I am interested in patterns and processes that give rise to phenotypic variation in natural populations over ecological timescales. Specifically, I study how phenotypes are shaped by complex selection scenarios, such as selection for combinations of traits (correlational selection) or modularization (phenotypic integration).

Moreover, I am investigating how variation in the environment experienced during early life stages can lead to alternative developmental trajectories (developmental plasticity), and how this may affect speed and direction of evolutionary change, for example, by selecting for plastic responses to variation of the environment (adaptive plasticity).


My aim is to understand both proximate and ultimate causes of phenotypic variation within and across natural populations.



Throughout my career I have used a variety of aquatic invertebrate model systems to investigate the causes of variation in phyisology, morphology, and behaviour with controlled laboratory experiments, outdoor mesocosm experiments, and field surveys. This includes stone corals (Scleractinia), marine and freshwater amphipods (Amphipoda) and isopods (Isopoda), and, more recently, damselflies and dragonflies (Odonata).

To uncover the causal links between genotypes, environmental factors, and multivariate phenotypes, I am collecting high dimensional phenotypic (phenomic) data in high throughput using computer vision; the automated extraction of meaningful information from digital images. To that end I employ a combination of techniques, ranging from semi-manual signal processeing over classical machine learning to deep learning.