Seminar of the Department of Microbiology
The development of terrestrial ecosystems emerging after glacier retreat
Gentile Francesco Ficetola – Professor - Università degli Studi di Milano Statale Milan, Italy
06.06.2024, 11:00 - Hybrid
- Join online
- or in presence: Seminarraum biologie - Foyer (Technikerstraße 25, EG)
Abstract
Multiple factors can determine biotic colonization of terrains exposed after the retreat of glaciers, including time after glacier retreat, macro-climatic differences across areas of the world, and the rapidly evolving abiotic and abiotic features of these environments. Until now, the complete reconstruction of soil communities was hampered by the complexity of identification of organisms, thus analyses at broad geographical and taxonomic scale have been so far impossible. We used the metabarcoding of environmental DNA extracted from soil to reconstruct the evolution of communities in chronosequences from 48 glacier forelands from four continents; we targeted all the major taxonomic groups (bacteria, fungi, plants, protists and soil animals). Soil animals colonize ice-free areas almost immediately. While both taxonomic and functional diversities quickly increase over time, this is modulated by climate so that colonization starts earlier in forelands with less cold summer temperatures. Colder forelands initially host poor communities, but the colonization rate then accelerates, eventually leveling biodiversity differences between climatic regimes after 150 years. Nevertheless, the rate of colonization is strongly different across taxonomic groups. Micro-organisms already attain high richness immediately after glacier retreat, but then community richness increases at a slow rate. Conversely, for animals and plants the rate of increase accelerates through time. This occurs because of the interplay between time, soil features and biotic components of communities. Environmental DNA allows an all-inclusive study of community ecology, which reveals how complex biotic interactions arise through time, and will help to predict the impacts of climate change on the whole ecosystems.