The University of British Columbia Burnaby, British Columbia, Canada
Aedes aegypti and Ae. togoi are mosquitoes with vast geographical distribution difference. While Ae. aegypti mosquitoes have spread to all continents, Ae. togoi have been localized to the Oriental and Palaearctic regions, and recently became established in northwestern North America, including British Columbia. Given that climate change might allow the establishment of Ae. aegypti in British Columbia in the future, the subsequent competitive interactions of the two species and their respective survival could become an interesting stream of investigation. To this end, we attempt to statistically classify and model the larval stage of the two mosquito species, and then proceed to experimentally simulate how their behaviour changes when the two larval species are placed in the same pooling container. All the behavioural experiments will be captured by Raspberry Pi cameras. To ensure precise tracking of the larval movements, DeepLabCut will be employed. DeepLabCut is a convolutional neural network that does markerless pose-estimation permitting for capturing all aspects of an animal’s motor movements. This intensive quantitative behavioural study gives insight to the future of these two organisms’ interaction, which will be most apparent in the larval stage, and how their behaviour will change each species' fitness against each other.
