Understanding why birds migrate is a long-standing problem that still largely eludes scientists. Recent advance in technology is currently leading migration science into a golden age as patterns of bird migration are increasingly being documented. However, the question of what are the ecological and evolutionary causes underlying the observed widespread variation in avian migration, remains open. Answering this will provide a greater comprehension of the forces driving how species distribute in space and time, and improve predictions of the fate of migratory birds under global change. In MIGRACAST, I will investigate the extent to which energy efficiency and biogeographic history shape avian migration patterns. These two key processes have been proposed to explain bird migration: stating that species’ migratory movements and seasonal redistribution are, respectively, energetically optimal and/or retrace postglacial colonisation routes. However, these processes have never been tested together and across many species on a large scale. To fill this important gap in migration science, I will design a novel modelling framework based on first ecological principles that uses recently developed computational tools. This model will leverage the power of multiple large datasets on the distribution, movement and genetic diversity of birds as well as environmental conditions to explicitly test hypotheses about mechanisms driving bird migration. This approach will be applied to North American bird species that are particularly rich in data and exhibits a diversity of migration behaviours. It will be utilised to (i) examine the extent to which energy efficiency drives bird migration, (ii) refine weekly bird migration forecasts on a continental scale, and (iii) back-cast bird migration to the Last Glacial Maximum (~20,000 years ago) to determine if the history of shift and expansion of seasonal ranges complements energy optimisation to shape migratory movements.
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