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

The impact of multifactorial stress combination on plants, crops, and ecosystems: how should we prepare for what comes next?

The complexity of environmental conditions encountered by plants in the field, or in nature, is gradually increasing due to anthropogenic activities that promote global warming, climate change, and increased levels of pollutants. While in the past it seemed sufficient to study how plants acclimate to one or even two different stresses affecting them simultaneously, the complex conditions developing on our planet necessitate a new approach of studying stress in plants: Acclimation to multiple stress conditions occurring concurrently or consecutively (termed, multifactorial stress combination [MFSC]). In an initial study of the plant response to MFSC, conducted with Arabidopsis thaliana seedlings subjected to an MFSC of six different abiotic stresses, it was found that with the increase in the number and complexity of different stresses simultaneously impacting a plant, plant growth and survival declined, even if the effects of each stress involved in such MFSC on the plant was minimal or insignificant. In three recent studies, conducted with different crop plants, MFSC was found to have similar effects on a commercial rice cultivar, a maize hybrid, tomato, and soybean, causing significant reductions in growth, biomass, physiological parameters, and/or yield traits. As the environmental conditions on our planet are gradually worsening, as well as becoming more complex, addressing MFSC and its effects on agriculture and ecosystems worldwide becomes a high priority. In this review, we address the effects of MFSC on plants, crops, agriculture, and different ecosystems worldwide, and highlight potential avenues to enhance the resilience of crops to MFSC.

Protective Role of Bergamot Polyphenolic Fraction (BPF) against Deltamethrin Toxicity in Honeybees (Apis mellifera)

Pesticide-induced poisoning phenomena are a serious problem for beekeeping and can cause large losses of honeybee populations due to acute and sub-acute poisoning. The reduced responsiveness of honeybees to the damage caused by pesticides used in agriculture can be traced back to a general qualitative and quantitative impoverishment of the nectar resources of terrestrial ecosystems. Malnutrition is associated with a decline in the functionality of the immune system and the systems that are delegated to the detoxification of the organism. This research aimed to verify whether bergamot polyphenolic extract (BPF) could have protective effects against poisoning by the pyrethroid pesticide deltamethrin. The studies were conducted with caged honeybees under controlled conditions. Sub-lethal doses of pesticides and related treatments for BPF were administered. At a dose of 21.6 mg/L, deltamethrin caused mortality in all treated subjects (20 caged honeybees) after one day of administration. The groups where BPF (1 mg/kg) was added to the toxic solution recorded the survival of honeybees by up to three days. Comparing the honeybees of the groups in which the BPF-deltamethrin association was added to the normal diet (sugar solution) with those in which deltamethrin alone was added to the normal diet, the BPF group had a statistically significant reduction in the honeybee mortality rate (p ≤ 0.05) and a greater consumption of food. Therefore, it can be argued that the inclusion of BPF and its constituent antioxidants in the honeybee diet reduces toxicity and oxidative stress caused by oral intake of deltamethrin. Furthermore, it can be argued that BPF administration could compensate for metabolic energy deficits often induced by the effects of malnutrition caused by environmental degradation and standard beekeeping practices.

Prevalence of Varroa destructor in Honeybee (Apis mellifera) Farms and Varroosis Control Practices in Southern Italy

The majority of honeybee farms in industrialized countries currently base their Varroa destructor control programs on the use of acaricides in conjunction with other management practices. However, the outcomes of these practices are often misunderstood and have only been studied to a limited extent. Better yields are guaranteed by having hives with low infection levels in the spring. Therefore, it is crucial to understand which beekeeping practices can result in increased control effectiveness. This study aimed to analyze the potential effects of environmental factors and beekeeping practices on the dynamics of V. destructor population. Experimental evidence was obtained by interpolating percentage infestation data from diagnoses conducted on several apiaries in the Calabria region (Southern Italy) with data acquired from a questionnaire on pest control strategies. Data on climatic temperature during the different study periods were also taken into account. The study was conducted over two years and involved 84 Apis mellifera farms. For each apiary, the diagnosis of infestation was made on a minimum of 10 hives. In total, 840 samples of adult honeybees were analyzed in the field to determine the level of infestation. In 2020, 54.7% of the inspected apiaries tested positive for V. destructor, and in 2021, 50% tested positive, according to a study of the field test findings (taking into account a threshold of 3% in July). A significant effect of the number of treatments on parasite prevalence was found. The results showed a significant reduction in the infestation rate in apiaries that received more than two treatments each year. Furthermore, it was shown that management practices, such as drone brood removal and frequent queen replacement, have a statistically significant impact on the infestation rate. The analysis of the questionnaires revealed some critical issues. In particular, only 50% of the interviewed beekeepers diagnosed infestation on samples of adult bees, and only 69% practiced drug rotation. In conclusion, it is only possible to maintain the infestation rate at an acceptable threshold by implementing integrated pest management (IPM) programs and using good beekeeping practices (GBPs).

Hydrocarbons and other risks in a beekeeping area of México: the precautionary principle for prevention and biotechnology for remediation

The Yucatan Peninsula is the most important beekeeping region. However, the presence of hydrocarbons and pesticides violates the human right to a healthy environment twice over; it can affect human beings directly due to its toxicological characteristics, but it also constitutes a risk, not very well dimensioned, regarding the loss of biodiversity of the ecosystem via the impact on pollination. On the other hand, the precautionary principle obliges the authorities to prevent damage to the ecosystem that may be caused by the productive activity of individuals. Although there are studies that separately warn about the decrease of bees in the Yucatan due to industrial activity, this work has the novelty of presenting an intersectoral analysis of the risk that includes the soy industry, the swine industry and the tourist industry. The latter incorporates a new risk not considered until now, which is the presence of hydrocarbons in the ecosystem. Additionally, we can demonstrate that hydrocarbons, such as diesel and gasoline, should be avoided when using no genetically modified organisms (GMOs) in bioreactors. The objective of this work was to propose the precautionary principle around the risks in a beekeeping area and to propose biotechnology without using GMOs.

Honey bee colony loss linked to parasites, pesticides and extreme weather across the United States

Honey bee (Apis mellifera) colony loss is a widespread phenomenon with important economic and biological implications, whose drivers are still an open matter of investigation. We contribute to this line of research through a large-scale, multi-variable study combining multiple publicly accessible data sources. Specifically, we analyzed quarterly data covering the contiguous United States for the years 2015-2021, and combined open data on honey bee colony status and stressors, weather data, and land use. The different spatio-temporal resolutions of these data are addressed through an up-scaling approach that generates additional statistical features which capture more complex distributional characteristics and significantly improve modeling performance. Treating this expanded feature set with state-of-the-art feature selection methods, we obtained findings that, nation-wide, are in line with the current knowledge on the aggravating roles of Varroa destructor and pesticides in colony loss. Moreover, we found that extreme temperature and precipitation events, even when controlling for other factors, significantly impact colony loss. Overall, our results reveal the complexity of biotic and abiotic factors affecting managed honey bee colonies across the United States.

