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Reports of honey bee population decline has spurred many national efforts to understand the extent of the problem and to identify causative or associated factors. However, our collective understanding of the factors has been hampered by a lack of joined up trans-national effort. Moreover, the impacts of beekeeper knowledge and beekeeping management practices have often been overlooked, despite honey bees being a managed pollinator. Here, we established a standardised active monitoring network for 5 798 apiaries over two consecutive years to quantify honey bee colony mortality across 17 European countries. Our data demonstrate that overwinter losses ranged between 2% and 32%, and that high summer losses were likely to follow high winter losses. Multivariate Poisson regression models revealed that hobbyist beekeepers with small apiaries and little experience in beekeeping had double the winter mortality rate when compared to professional beekeepers. Furthermore, honey bees kept by professional beekeepers never showed signs of disease, unlike apiaries from hobbyist beekeepers that had symptoms of bacterial infection and heavy Varroa infestation. Our data highlight beekeeper background and apicultural practices as major drivers of honey bee colony losses. The benefits of conducting trans-national monitoring schemes and improving beekeeper training are discussed.

Austrian beekeepers frequently suffered severe colony losses during the last decade similar to trends all over Europe. This first surveillance study aimed to describe the health status of Austrian bee colonies and to analyze the reasons for losses for both the summer and winter season in Austria. In this study 189 apiaries all over Austria were selected using a stratified random sampling approach and inspected three times between July 2015 and spring 2016 by trained bee inspectors. The inspectors made interviews with the beekeepers about their beekeeping practice and the history of the involved colonies. They inspected a total of 1596 colonies for symptoms of nine bee pests and diseases (four of them notifiable diseases) and took bee samples for varroa mite infestation analysis. The most frequently detected diseases were three brood diseases: Varroosis, Chalkbrood and Sacbrood. The notifiable bee pests Aethina tumida and Tropilaelaps spp. were not detected. During the study period 10.8% of the 1596 observed colonies died. Winter proved to be the most critical season, in which 75% of the reported colony losses happened. Risks for suffering summer losses increased significantly, when colonies were weak in July, had queen problems or a high varroa mite infestation level on bees in July. Risks for suffering winter losses increased significantly, when the colonies had a high varroa mite infestation level on bees in September, were weak in September, had a queen older than one year or the beekeeper had few years of beekeeping experience. However, the effect of a high varroa mite infestation level in September had by far the greatest potential to raise the winter losses compared to the other significant factors.

Laboratory infection experiments and field data show that emerging infectious diseases of honeybees are widespread infectious agents within the pollinator assemblage; the prevalence of deformed wing virus (DWV) and the parasite Nosema ceranae in honeybees and bumblebees is linked, and sympatric bumblebees and honeybees are infected by the same DWV strains, indicating ongoing disease transmission. Honeybee diseases threaten wild pollinators Efficient pollination is vital for both crop production and ecosystem sustainability, and there is evidence to suggest that emerging infectious diseases are contributing to a decline in populations of some important insect pollinators. This study combines laboratory infection experiments and field studies to demonstrate infectivity of two serious honeybee ( Apis mellifera ) pathogens in a wild pollinator, the bumblebee ( Bombus terrestris ). Data from across the United Kingdom show that there is co-localization of deformed wing virus (DWV) and the microsporidian parasite Nosema ceranae in the two types of pollinator, and that the honeybee disease can be infectious in bumblebees. This work indicates that wild pollinator populations may be at risk, and unlike managed populations of Apis , they are not protected by intervention from beekeepers. Such a loss of wild pollinators would significantly decrease crop pollination efficiency. Emerging infectious diseases (EIDs) pose a risk to human welfare, both directly 1 and indirectly, by affecting managed livestock and wildlife that provide valuable resources and ecosystem services, such as the pollination of crops 2 . Honeybees ( Apis mellifera ), the prevailing managed insect crop pollinator, suffer from a range of emerging and exotic high-impact pathogens 3 , 4 , and population maintenance requires active management by beekeepers to control them. Wild pollinators such as bumblebees ( Bombus spp.) are in global decline 5 , 6 , one cause of which may be pathogen spillover from managed pollinators like honeybees 7 , 8 or commercial colonies of bumblebees 9 . Here we use a combination of infection experiments and landscape-scale field data to show that honeybee EIDs are indeed widespread infectious agents within the pollinator assemblage. The prevalence of deformed wing virus (DWV) and the exotic parasite Nosema ceranae in honeybees and bumblebees is linked; as honeybees have higher DWV prevalence, and sympatric bumblebees and honeybees are infected by the same DWV strains, Apis is the likely source of at least one major EID in wild pollinators. Lessons learned from vertebrates 10 , 11 highlight the need for increased pathogen control in managed bee species to maintain wild pollinators, as declines in native pollinators may be caused by interspecies pathogen transmission originating from managed pollinators.

