Reducing the risk of honey bee colony loss through beekeeping management practices

As primary pollinators in agricultural settings, managed honey bee colonies (Apis mellifera L.) are a highly value commodity for which demand is only growing. With high levels of colony loss experienced in the USA and around the world, there is demand for a better understanding of the drivers of colony mortality and identification of suites of management practices which are optimal for colony survivorship. This dissertation responds to these demands by summarizing the state of knowledge on the causes of colony loss (Chapter 1); describing the epidemiological tools used to investigate honey bee colony health (Chapter 2); describing the variability of colony loss across stakeholder typology, regions, seasons and years (Chapters 3 and 4); and investigating the association between management practices and colony mortality (Chapter 5). Honey bee health, and ultimately, colony loss, is affected by multiple stressors acting concomitantly and sometimes interacting. Those stressors include pests and diseases, forage availability and pesticide exposure. Management practices have the potential, when used judiciously, to alleviate some of those stressors. Investigations of sets of management practices have been frustrated by the lack of methodology to handle large complex and incomplete datasets that are typical in observational studies. Using long term observational data obtained from the Bee Informed Partnership monitoring of honey bee colony losses and management practices in the US, we were able to describe the variation in colony loss across years, seasons, States and stakeholder’s types. In parallel, we summarized management information into a quality index, based on experts’ opinion, and confirmed the association between management practices quality and overwintering colony loss. Further, we ranked individual practices based on their associated potential reduction in colony mortality. Because our method accounts for the pre-existing prevalence of practices, we propose that those sets of practices should be prioritized as recommendations, rather than those identified by experts, to derive the highest reduction in risk of colony mortality. The methodology we developed could benefit other Ag or epidemiological systems interested in the summarization of a great number of practices and their prioritization based on highest potential to reduce risk

Prioritizing changes in management practices associated with reduced winter honey bee colony losses for US beekeepers.

peer reviewedBeekeepers attempt to manage their honey bee colonies in ways that optimize colony health. Disentangling the impact of management from other variables affecting colony health is complicated by the diversity of practices used and difficulties handling typically complex and incomplete observational datasets. We propose a method to 1) compress multi-factored management data into a single index, to holistically investigate the real world impact of management on colony mortality, and 2) simplify said index to identify the core practices for which a change in behavior is associated with the greatest improvement in survivorship. Experts scored the practices of US beekeepers (n = 18,971) documented using four years of retrospective surveys (2012-2015). Management Index scores significantly correlated with loss rates, with beekeepers most in line with recommendations suffering lower losses. The highest ranked practices varied by operation type, as recommendations accounted for the current prevalence of practices. These results validate experts' opinion using empirical data, and can help prioritize extension messages. Improving management will not prevent all losses; however, we show that few behavioral changes (in particular related to comb management, sources of new colonies and Varroa management) can lead to a non-negligible reduction in risk

Risk and protective indicators of beekeeping management practices

Explaining the reasons for the high honey bee (Apis mellifera) colony loss rate in recent years has become a top global research priority in apicultural and agricultural sciences. Although there are indications of the role played by beekeeping management practices on honey bee health, very little information is currently available. Our study aimed to characterize the beekeeping management practices carried out in Belgium, and to determine the relationship between beekeeping management practices and colony losses. Variables obtained from face-to-face questioning of a representative randomized and stratified sample of Belgian beekeepers (n = 186) were integrated into a logistic regression model (univariate and multivariate) and correlated to the declared colony loss rates to identify risk and protective indicators. We used a classification tree analysis to validate the results. We present evidence of a relationship between poor beekeeping management practices and colony losses. The main factors protecting honey bee colonies are the aptitude of the beekeeper to change his management practices, the hive type, the equipment origin and hygiene, wintering in proper conditions (the use of divider boards, i.e. board blocks or space fillers off part of the hive body), the colony strength estimation before wintering, winter monitoring, and last but not least, appropriate integrated pest management. Proper estimation of the Varroa infestation level should be performed prior to treatment. The consequences of poor beekeeping practices on honey bee health can be addressed by proper training of beekeepers. An online tool was developed and published for beekeepers allowing them to evaluate the effect of their management practices on colony health. (c) 2021 Elsevier B.V. All rights reserved

Quick Order Fairness

Leader-based protocols for consensus, i.e., atomic broadcast, allow some processes to unilaterally affect the final order of transactions. This has become a problem for blockchain networks and decentralized finance because it facilitates front-running and other attacks. To address this, order fairness for payload messages has been introduced recently as a new safety property for atomic broadcast complementing traditional agreement and liveness. We relate order fairness to the standard validity notions for consensus protocols and highlight some limitations with the existing formalization. Based on this, we introduce a new differential order-fairness property that fixes these issues. We also present the quick order-fair atomic broadcast protocol that guarantees payload message delivery in a differentially fair order and is much more efficient than existing order-fair consensus protocols. It works for asynchronous and for eventually synchronous networks with optimal resilience, tolerating corruptions of up to one third of the processes. Previous solutions required there to be less than one fourth of faults. Furthermore, our protocol incurs only quadratic cost, in terms of amortized message complexity per delivered payload