The BEEHAVEecotox Model-Integrating a Mechanistic Effect Module into the Honeybee Colony Model

Mechanistic effect models are powerful tools for extrapolating from laboratory studies to field conditions. For bees, several good models are available that can simulate colony dynamics. Controlled and reliable experimental systems are also available to estimate the inherent toxicity of pesticides to individuals. However, there is currently no systematic and mechanistic way of linking the output of experimental ecotoxicological testing to bee models for bee risk assessment. We introduce an ecotoxicological module that mechanistically links exposure with the hazard profile of a pesticide for individual honeybees so that colony effects emerge. This mechanistic link allows the translation of results from standard laboratory studies to relevant parameters and processes for simulating bee colony dynamics. The module was integrated into the state-of-the-art honeybee model BEEHAVE. For the integration, BEEHAVE was adapted to mechanistically link the exposure and effects on different cohorts to colony dynamics. The BEEHAVEecotox model was tested against semifield (tunnel) studies, which were deemed the best study type to test whether BEEHAVEecotox predicted realistic effect sizes under controlled conditions. Two pesticides used as toxic standards were chosen for this validation to represent two different modes of action: acute mortality of foragers and chronic brood effects. The ecotoxicological module was able to predict effect sizes in the tunnel studies based on information from standard laboratory tests. In conclusion, the BEEHAVEecotox model is an excellent tool to be used for honeybee risk assessment, interpretation of field and semifield studies, and exploring the efficiency of different mitigation measures. The principles for exposure and effect modules are portable and could be used for any well-constructed honeybee model. Environ Toxicol Chem 2022;41:2870-2882. © 2022 Bayer AG & Sygenta, et al. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Citizen science monitoring reveals links between honeybee health, pesticide exposure and seasonal availability of floral resources

We use a national citizen science monitoring scheme to quantify how agricultural intensification affects honeybee diet breadth (number of plant species). To do this we used DNA metabarcoding to identify the plants present in 527 honey samples collected in 2019 across Great Britain. The species richness of forage plants was negatively correlated with arable cropping area, although this was only found early in the year when the abundance of flowering plants was more limited. Within intensively farmed areas, honeybee diets were dominated by Brassica crops (including oilseed rape). We demonstrate how the structure and complexity of honeybee foraging relationships with plants is negatively affected by the area of arable crops surrounding hives. Using information collected from the beekeepers on the incidence of an economically damaging bee disease (Deformed Wing Virus) we found that the occurrence of this disease increased where bees foraged in agricultural land where there was a high use of foliar insecticides. Understanding impacts of land use on resource availability is fundamental to assessing long-term viability of pollinator populations. These findings highlight the importance of supporting temporally timed resources as mitigation strategies to support wider pollinator population viability.

Hornets and Honey Bees: A Coevolutionary Arms Race between Ancient Adaptations and New Invasive Threats

Hornets and honey bees have a long history of coevolution resulting in a plethora of captivating adaptations and counteradaptations between predator and prey. From simple physiological mechanisms to complex behavioral strategies, some Vespa hornets have specialized in hunting honey bees, while the latter have put in place effective defenses to counteract their attack. Both hornets and honey bees have evolved the ability to detect the odors and the pheromones emitted by the other to locate the prey or to spot foraging predators. Hornets often rely on their bigger size, heavily armored body and destructive attacks, while honey bees differentiated collective defense responses finely coordinated to deter or kill the hornet menace. However, when new species of hornets and honey bees come into contact, the absence of coevolution can have a heavy impact on the defenseless bees. The evolutionary arms race between hornets and honey bees provides not only compelling examples of adaptations and counteradaptations between predator and prey, but could also represent a starting point for the development of effective and sustainable strategies to protect honey bees and beekeeping activities and to control invasive alien species of hornets.

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.

Robust Variable Selection with Optimality Guarantees for High-Dimensional Logistic Regression

High-dimensional classification studies have become widespread across various domains. The large dimensionality, coupled with the possible presence of data contamination, motivates the use of robust, sparse estimation methods to improve model interpretability and ensure the majority of observations agree with the underlying parametric model. In this study, we propose a robust and sparse estimator for logistic regression models, which simultaneously tackles the presence of outliers and/or irrelevant features. Specifically, we propose the use of L0-constraints and mixed-integer conic programming techniques to solve the underlying double combinatorial problem in a framework that allows one to pursue optimality guarantees. We use our proposal to investigate the main drivers of honey bee (Apis mellifera) loss through the annual winter loss survey data collected by the Pennsylvania State Beekeepers Association. Previous studies mainly focused on predictive performance, however our approach produces a more interpretable classification model and provides evidence for several outlying observations within the survey data. We compare our proposal with existing heuristic methods and non-robust procedures, demonstrating its effectiveness. In addition to the application to honey bee loss, we present a simulation study where our proposal outperforms other methods across most performance measures and settings.

Japanese Honeybees (Apis cerana japonica Radoszkowski, 1877) May Be Resilient to Land Use Change

Simple Summary

Pollinators are threatened globally by growing urban sprawl and agriculture. The Western Honeybee (Apis mellifera) readily adapts to whatever food is available, so people have made it the most widely distributed pollinator across the world. Previous research has suggested that the Western Honeybee may be less resilient to land use change outside of its natural range. This study examines a different honeybee species—the Japanese Honeybee (Apis cerana japonica). Unlike the Western Honeybee, this species is found almost exclusively in its natural range in Japan. Consequently, it may be better adapted to its local food sources and therefore more resilient. Working in southern Japan, in the Nagasaki and Saga prefectures, we looked at the nectar and pollen that the Japanese Honeybee feeds on. Their food intake was then examined in relation to local land use composition. We found minimal impact of increasing urban sprawl on the forage of the Japanese Honeybee. This goes against previous studies on the Western Honeybee elsewhere in the world. Though in need of a direct comparison with Western Honeybee, these preliminary results could be due to differences in urban green infrastructure in Japan, or due to an adaptation by the Japanese honeybee to its surroundings.

Abstract

Pollinators are being threatened globally by urbanisation and agricultural intensification, driven by a growing human population. Understanding these impacts on landscapes and pollinators is critical to ensuring a robust pollination system. Remote sensing data on land use attributes have previously linked honeybee nutrition to land use in the Western Honeybee (Apis mellifera L.). Here, we instead focus on the less commonly studied Apis cerana japonica—the Japanese Honeybee. Our study presents preliminary data comparing forage (honey and pollen) with land use across a rural-urban gradient from 22 sites in Kyushu, southern Japan. Honey samples were collected from hives between June 2018 and August 2019. Pollen were collected and biotyped from hives in urban and rural locations (n = 4). Previous studies of honey show substantial variation in monosaccharide content. Our analysis of A. cerana japonica honey found very little variation in glucose and fructose (which accounted for 97% of monosaccharides), despite substantial differences in surrounding forage composition. As expected, we observed temporal variation in pollen foraged by A. cerana japonica, likely dependent on flowering phenology. These preliminary results suggest that the forage and nutrition of A. cerana japonica may not be negatively affected by urban land use. This highlights the need for further comparative studies between A. cerana japonica and A. mellifera as it could suggest a resilience in pollinators foraging in their native range.

