ALBERT

Description: Here, we provide the raw pollen data archived in three Siberian lake sediment cores spanning the mid-Holocene to the present (7.6-0 cal ka BP), from northern typical tundra to southern open larch forest in the Omoloy region. There are three cores: 1. 14-OM-20B, Lat. / °: 70.53, Lon. / °: 132.91, Ele. / m a.s.l.: 52, Modern vegetation: open larch forest, Lake area / km2: 0.26, Maximal depth / m: 3.4 2. 14-OM-02B, Lat. / °: 70.72, Lon. / °: 132.67, Ele. / m a.s.l.: 58, Modern vegetation: forest tundra, Lake area / km2: 0.08, Maximal depth / m: 3.5 3. 14-OM-12A, Lat. / °: 70.96, Lon. / °: 132.57, Ele. / m a.s.l.: 60, Modern vegetation: tundra, Lake area / km2: 0.09, Maximal depth / m: 4.5 Three lake sediment cores, 14OM12A (33 cm long), 14OM02B (49.5 cm long) and 14OM20B (86 cm long), were recovered from three sites using a UWITEC gravity corer (6 cm internal diameter) equipped with a hammer tool in July 2014. From the three cores, 16 bulk organic carbon samples were selected because of the lack of macrofossil remains and radiocarbon dated using accelerator mass spectrometry (AMS) at Poznań radiocarbon laboratory of Adam Mickiewicz University, Poland. In addition, 30 freeze-dried samples per core at 0.25 or 0.5 cm intervals between 0 and 15 cm were analysed for 210Pb/137Cs at the Liverpool University Environmental Radioactivity Laboratory. In this project, we analyse pollen and sedaDNA (Liu et al., 2020; doi:10.5061/dryad.69p8cz900) from three lake sediment cores from the Omoloy region in north-eastern Siberia (northern Yakutia), which are currently surrounded by different vegetation types ranging from typical tundra to open larch forest. First, our aim is to compare sedaDNA with the pollen data to see whether both methods track the same pattern with respect to compositional changes and diversity changes across the northern Russian treeline zone or are complementary to each other. Second, we reconstruct the mid- to late-Holocene changes of vegetation composition along a north–south transect. Third, we use the sedaDNA data to reconstruct variations in species richness and relate this to vegetation and climate change.