PARAMETERS OF CHARACTERISTIC RAMAN LINES IN THE LINEAR-CHAINED CARBON FILMS

In the present work, experimental Raman spectra of linear-chain carbon (LСС) films of different thickness were studied. The dependence of the Raman shift frequency and its width at half the height on the thickness of the linear-chained carbon film was established. According to the results obtained, hypotheses were put forward about the cause of the appearance of spectral shifts

Pollen, non-pollen palynomorphs, LOI, micro- and macrocharcoal and C14 records from core Peny (Kursk region, Russia)

The dataset represent pollen, non-pollen palynomorphs, LOI, micro- and macrocharcoal and C14 records from core Peny, Kursk region, Russia. The core Peny was collected in 2009 by Lyudmila Shumilovskikh, Frank Schlütz, Jens Schneeweiß and Oleg Radyush with a Russian corer. Laboratory processing for palynological studies took place in the Dep. Palynology and Climate Dynamics, Georg-August-University of Göttingen in 2009 by Lyudmila Shumilovskikh and 2020 by Alisa Kasianova. For each palynological sample, one millilitre of material was treated with hydrochloric acid, potassium hydroxide, hydrofluoric acid, acetolysis mixture, microsieved (6 μm) and stored in glycerol. Before acid, Lycopodium spores were added to calculate pollen influx. Counting was carried out by Alisa Kasianova. Standard microscopical magnification was 400×, for ambiguous objects 1000x with oil immersion. Identification and morphological pollen types follow Beug (2004) and type collections. Non-pollen palynomorphs (NPP) follow Miola (2012) and the Non-Pollen Palynomorphs Image Database (NPP ID, http://non-pollen-palynomorphs.uni-goettingen.de/). New NPP types were described and have been uploaded to the Non-Pollen Palynomorphs Image Database (NPP ID, http://non-pollen-palynomorphs.uni-goettingen.de/). In addition, pieces of burnt plant fragments of > 50 µm were counted. Laboratory processing for macrocharcoal took place in the Dep. Palynology and Climate Dynamics, Georg-August-University of Göttingen in 2020 by Alisa Kasianova. These samples were treated in the laboratory in Sodium Hexametaphosphate and in bleach, living overnight after each treatment and followed by sieving through 125 µm sieve, and eventually counting of charcoal particles under a binocular microscope under 10× to 15× magnification. Samples for loss-on-ignition was processed by Ekaterina Lukanina in 2021. Samples (1 ml) were obtained at 2 cm intervals (44 samples). LOI samples were oven-dried for 22 hours at 105 °C, for 4 hours at 550 °C and for 2 hours at 950 °C (Dean 1974; Heiri et al. 2001). LOI records are given as percentages. For an absolute chronology, bulk samples, macroremains and pollen were dated by the radiocarbon laboratories of Poznan (Poland) and Erlangen (Germany)

Testing the Effect of Relative Pollen Productivity on the REVEALS Model: A Validated Reconstruction of Europe-Wide Holocene Vegetation

Reliable quantitative vegetation reconstructions for Europe during the Holocene are crucial to improving our understanding of landscape dynamics, making it possible to assess the past effects of environmental variables and land-use change on ecosystems and biodiversity, and mitigating their effects in the future. We present here the most spatially extensive and temporally continuous pollen-based reconstructions of plant cover in Europe (at a spatial resolution of 1 degrees x 1 degrees) over the Holocene (last 11.7 ka BP) using the 'Regional Estimates of VEgetation Abundance from Large Sites' (REVEALS) model. This study has three main aims. First, to present the most accurate and reliable generation of REVEALS reconstructions across Europe so far. This has been achieved by including a larger number of pollen records compared to former analyses, in particular from the Mediterranean area. Second, to discuss methodological issues in the quantification of past land cover by using alternative datasets of relative pollen productivities (RPPs), one of the key input parameters of REVEALS, to test model sensitivity. Finally, to validate our reconstructions with the global forest change dataset. The results suggest that the RPPs.st1 (31 taxa) dataset is best suited to producing regional vegetation cover estimates for Europe. These reconstructions offer a long-term perspective providing unique possibilities to explore spatial-temporal changes in past land cover and biodiversity