Pesticides in honey bee colonies: Establishing a baseline for real world exposure over seven years in the USA

Honey bees Apis mellifera forage in a wide radius around their colony, bringing back contaminated food resources that can function as terrestrial bioindicators of environmental pesticide exposure. Evaluating pesticide exposure risk to pollinators is an ongoing problem. Here we apply five metrics for pesticide exposure risk (prevalence, diversity, concentration, significant pesticide prevalence, and hazard quotient (HQ)) to a nation-wide field study of honey bees, Apis mellifera in the United States. We examined samples from 1055 apiaries over seven years for 218 different pesticide residues and metabolites, determining that bees were exposed to 120 different pesticide products with a mean of 2.78 per sample. Pesticides in pollen were highly prevalent and variable across states. While pesticide diversity increased over time, most detections occurred at levels predicted to be of low risk to colonies. Varroacides contributed most to concentration, followed by fungicides, while insecticides contributed most to diversity above a toxicity threshold. High risk samples contained one of 12 different insecticides or varroacides. Exposures predicted to be low-risk were nevertheless associated with colony morbidity, and low-level fungicide exposures were tied to queen loss, Nosema infection, and brood diseases.

A systems-based approach to the environmental risk assessment of multiple stressors in honey bees

The European Parliament requested EFSA to develop a holistic risk assessment of multiple stressors in honey bees. To this end, a systems-based approach that is composed of two core components: a monitoring system and a modelling system are put forward with honey bees taken as a showcase. Key developments in the current scientific opinion (including systematic data collection from sentinel beehives and an agent-based simulation) have the potential to substantially contribute to future development of environmental risk assessments of multiple stressors at larger spatial and temporal scales. For the monitoring, sentinel hives would be placed across representative climatic zones and landscapes in the EU and connected to a platform for data storage and analysis. Data on bee health status, chemical residues and the immediate or broader landscape around the hives would be collected in a harmonised and standardised manner, and would be used to inform stakeholders, and the modelling system, ApisRAM, which simulates as accurately as possible a honey bee colony. ApisRAM would be calibrated and continuously updated with incoming monitoring data and emerging scientific knowledge from research. It will be a supportive tool for beekeeping, farming, research, risk assessment and risk management, and it will benefit the wider society. A societal outlook on the proposed approach is included and this was conducted with targeted social science research with 64 beekeepers from eight EU Member States and with members of the EU Bee Partnership. Gaps and opportunities are identified to further implement the approach. Conclusions and recommendations are made on a way forward, both for the application of the approach and its use in a broader context.

Markerless tracking of an entire honey bee colony

From cells in tissue, to bird flocks, to human crowds, living systems display a stunning variety of collective behaviors. Yet quantifying such phenomena first requires tracking a significant fraction of the group members in natural conditions, a substantial and ongoing challenge. We present a comprehensive, computational method for tracking an entire colony of the honey bee Apis mellifera using high-resolution video on a natural honeycomb background. We adapt a convolutional neural network (CNN) segmentation architecture to automatically identify bee and brood cell positions, body orientations and within-cell states. We achieve high accuracy (~10% body width error in position, ~10° error in orientation, and true positive rate > 90%) and demonstrate months-long monitoring of sociometric colony fluctuations. These fluctuations include ~24 h cycles in the counted detections, negative correlation between bee and brood, and nightly enhancement of bees inside comb cells. We combine detected positions with visual features of organism-centered images to track individuals over time and through challenging occluding events, recovering ~79% of bee trajectories from five observation hives over 5 min timespans. The trajectories reveal important individual behaviors, including waggle dances and crawling inside comb cells. Our results provide opportunities for the quantitative study of collective bee behavior and for advancing tracking techniques of crowded systems.

Landscape Structure Is a Major Driver of Bee Functional Diversity in Crops

Land-use change is having a negative effect on pollinator communities, and these changes in community structure may have unexpected impacts on the functional composition of those communities. Such changes in functional composition may impact the capacity of these assemblages to deliver pollination services, affecting the reproduction of native and wild plants. However, elucidating those relationships requires studies in multiple spatial scales because effects and consequences are different considering biological groups and interactions. In that sense, by using a multi-trait approach, we evaluated whether the landscape structure and/or local environmental characteristics could explain the functional richness, divergence, and dispersion of bee communities in agroecosystems. In addition, we investigated to what extent this approach helps to predict effects on pollination services. This study was conducted in an agroecosystem situated in the Chapada Diamantina region, State of Bahia, Brazil. Bees were collected using two complementary techniques in 27 sample units. They were classified according to their response traits (e.g., body size, nesting location) and effect traits (e.g., means of pollen transportation, specialty in obtaining resources). The Akaike information criterion was used to select the best models created through the additive combination of landscape descriptors (landscape diversity, mean patch shape, and local vegetation structure) at the local, proximal, and broad landscape levels. Our results indicate that both landscape heterogeneity and configuration matter in explaining the three properties of bee functional diversity. We indicate that functional diversity is positively correlated with compositional and configurational heterogeneity. These results suggest that landscape and local scale management to promote functional diversity in pollinator communities may be an effective mechanism for supporting increased pollination services.

RNA Interference-Mediated Knockdown of Genes Encoding Spore Wall Proteins Confers Protection against Nosema ceranae Infection in the European Honey Bee, Apis mellifera

Nosema ceranae (Opisthosporidia: Microsporidia) is an emergent intracellular parasite of the European honey bee (Apis mellifera) and causes serious Nosema disease which has been associated with worldwide honey bee colony losses. The only registered treatment for Nosema disease is fumagillin-b, and this has raised concerns about resistance and off-target effects. Fumagillin-B is banned from use in honey bee colonies in many countries, particularly in Europe. As a result, there is an urgent need for new and effective therapeutic options to treat Nosema disease in honey bees. An RNA interference (RNAi)-based approach can be a potent strategy for controlling diseases in honey bees. We explored the therapeutic potential of silencing the sequences of two N. ceranae encoded spore wall protein (SWP) genes by means of the RNAi-based methodology. Our study revealed that the oral ingestion of dsRNAs corresponding to SWP8 and SWP12 used separately or in combination could lead to a significant reduction in spore load, improve immunity, and extend the lifespan of N. ceranae-infected bees. The results from the work completed here enhance our understanding of honey bee host responses to microsporidia infection and highlight that RNAi-based therapeutics are a promising treatment for honey bee diseases.

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.

Persistent effects of management history on honeybee colony virus abundances

Infectious diseases are a major threat to both managed and wild pollinators. One key question is how the movement or transplantation of honeybee colonies under different management regimes affects honeybee disease epidemiology. We opportunistically examined any persistent effect of colony management history following relocation by characterising the virus abundances of honeybee colonies from three management histories, representing different management histories: feral, low-intensity management, and high-intensity "industrial" management. The colonies had been maintained for one year under the same approximate 'common garden' condition. Colonies in this observational study differed in their virus abundances according to management history, with the feral population history showing qualitatively different viral abundance patterns compared to colonies from the two managed population management histories; for example, higher abundance of sacbrood virus but lower abundances of various paralysis viruses. Colonies from the high-intensity management history exhibited higher viral abundances for all viruses than colonies from the low-intensity management history. Our results provide evidence that management history has persistent impacts on honeybee disease epidemiology, suggesting that apicultural intensification could be majorly impacting on pollinator health, justifying much more substantial investigation.

