This article presents managed honey bee colony loss rates over winter 2018/19 resulting from using the standardised COLOSS questionnaire in 35 countries (31 in Europe). In total, 28,629 beekeepers supplying valid loss data wintered 738,233 colonies, and reported 29,912 (4.1%, 95% confidence interval (CI) 4.0-4.1%) colonies with unsolvable queen problems, 79,146 (10.7%, 95% CI 10.5-10.9%) dead colonies after winter and 13,895 colonies (1.9%, 95% CI 1.8-2.0%) lost through natural disaster. This gave an overall colony winter loss rate of 16.7% (95% CI 16.4-16.9%), varying greatly between countries, from 5.8% to 32.0%. We modelled the risk of loss as a dead/empty colony or from unresolvable queen problems, and found that, overall, larger beekeeping operations with more than 150 colonies experienced significantly lower losses (p < 0.001), consistent with earlier studies. Additionally, beekeepers included in this survey who did not migrate their colonies at least once in 2018 had significantly lower losses than those migrating (p < 0.001). The percentage of new queens from 2018 in wintered colonies was also examined as a potential risk factor. The percentage of colonies going into winter with a new queen was estimated as 55.0% over all countries. Higher percentages of young queens corresponded to lower overall losses (excluding losses from natural disaster), but also lower losses from unresolvable queen problems, and lower losses from winter mortality (p < 0.001). Detailed results for each country and overall are given in a table, and a map shows relative risks of winter loss at regional level.
This article presents managed honey bee colony loss rates over winter 2019/20 resulting from using the standardised COLOSS questionnaire in 37 countries. Six countries were from outside Europe, including, for the first time in this series of articles, New Zealand. The 30,491 beekeepers outside New Zealand reported 4.5% of colonies with unsolvable queen problems, 11.1% of colonies dead after winter and 2.6% lost through natural disaster. This gave an overall colony winter loss rate of 18.1%, higher than in the previous year. The winter loss rates varied greatly between countries, from 7.4% to 36.5%. 3216 beekeepers from New Zealand managing 297,345 colonies reported 10.5% losses for their 2019 winter (six months earlier than for other, Northern Hemisphere, countries). We modelled the risk of loss as a dead/empty colony or from unresolvable queen problems, for all countries except New Zealand. Overall, larger beekeeping operations with more than 50 colonies experienced significantly lower losses (p < 0.001). Migration was also highly significant (p < 0.001), with lower loss rates for operations migrating their colonies in the previous season. A higher proportion of new queens reduced the risk of colony winter loss (p < 0.001), suggesting that more queen replacement is better. All three factors, operation size, migration and proportion of young queens, were also included in a multivariable main effects quasi-binomial GLM and all three remained highly significant (p < 0.001). Detailed results for each country and overall are given in a table, and a map shows relative risks of winter loss at the regional level.
Virtual reality can provide the means of computer interaction for disabled people. There are many methods for aiding disabled people to communicate with computer; however some of them may require high amount of processing and cannot be implemented in real-time applications. In addition, many methods may require additional equipment to be attached to the users, which can reduce freedom of movement and increase cost of the system. In this article, we propose a real time, low cost and hands free method for typing; only utilizing user's head movements. Head movement detection is done by a color-marker discrimination algorithm, which compares differences between RGB, hue and saturation components of the markers and the environment. The method has shown to be adoptable to different lighting conditions. Also, trained users showed to be able to type a text with a reasonable speed (4.5 s for each character), and with a low error rate (0.0% to 5.5%).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.