Collective sensing over multiple scales during migration

2 Ph.D/Postdoctoral Positions

Research objectives: Each year, billions of animals migrate to follow changes in seasonal food availability, escape pathogens and predators, or seek physiologically optimal climates, often navigating through complex environments to complete their migration routes. With some exceptions, migration research has largely focused on individuals, but movement decisions can be strongly influenced by social interactions. Social information could be used to reduce uncertainty with respect to migratory timing (when to migrate), as well as when and where to exploit stopover sites, and the local trajectory taken when on the move. In addition, animal groups may be able to track environmental gradients by behaving as a distributed sensory network (the collective sensing hypothesis).

We will address the role of social influence in migration, focusing on two main questions: 1) Collective sensing and the timing of movements: how do individuals within a local population make movement decisions relative to changing resource availability and energy landscapes? 2) Collective tracking of resource gradients, other environmental cues, and migration routes: how do dynamic social environments shape migratory routes, or is migration a result of large-scale gradient tracking?

The Department of Biology and the Max Planck Institute for Ornithology seeks one Ph.D. candidate to study collective sensing of the resource landscape in migratory fruit bats. Migration is a common phenomenon in birds, but is rare in bats. It is thought to be resource driven, but it is unknown for most bats how the coordinated, sudden appearance of animals at a colony occurs. Are bats just following the shifting resource landscape, or do social interactions guide the direction and distance that bats move to find their next home? The African straw-coloured fruit bat (Eidolon helvum) is one of these few species that regularly migrate over long distances. This species occurs in vast colonies across the tropical belt of Africa from where it then seasonally migrates, probably into the savannah, during the rainy season. We will use long-term deployments of ICARUS GPS tags to track individuals as they move across ecosystems. Local higher-resolution GPS tracking will be used to identify and monitor food trees to measure how movement decisions are related to foraging returns relative to energetic expenditure. This will allow us to explore how colonies may function as extended sensory networks to scout out environmental conditions and trigger the massive migratory movements of these colonies. This position would involve tagging large bats, ground truthing tracks and visiting stop-over sites. You would have to work closely with African collaborators and take the lead on organizing the logistics of field trips. Data analysis would cover movement data, remote sensing, and drone image analysis using machine learning techniques for food availability extrapolations. (Advisers: Dr. Dina Dechmann, Dr. Teague O’Mara  and Prof. Martin Wikelski).

The Department of Biology and the Max Planck Institute for Ornithology seeks one Postdoctoral candidate to study collective sen sing in white storks. Seasonal variability in resource availability is the driving force for migratory behaviour. Able to travel thousands of kilometres, white storks form large migratory groups without differentiated social relations. Instrumented with GPS plus additional acceleration and remote sensing data we will track the migrations of storks to inform us about individuals and their environment. The main goal is to understand how social information and the collective sensing of environmental gradients drive migration timing, routes, and fine-scale movements. we will record movements of large parts of the white stork population in south-western Germany, using ICARUS tags with GPS and inertial measurements. These data will be used to reveal how these social migrants 1) synchronise movements over large spatial scales; 2) form and maintain spatio-temporally dynamic group structures, and 3) integrate environmental and social information while travelling long distances. (Advisers: Dr. Andrea Flack  and Prof. Martin Wikelski).