothetical as they are obtained from simplified landscape settings, but they nevertheless match empirical observations, in particular the viability threshold. Our framework can be used to assess the effects of cropping systems on honey bee viability and to develop land-use strategies that help maintain pollination services by avoiding prolonged and badly timed forage gaps.

OneHealth implications of infectious diseases of wild and managed bees

The OneHealth approach aims to further our understanding of the drivers of human, animal and environmental health, and, ultimately, to improve them by combining approaches and knowledge from medicine, biology and fields beyond. Wild and managed bees are essential pollinators of crops and wild flowers. Their health thus directly impacts on human and environmental health. At the same time, these bee species represent highly amenable and relevant model organisms for a OneHealth approach that aims to study fundamental epidemiological questions. In this review, we focus on how infectious diseases of wild and managed bees can be used as a OneHealth model system, informing fundamental questions on ecological immunology and disease transmission, while addressing how this knowledge can be used to tackle the issues facing pollinator health.

Lethal and Sublethal Effects of Pyriproxyfen on Apis and Non-Apis Bees

Pyriproxyfen is a juvenile hormone mimic used extensively worldwide to fight pests in agriculture and horticulture. It also has numerous applications as larvicide in vector control. The molecule disrupts metamorphosis and adult emergence in the target insects. The same types of adverse effects are expected on non-target insects. In this context, the objective of this study was to evaluate the existing information on the toxicity of pyriproxyfen on the honey bee (Apis mellifera) and non-Apis bees (bumble bees, solitary bees, and stingless bees). The goal was also to identify the gaps necessary to fill. Thus, whereas the acute and sublethal toxicity of pyriproxyfen against A. mellifera is well-documented, the information is almost lacking for the non-Apis bees. The direct and indirect routes of exposure of the non-Apis bees to pyriproxyfen also need to be identified and quantified. More generally, the impacts of pyriproxyfen on the reproductive success of the different bee species have to be evaluated as well as the potential adverse effects of its metabolites.

The importance of competition between insect pollinators in the Anthropocene

Resource competition likely plays an important role in some insect pollinator declines and in shaping effects of environmental change on pollination services. Past research supports that competition for floral resources affects bee foragers, but mostly with observational evidence and rarely linking foraging with population change. An increasing number of studies ask whether resources limit pollinator populations, using field measurements of reproductive success, time series and models. Findings generally support positive effects of floral resources, but also highlight the potential importance of nest site availability and parasitism. In parallel, recent experiments strengthen evidence that competition reduces access to floral resources. Developing common currencies for quantifying floral resources and integrating analyses of multiple limiting factors will further strengthen our understanding of competitive interactions and their effects in the Anthropocene.

Lethal and sublethal effects of toxicants on bumble bee populations: a modelling approach

Pollinator decline worldwide is well-documented; globally, chemical pesticides (especially the class of pesticides known as neonicotinoids) have been implicated in hymenopteran decline, but the mechanics and drivers of population trends and dynamics of wild bees is poorly understood. Declines and shifts in community composition of bumble bees (Bombus spp.) have been documented in North America and Europe, with a suite of lethal and sub-lethal effects of pesticides on bumble bee populations documented. We employ a mathematical model parameterized with values taken from the literature that uses differential equations to track bumble bee populations through time in order to attain a better understanding of toxicant effects on a developing colony of bumble bees. We use a delay differential equation (DDE) model, which requires fewer parameter estimations than agent-based models while affording us the ability to explicitly describe the effect of larval incubation and colony history on population outcomes. We explore how both lethal and sublethal effects such as reduced foraging ability may combine to affect population outcomes, and discuss the implications for the protection and conservation of ecosystem services.

Global Trends in Bumble Bee Health

Bumble bees (Bombus) are unusually important pollinators, with approximately 260 wild species native to all biogeographic regions except sub-Saharan Africa, Australia, and New Zealand. As they are vitally important in natural ecosystems and to agricultural food production globally, the increase in reports of declining distribution and abundance over the past decade has led to an explosion of interest in bumble bee population decline. We summarize data on the threat status of wild bumble bee species across biogeographic regions, underscoring regions lacking assessment data. Focusing on data-rich studies, we also synthesize recent research on potential causes of population declines. There is evidence that habitat loss, changing climate, pathogen transmission, invasion of nonnative species, and pesticides, operating individually and in combination, negatively impact bumble bee health, and that effects may depend on species and locality. We distinguish between correlational and causal results, underscoring the importance of expanding experimental research beyond the study of two commercially available species to identify causal factors affecting the diversity of wild species.

