SPAECO · Spatial ecology: bringing mathematical theory and data together

The goal of my research plan is to make fundamental progress in the understanding of the ecological and evolutionary dynamics of populations inhabiting the heterogeneous and changing landscapes of the real world. To reach this goal, I will construct general and mathematically rigorous theories and develop novel statistical approaches linking the theories to data. In the mathematical part of the project, I will construct and analyze spatial and stochastic individual-based models formulated as spatiotemporal point processes. I have already made a methodological breakthrough by showing how such models can be analyzed in a mathematically rigorous manner. I plan to use and further develop the mathematical theory to study the interplay among endogenous and exogenous factors in spatial ecology, genetics, and evolution. To link the theory with data, I will develop novel combinations of forward (from process to pattern) and inverse (from pattern to process) approaches in the context of five empirical problems. First, I will build on the strong interaction between empirical studies and modelling in the Glanville fritillary butterfly to develop approaches that integrate genetics with ecology and evolutionary biology in highly fragmented landscapes. Second, I will investigate dead-wood dependent species as a model system of population dynamics in dynamic landscapes, bridging the current gap between data and theory in this system. Third, I will use existing data on butterflies, wolves and bears to study how animal movement depends on the interplay between landscape structure and movement behaviour and on intra- and interspecific interactions. Fourth, I will address fundamental questions in evolutionary quantitative genetics, e.g. the evolution of the matrix of additive genetic variances and covariances. Finally, I will develop Bayesian state-space approaches to root species distribution modelling more deeply in ecological theory.