Simulating Honey Bee Large-Scale Colony Feeding Studies Using the BEEHAVE Model-Part I: Model Validation

In pesticide risk assessments, semifield studies, such as large-scale colony feeding studies (LSCFSs), are conducted to assess potential risks at the honey bee colony level. However, such studies are very cost and time intensive, and high overwintering losses of untreated control hives have been observed in some studies. Honey bee colony models such as BEEHAVE may provide tools to systematically assess multiple factors influencing colony outcomes, to inform study design, and to estimate pesticide impacts under varying environmental conditions. Before they can be used reliably, models should be validated to demonstrate they can appropriately reproduce patterns observed in the field. Despite the recognized need for validation, methodologies to be used in the context of applied ecological models are not agreed on. For the parameterization, calibration, and validation of BEEHAVE, we used control data from multiple LSCFSs. We conducted detailed visual and quantitative performance analyses as a demonstration of validation methodologies. The BEEHAVE outputs showed good agreement with apiary-specific validation data sets representing the first year of the studies. However, the simulations of colony dynamics in the spring periods following overwintering were identified as less reliable. The comprehensive validation effort applied provides important insights that can inform the usability of BEEHAVE in applications related to higher tier risk assessments. In addition, the validation methodology applied could be used in a wider context of ecological models. Environ Toxicol Chem 2020;39:2269-2285. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Simulating Honey Bee Large-Scale Colony Feeding Studies Using the BEEHAVE Model-Part II: Analysis of Overwintering Outcomes

Large-scale colony feeding studies (LSCFSs) aim to assess potential pesticide exposure to and effects on honey bees at the colony level. However, these studies are sometimes affected by high losses of control colonies, indicating that other stressors may impact colonies and confound the analysis of potential pesticide impacts. We assessed the study design and environmental conditions experienced by the untreated control colonies across 7 LSCFSs conducted in North Carolina (USA). Overwintering success differed considerably among the studies, as did their initial colony conditions, amount and timing of sugar feeding, landscape composition, and weather. To assess the effects of these drivers on control colonies' overwintering success, we applied the mechanistic colony model BEEHAVE. Sugar feedings and initial status of the simulated colonies were more important for fall colony condition than were landscape and weather. Colonies that had larger colony sizes and honey stores in the fall were those that began with larger honey stores, were provided more sugar, and had supplemental feedings before the fall. This information can be used to inform the standardization of a study design, which can increase the likelihood of overwintering survival of controls and help ensure that LSCFSs are comparable. Our study demonstrates how a mechanistic model can be used to inform study designs for higher tier effects studies. Environ Toxicol Chem 2020;39:2286-2297. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Modeling the Influence of Mites on Honey Bee Populations

The Varroa destructor mite has been associated with the recent decline in honey bee populations. While experimental data are crucial in understanding declines, insights can be gained from models of honey bee populations. We add the influence of the V. destructor mite to our existing honey bee model in order to better understand the impact of mites on honey bee colonies. Our model is based on differential equations which track the number of bees in each day in the life of the bee and accounts for differences in the survival rates of different bee castes. The model shows that colony survival is sensitive to the hive grooming rate and reproductive rate of mites, which is enhanced in drone capped cells.

Effects on Some Therapeutical, Biochemical, and Immunological Parameters of Honey Bee (Apis mellifera) Exposed to Probiotic Treatments, in Field and Laboratory Conditions

Simple Summary

Various negative factors contribute to a decline in insect pollinators. The aim of this study was to assess the impact of commercial probiotic EM^® PROBIOTIC FOR BEES on honey bees. The study was conducted in field and laboratory-controlled conditions. In the field, the sugar syrup with 10% of probiotic was administered by spraying or feeding the honey bee colonies in order to evaluate the colonies’ strength and Nosema spp. infection levels. In the laboratory, the adult workers have been fed with sugar syrup supplemented with 2.5, 5, and 10% of EM^® for bees for biochemical and immunological analyses of hemolymph, and with 5 and 10% for measuring the size of hypopharyngeal glands. It was found that following the EM^® for bees administration the Nosema spp. spore counts in colonies were significantly reduced, and colonies’ strength was increased. The results at the individual level showed positive physiological changes in treated groups of adult bees, but, at the same time, a higher mortality rate. Our findings indicate that the EM^® for bees is a promising food additive for nosemosis combating. Therefore, additional emphasis needs to be placed on studies investigating the nutritional requirements crucial to improve and sustain honey bee colonies health.

Abstract

Several negative factors contribute to a decline in the number of insect pollinators. As a novel approach in therapy, we hypothesize that the EM^® for bees could potentially have an important therapeutic and immunomodulatory effect on honey bee colonies. The aim of our study was to evaluate its impact on honey bees at the individual and colony level. This is the first appliance of the commercial probiotic mix EM^® PROBIOTIC FOR BEES in honey bees as economically important social insects. The sugar syrup with 10% of probiotic was administered by spraying or feeding the honey bee colonies in the field conditions, in order to evaluate the infection levels with spores of Nosema spp. and colonies’ strength. Moreover, in laboratory-controlled conditions, in the hoarding cages, adult workers have been fed with sugar syrup supplemented with 2.5, 5, and 10% of EM^® for bees for biochemical and immunological analyses of hemolymph, and with 5 and 10% for measuring the size of hypopharyngeal glands. It was found that following the EM^® for bees administration the Nosema spp. spore counts in colonies were significantly reduced, and colonies’ strength was increased. The results at the individual level showed significant positive physiological changes in treated groups of adult bees, revealing at the same time a higher mortality rate when feeding sugar syrup supplemented with the probiotic.

The effects of diploid male production on honey bee colony evolution and survival

The order Hymenoptera includes most of the eusocial species on the planet. Correlated is the fact that many of the social species within the order are haplodiploid and use complementary sex determination (CSD) to determine the sex of offspring. CSD is the mechanism by why single sex alleles within an organism result in male development (haploid) and mismatched sex alleles develop into females (diploids). Related to this is the production of diploid males: fertilized eggs with matched sex alleles which develop as male instead of female. Honey bees are no exception to this, and as their numbers continue to suffer globally and their genetic diversity lowers, the effects of diploid male production (DMP) may pose an increased risk to the survival of bee colonies. In the present study, we develop a model for diploid male production in a honey bee colony and show that with ample resources, this phenomena has little effect on a colony's health, but there is a limit to the sustainability of a colony suffering from diploid male production. We use our model to show that there were likely no great evolutionary pressures against CSD and DMP in wild honey bees as its effects on colony health in the wild would have been negligible but increased environmental hazards such as pesticides and monoculture crops increase the effects of DMP on colony health.

