24 May 2022
24 May 2022
Status: this preprint is currently under review for the journal ESSD.

Forest structure and individual tree inventories of north-eastern Siberia along climatic gradients

Timon Miesner1,2, Ulrike Herzschuh1,2,3, Luidmila A. Pestryakova4, Mareike Wieczorek1, Evgenii S. Zakharov5,4, Alexei I. Kolmogorov4, Paraskovya V. Davydova4, and Stefan Kruse1 Timon Miesner et al.
  • 1Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Telegrafenberg A45, 14473 Potsdam, Germany
  • 2Institute of Environmental Sciences and Geography, University of Potsdam, 14476 Potsdam-Golm, Germany
  • 3Institute of Biochemistry and Biology, University of Potsdam, 14476 Potsdam-Golm, Germany
  • 4Institute of Natural Sciences, North-Eastern Federal University, 677000 Yakutsk, Russia
  • 5Institute for Biological Problems of Cryolithozone, 677000 Yakutsk, Russia

Abstract. We compile a data set of forest surveys from expeditions to the north-east of the Russian Federation, in Krasnoyarsk Krai, the Republic of Sakha (Yakutia) and the Chukotka Autonomous Okrug (59-73° N, 97-169° E). The region is characterized by permafrost soils, and forests dominated by larch (Larix gmelinii RUPR., Larix cajanderi MAYR).

Our dataset consists of a plot data base describing 226 georeferenced vegetation survey sites, and of a tree data base with information about all trees on these plots. The tree data base contains information on height, species and vitality of 40,289 trees. A subset of the trees was subject to a more detailed inventory, recording stem diameter at base and at breast height, crown diameter and height of the beginning of the crown.

We recorded heights up to 28.5 m (median = 2.5 m) and stand densities up to 120,000 trees per ha (median = 1197 ha−1), both values tending to be higher in the more southerly areas. Observed taxa include Larix MILL., Pinus L., Picea A.DIETR., Abies MILL., Salix L., Betula L., Populus L., Alnus MILL. and Ulmus L..

In this study, we present the forest inventory data aggregated per site. Additionally, we connect it with different remote sensing data products to find out how accurately forest structure can be predicted from such products. Allometries were calculated to obtain the diameter from height measurements for every species group. For Larix, the most frequent of ten species groups, allometries depend also on the stand density, as denser stands are characterized by thinner trees, relative to height. The remote sensing products used to compare against the inventory data include climate, forest biomass, canopy height, and forest loss or disturbance. We find that the forest metrics measured in the field can only be reconstructed from the remote sensing data to a limited extent, as they depend on local properties. This illustrates the need for ground inventories like those data we present here.

The data can be used for studying the forest structure of north-eastern Siberia, and for the calibration and validation of remotely sensed data.

Timon Miesner et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-152', Anonymous Referee #1, 07 Jun 2022
  • RC2: 'Comment on essd-2022-152', Anonymous Referee #2, 16 Jun 2022
  • RC3: 'Comment on essd-2022-152', Anonymous Referee #3, 19 Jun 2022

Timon Miesner et al.

Data sets

Tree data set from forest inventories in north-eastern Siberia Miesner, Timon; Herzschuh, Ulrike; Pestryakova, Luidmila A; Wieczorek, Mareike; Kolmogorov, Alexei; Heim, Birgit; Zakharov, Evgenii S; Shevtsova, Iuliia; Epp, Laura Saskia; Niemeyer, Bastian; Jacobsen, Inga; Schröder, Julius; Trense, Darjona; Schnabel, Ellen; Schreiber, Xenia; Bernhardt, Nadine; Stuenzi, Simone Maria; Brieger, Frederic; Schulte, Luise; Smirnikov, Viktor; Gloy, Josias; von Hippel, Barbara; Jackisch, Robert; Kruse, Stefan

Timon Miesner et al.


Total article views: 405 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
312 79 14 405 3 2
  • HTML: 312
  • PDF: 79
  • XML: 14
  • Total: 405
  • BibTeX: 3
  • EndNote: 2
Views and downloads (calculated since 24 May 2022)
Cumulative views and downloads (calculated since 24 May 2022)

Viewed (geographical distribution)

Total article views: 371 (including HTML, PDF, and XML) Thereof 371 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 08 Aug 2022
Short summary
We present data which were collected on expeditions to the north-east of the Russian Federation: One table describes the 226 locations we visited during those expeditions, and the other one describes 40,2895 trees which we recorded at these locations. We found out that important information on the forest cannot be predicted precisely from satellites. Thus, for anyone interested in distant forests, it is important to go to there and take measurements, or use data like the ones we present here.