Projects
'Glacial legacy on the establishment of evergreen vs summergreen boreal forests'
Ecosystem services of boreal forests are of critical importance for humanity and differ markedly between evergreen and summergreen needle‐leaf forests. GlacialLegacy will address the timely questions “Why is northern Asia dominated by summergreen boreal forests?" and “How will these larch forests change in the future?” with a coherent empirical and modelling approach integrating pollen data synthesis, sedimentary ancient DNA analyses, vegetation and biophysical surveys and vegetation modelling.
The hypothesis is that summergreen and evergreen needle‐leaf forests represent alternative quasi‐stable states occurring under similar climates today but which came about because of the different (genetic) characteristics of the northern tree refugia – a legacy of the preceding glacial stage. Once established Asian larch forests stabilised because of their unique vegetation–fire–permafrost–climate system that inhibits the invasion of evergreen taxa. However, the long‐term vegetation trajectory causes the irreversible transition of summergreen into evergreen needle‐leaf forests. This is mainly because larch is a poor competitor compared to evergreen spruce and pine when growing in mixed stands. Asian larch forest would only be able to re‐establish after a new forest‐free glacial stage. As both boreal forest types are only stable across a certain climate range, a future warmer and drier climate may cause their transition into steppe, which is irreversible for Asian larch forests.
Funding: European Research Council Consolidator Grant 2018-2023
Cooperation:
- Prof. Dr. Luidmila A. Pestryakova (NEFU, University Yakutsk)
Further reading:
Herzschuh, U., Birks, H.J.B., Laepple, T., Andreev, A., Melles, M., & Brigham-Grette, J. (2016). Glacial legacies on interglacial vegetation at the Pliocene-Pleistocene transition in NE Asia. Nature Communications. 7, 1–11. doi:10.1038/ncomms11967, https://www.nature.com/articles/ncomms11967.pdf
Lake & Sea-ice algae
The seasonal extent and properties of Arctic ice on land and in the ocean determine the efficacy of the albedo feedback mechanism causing arctic climate amplification. Various ice types are inhabited by specific ice algae that across taxonomic boundaries share similar mechanisms to survive in these extreme environments. This project explores the potential of sedimentary DNA as a proxy for ice cover changes on millennial time-scales (last 6000 years) by analysing the taxonomic and functional community composition in ice, water column and sediment-surface samples, and in marine and lake sediment cores from the Fram Strait, Northwest Pacific, and Siberia (Samoylov, Central Yakutia).
Research focus: High-latitude Biodiversity
Contact: Kathleen Stoof-Leichsenring, Heike Zimmermann
Cooperation:
- AWI Bremerhaven:
Marine Geology (Prof. Dr. Rüdiger Stein, Dr. Juliane Müller)
Polar Biological Oceanography (Dr. Katja Metfies) - NEFU Yakutsk: Prof. L. Pestryakova
High-resolution reconstruction of regional climate changes in Antarctica
- Glaciological and isotope-geochemical studies on the Antarctic Peninsula and the West Antarctic Ice Sheet
This project is investigating the recent and past climate variability of two high-accumulation regions in West Antarctica - the northern Antarctic Peninsula and the Union Glacier region in the Ellsworth Mountains on the West Antarctic Ice Sheet - and will determine the potential forcing factors for observed changes. To do so, newly collected firn cores from both regions are used as natural climate archives and analysed at high (sub-annual) resolution for density, stable water isotopes and various chemical parameters. New data on accumulation rates and meteorological parameters (e.g. air temperature) as well as information on moisture-source regions and transport paths of precipitating air masses will be collected.
Research Focus: Past Climate Change
Contact: Kirstin Hoffmann, Hanno Meyer
Funding: Elsa-Neumann Scholarship of the state of Berlin for Kirstin Hoffmann (2016-2019)
Cooperation:
- Department of Geography, Humboldt-University of Berlin, Germany – Prof. Dr. Christoph Schneider
- Facultad de Ingeniería, Universidad Nacional Andrés Bello (UNAB), Viña del Mar, Chile – Dr. Francisco Fernandoy
- Trace Chemistry Laboratory, Division of Hydrologic Sciences, Desert Research Institute (DRI), Reno, Nevada, USA – Dr. Joseph R. McConnell
- Ice Dynamics and Paleoclimate, British Antarctic Survey (BAS), UK – Dr. Elizabeth R. Thomas
HEIBRiDS research projects
Interdisciplinary research projects at the interface between natural science and data science
Topic A: "Arctic Environmental Data Analytics"– Gregor Pfalz
Topic B: "Data fusion using remote sensing data and machine/deep learning techniques to better understand present, past and future vegetation dynamics in Central Yakutia" – Femke van Geffen
The Helmholtz Einstein International Research School in Data Science (HEIBRiDS) is a cooperation project with the Einstein Center Digital Future (ECDF), Berlin’s universities and the six Helmholtz Centers in the capital region.
The different doctoral theses focus on topics from the fields of imaging, machine learning, modeling, innovative hardware concepts, visualization and sequencing. The interdisciplinary topics are formulated and supervised by a team consisting of two professors, one of whom is a member of the Helmholtz Association and one an ECDF member
HEIBRiDS can therefore rely on a unique environment that enables research, from different perspectives, into the core methods, algorithms and processes of digitalization, while at the same time transporting knowledge between different disciplines.
Topic A tries to reconstruct past and present relationships between climate changes in the Arctic and ecosystem dynamics in northern lake systems, by developing a data analysis system designed for multivariate statistics on lake sediment core parameters.