Mathematical modelling of population and food storage dynamics in a honey bee colony infected with Nosema ceranae

Unusually high wintering losses of Apis mellifera in recent years has raised concerns regarding the well-being and productivity of honey bees across the globe. While these losses are likely multi-factorial, a proposed contributor are diseases, including those caused by parasites. We formulate and present a mathematical model for a colony of Apis mellifera honey bees infected with the microsporidian parasite Nosema ceranae. The model is numerically analyzed to determine the effects of N. ceranae infection on population and food storage dynamics and their subsequent implications towards colony survival and annual honey yield. Depending on the strength of disease, it is possible for either parasite fadeout, co-existence between bees and N. ceranae, or colony failure to occur. In all cases, the yield of honey collected by the beekeeper is reduced. We further extend the model to include various treatment schemes with the, now discontinued, antimicrobial fumagillin. Treatment with fumagillin can reduce the risk of colony failure and will increase honey yield compared to when no treatment is applied.

Bee Visitation on Flowers in Maine, United States, Reveals the Relative Attractiveness of Plants Through Space and Time: Part I

Bee reservoirs can be effective in agricultural and habitat restoration projects, but the relative attractiveness of plants is not fully understood. To improve plant selection with better knowledge of spatial, temporal, and competition aspects, we tested up to 90 plant subjects from 2012 to 2015 at four sites in Maine. We recognized Apis mellifera L., Bombus ternarius Say, 1837, 'Most Bombus' (except B. ternarius), 'Halictidae' and 'Other Bees' (collectively the so-called 'bee groups') on open flowers in three 1-min periods per site and day, with numerous repeated observations per plant taxon. In 14,311 observations, we recorded 17,792 bees in 61 species. Most-visited plants included Asclepias tuberosa, Borago officinalis, Clethra alnifolia cv. Hummingbird (especially by A. mellifera), Melilotus officinalis, Origanum vulgare, Rosa palustris (especially before 1400 hours), Spiraea alba var. latifolia, and taxa in the family Asteraceae. Early-flowering shrubs were visited, especially by 'Other Bees'. Bee groups each ranked plants uniquely, with some overlap, and differed in most-visited of six plant taxa that we had included in all 4 yr and sites. For 'All Bees' among 84 plant taxa, the most-visited plants were M. officinalis (June), A. tuberosa (July), and C. alnifolia (August). Indicator Species Analysis revealed low bee fidelity to host plants for all but a few plant taxa. Apis mellifera differed from native bees in plants it visited intensively, with some overlap (e.g., A. tuberosa), and was associated with increased visitation on seven plant taxa by 'Most Bombus' and B. ternarius.

Distribution of chemical residues in the beehive compartments and their transfer to the honeybee brood

Honeybee (Apis mellifera) is one of the most important crop and wild plant pollinators, playing an essential role in the agricultural production and the natural ecosystems. However, the number of honeybee colonies is decreasing alarmingly, which has motivated extensive research on the factors affecting their development and survival in some regions. Honeybees' exposure to pesticides and other chemicals has been identified as one of the causes of their decline. The present study evaluates the distribution of plant protection products, veterinary treatments and environmental contaminants inside the beehive, their persistence and their migration to the bee brood. During the five-month sampling period, only amitraz was applied to the colonies. Samples of beeswax, beebread (processed pollen) and bee brood were extracted and analyzed using GC-MS/MS and LC-MS/MS with a multiresidue method. The results showed the presence of 31 chemical residues in the samples. The highest concentrations of residues were detected in the beeswax and corresponded to amitraz (expressed as the sum of DMF and DMPF), coumaphos and tau-fluvalinate, with total concentrations of up to 16,858, 7102 and 1775 μg kg^-1, respectively. These and other veterinary treatments were found to accumulate in the beeswax and migrate to other beehive matrices such as beebread and bee brood. Plant protection products used in agriculture were also found in the beehive matrices, especially in the beebread. Five different chemical residues (acrinathrin, amitraz, coumaphos, cypermethrin and tau-fluvalinate) were found in bee brood samples at concentration levels ranging from 1 to 167 μg kg^-1. These findings reveal that bee brood reared in field conditions is in fact exposed to plant protection products and veterinary residues through direct contact with contaminated wax and via beebread although they had not been applied to the beehive.

American foulbrood in a honeybee colony: spore-symptom relationship and feedbacks

BACKGROUND

The most severe bacterial disease of honeybees is American foulbrood (AFB). The epidemiology of AFB is driven by the extreme spore resilience, the difficulty of bees to remove these spores, and the considerable incidence of undetected spore-producing colonies. The honeybee collective defence mechanisms and their feedback on colony development, which involves a division of labour at multiple levels of colony organization, are difficult to model. To better predict disease outbreaks we need to understand the feedback between colony development and disease progression within the colony. We therefore developed Bayesian models with data from forty AFB-diseased colonies monitored over an entire foraging season to (i) investigate the relationship between spore production and symptoms, (ii) disentangle the feedback loops between AFB epidemiology and natural colony development, and (iii) discuss whether larger insect societies promote or limit within-colony disease transmission.

RESULTS

Rather than identifying a fixed spore count threshold for clinical symptoms, we estimated the probabilities around the relationship between spore counts and symptoms, taking into account modulators such as brood amount/number of bees and time post infection. We identified a decrease over time in the bees-to-brood ratio related to disease development, which should ultimately induce colony collapse. Lastly, two contrasting theories predict that larger colonies could promote either higher (classical epidemiological SIR-model) or lower (increasing spatial nest segregation and more effective pathogen removal) disease prevalence.

CONCLUSIONS

AFB followed the predictions of the SIR-model, partly because disease prevalence and brood removal are decoupled, with worker bees acting more as disease vectors, infecting new brood, than as agents of social immunity, by removing infected brood. We therefore established a direct link between disease prevalence and social group size for a eusocial insect. We furthermore provide a probabilistic description of the relationship between AFB spore counts and symptoms, and how disease development and colony strength over a season modulate this relationship. These results help to better understand disease development within honeybee colonies, provide important estimates for further epidemiological modelling, and gained important insights into the optimal sampling strategy for practical beekeeping and honeybee research.

ColEval: Honeybee COLony Structure EVALuation for Field Surveys

Methods for the evaluation and comparison of the structure of numerous honeybee colonies are needed for the development of applied and fundamental field research, as well as to evaluate how the structure and activity of honeybee colonies evolve over time. ColEval complements existing methods, as it uses an online reference image bank for (human) learning and training purposes. ColEval is based on the evaluation of the surface area percentage occupied by different components of a honeybee colony: adult worker bees, open and capped brood, honey, nectar, and pollen. This method is an essential tool for the description of the evolution in the size of honeybee colonies. The procedure makes allowances for tendencies between different observers and uses them to calculate accurate measurements of honeybee colony evaluation. ColEval thus allows for a posteriori comparison of under- or over-evaluation made by different observers working on the same project; it is thus possible to eliminate observer bias in the measurements and to conduct large surveys.

