EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

An individual-based tree data set on forest structure in Siberia‘s remote north-east

Timon Miesner1,2, Ulrike Herzschuh1,2,3, Luidmila A. Pestryakova4, Mareike Wieczorek1, Evgenii S. Zakharov4,5, Alexei I. Kolmogorov4, and Stefan Kruse1
Timon Miesner et al.
  • 1Alfred-Wegener-Institut, Helmholz-Zentrum für Polar- und Meeresforschung, Potsdam, Germany
  • 2Institute for Environmental Science and Geography, University of Potsdam, Potsdam, Germany
  • 3Institute for Biochemistry and Biology, University of Potsdam, Potsdam, Germany
  • 4Institute of Natural Sciences, North-Eastern Federal University of Yakutsk, Yakutsk, Russia
  • 5Institute for Biological Problems of the Cryolithozone, Russian Academy of Sciences, Siberian Branch, Yakutsk, Russia

The permafrost-underlain deciduous forests of north-east Siberia form a unique ecosystem that is experiencing pressure from global warming, in the form of permafrost thaw, wildfires of increasing intensity and frequency, and drought stress. Even though it covers millions of square kilometers and could become an important driver in the global climate system with the vast amounts of carbon stored in its soil and plants, there is relatively little knowledge on it because of its remoteness.

In a series of expeditions between 2011 and 2021, a consortium of researchers from the North East Federal University Yakutsk (NEFU) and the Alfred Wegener Institute (AWI) surveyed more than 160 forest sites in Yakutia and at the northern treeline, in Chukotka and the Taymir Peninsula. These include intact larch forest and forest tundra sites, as well as different stages of succession after wildfire disturbance. We observed species, height and vitality status for over 39,000 trees, of which around 2000 were inventorized in a more detailed manner, including diameters and crown diameters.

We will present analyses of individual-based metrics necessary for upscaling the forest inventory to the plot level. Additionally, we compared our ground inventory data with freely available remote sensing products to evaluate their performance in predicting forest structure on the small scale. The comparison yielded large errors, as the forest metrics vary strongly on the local scale, thereby emphasizing the need for ground data like we collected.

This dataset gives a unique insight into the forest structure of this remote area, and can be used for a variety of purposes.

How to cite: Miesner, T., Herzschuh, U., Pestryakova, L. A., Wieczorek, M., Zakharov, E. S., Kolmogorov, A. I., and Kruse, S.: An individual-based tree data set on forest structure in Siberia‘s remote north-east, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11575,, 2022.

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