Our experimental work is complemented with modelling, often in close interaction with each other. We do optimality models of life history traits as well as models on population dynamics, often linked to the individual level.

  • Optimality models (dynamic programming) 

Many animals of different taxonomic groups engage in seasonal or life-stage migrations. Although those migrations differ in many respects, e.g. in the mode of locomotion, the distances covered, the body changes made, etc., migrants typically face similar fundamental challenges namely “WHERE to go”, dealing with orientation and navigation, and “WHEN to go”, dealing with the timing of activities and migration schedules.

To find solutions to these questions, animals probably rely on environmental information but also on their (physiological) state and the responses to internal and external conditions have most likely been shaped by evolutionary processes. We use state-dependent dynamic optimality models to investigate the potential causes and consequences of migration routes and schedules. These models find the optimal behaviour of organisms under a set of environmental conditions, e.g. food and wind, and produce predictions of individual trajectories, which can be compared to and scrutinized by empirical observations.

  • Movement models (Levy walks)

Foraging movement of animals in unpredictable habitats is often modelled as a Lévy walk. In the project group Movement Ecology we aim to theoretically and experimentally examine possible mechanisms causing apparent Lévy movement as well as incorporate more realistic features like interactions with landscape features.

We study this by simulating Lévy walks in the framework of optimal foraging, trying to understand the influence of changes in landscape properties as well as movement parameters on foraging success. Furthermore, we carefully analyse movement tracks, relating theory to what we find in real ecological systems. Using insights gained from data analysis results, new movement model paradigms are developed.

  • Population models

Population biology aims to understand the factors influencing changes in population size and structure across time and space. These insights can then be used to parameterise population models, which are useful tools for analysing likely impacts of environmental perturbations (e.g. climate change) on populations.

Our long-term population studies on great tits provide an ideal opportunity to explore these issues. We use statistical modelling techniques such as generalized linear mixed models to infer how climate and density-dependent processes interactively shape fluctuations in demographic rates and population growth. We also develop matrix population models to project potential changes in population size and structure. A key goal of this modelling work is to link evolutionary processes with ecological processes in a demographic framework. By coupling demographic models with IPCC climate projections, for example, we can begin to explore critical questions such as: ‘Can rapid evolution help populations persist in the face of detrimental climate change?’