Demography, Information and the Movement Ecology of Capuchins
Background. Patterns of animal movement are shaped by a variety of factors, including the distribution of resources across the landscape, individuals’ sensory capabilities, and their past experience and memory. In social species, individual and group-level characteristics both shape patterns of movement and space-use, but how they interact remains poorly understood. Further, demography likely plays an underappreciated role in the movement ecology of social species, as the immigration of ‘strangers’ may be an important source of novel information about the environment. If immigrants expand their newly adopted group’s spatial horizons, we expect that the arrival of new group members will coincide with the discovery of new resources on the landscape and result in changes in group ranging behavior.
Project Details. The student will compare the movement ecology of capuchin groups of different sizes and demographic histories and will investigate how immigration (and emigration) of individuals impacts the ranging patterns of groups by combining data on movement and demography from long-term studies of capuchin monkeys in Panama and Costa Rica. Research will primarily involve modeling and quantitative analysis of existing data, but may also include field work at the Lomas Barbudal field-site in Costa Rica. Start date is flexible and will be between June and October of 2020.
Supervision and Research Community. The student will join the International Max Planck Research School for Organismal Biology (IMPRS), a cooperative doctoral program between the Max Planck Institute of Animal Behavior, the Max Planck Institute for Ornithology and the University of Konstanz, and will be co-supervised by Prof. Meg Crofoot (MPI-AB, University of Konstanz), Dr. Susan Perry (UCLA) and potentially Dr. Brendan Barrett (MPI-AB, MPI-EvA). The University of Konstanz and the Max Planck Institute for Animal Behavior together form a thriving research community representing a global hotspot for collective behavior and animal movement research.
Qualifications. The project will involve theoretical modelling and quantitative data analysis of movement data using programming. The ideal candidate should have a background in behavioral ecology and experience in at least one of these areas as well as a positive attitude and enthusiasm for learning the other. Demonstrated ability to engage in independent research is desirable. A collaborative spirit and the ability to work as part of a team are essential. A Masters degree in ecology, zoology, evolutionary anthropology or a related subject is desirable, but is not required to apply. Applicants who have not completed a Masters will be considered on a case-by-case basis by the Doctoral Committee and might be required to complete additional course-work. The working language of the group is English, and German language skills are not a requirement.
Location. Konstanz is a vibrant small city located on the border between Germany and Switzerland, on the shores of the Bodensee (Lake Constance). It is easy to get out into the beautiful German and Swiss countryside and the Alps, as well as to neighboring Zurich and Munich.
Application Process. Applicants should apply via the IMPRS application system (due 15 January 2020), and are also required to include a CV and a research statement (see below for details).
Research Statement Instructions. Applicants should include a 1-2 page research statement that addresses the following points:
- Describe your main research interests, how they developed, and how they relate to the proposed research project.
- Describe 1-2 hypotheses you would like to test (or analyses you would like to perform) in the context of the described project, and indicate how you would address them using field experiments or analysis of movement data.
- Give an example of a time in your past education or research experience in which you faced a problem or a challenge, and describe how you addressed it.
Keywords. Movement ecology, ranging and space-use, information, collective behavior, computational analysis