Catch my drift: Using computer vision to study honey bee drifting's effect on pest and pathogen transmission

The honey bee (Apis mellifera) is currently facing a global increase in annual colony losses. This increase in mortality is not the product of one ecological factor but is attributed to a combination of habitat loss, pests, pathogens, poor nutrition, and agrochemicals. Pests and pathogens are considered the strongest drivers of colony decline in North America and gaps remain in their transmission between hives that impedes alleviating these stressors. One method of pest and pathogen transmission between colonies is through “drifting,” when an individual bee returns to a different colony, is accepted, and subsequently may introduce new health threats to the colony. This behavior can have a detrimental effect on the hive, especially in commercial apiaries, via the transmission of Varroa destructor mites or Nosema spp. spores potentially leading to colony death without management intervention. With new advancements in animal tracking and sensor engineering, we can gain new insight into honey bee drifting to better understand the relationships between drifting, pest and pathogen transmission, and overall colony health. Here, I implement a video monitoring system leveraging new advances in automated computer vision to identify individually marked bees and observe their movements between hives. I quantify pest and pathogen loads, measure colony health metrics, and analyze the relationship between individual bee movement and the spread of pests and pathogens in a controlled apiary. This study provides novel methodology for drifting research and aims to better current pest and pathogen management through chemical and pesticide-free methods.