Toxicity of insecticides on Neotropical stingless bees Plebeia emerina (Friese) and Tetragonisca fiebrigi (Schwarz) (Hymenoptera: Apidae: Meliponini)

Use of pesticides in agroecosystems is considered a major cause of bees diversity losses in the Neotropics, where Plebeia emerina (Friese) and Tetragonisca fiebrigi (Schwarz) (Hymenoptera: Apidae: Meliponini) are wild pollinators of native and crop plants. The aim of this study was to know the acute lethal toxicity of acetamiprid, malathion, phosmet and spinosad insecticides on P. emerina and T. fiebrigi. We obtained the mean concentration and mean lethal dose (LC₅₀ and LD₅₀) and the mean survival of workers after oral and topical exposure to insecticides, respectively. The LC₅₀ values (ng a.i./μl of diet) and the decreasing order of toxicity for P. emerina was spinosad (4.96) > malathion (18.75) > phosmet (97.33) > acetamiprid (4204.06), and for T. fiebrigi also was spinosad (5.65) > malathion (8.39) > phosmet (53.91) > acetamiprid (9841.32), when orally exposed. The LD₅₀ values (ng a.i./bee) and the decreasing order of toxicity for P. emerina was spinosad (1.90) > malathion (10.90) > phosmet (19.54) > acetamiprid (6216.55) and for T. fiebrigi was malathion (29.29) ≥ spinosad (29.79) > phosmet (41.95) > acetamiprid (1421.23), when topically exposed. The mean survival (hours) of contaminated bees by malathion, phosmet, and spinosad, was 11.81, 7.20, and 12.32 for P. emerina and 8.55, 7.20, and 13.34 for T. fiebrigi when orally exposed; and was 4.87, 9.87 and 11.17 for P. emerina, and 4.87, 4.76, and 19.05 for T. fiebrigi when topically exposed. Malathion, phosmet, and spinosad were highly toxic, while acetamiprid was moderately toxic. Our results indicated that the insecticides tested, mainly malathion, phosmet, and spinosad may be harmful to P. emerina and T. fiebrigi, making it essential to propose measures to minimize their impact on wild pollinators.

A mathematical model of honey bee colony dynamics to predict the effect of pollen on colony failure

The decline in colony populations of the honey bee, known as the Colony Collapse Disorder (CCD), is a global concern. Numerous studies have reported possible causes, including pesticides, parasites, and nutritional stress. Poor nutrition affects the immune system at both the individual and colony level, amplifying effects of other stress factors. Pollen is the only source of ten amino acids that are essential to honey bee development, brood rearing and reproduction. This paper presents a new mathematical model to explore the effect of pollen on honey bee colony dynamics. In this model, we considered pollen and nectar as the required food for the colony. The effect of pollen and nectar collected by foragers was evaluated at different mortality rates of pupa, pollen and nectar foragers.

Stability and changes in the distribution of Pipiza hoverflies (Diptera, Syrphidae) in Europe under projected future climate conditions

Climate change is now considered a significant threat to terrestrial biodiversity. Species distribution models (SDMs) are among the modern tools currently used to assess the potential impacts of climate change on species. Pipiza Fallén, 1810 is a well known aphidophagous hoverfly genus (Diptera, Syrphidae) at the European level, for which sampling has been conducted across the region, and long-term databases and geo-referenced datasets have been established. Therefore, in this work, we investigated the potential current distributions of the European species of this genus and their response to future climate change scenarios, as well as evaluated stability in their ranges and potential changes in species-richness patterns. We applied three climate models (BCC_CSM1.1, CCSM4, HadGEM2-ES) to four representative concentration pathways (RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5) for two time frames (2050 and 2070). Our results show that the distribution of most Pipiza species may slightly differ under different climate models. Most Pipiza species were predicted not to be greatly affected by climate change, maintaining their current extent. Percentages of stable areas will remain high (above 50%) for the majority of studied species. According to the predicted turnover of species, northern Europe, could become the richest in terms of species diversity, thus replacing Central Europe as the current hot spot.

Industrial bees: The impact of apicultural intensification on local disease prevalence

It is generally thought that the intensification of farming will result in higher disease prevalences, although there is little specific modelling testing this idea. Focussing on honeybees, we build multi-colony models to inform how "apicultural intensification" is predicted to impact honeybee pathogen epidemiology at the apiary scale.We used both agent-based and analytical models to show that three linked aspects of apicultural intensification (increased population sizes, changes in population network structure and increased between-colony transmission) are unlikely to greatly increase disease prevalence in apiaries. Principally this is because even low-intensity apiculture exhibits high disease prevalence.The greatest impacts of apicultural intensification are found for diseases with relatively low R0 (basic reproduction number), however, such diseases cause little overall disease prevalence and, therefore, the impacts of intensification are minor. Furthermore, the smallest impacts of intensification are for diseases with high R0 values, which we argue are typical of important honeybee diseases. Policy Implications: Our findings contradict the idea that apicultural intensification by crowding honeybee colonies in large, dense apiaries leads to notably higher disease prevalences for established honeybee pathogens. More broadly, our work demonstrates the need for informative models of all agricultural systems and management practices in order to understand the implications of management changes on diseases.

Long-term dynamics of honey bee colonies following exposure to chemical stress

Pesticide residues have been linked to reduced bee health and increased honey bee colony failure. Most research to date has investigated the role of pesticides on individual honey bees, and it is still unclear how trace levels of pesticides change colony viability and productivity over seasonal time scales. To address this question we exposed standard bee colonies to chemical stressors known to have negative effects on individual bees, and measured the productivity of bee colonies across a whole year in two environments: near Tucson Arizona and Sydney Australia. We exposed hives to a trace amount of the neonicotinoid imidacloprid and to the acaricide thymol, and measured capped brood, bee and honey production, as well as the temperature and foraging force of the colonies. The effect of imidacloprid on colony dynamics differed between the two environments. In Tucson we recorded a positive effect of imidacloprid treatment on bee and brood numbers. Thymol was associated with short-term negative effects on bee numbers at both locations, and may have affected colony survival at one location. The overall benefits of thymol for the colonies were unclear. We conclude that long-term and colony-level measures of the effects of agrochemicals are needed to properly understand risks to bees.

Traces of a Neonicotinoid Induce Precocious Foraging and Reduce Foraging Performance in Honey Bees

There is increasing worldwide concern about the impacts of pesticide residues on honey bees and bee colony survival, but how sublethal effects of pesticides on bees might cause colony failure remains highly controversial, with field data giving very mixed results. To explore how trace levels of the neonicotinoid pesticide imidacloprid impacted colony foraging performance, we equipped bees with RFID tags that allowed us to track their lifetime flight behavior. One group of bees was exposed to a trace concentration (5 μg/kg, ppb) of imidacloprid in sugar syrup while in the larval stage. The imidacloprid residues caused bees to start foraging when younger as adults and perform fewer orientation flights, and reduced their lifetime foraging flights by 28%. The magnitude of the effects of a trace imidacloprid concentration delivered only during larval stage highlights the severity of pesticide residues for bee foraging performance. Our data suggest that neonicotinoids could impact colony function by imbalancing the normal age based division of labor in a colony and reducing foraging efficiency. Understanding this mechanism will help the development of interventions to safeguard bee colony health.

