Gregor Pfalz

Gregor Pfalz

Arctic Environmental Data Analytics (2018 - )

The goal of this PhD  is to detect the past ecosystem‐climate relationships in Arctic lake settings by big data analytics of a polar proxy dataset. We focus on two topics: Data management and data science ‐ development of a data analytics system for palaeolimnological proxy data designed for multivariate statistics. Geoscience ‐ Past and present environmental dynamics in Arctic landscapes and their impact on polar lake ecosystems. A unique, standardized, data set of proxy data from lake sediment cores in the Eastern Arctic will be compiled using the new PALIM Database. To correlate ecosystem changes with climate changes, multivariate statistics will be performed on quality controlled biotic and abiotic proxy data. The objective of this project is to develop a state‐of‐the‐art data analytics system that allows to detect the main relationships of ecosystem dynamics and climate changes and their spatiotemporal pattern in dependence to lake attributes, i.e. thermokarst or glacial origin, landscape‐type, lake‐ecosystem‐type, lake age, and catchment‐vegetation.

Peer-reviewed Publications (journal or conference)

  1. H. Grotheer, V. Meyer, T. Riedel, G. Pfalz, L. Mathieu, J. Hefter et al. (2020). Burial and origin of permafrost‐derived carbon in the nearshore zone of the southern Canadian Beaufort Sea.Geophysical Research Letters, 47, e2019GL085897. https://doi.org/10.1029/2019GL085897
  2. G. Pfalz, B. Diekmann, J.-C. Freytag, and B.K. Biskaborn (2021). Harmonizing heterogeneous multi-proxy data from lake systems. Computers & Geosciences. https://doi.org/10.1016/j.cageo.2021.104791
  3. B.K. Biskaborn, L. Nazarova, T. Kröger, L.A. Pestryakova, L. Syrykh, G. Pfalz, U. Herzschuh, and B. Diekmann (2021). Late quaternary climate reconstruction and lead-lag relationships of biotic and sediment-geochemical indicators at lake Bolshoe Toko, Siberia.Front. Earth Sci., 9, 703. https://doi.org/10.3389/feart.2021.737353
  4. S.A. Vyse, U. Herzschuh, G. Pfalz, L.A. Pestryakova, B. Diekmann, N. Nowaczyk, and B.K. Biskaborn (2021). Sediment and carbon accumulation in a glacial lake in Chukotka (Arctic Siberia) during the late Pleistocene and Holocene: Combining hydroacoustic profiling and down-core analyses. Biogeosciences. https://doi.org/10.5194/bg-18-4791-2021
  5. L. Hughes-Allen, F. Bouchard, C. Hatté, H. Meyer, LA. Pestryakova, G. Pfalz, B. Diekmann, D.A. Subetto, and B.K. Biskaborn (2021). 14 000-year carbon accumulation dynamics in a Siberian lake reveal catchment and lake productivity changes, Front. Earth Sci., 9, 1–19. https://doi.org/10.3389/feart.2021.710257
  6. G. Pfalz, B. Diekmann, J.-C. Freytag, L. Sryrkh, D.A. Subetto, and B.K. Biskaborn (2022). Improving age-depth correlations by using the LANDO model ensemble. Geochronology, 4, 269–295. https://doi.org/10.5194/gchron-4-269-2022

Other (presentations at conferences or preprints)

  1. G. Pfalz, B. Diekmann, J.-C. Freytag, and B.K. Biskaborn. Decipher Arctic lakes ecosystem dynamics. (Poster presentation), YES Congress, Berlin, Germany, September 9-13, 2019.
  2. G. Pfalz, B. Diekmann, J.-C. Freytag, and B.K. Biskaborn. Harmonizing heterogeneous multi-proxy data from Arctic lake sediment records. (PICO presentation), EGU General Assembly, Online, 19–30 April 2021, EGU21-9401. https://doi.org/10.5194/egusphere-egu21-9401
  3. G. Pfalz, B. Diekmann, J.-C. Freytag, L. Syrykh, D. A. Subetto, and B. K.  Biskaborn, Using LANDO as a universal wrapper for applying multiple age-depth modeling systems for sediment records from Arctic lake systems.EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8743, https://doi.org/10.5194/egusphere-egu22-8743