The Impact of Pesticides on Flower-Visiting Insects: A Review with Regard to European Risk Assessment

Flower-visiting insects (FVIs) are an ecologically diverse group of mobile, flying species that should be protected from pesticide effects according to European policy. However, there is an ongoing decline of FVI species, partly caused by agricultural pesticide applications. Therefore, the risk assessment framework needs to be improved. We synthesized the peer-reviewed literature on FVI groups and their ecology, habitat, exposure to pesticides, and subsequent effects. The results show that FVIs are far more diverse than previously thought. Their habitat, the entire agricultural landscape, is potentially contaminated with pesticides through multiple pathways. Pesticide exposure of FVIs at environmentally realistic levels can cause population-relevant adverse effects. This knowledge was used to critically evaluate the European regulatory framework of exposure and effect assessment. The current risk assessment should be amended to incorporate specific ecological properties of FVIs, that is, traits. We present data-driven tools to improve future risk assessments by making use of trait information. There are major knowledge gaps concerning the general investigation of groups other than bees, the collection of comprehensive data on FVI groups and their ecology, linking habitat to FVI exposure, and study of previously neglected complex population effects. This is necessary to improve our understanding of FVIs and facilitate the development of a more protective FVI risk assessment. Environ Toxicol Chem 2019;38:2355-2370. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

MALDI-MS Profiling to Address Honey Bee Health Status under Bacterial Challenge through Computational Modeling

Honey bees play a critical role in the maintenance of plant biodiversity and sustainability of food webs. In the past few decades, bees have been subjected to biotic and abiotic threats causing various colony disorders. Therefore, monitoring solutions to help beekeepers to improve bee health are necessary. Matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS) profiling has emerged within this decade as a powerful tool to identify in routine micro-organisms and is currently used in real-time clinical diagnosis. MALDI BeeTyping is developed to monitor significant hemolymph molecular changes in honey bees upon infection with a series of entomopathogenic Gram-positive and -negative bacteria. A Serratia marcescens strain isolated from one naturally infected honey bee collected from the field is also considered. A series of hemolymph molecular mass fingerprints is individually recorded and to the authors' knowledge, the first computational model harboring a predictive score of 97.92% and made of nine molecular signatures that discriminate and classify the honey bees' systemic response to the bacteria is built. Hence, the model is challenged by classifying a training set of hemolymphs and an overall recognition of 91.93% is obtained. Through this work, a novel, time and cost saving high-throughput strategy that addresses honey bee health on an individual scale is introduced.

Are honeybees suitable surrogates for use in pesticide risk assessment for non-Apis bees?

Historically, bee regulatory risk assessment for pesticides has centred on the European honeybee (Apis mellifera), primarily due to its availability and adaptability to laboratory conditions. Recently, there have been efforts to develop a battery of laboratory toxicity tests for a range of non-Apis bee species to directly assess the risk to them. However, it is not clear whether the substantial investment associated with the development and implementation of such routine screening will actually improve the level of protection of non-Apis bees. We argue, using published acute toxicity data from a range of bee species and standard regulatory exposure scenarios, that current first-tier honeybee acute risk assessment schemes utilised by regulatory authorities are protective of other bee species and further tests should be conducted only in cases of concern. We propose similar analysis of alternative exposure scenarios (chronic and developmental) once reliable data for non-Apis bees are available to expand our approach to these scenarios. In addition, we propose that in silico (simulation) approaches can then be used to address population-level effects in more field-realistic scenarios. Such an approach could lead to a protective, but also workable, risk assessment for non-Apis species while contributing to pollination security in agricultural landscapes around the globe. © 2019 Society of Chemical Industry.

Bombus terrestris in a mass-flowering pollinator-dependent crop: A mutualistic relationship?

Bumblebees (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.

Bumble-BEEHAVE: A systems model for exploring multifactorial causes of bumblebee decline at individual, colony, population and community level

World‐wide declines in pollinators, including bumblebees, are attributed to a multitude of stressors such as habitat loss, resource availability, emerging viruses and parasites, exposure to pesticides, and climate change, operating at various spatial and temporal scales. Disentangling individual and interacting effects of these stressors, and understanding their impact at the individual, colony and population level are a challenge for systems ecology. Empirical testing of all combinations and contexts is not feasible. A mechanistic multilevel systems model (individual‐colony‐population‐community) is required to explore resilience mechanisms of populations and communities under stress.

We present a model which can simulate the growth, behaviour and survival of six UK bumblebee species living in any mapped landscape. Bumble‐BEEHAVE simulates, in an agent‐based approach, the colony development of bumblebees in a realistic landscape to study how multiple stressors affect bee numbers and population dynamics. We provide extensive documentation, including sensitivity analysis and validation, based on data from literature. The model is freely available, has flexible settings and includes a user manual to ensure it can be used by researchers, farmers, policy‐makers, NGOs or other interested parties.

Model outcomes compare well with empirical data for individual foraging behaviour, colony growth and reproduction, and estimated nest densities.

Simulating the impact of reproductive depression caused by pesticide exposure shows that the complex feedback mechanisms captured in this model predict higher colony resilience to stress than suggested by a previous, simpler model.

Synthesis and applications. The Bumble‐BEEHAVE model represents a significant step towards predicting bumblebee population dynamics in a spatially explicit way. It enables researchers to understand the individual and interacting effects of the multiple stressors affecting bumblebee survival and the feedback mechanisms that may buffer a colony against environmental stress, or indeed lead to spiralling colony collapse. The model can be used to aid the design of field experiments, for risk assessments, to inform conservation and farming decisions and for assigning bespoke management recommendations at a landscape scale.

The Bumble‐BEEHAVE model represents a significant step towards predicting bumblebee population dynamics in a spatially explicit way. It enables researchers to understand the individual and interacting effects of the multiple stressors affecting bumblebee survival and the feedback mechanisms that may buffer a colony against environmental stress, or indeed lead to spiralling colony collapse. The model can be used to aid the design of field experiments, for risk assessments, to inform conservation and farming decisions and for assigning bespoke management recommendations at a landscape scale.