B-GOOD: Giving Beekeeping Guidance by cOmputatiOnal-assisted Decision making

A key to healthy beekeeping is the Health Status Index (HIS) inspired by EFSA’s Healthy-B toolbox which we will make fully operational, with the active collaboration of beekeepers, by facilitating the coordinated and harmonised flow of data from various sources and by testing and validating each component thoroughly. We envisage a step-by-step expansion of participating apiaries, and will eventually cover all EU biogeographic regions. The key to a sustainable beekeeping is a better understanding of its socio-economics, particularly within local value chains, its relationship with bee health and the human-ecosystem equilibrium of the beekeeping sector and to implement these insights into the data processing and decision making. We will fully integrate socio-economic analyses, identify viable business models tailored to different contexts for European beekeeping and determine the carrying capacity of the landscape. In close cooperation with the EU Bee Partnership, an EU-wide bee health and management data platform and affiliated project website will be created to enable sharing of knowledge and learning between scientists and stakeholders within and outside the consortium. We will utilise and further expand the classification of the open source IT-application for digital beekeeping, BEEP, to streamline the flow of data related to beekeeping management, the beehive and its environment (landscape, agricultural practices, weather and climate) from various sources. The dynamic bee health and management data platform will allow us to identify correlative relationships among factors impacting the HSI, assess the risk of emerging pests and predators, and enable beekeepers to develop adaptive management strategies that account for local and EU-wide issues. Reinforcing and establishing, where necessary, new multi-actor networks of collaboration will engender a lasting learning and innovation system to ensure social-ecological resilient and sustainable beekeeping

西方蜜蜂研究的统计指南

In this article we provide guidelines on statistical design and analysis of data for all kinds of honey bee research. Guidelines and selection of different methods presented are, at least partly, based on experience. This article can be used: to identify the most suitable analysis for the type of data collected; to optimise one’s experimental design based on the experimental factors to be investigated, samples to be analysed, and the type of data produced; to determine how, where, and when to sample bees from colonies; or just to inspire. Also included are guidelines on presentation and reporting of data, as well as where to find help and which types of software could be useful.En este trabajo se proporcionan directrices sobre el diseño estadístico y el análisis de datos para todo tipo de investigación sobre abejas. Tanto las directrices como la selección de los diferentes métodos que se presentan están basadas, al menos en parte, en la experiencia. Este artículo se puede utilizar: para identificar el análisis más adecuado para el tipo de datos recogidos; para optimizar el diseño experimental basado en los factores experimentales a ser investigados, las muestras a analizar, y el tipo de datos que se producen; para determinar cómo, dónde , y cuando muestras abejas de las colonias, o simplemente para inspirar. También se incluyen directrices para la presentación y comunicación de los datos, así como dónde encontrar ayuda y distintos software que puedan ser útiles.在本文中，我们提供了针对蜜蜂所有研究的统计设计和数据分析指南。这些指南和方法的选择至少部分基于我们的经验。本文也可用于：针对收集到的数据类型选择最优分析方法；基于所研究的实验因素、待分析的样本和获得的数据类型优化实验设计；确定从蜂群中采集蜜蜂样本的地点、时间和方式；或者仅为实验提供参考。另外，也包含展示和报告数据时的指南，以及如何寻求帮助和选用何种软件。The University of Pretoria, the National Research Foundation of South Africa and the Department of Science and Technology of South Africa (CWWP).http://www.ibra.org.uk/am201

Winter Survival of Individual Honey Bees and Honey Bee Colonies Depends on Level of Varroa destructor Infestation

Background: Recent elevated winter loss of honey bee colonies is a major concern. The presence of the mite Varroa destructor in colonies places an important pressure on bee health. V. destructor shortens the lifespan of individual bees, while long lifespan during winter is a primary requirement to survive until the next spring. We investigated in two subsequent years the effects of different levels of V. destructor infestation during the transition from short-lived summer bees to long-lived winter bees on the lifespan of individual bees and the survival of bee colonies during winter. Colonies treated earlier in the season to reduce V. destructor infestation during the development of winter bees were expected to have longer bee lifespan and higher colony survival after winter. Methodology/Principal Findings: Mite infestation was reduced using acaricide treatments during different months (July, August, September, or not treated). We found that the number of capped brood cells decreased drastically between August and November, while at the same time, the lifespan of the bees (marked cohorts) increased indicating the transition to winter bees. Low V. destructor infestation levels before and during the transition to winter bees resulted in an increase in lifespan of bees and higher colony survival compared to colonies that were not treated and that had higher infestation levels. A variety of stress-related factors could have contributed to the variation in longevity and winter survival that we found between years. Conclusions/Significance: This study contributes to theory about the multiple causes for the recent elevated colony losses in honey bees. Our study shows the correlation between long lifespan of winter bees and colony loss in spring. Moreover, we show that colonies treated earlier in the season had reduced V. destructor infestation during the development of winter bees resulting in longer bee lifespan and higher colony survival after winter

Bridging the Gap between Field Experiments and Machine Learning: The EC H2020 B-GOOD Project as a Case Study towards Automated Predictive Health Monitoring of Honey Bee Colonies.