The aim of this study was to evaluate the technical efficiency, energy balance and economic analysis of honey production in Bingöl province, Turkey. Data were collected through face-to-face interviews with 94 honey producers, using proportional sampling to determine the sample selection. The technical efficiency of honey production was evaluated using stochastic frontier analysis. The results showed energy efficiency scores of 0.27, 0.16 and 0.11 for the respective groups. It was observed that the proportion of direct energy inputs was lower than that of indirect energy, with fuel identified as the primary energy input. The benefit-cost ratio for beekeeping was found to be 1.35. For honey production, the gross income per unit of energy was calculated to be 14.5₺, resulting in a net income of 3.86₺. In addition, the gross income per unit of energy for the farms surveyed was 2.49₺, with a net income of 0.65₺. Despite the unfavourable energy input-output ratios, the enterprises studied were considered sustainable in terms of energy costs and gross income. The efficiency analysis yielded technical efficiency scores of 0.83, 0.86 and 0.90 for the respective groups, indicating that the third group of enterprises used inputs in honey production more effectively. To improve the overall efficiency of honey production in Bingöl province, an increase in the number of hives is recommended and adopting modern beekeeping techniques is essential to improve energy efficiency.

This study reports for the first-time a multi-country survey of managed honey bee colony loss rates and associated risk factors during the active beekeeping season 2022/2023 in nine Sub-Saharan African countries, namely Kenya, Ethiopia, Rwanda, Uganda, Benin, Liberia, Nigeria, Cameroon and Democratic Republic of the Congo. It also evaluates the sustainability of bee swarm catches as a primary source for expanding apiary size by African beekeepers. In this survey, the 1,786 interviewed beekeepers across these countries collectively managing 41,761 colonies registered an overall loss rate of 21.3%, which varied significantly among countries (from 9.7 to 45.3%) and hive types (from 10.6% in hives with movable frames to 17.9% in frameless hives). The perceived causes of losses in order of significance were issues beyond the beekeeper’s control (mostly theft, drought, and bushfire), absconding and pests (mostly wax moth, small and large hive beetles, ants and Varroa destructor mite), but this pattern varied greatly across countries. Among the management practices and characteristics, migratory beekeepers and professional beekeepers experienced lower losses than beekeepers practicing stationary beekeeping and semi-professionals and hobby beekeepers, respectively. Insights into the number of bee swarms caught revealed a significant decrease in swarm availability over the past three years in Kenya, while some regions in Ethiopia showed the opposite trend, requiring further investigation. Overall, this comprehensive survey highlights the complexities and challenges faced by beekeepers in Sub-Saharan Africa, underscoring the need for targeted interventions and sustained research to support the resilience and growth of the apicultural sector.

Bees play a vital ecological role as pollinators, contributing to biodiversity, forest regeneration, and agricultural productivity. In recent years, precision beekeeping has emerged as a promising approach to support hive management through sensor-based monitoring. However, existing systems often lack predictive capabilities, limiting their usefulness in anticipating disruptive events that threaten colony health. To address this gap, we present BeeViz, an intelligent monitoring system that combines time series forecasting and anomaly detection to enhance decision-making in apiculture. The system integrates sensor networks, cloud infrastructure, and AI-based data processing modules to continuously track key hive parameters (temperature, humidity, and weight) and generate short-term forecasts and real-time alerts. Preliminary results show that the system can effectively detect anomalies and generate short-term forecasts for key hive parameters, with promising accuracy across different metrics. By enabling proactive interventions, BeeViz supports more resilient and sustainable beekeeping practices, paving the way for collaborative learning and data-driven hive management.

As pollinator decline is increasingly reported in natural and agricultural environments, cities are perceived as shelters for pollinators because of low pesticide exposure and high floral diversity throughout the year. This has led to the development of environmental policies supporting pollinators in urban areas. However, policies are often restricted to the promotion of honey bee colony installations, which resulted in a strong increase in apiary numbers in cities. Recently, competition for floral resources between wild pollinators and honey bees has been highlighted in semi-natural contexts, but whether urban beekeeping could impact wild pollinators remains unknown. Here, we show that in the city of Paris (France), wild pollinator visitation rates are negatively correlated to honey bee colony densities present in the surrounding landscape (500m-slope =-0.614; p = 0.001-and 1000m-slope =-0.489; p = 0.005). Regarding the morphological groups of wild pollinators, large solitary bee and beetle visitation rates were negatively affected by honey bee colony densities within a 500m buffer (slope =-0.425, p = 0.007 and slope =-0.671, p = 0.002, respectively) and bumblebee visi-tation rates were negatively affected by honey bee colony density within a 1000m buffer (slope =-0.451, p = 0.012). Further, lower interaction evenness in plant-pollinator networks was observed with high honey bee colony density within a 1000m buffer (slope =-0.487, p = 0.008). Finally, honey bees tended to focus their foraging activity on managed rather than wild plant species (student t-test, p = 0.001) whereas wild pollinators equally visited managed and wild species. We advocate responsible practices mitigating the introduction of high density of honey bee colonies in urban environments. Further studies are however needed to deepen our knowledge about the potential negative interactions between wild and domesticated pollinators.