The goal of Topic B, is to employ machine-learning and deep-learning methods to analyse data to gain better insights into the dynamics of the vegetation species and how these are changing over time. In order to accomplish this goal, various types of remote-sensing data are used such as Sentinel-2 and Landsat 7/8 as well as drone data collected in the field. The ultimate goal is to develop a fusion method that can use the available data to create a comprehensive overview of vegetation dynamics of the past, present and future. .
Research focus: Arctic Lake System Dynamics (Topic A)
High-latitude Vegetation Change (Topic B)
Contact: Boris Biskaborn, Ulrike Herzschuh, Bernhard Diekmann, Gregor Pfalz, Femke van Geffen
Funding: HEIBRiDS Graduate School (2018 – 2022)
Cooperation:
- Einstein Center Digital Future
- Humboldt-Universität zu Berlin – Databases and Information Systems: Prof. J.-C. Freytag, Ph.D. (Topic A)
- Technische Universität Berlin – Remote Sensing Image Analysis Group: Prof. Dr. Begüm Demir (Topic B)
ESA CCI+ Permafrost
The European Space Agency (ESA) Climate Change Initiative (CCI+) provides consistent time series for climate-research related applications. Within CCI+ Permafrost (2018-2021) the University Oslo produces circum-Arctic time series of permafrost temperature and active layer thickness for the period from 2003 to 2017 using the transient equilibrium model CryoGrid forced by land surface temperature and snow water equivalent derived from satellite data.
AWI Potsdam is responsible for the Permafrost_cci permafrost product validation. We are assembling the Permafrost_cci und REKLIM data collection of shallow ground temperature measurements and data on stratigraphy, ground ice and vegetation. According to the Earth System 3-Layer model for permafrost landscapes (Warwick et al. 2017) we bring together all data of the three layers, namely the active layer, permafrost and the buffer layer consisting of vegetation/infrastructure/snow layer.
Research focus: High-latitude Vegetation Change
Contact: Birgit Heim, Mareike Wieczorek
Partner: ESA Climate Change Initiative
Cooperation:
- Gamma Remote Sensing and Consulting AG (GAMMA), Switzerland - Dr. Tazio Strozzi
- b.geos GmbH (B.GEOS), Austria - Dr. Annett Bartsch
- AWI Potsdam Permafrost Research, Germany – Prof. Dr. Guido Grosse, Dr. Ingmar Nitze
- AWI Potsdam Atmospheric Research, Germany – Dr. Heidrun Matthes, Prof. Dr. Annette Rinke
- University of Oslo, Geosciences, Norway - Prof. Dr. Sebastian Westermann, Dr. Jaros Obu
- University of Fribourg, Geosciences, Switzerland - Prof. Dr. xxx
- Bolin Centre of Climate Research of Stockholm University, Sweden - Prof. Dr. Gustaf Hugelius
- West University of Timișoara, Geosciences, Romania
- TERRASIGNA, Bucharest, Romania
- Norwegian Research Centre NORCE, Tromsø, Norway
- University Centre in Svalbard UNIS Norway
Figure (left) Northern hemisphere Permafrost_cci permafrost probability and in situ ground temperature + environmental data collection from a wide range of measurement programs. (right) This Permafrost-cci and REKLIM data collection brings all data together according to the 3-layer concept of permafrost landscapes where 2 layers are permafrost and active layer from the Geo-and Cryosphere and the 3rd layer is the buffer layer of the Bio-and Hydrosphere including the infrastructure (data collection is ongoing during this project).
Space-time structure of climate change
SPACE determines and uses the space-time structure of climate change from years to millennia to test climate models, fundamentally improve the understanding of climate variability and provide a stronger basis for the quantitative use of paleoclimate records. The instrumental record is only a snapshot of our climate record. Two recent advances allow a deeper use of the paleo-record: (1) the increased availability and number of paleoclimate records and (2) major advances in the understanding of climate proxies (see also the ECUS project). We recently showed (see Laepple and Huybers, 2014, PNAS) that consistent estimates of regional temperature variability across instruments and proxies can now be obtained by inverting the process by which nature is sampled by proxies.
Empirical evidence and physics suggest an intrinsic link between the time scale and the associated spatial scale of climate variations: While fast variations such as weather are regional, glacial-interglacial cycles appear to be globally coherent. SPACE will quantify this presumed tendency of the climate system to reduce its degrees of freedom on longer time scales, and use it to constrain the sparse, noisy and at times contradictory evidence of past climate changes. This will provide a key step forward in transforming paleoclimate science from describing data to using the data as a quantitative test for models and system understanding in order to see more clearly into the future.
Research Focus: Earth System Diagnostics
Contact: Thomas Laepple
Funding: €1.5M European Research Council Horizon 2020 Grant 2017-2022
further information:
Rehfeld, Kira, Thomas Münch, Sze Ling Ho, and Thomas Laepple. 2018. “Global Patterns of Declining Temperature Variability from the Last Glacial Maximum to the Holocene.” Nature 554 (7692): 356–59. https://doi.org/10.1038/nature25454.
Kunz, T., Dolman, A. M., & Laepple, T. (2020). Estimating the timescale-dependent uncertainty of paleoclimate records – a spectral approach. Part I: Theoretical concept. Climate of the Past Discussions, 1–38. https://doi.org/10.5194/cp-2019-150
figures: On longer time-scales, the spatial extent of the variations is increasing (space-time structure)
