Supervisors: Quentin Horta-Lacueva & Mark Ravinet
Background
Understanding how species rapidly adapt to new environments is crucial to address the global biodiversity crisis. The Common crossbill (Loxia curvirostra), a bird displaying highly a specialised beak shape, established in Iceland recently and appear to successfully feed on novel, exotic trees. To understand whether and how these birds have evolved feeding adaptations, we first need to know from which part of the world they originate. Our preliminary genomic data suggest that the crossbills living in Iceland come from Europe, but we don’t have enough information to locate specific founding populations. Crossbills show extensive regional variations in song and call types, so we will take advantage of this unique feature to identify regions where crossbills show the closest “dialect” to the calls recorded in Iceland. By using the extensive databanks of sounds records available on participative science databases, you will classify the call types recorded in Iceland among local areas of the western Palearctic. You will also explore the hypothesis that crossbill in Iceland may have evolved a unique call type.
We are seeking
A student interested in acoustic ecology. You will generate automated sound recognition models by using the thousands of publicly available soundtracks of crossbill calls recorded over the Palearctic. You are a biologist keen in using machine learning (you are not expected to start with a high level of expertise in programming). With the generated data in hand, you will be encouraged to explore how bird calls evolve as a trait.
What you will learn
You will build an expertise in using and developing machine learning models to tackle evolutionary questions. You will acquire experience in sound analyses and acoustic ecology. Your project will be integrated into a larger study on the ecology and evolution of crossbills, so you will gain insights on evolutionary concepts and accumulate knowledge in natural history. You will be equipped with the background to pursue a PhD project in ecology and evolution or to seek jobs in the private sector requiring skills in data analysis.
What we offer
Our research group is friendly and small. We focus on close mentorship and skills development. We conduct weekly lab meetings, during which we discuss ongoing research within the group or relevant academic literature.