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies' exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony's health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project's data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping

Can colony size of honeybees (Apis mellifera) be used as predictor for colony losses due to varroa destructor during winter?

For more than three decades, honeybee colonies (Apis mellifera) have experienced high losses during winter and these losses are still continuing. It is crucial that beekeepers monitor their colonies closely and anticipate losses early enough to apply mitigating actions. We tested whether colony size can be used as early predictor for potential colony losses, in particular due to the parasitic mite Varroa destructor. V. destructor is one of the most important causes of these losses. Such an early predictor for potential V. destructor induced losses is especially relevant as measuring V. destructor load in colonies is difficult and cumbersome. Over three years, we monitored colonies with high and low V. destructor loads from July until March of the next year. We found that differences in colony size were only visible after November, even though we lost almost all colonies every winter in the group with a high V. destructor load. In the Northern hemisphere, November is considered to be too late for beekeepers to strengthen colonies in preparation for winter. We therefore argue that early warning signs for potential colony losses due to V. destructor are urgently needed to allow beekeepers to prevent winter losses. We discuss the role of precision apiculture in monitoring the health and productivity of beehive colonies.</p

Flight performance 2015-11-13

BeeNr: ID individual; Colony: ID colony; Molaire: 1 or 2M sugar concentration fed as fuel for flight; Varroa: treatment 0= low infestation (treated with acaricide), treatment 1= high infestation (NOT treated with acaricide); Imidacloprid: treatment 0= control 0 microgram per Liter, treatment 1= 6 microgram per Liter imidacloprid a.i. (in 660ml sugarwater 50% per week); FlightDate: date of the flight(s); Flightday: day since start, first flight date; Flightmill: ID flightmill; N: number of rounds continuous flight; Distancem: Distance in meters; Log_Distancem: log10 Distance in meters; Flighttimemin: Flight time in minutes; Log_Flighttimemin: log10 Flight time in minutes; Averagems: Average speed in meters per second; Maxms: Maximum speed in meters per second; Weightmg: Weight of the bee in milligram after the flight(s); Winglengthmm: Winglength of front wing from the joint to tip in millimeter; Survivalapril14: survival of the colony in April 2014 0=alive, 1=dead

Mites 2015-11-13

Varroa: treatment 0= low infestation (treated with acaricide), treatment 1= high infestation (NOT treated with acaricide); Imidacloprid: treatment 0= control 0 microgram per Liter, treatment 1= 6 microgram per Liter imidacloprid a.i. (in 660ml sugarwater 50% per week); Colony: ID colony; Succes: 0=group that did not fly, 1=groep that did succesfully fly; numberofbees: Number of individuals that was tested; Mitesgrambees: Number of phoretic mites per gram bees in October 2013; LNmites: Natural log of (number of mites per gram bees + 0.01)

Data from: Interaction between Varroa destructor and imidacloprid reduces flight capacity of honeybees

Current high losses of honey bees seriously threaten crop pollination. Whereas parasite exposure is acknowledged as an important cause of these losses, the role of insecticides is controversial. Parasites and neonicotinoid insecticides reduce homing success of foragers, e.g., by reduced orientation, but it is unknown whether they negatively affect flight capacity. We investigated how exposing colonies to the parasitic mite Varroa destructor and the neonicotinoid insecticide imidacloprid affect flight capacity of foragers. Flight distance, time and speed of foragers were measured in flight mills to assess the relative and interactive effects of high V. destructor load and a field-realistic, chronic sub-lethal dose of imidacloprid. Foragers from colonies exposed to high levels of V. destructor flew shorter distances, with a larger effect when also exposed to imidacloprid. Bee body mass partly explained our results as bees were heavier when exposed to these stressors, possibly due to an earlier onset of foraging. Our findings contribute to understanding of interacting stressors that can explain colony losses. Reduced flight capacity decreases the food-collecting ability of honey bees and may hamper the use of precocious foraging as a coping mechanism during colony (nutritional) stress. Ineffective coping mechanisms may lead to destructive cascading effects and subsequent colony collapse

Data underlying the publication: "Corpse removal increases when honey bee colonies experience high Varroa destructor infestation"

Datasets of the publication "Corpse removal increases when honey bee colonies experience high Varroa destructor infestation" published in Insectes Sociau