In the focus of this study are the sedimentary characteristics, chronology, magnitude, and causes of past soil erosion dynamics of an agriculturally intensively used glacial lowland landscape. From the mesoscale Quillow river catchment, sedimentary sections bearing colluvial sediments from different landforms were analysed to explore their geoarchive potential and to establish a local chronology of Late Holocene soil erosion. Sections from footslopes contain a rather simple stratigraphy with one topping colluvial horizon of up to 1 m thickness burying a palaeosol. In contrast glacial kettle holes preserve more complex sequences partly having several colluvial layers with intercalating palaeosols. The most complex stratigraphy is associated with a kettle hole being the ultimate sediment trap for a dendritic gully system, forming a 4 m thick sequence of alternating peat and colluvial layers. Thirty OSL ages and 13 radiocarbon ages are used to reconstruct phases of soil erosion. Potentially human-induced soil erosion, which is corroborated by local archaeological and palynological data, can be traced back to the last c. 4000 years. The oldest colluvial deposits date back to the Late Bronze Age. Most datings, however, cluster within the last 600 years with a peak in the last 200 years, ascribing the main phase of local soil erosion to the recent past. Thus, although numerous archaeological finds are detected in the catchment since the Neolithic, considerable agricultural soil erosion does not occur before the last millennium. A compilation of OSL chronologies based on colluvial sediments from other regions in Central Europe shows a more complex erosion history there with a pronounced two-or three-phased distribution of ages primarily dating into the last c. 4000-5000 years. This study underlines that in northeastern Central Europe human impact on landscapes was effective apparently at a later stage as compared to some adjacent regions.

Of all terrestrial ecosystems, peatlands store carbon most effectively in long-term scales of millennia. However, many peatlands have been drained for peat extraction or agricultural use. This converts peatlands from sinks to sources of carbon, causing approx. 5% of the anthropogenic greenhouse effect and additional negative effects on other ecosystem services. Rewetting peatlands can mitigate climate change and may be combined with management in the form of paludiculture. Rewetted peatlands, however, do not equal their pristine ancestors and their ecological functioning is not understood. This holds true especially for groundwater-fed fens. Their functioning results from manifold interactions and can only be understood following an integrative approach of many relevant fields of science, which we merge in the interdisciplinary project WETSCAPES. Here, we address interactions among water transport and chemistry, primary production, peat formation, matter transformation and transport, microbial community, and greenhouse gas exchange using state of the art methods. We record data on six study sites spread across three common fen types (Alder forest, percolation fen, and coastal fen), each in drained and rewetted states. First results revealed that indicators reflecting more long-term effects like vegetation and soil chemistry showed a stronger differentiation between drained and rewetted states than variables with a more immediate reaction to environmental change, like greenhouse gas (GHG) emissions. Variations in microbial community composition explained differences in soil chemical data as well as vegetation composition and GHG exchange. We show the importance of developing an integrative understanding of managed fen peatlands and their ecosystem functioning.

Abstract. The Eurasian (née European) Modern Pollen Database (EMPD) was established in 2013 to provide a public database of high-quality modern pollen surface samples to help support studies of past climate, land cover, and land use using fossil pollen. The EMPD is part of, and complementary to, the European Pollen Database (EPD) which contains data on fossil pollen found in Late Quaternary sedimentary archives throughout the Eurasian region. The EPD is in turn part of the rapidly growing Neotoma database, which is now the primary home for global palaeoecological data. This paper describes version 2 of the EMPD in which the number of samples held in the database has been increased by 60 % from 4826 to 8134. Much of the improvement in data coverage has come from northern Asia, and the database has consequently been renamed the Eurasian Modern Pollen Database to reflect this geographical enlargement. The EMPD can be viewed online using a dedicated map-based viewer at https://empd2.github.io and downloaded in a variety of file formats at https://doi.pangaea.de/10.1594/PANGAEA.909130 (Chevalier et al., 2019).

Hitherto, the Landscape Reconstruction Algorithm (LRA) has been the only truly quantitative approach to stand-scale palynology. However, the LRA requires information on pollen productivity and dispersal, which is not always available. The alternative approach MARCO POLO (MAnipulating pollen sums to ReCOnstruct POllen of Local Origin) presented here is solely based on pollen values and does not rely on a pollen dispersal function. In a stepwise fashion, MARCO POLO removes those pollen types from the pollen sum whose values are significantly higher than in a neighbouring large basin. The resulting regional pollen sum is free of the disturbing factor of (extra-)local pollen. Based on this sum, comparison with the pollen record from the large basin allows calculating sharp (extra-)local signals. Treating the (extra-)local pollen portion with representation factors ( R-values) then produces a quantitative reconstruction of the stand-scale vegetation composition. We tested MARCO POLO and the LRA on a dataset of pollen surface samples and forest vegetation relevés from northern Central Europe. Both approaches reconstruct the presence or absence of taxa at the stand scale within a small margin of error. Where observed cover was ⩾2%, both models always reconstructed presence, where modelled cover was ⩾2% the taxon was always present. Overall, both approaches perform well in reconstructing the cover of taxa within a 100-m radius. In our tests, MARCO POLO is slightly better at reconstructing cover values for more taxa. Although some model parameters evidently need revision, the simple correlative approach of MARCO POLO appears to perform at least as well as the complex LRA model.

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