Insects are the most species-rich group of organisms on Earth. It has long been suggested that evolution of the wing played a crucial role in their success, but our understandings on how phenotypic variation of wing size and shape impact fitness in nature is limited.
We have an opportunity for a master’s project to study the function of wings in a damselfly in their natural habitat. We will use AI-based imaging tools to automatically extract information from digital image and combine this with a manipulative experiment conducted in the field. Our idea is to use wing damages as representation of the fitness associated with different aspects of wing morphology, then relate the fitness estimates to standing genetic and phenotypic variation of different characteristics of the wing.
The task of the student will include (1) field experiment using a mark-capture-recapture method, (2) automatized phenotyping using a machine-learning based computer vision tool, (3) statistical analyses of phenotypic and genetic variation in R statistical environment, and (4) interpretation of results based on theories in population and quantitative genetics. We are ready to incorporate with your own interest and ideas with our data and analytical resources. You will gain rich experience in image analyses using state-of-the-art computer vision tools and ways to relate this to biological questions, both empirically and theoretically.
If interested, please contact Masahito Tsuboi (masahito.tsuboi@biol.lu.se) for further details of the project.