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.
- G. Pfalz, B. Diekmann, JC. Freytag and B.K. Biskaborn. Decipher Arctic Lakes Ecosystem Dynamics. Poster presentation at YES Congress 2019, Berlin, Germany, September 9-13, 2019.
- 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 Discuss. [preprint]. https://doi.org/10.5194/bg-2021-39