I study how forests respond to their environment and how the complex interplay of phenotypic traits determines tree response variation.
Motivated by the general quest of finding tree species, provenances and genotypes coping well with the changing climate, I am interested in answering questions such as which individuals benefit the most from an earlier start of the growing season? Which suffer the least from the increasing frequency of droughts or beetle infestations? And which show the highest potential for assisted migration at critical sites?
To answer these and other questions, I make use of proximal and remote sensing techniques, e.g., leaf-level spectroscopy, drone-based imaging, air- and satellite-borne data time series. I combine these with statistical methods and machine learning, to develop scalable, high-throughput, phenotyping approaches that alleviate the challenges of traditional measurements of plant traits and physiology.