Quick Order Fairness

Leader-based protocols for consensus, i.e., atomic broadcast, allow some processes to unilaterally affect the final order of transactions. This has become a problem for blockchain networks and decentralized finance because it facilitates front-running and other attacks. To address this, order fairness for payload messages has been introduced recently as a new safety property for atomic broadcast complementing traditional agreement and liveness. We relate order fairness to the standard validity notions for consensus protocols and highlight some limitations with the existing formalization. Based on this, we introduce a new differential order fairness property that fixes these issues. We also present the quick order-fair atomic broadcast protocol that guarantees payload message delivery in a differentially fair order and is much more efficient than existing order-fair consensus protocols. It works for asynchronous and for eventually synchronous networks with optimal resilience, tolerating corruptions of up to one third of the processes. Previous solutions required there to be less than one fourth of faults. Furthermore, our protocol incurs only quadratic cost, in terms of amortized message complexity per delivered payload

CaronDeweyHortNationalSurveyManaged.pdf

Honey bee colony losses are a major concern in the USA and across the globe. Long-term data on losses are critical for putting yearly losses in context. US colony loss surveys have been conducted yearly since the winter of 2006–2007. Here, we report the results from the eighth annual survey on winter losses and the second annual survey of summer and annual losses. There were 7425 valid respondents (7123 backyard, 190 sideline, and 112 commercial beekeepers) managing 497,855 colonies, 19 % of the total US colonies. Total losses reported were 19.8% [95% CI 19.3–20.3 %] over the summer, 23.7 % [95% CI 23.3–24.1 %] over the winter, and 34.1 % [95 % CI 33.6–34.6 %] for the whole year. Average losses were 15.1 % [95 % CI 14.5–15.7 %] over the summer, 44.8 % [95 % CI 43.9–45.7 %] over the winter, and 51.1 % [95 % CI 50.2–51.6 %] for the whole year. While total winter loss was one of the lowest reported in 8 years, 66%of all beekeepers had higher losses than they deemed acceptable.Keywords: mortality, honey bee, survey, USA, colony losse

Winter weather predicts honey bee colony loss at the national scale

Western honey bees (Apis mellifera) have experienced elevated rates of colony loss over the past decade. Past studies have attempted to determine what factors are behind these losses; however, few have considered the effects of environmental variables; key drivers in ecological systems. Existing investigations were conducted at local spatial scales, over small geographic areas, and failed to measure how environmental variables may influence colony loss rates differently across space. Here, we sought to determine the ability of environmental variables to explain honey bee colony winter loss rates across the contiguous U.S. over a nine-year study period, while elucidating how spatial methods produce results which differ from non-spatial approaches. To conduct this study, loss data from stationary beekeepers were obtained from the Bee Informed Partnership’s national Colony Loss and Management Survey for winters spanning from 2011 to 2019 and were aggregated by zip code. Environmental data (i.e., temperature, precipitation, relative humidity, wind speed, elevation) were obtained from PRISM, the Global Wind Atlas, and the U.S. Geological Survey, and averaged by month across the study period. Environmental variables and loss were regressed using linear and geographically weighted regressions. Results demonstrated that effects of environmental variables on colony loss varied across space, indicating that spatial models should be used when studying honey bee colony losses. Additionally, we found that increased winter colony loss rates were linked to lower November mean maximum temperatures and less February mean precipitation, thus, these two variables may be good predictors of observed winter loss rates. Finally, results also revealed that weather conditions during winter months were better predictors of winter colony loss than conditions during other months of the year. Overall, our results illustrate how environmental factors strongly impact managed honey bees and highlight the importance of regionally specific management practices to help prevent losses in the future

Survey-derived best management practices for backyard beekeepers improve colony health and reduce mortality.

Honey bee colony losses in the US have exceeded acceptable levels for at least a decade, leaving beekeepers in need of management practices to improve colony health and survival. Here, an empirical Best Management Practice (BMP) regimen was tested, comprised of the top four management practices associated with reduced colony mortality in backyard beekeeping operations according to Bee Informed Partnership Loss and Management survey results. Seven study locations were established across the US, and each location consisted of ten colonies treated according to empirical BMPs and ten according to average beekeeping practice. After 3 years, colonies treated according to empirical BMPs experienced reduced Varroa infestation, viral infection, and mortality compared to colonies managed with Average practices. In addition, BMP colonies produced more new colonies via splits. The colonies under Average practices were given chemical Varroa treatments only once per year, and thus spent more months above economic threshold of 3.0 mites/100 bees. Increased time spent above the economic threshold was significantly correlated to both increased viral infection and colony mortality. This study demonstrates the cumulative effects of management and colony health stressors over months and years, especially the dire importance of regular Varroa monitoring and management