Chrome Extension
WeChat Mini Program
Use on ChatGLM

Well-hidden forests? Modern pollen spectra from Central Yakutia (Eastern Siberia) contribute to the interpretation of the last glacial vegetation in Central Europe

Folia Geobotanica(2023)

Cited 0|Views8
No score
Abstract
The landscape of central Europe is thought to have been dominated by steppe, forest-steppe, or tundra during the Last Glacial. This classical view is mostly based on the pollen records. However, as the pollen production and taphonomy during the cold periods are largely unknown, modern analogies of past landscapes need to be involved to provide more plausible vegetation reconstructions. Here we performed pollen analyses of recent samples from small lakes in Yakutia, eastern Siberia, a cold region where larch taiga forest is maintained by water from cyclically melting permafrost. We compared the pollen samples using multivariate (PCA) and analogue matching techniques with 830 fossil pollen samples from central Europe dated to MIS3–MIS1 (ca 35,000–11,700 cal BP). We have shown that the non-arboreal pollen proportion is around 50% in the lakes within Yakutian forested landscape, while such proportions have been interpreted as an indication of forestless landscape in European fossil records. Some central European fossil samples are more similar to samples from present-day Yakutia than to the South Siberian steppes so far considered analogous; this is especially true for samples from areas on unconsolidated bedrock with water-saturated permafrost from the Late Glacial, Bølling–Allerød interstadials. We advocate the idea of extending existing interpretations of past landscapes. The fossil pollen might not only reflect steppe–tundra vegetation, but, in addition to that, at least the Late Glacial pollen samples from central Europe may reflect a landscape forested by ‘invisible’ larch with spatially limited steppe patches, like the one found in present-day Yakutia.
More
Translated text
Key words
Pollen analysis,Modern analogues,Larix,Late Glacial,Vegetation history
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined