Christoph Scherber is head of the Centre for Biodiversity Monitoring at the Leibniz Institute for the Analysis of Biodiversity Change in Bonn, Germany. He received his PhD in Jena (Germany) working in a grassland biodiversity field experiment and worked as a postdoc in Goettingen (Germany) in the Faculty of Agricultural Sciences, where he studied biodiversity in grassland and cropland, and was involved in climate and land-use change experiments. From 2015-2020 he was professor for Animal Ecology and Multitrophic Interactions at University of Muenster (Germany) at the Faculty of Geosciences. He is author of more than one hundred peer-reviewed scientific manuscripts, several book chapters, and a member of the Editorial board of “Ecology Letters”.
The assessment of biodiversity in agricultural ecosystems has been hampered by difficulties accessing the interior of large fields, high species numbers of “dark taxa” such as flies, wasps and beetles, and biased functional classification of organisms into “pests” and “beneficial” taxa. Recent advances in available hardware (sensor systems) and software (machine learning approaches), coupled with molecular revolutions in metabarcoding, now allow unprecedented insights. I will show examples from recent research projects, highlighting how modern technology and software algorithms can help elucidate biodiversity in agro-ecosystems at previously unattainable detail.