Pesticides and pollinators: A socioecological synthesis

The relationship between pesticides and pollinators, while attracting no shortage of attention from scientists, regulators, and the public, has proven resistant to scientific synthesis and fractious in matters of policy and public opinion. This is in part because the issue has been approached in a compartmentalized and intradisciplinary way, such that evaluations of organismal pesticide effects remain largely disjoint from their upstream drivers and downstream consequences. Here, we present a socioecological framework designed to synthesize the pesticide-pollinator system and inform future scholarship and action. Our framework consists of three interlocking domains-pesticide use, pesticide exposure, and pesticide effects-each consisting of causally linked patterns, processes, and states. We elaborate each of these domains and their linkages, reviewing relevant literature and providing empirical case studies. We then propose guidelines for future pesticide-pollinator scholarship and action agenda aimed at strengthening knowledge in neglected domains and integrating knowledge across domains to provide decision support for stakeholders and policymakers. Specifically, we emphasize (1) stakeholder engagement, (2) mechanistic study of pesticide exposure, (3) understanding the propagation of pesticide effects across levels of organization, and (4) full-cost accounting of the externalities of pesticide use and regulation. Addressing these items will require transdisciplinary collaborations within and beyond the scientific community, including the expertise of farmers, agrochemical developers, and policymakers in an extended peer community.

Honey bee colony-level exposure and effects in realistic landscapes: An application of BEEHAVE simulating clothianidin residues in corn pollen

Discerning potential effects of insecticides on honey bee colonies in field studies conducted under realistic conditions can be challenging because of concurrent interactions with other environmental conditions. Honey bee colony models can control exposures and other environmental factors, as well as assess links among pollen and nectar residues in the landscape, their influx into the colony, and the resulting exposures and effects on bees at different developmental stages. We extended the colony model BEEHAVE to represent exposure to the insecticide clothianidin via residues in pollen from treated cornfields set in real agricultural landscapes in the US Midwest. We assessed their potential risks to honey bee colonies over a 1-yr cycle. Clothianidin effects on colony strength were only observed if unrealistically high residue levels in the pollen were simulated. The landscape composition significantly impacted the collection of pollen (residue exposure) from the cornfields, resulting in higher colony-level effects in landscapes with lower proportions of semi-natural land. The application of the extended BEEHAVE model with a pollen exposure-effects module provides a case study for the application of a mechanistic honey bee colony model in pesticide risk assessment integrating the impact of a range of landscape compositions. Environ Toxicol Chem 2019;38:423-435. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Thermal efficiency extends distance and variety for honeybee foragers: analysis of the energetics of nectar collection and desiccation by Apis mellifera

The desiccation of nectar to produce honey by honeybees ( Apis mellifera L.) is an energy-intensive process, as it involves a quasi-isothermal change in the concentration of sugars from typically 20 to 80% by vaporization (honey ripening). This analysis creates mathematical models for: the collected nectar to honey ratio; energy recovery ratio; honey energy margin; and the break-even distance, which includes the factors of nectar concentration and the distance to the nectar from the nest; energetics of desiccation and a new factor, thermal energy efficiency (TEE) of nectar desiccation. These models show a significant proportion of delivered energy in the nectar must be used in desiccation, and that there is a strong connection between TEE and nest lumped thermal conductance with colony behaviour. They show the connection between TEE and honeybee colony success, or failure, in the rate of return, in terms of distance or quality of foraging. Consequently, TEE is a key parameter in honeybee populations and foraging modelling. For bee keeping, it quantifies the summer benefits of a key hive design parameter, hive thermal conductance and gives a sound theoretical basis for improving honey yields, as seen in expanded polystyrene hives.

Influence of Feeding Type and Nosema ceranae Infection on the Gut Microbiota of Apis cerana Workers

The gut microbiota plays an essential role in the health of bees. To elucidate the effect of feed and Nosema ceranae infection on the gut microbiota of honey bee (Apis cerana), we used 16S rRNA sequencing to survey the gut microbiota of honey bee workers fed with sugar water or beebread and inoculated with or without N. ceranae. The gut microbiota of A. cerana is dominated by Serratia, Snodgrassella, and Lactobacillus genera. The overall gut microbiota diversity was show to be significantly differential by feeding type. N. ceranae infection significantly affects the gut microbiota only in bees fed with sugar water. Higher abundances of Lactobacillus, Gluconacetobacter, and Snodgrassella and lower abundances of Serratia were found in bees fed with beebread than in those fed with sugar water. N. ceranae infection led to a higher abundance of Snodgrassella and a lower abundance of Serratia in sugar-fed bees. Imputed bacterial Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways showed the significant metagenomics functional differences by feeding and N. ceranae infections. Furthermore, A. cerana workers fed with sugar water showed lower N. ceranae spore loads but higher mortality than those fed with beebread. The cumulative mortality was strongly positive correlated (rho = 0.61) with the changes of overall microbiota dissimilarities by N. ceranae infection. Both feeding types and N. ceranae infection significantly affect the gut microbiota in A. cerana workers. Beebread not only provides better nutrition but also helps establish a more stable gut microbiota and therefore protects bees in response to N. ceranae infection. IMPORTANCE The gut microbiota plays an essential role in the health of bees. Scientific evidence suggests that diet and infection can affect the gut microbiota and modulate the health of the gut; however, the interplay between those two factors and the bee gut microbiota is not well known. In this study, we used a high-throughput sequencing method to monitor the changes of gut microbiota associated with both feeding types and Nosema ceranae infection. Our results showed that the gut microbiota composition and diversity of Asian honey bee were significantly associated with both feeding types and the N. ceranae infection. More interestingly, bees fed with beebread showed higher microbiota stability and lower mortality rates than those fed with sugar water when infected by N. ceranae. Those data suggest that beebread has the potential not only to provide better nutrition but also help to establish a more stable gut microbiota to protect bees against N. ceranae infection.

Climate-driven declines in arthropod abundance restructure a rainforest food web

A number of studies indicate that tropical arthropods should be particularly vulnerable to climate warming. If these predictions are realized, climate warming may have a more profound impact on the functioning and diversity of tropical forests than currently anticipated. Although arthropods comprise over two-thirds of terrestrial species, information on their abundance and extinction rates in tropical habitats is severely limited. Here we analyze data on arthropod and insectivore abundances taken between 1976 and 2012 at two midelevation habitats in Puerto Rico's Luquillo rainforest. During this time, mean maximum temperatures have risen by 2.0 °C. Using the same study area and methods employed by Lister in the 1970s, we discovered that the dry weight biomass of arthropods captured in sweep samples had declined 4 to 8 times, and 30 to 60 times in sticky traps. Analysis of long-term data on canopy arthropods and walking sticks taken as part of the Luquillo Long-Term Ecological Research program revealed sustained declines in abundance over two decades, as well as negative regressions of abundance on mean maximum temperatures. We also document parallel decreases in Luquillo's insectivorous lizards, frogs, and birds. While El Niño/Southern Oscillation influences the abundance of forest arthropods, climate warming is the major driver of reductions in arthropod abundance, indirectly precipitating a bottom-up trophic cascade and consequent collapse of the forest food web.

Pollinator decline - an ecological calamity in the making?