Pressures on honey bee health have substantially increased both colony mortality and beekeepers’ costs for hive management across Europe. Although technological advances could offer cost-effective solutions to these challenges, there is little research into the incentives and barriers to technological adoption by beekeepers in Europe. Our study is the first to investigate beekeepers’ willingness to adopt the Bee Health Card, a molecular diagnostic tool developed within the PoshBee EU project which can rapidly assess bee health by monitoring molecular changes in bees. The Bee Health Card, based on MALDI BeeTyping®, is currently on level six of the Technology Readiness Level scale, meaning that the technology has been demonstrated in relevant environments. Using an on-line survey from seven European countries, we show that beekeepers recognise the potential for the tool to improve colony health, and that targeted economic incentives, such as subsidises, may help reduce cost being a barrier to the adoption and frequent use of the tool. Based on the description of the tool, 43% of beekeepers appear to be moderately confident in the effectiveness of the Bee Health Card. This confidence could increase if the tool was easy to use and not time consuming, and a higher confidence could also contribute to raising the probability of accepting extra costs linked to it. We estimate that, in the worst-case scenario, the cost per single use of the Bee Health Card should be between €47–90 across a range of European countries, depending on the labour and postage costs. However, the monetary benefits in terms of honey production could exceed this. In order to successfully tackle colony health issues, it is recommended using the BHC five times per year, from the end to the beginning of winter. Finally, we discuss the knowledge needs for assessing beekeeper health tools in future research.

Bee populations are rapidly declining, and biotechnology offers scalable, sustainable solutions for bee health.Genomics and sensor-based continuous monitoring generate large, complex datasets that can be integrated by artificial intelligence (AI) to provide stressor diagnostics, inform precision beekeeping, and accelerate breeding programs for resilient bees.Molecular interventions such as RNAi and protein biologics provide targeted pest controls, and their stability can be enhanced by nanocarrier delivery systems.Natural product drug discovery and high-throughput screening facilitate the development of eco-friendly pathogen treatments for managed bee colonies.Genome editing and synthetic biology are emerging as plausible conservation and management strategies, but they face a host of practical, regulatory, and public perception challenges. Bees are vital to global food security and biodiversity but their populations are threatened by a steady flux of interacting stressors. Current mitigation strategies are failing to address the complexity and scale of these threats. Biotechnology offers innovative solutions to protect essential pollination services and secure the future of beekeeping. Omic tools guided by artificial intelligence can unlock new possibilities for strengthening bee populations and improve their ability to adapt to emerging challenges. Molecular and bio-based treatments offer precise, nonchemical inputs for managed hives. Synthetic biology enables engineered gut microbiomes, pollinator-friendly crops, and artificial diets that are tailored to bee health. We discuss recent progress and future directions of biotechnology to help bees cope with a rapidly changing world. Bees are vital to global food security and biodiversity but their populations are threatened by a steady flux of interacting stressors. Current mitigation strategies are failing to address the complexity and scale of these threats. Biotechnology offers innovative solutions to protect essential pollination services and secure the future of beekeeping. Omic tools guided by artificial intelligence can unlock new possibilities for strengthening bee populations and improve their ability to adapt to emerging challenges. Molecular and bio-based treatments offer precise, nonchemical inputs for managed hives. Synthetic biology enables engineered gut microbiomes, pollinator-friendly crops, and artificial diets that are tailored to bee health. We discuss recent progress and future directions of biotechnology to help bees cope with a rapidly changing world.

Precision beekeeping or precision apiculture is an apiary management strategy based on the monitoring of individual bee colonies to minimize resource consumption and maximize the productivity of bees. Bees play a fundamental role in ensuring pollination; they can also be considered as indicators of the state of pollution and are used as bio monitors. Beekeeping needs continuous monitoring of the animals and can benefit from advanced intelligent ambiance technologies. The aim of this study was the design of a precision apiculture system (PAS) platform for monitoring and controlling the following environmental parameters: wind, temperature, and relative humidity inside and outside the hive, in order to assess their influence on honey production. PAS is based on an Arduino board with an Atmel microcontroller, and the connection of a load cell for recording the weight of the hive, relative humidity and temperature sensor inside the hive, and relative humidity and temperature sensor outside the hive using an anemometer. PAS was installed in common hives and placed in an open field in a French honeysuckle plot; the system was developed to operate in continuous mode, monitoring the period of 24 April–1 June 2019. Temperature was constant in the monitored period, around 35 °C, inside the hive, proving that no criticalities occurred regarding swarming or absconding. In the period between 24 and 28 May, a lack of honey production was recorded, attributed to a lowering of the external temperature. PAS was useful to point out the eventual reduction in honey production due to wind; several peaks of windiness exceeding 5 m s−1 were recorded, noting that honey production decreases with the peaks in wind. Therefore, the data recorded by PAS platform provided a valid decisional support to the operator. It can be implemented by inserting additional sensors for detecting other parameters, such as rain or sound.