Effect of pathogen load, environment, and their interactions on colony-level traits

Citation

Borba RS, Hoover SE, Giovenazzo P, Currie RW, Pernal SF, Zayed A, Foster LJ (2018) Effect of pathogen load, environment, and their interactions on colony-level traits. Entomological Society of America, Entomological Society of Canada and Entomological Society of British Columbia Joint Annual Meeting, 11-14 Nov 2018, Vancouver, BC. https://esa.confex.com/esa/2018/meetingapp.cgi/Paper/137683

Abstract

Overwintering mortality of honey bee colonies in Canada has been continuously greater than the acceptable range of 0% to 15% since the winter of 2006/2007. The main causes of colony death, as reported by Canadian beekeepers, include high pathogen/parasite infestation levels poor quality queens and severe weather conditions. Every year, Canadian beekeepers import hundreds of thousands of queens, mainly from the U.S.A. and New Zealand. The importation of foreign queens has the potential to introduce undesirable pathogens or genetics and supply bees that have not been selected to survive in northern temperate climates. The goal of our project is to measure 12 economically-valuable traits of honey bees and develop genomic and proteomic markers for each trait that will enable beekeepers to rapidly select and breed healthy and productive colonies that are well adapted to the Canadian climate. In addition, this project also aims to study the effects that the different landscapes and climate found in various geographical locations in Canada have on these colony traits and bee behaviours. In 2016, colonies across Canada were sampled and phenotypic data was collected for the following colony-level traits: 1) Varroa mite population growth 2) grooming behaviour; 3) hygienic behaviour; 4) defensive behaviour; 5) honey production; 6) sealed brood population; 7-9) pathogen abundance (viruses, Nosema spp., Trypanosomatids); 10) innate immunity factors; 11) gut microbiota; and 12) overwintering success. This talk will focus on our progress to model and analyse this data to identify predictive relationships between pathogen load, environment and colony-level traits.

Publication date

2018-11-11

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