Fingerprints and turnover of multiple plant-derived molecular markers in floodplain soils: Assessing the potential for historical floodplain vegetation reconstruction
As a consequence of climate change and an increased frequency of extreme weather conditions, pronounced changes in the runoff situation of floodplain ecosystems are expected. This in turn likely effects biogeochemical cycles in floodplain soils. Our project aims to preserve the functional integrity of floodplain forest ecosystems by adoption of silvicultural management strategies to changed micro-climatic conditions and to facilitate the renaturation of floodplain ecosystems by reconstructing vegetation changes as a result of historical land-use changes and river regulation. Therefore, the main objectives of this proposal are i) to determine the specific molecular fingerprints for different types of floodplain vegetation along the rivers Rhine and Middle Elbe based on the combined information from multiple lipid fractions. In contrast to most of the previous studies on modern reference biomarker signatures, this proposal aims toward a systematic investigation of ecosystem specific fingerprints; ii) to assess if molecular pattern of diagnostic relevance are sustained in soil depth profiles and river sediments and, to characterize the changes of the molecular pattern from topsoil to the subsoil horizons. This question is of special relevance for future applications in geoarchives, as in fossil soil-sediment sequences former topsoils often are eroded and only subsoils are preserved. Hence, it will be investigated if the respective ecosystem signals can be also differentiated by molecular fingerprints specifically on the subsoil level; iii) to determine and compare the turnover and degradation rates, respectively, of various free lipid fractions (alkanes, fatty acids) by compound-specific 14C dating; and iv) to analyze the effect of changing environmental conditions on biogeochemical cycles in floodplain soils by combining position-specific 13C-labelling approaches with compound-specific phospholipid fatty acid (PLFA) analysis.