Since pollination by insects is vitally important for much of global crop production, and to provide pollination services more widely throughout the planetary ecosystems, the prospect of an imminent 'pollination crisis', due to a die-off of flying insects, is most disquieting, to say the least. Indeed, the term 'ecological Armageddon' has been used in the media. However, to know whether or not a wholesale decline in flying pollinators (including non-bee species) is occurring across the world is very difficult, due to an insufficiency of geographically widespread and long-term data. Bees, as the best documented species, can be seen to be suffering from chronic exposure to a range of stressors, which include: a loss of abundance and diversity of flowers, and a decline in suitable habitat for them to build nests; long-term exposure to agrochemicals, including pesticides such as neonicotinoids; and infection by parasites and pathogens, many inadvertently spread by the actions of humans. It is likely that climate change may impact further on particular pollinators, for example bumble bees, which are cool-climate specialists. Moreover, the co-operative element of various different stress factors should be noted; thus, for example, exposure to pesticides is known to diminish detoxification mechanisms and also immune responses, hence lowering the resistance of bees to parasitic infections. It is further conspicuous that for those wild non-bee insects - principally moths and butterflies - where data are available, the picture is also one of significant population losses. Alarmingly, a recent study in Germany indicated that a decline in the biomass of flying insects had occurred by 76% in less than three decades, as sampled in nature reserves across the country. Accordingly, to fully answer the question posed in the title of this article 'pollinator decline - an ecological calamity in the making?' will require many more detailed, more geographically encompassing, more species-inclusive, and longer-term studies, but the available evidence points to a clear 'probably', and the precautionary principle would suggest this is not a prospect we can afford to ignore.

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.

Sensitivity analyses for simulating pesticide impacts on honey bee colonies

We employ Monte Carlo simulation and sensitivity analysis techniques to describe the population dynamics of pesticide exposure to a honey bee colony using the VarroaPop+Pesticide model. Simulations are performed of hive population trajectories with and without pesticide exposure to determine the effects of weather, queen strength, foraging activity, colony resources, and Varroa populations on colony growth and survival. The daily resolution of the model allows us to conditionally identify sensitivity metrics. Simulations indicate queen strength and forager lifespan are consistent, critical inputs for colony dynamics in both the control and exposed conditions. Adult contact toxicity, application rate and nectar load become critical parameters for colony dynamics within exposed simulations. Daily sensitivity analysis also reveals that the relative importance of these parameters fluctuates throughout the simulation period according to the status of other inputs.

Bacterial communities associated with honeybee food stores are correlated with land use

Microbial communities, associated with almost all metazoans, can be inherited from the environment. Although the honeybee (Apis mellifera L.) gut microbiome is well documented, studies of the gut focus on just a small component of the bee microbiome. Other key areas such as the comb, propolis, honey, and stored pollen (bee bread) are poorly understood. Furthermore, little is known about the relationship between the pollinator microbiome and its environment. Here we present a study of the bee bread microbiome and its relationship with land use. We estimated bacterial community composition using both Illumina MiSeq DNA sequencing and denaturing gradient gel electrophoresis (DGGE). Illumina was used to gain a deeper understanding of precise species diversity across samples. DGGE was used on a larger number of samples where the costs of MiSeq had become prohibitive and therefore allowed us to study a greater number of bee breads across broader geographical axes. The former demonstrates bee bread comprises, on average, 13 distinct bacterial phyla; Bacteroidetes, Firmicutes, Alpha-proteobacteria, Beta-proteobacteria, and Gamma-proteobacteria were the five most abundant. The most common genera were Pseudomonas, Arsenophonus, Lactobacillus, Erwinia, and Acinetobacter. DGGE data show bacterial community composition and diversity varied spatially and temporally both within and between hives. Land use data were obtained from the 2007 Countryside Survey. Certain habitats, such as improved grasslands, are associated with low diversity bee breads, meaning that these environments may be poor sources of bee-associated bacteria. Decreased bee bread bacterial diversity may result in reduced function within hives. Although the dispersal of microbes is ubiquitous, this study has demonstrated landscape-level effects on microbial community composition.

Exposure of larvae to thiamethoxam affects the survival and physiology of the honey bee at post-embryonic stages

Under laboratory conditions, the effects of thiamethoxam were investigated in larvae, pupae and emerging honey bees after exposure at larval stages with different concentrations in the food (0.00001 ng/μL, 0.001 ng/μL and 1.44 ng/μL). Thiamethoxam reduced the survival of larvae and pupae and consequently decreased the percentage of emerging honey bees. Thiamethoxam induced important physiological disturbances. It increased acetylcholinesterase (AChE) activity at all developmental stages and increased glutathione-S-transferase (GST) and carboxylesterase para (CaEp) activities at the pupal stages. For midgut alkaline phosphatase (ALP), no activity was detected in pupae stages, and no effect was observed in larvae and emerging bees. We assume that the effects of thiamethoxam on the survival, emergence and physiology of honey bees may affect the development of the colony. These results showed that attention should be paid to the exposure to pesticides during the developmental stages of the honey bee. This study represents the first investigation of the effects of thiamethoxam on the development of A. mellifera following larval exposure.

Projected climate change threatens pollinators and crop production in Brazil

Animal pollination can impact food security since many crops depend on pollinators to produce fruits and seeds. However, the effects of projected climate change on crop pollinators and therefore on crop production are still unclear, especially for wild pollinators and aggregate community responses. Using species distributional modeling, we assessed the effects of climate change on the geographic distribution of 95 pollinator species of 13 Brazilian crops, and we estimated their relative impacts on crop production. We described these effects at the municipality level, and we assessed the crops that were grown, the gross production volume of these crops, the total crop production value, and the number of inhabitants. Overall, considering all crop species, we found that the projected climate change will reduce the probability of pollinator occurrence by almost 0.13 by 2050. Our models predict that almost 90% of the municipalities analyzed will face species loss. Decreases in the pollinator occurrence probability varied from 0.08 (persimmon) to 0.25 (tomato) and will potentially affect 9% (mandarin) to 100% (sunflower) of the municipalities that produce each crop. Municipalities in central and southern Brazil will potentially face relatively large impacts on crop production due to pollinator loss. In contrast, some municipalities in northern Brazil, particularly in the northwestern Amazon, could potentially benefit from climate change because pollinators of some crops may increase. The decline in the probability of pollinator occurrence is found in a large number of municipalities with the lowest GDP and will also likely affect some places where crop production is high (20% to 90% of the GDP) and where the number of inhabitants is also high (more than 6 million people). Our study highlights key municipalities where crops are economically important and where pollinators will potentially face the worst conditions due to climate change. However, pollinators may be able to find new suitable areas that have the potential to improve crop production. The results shown here could guide policy decisions for adapting to climate change and for preventing the loss of pollinator species and crop production.

A mathematical model for the interplay of Nosema infection and forager losses in honey bee colonies

We present a mathematical model (a) for the infection of a honey bee colony with Nosema ceranae. This is a system of five ordinary differential equations for the dependent variables healthy and infected worker bees in the hive, healthy and infected forager bees, and disease potential deposited in the hive. The model is then (b) extended to account for increased forager losses, e.g. caused by exposure to external stressors. The model is non-autonomous with periodic coefficient functions. Algebraic complexity prevents a rigorous mathematical analysis. Therefore, we resort to computer simulations in addition to some analytical results in the constant coefficient case. We investigate each of the two stressors (a) and (b) individually and jointly. Our results indicate that the combined effect of two stressors, both of which can be tolerated by the colony individually, might lead to colony failure, suggesting multi-factorial causes behind losses of honey bee colonies.