This research is supported by an Individual Research Grant by the German Research Foundation DFG (2021-2025, grant no. WO 2420/2-1 to Juliane Wolter)
Lakes and drained lake basins cover large areas of arctic lowlands from Siberia to the western Canadian Arctic. Lakes are important contributors to greenhouse gas emissions from arctic lowlands because of increased microbial activity in thawed zones beneath them. After lake drainage, permafrost refreezing, vegetation colonization and wetland development in drained lake basins may potentially limit and reshape these emissions.
The main goals of QUIC-DRAIN are (i) to understand organic matter dynamics in arctic drained lake basins in relation to changes in vegetation, and (ii) to upscale these findings to the regional scale to identify potential current and future greenhouse gas emission hotspots. Data on vegetation succession, organic matter composition and carbon storage, and even drainage frequencies are still scarce and spatial coverage is low. Estimations of carbon contribution from permafrost regions to the atmosphere must include reliable data from wetlands in drained lake basins, which are currently missing. QUIC-DRAIN will fill this knowledge gap by focussing on three objectives aimed at (1) defining the timing, spatio-temporal patterns and drivers of Holocene thermokarst lake drainage, (2) assessing vegetation succession and carbon dynamics following drainage at plot-scale, and (3) upscaling carbon pools and cycling in different vegetation succession stages to regional scale and identifying potential future GHG production hotspots.
We will address these objectives in an interdisciplinary approach by reconstructing drainage ages and environmental drivers of drainage using remote sensing and sediment cores from drained lake basins. We will study post-drainage vegetation succession, organic matter properties and vegetation-organic matter relationships in plant macrofossil and biogeochemical laboratory analyses and incubation experiments on sediment core material as well as in vegetation surveys. Finally, QUIC-DRAIN will upscale these findings to region scale using remote sensing and machine-learning techniques, with remotely sensed land cover as a proxy for carbon dynamics. QUIC-DRAIN is unique in that it specifically targets past and present drainage events and the environmental conditions following them across large regions.
Prof. Dr. Bertrand Fournier, Institute of Environmental Sciences and Geography, University of Potsdam, Germany
Prof. Dr. Guido Grosse, Permafrost Research Section, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (AWI) Potsdam, Germany
Dr. Benjamin M. Jones, Water and Environmental Research Center, University of Alaska Fairbanks, USA
Dr. Susanne Liebner, Section 5.3: Geomicrobiology, Helmholtz Centre Potsdam German Research Centre for Geosciences (GFZ) Potsdam, Germany
Prof. Dr. Gesine Mollenhauer, Marine Geochemistry Section, AWI Bremerhaven, Germany
Dr. Isla Myers-Smith, School of GeoSciences, University of Edinburgh, UK
Dr. Jens Strauss, Permafrost Research Section, AWI Potsdam, Germany
Dr. George Tanski, Geological Survey Canada, Halifax, Canada
Prof. Dr. Damaris Zurell, Institute for Biochemistry and Biology, University of Potsdam, Germany