I am a modeller in ecological research mainly focusing on spatially explicit and individual-based approaches. I personally aspire towards research that incorporates environmental factors influencing animals with a focus on causes and consequences of animal movement. Furthermore, I prefer spatially-explicit approaches to simulate and evaluate these effects. In addition, I have empirical experiences in tracking mammals (e.g. European brown hares, raccoons) and handling of GPS and acceleration data. I consider movement ecology an important avenue for predicting effects of environmental change and landscape fragmentation on animals and thus for biodiversity conservation.
Understanding the pattern of complex disease dynamics and host-pathogen coexistence requires unravelling the mechanisms behind the variation in host behavior and contact processes acting at different spatial and temporal scales (Tompkins et al. 2010 J Animal Ecology). Many wildlife species are distributed in distinct spatial clusters, be it depending on social groups or due to habitat fragmentation. Thus, host movement plays an important role in driving on-going disease dynamics by transmitting pathogens to distant hosts, thereby connecting infected host patches with new areas that would otherwise be isolated. In concert with heterogeneous environments, variability in host movements will change contact and transmission processes by bridging between locally unstable host-virus interactions (Hagenaars et al. 2004 J Theo Biol) with consequences for the speed of the epidemic front (McCallum 2008 in: “Infectious Disease Ecology”) Since a major issue for controlling diseases is to understand how pathogens can persist within their host’s population, it is of paramount importance to understand the role of movement and dispersal on the transmission process. This is particularly challenging in dynamic landscapes with high levels of human disturbance.
Spatially-explicit individual-based models provide a suitable experimental system in which individual variability in movement patterns of the host can be combined with a quantitative description of the infection process. Recently, Riley et al. (2015 Epidemics) proposed the incorporation of more flexible and accurate movement assumptions as a current challenge for spatially-explicit disease models.
My PhD project deals with the interplay of movement decisions, landscape heterogeneity and disease dynamics. The project aims to understand how spatio-temporal host-pathogen coexistence patterns (e.g. rabies in foxes, classical swine fever in wild boars) are affected by combined effects of (1) spatial and temporal land-use change, and (2) host individual’s movement decisions and life-history traits.
By combining existing spatially explicit epidemiological approaches with more accurate habitat-dependent movement models we hope to gain new insights on landscape effects on movement patterns and disease persistence. We will assess whether stabilizing mechanisms play a role in host-pathogen systems when both pathogen (upon its arrival) and host (after being suppressed to low numbers by a pathogen) are at low densities.