Designing a Model of the Picea L. and Abies L. Biomass for Regional Climatic Conditions in Eurasia. P. 38-54

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630*52:630*174.754

DOI:

10.37482/0536-1036-2022-6-38-54

Abstract

Forest ecosystems play a major role in climate stabilization, and continuous monitoring of their biomass is of paramount importance. Airborne laser scanning technology has become widespread in assessing tree biomass by remote sensing of such inventory indices of trees and stands as crown width and projection area, tree and stand height. The work uses the author’s observation database of 1550 model trees of spruce (Picea L.) and 535 model trees of fir (Abies L.) growing in Eurasia. The database provides information on tree height, crown width and length, as well as biomass of trunk, foliage, branches and roots. It was found that two-factor allometric models of biomass components, including crown width and tree height as independent variables, are the most informative. A positive correlation with crown width and tree height has been identified for all biomass components. Biomass of components of similar-sized fir trees was found to be 45–71 % higher than that of spruce at the statistically reliable level. This is possibly due to the fact that with the same height the crown width of the fir is 11 % less compared to the spruce. The contribution of winter temperatures and precipitation to the variability of biomass components was estimated. The biomass of all components of equal-sized trees is described by a propeller-like 3D dependence. In warm regions, the biomass increases with increasing precipitation; the dependence is characterized by an opposite or neutral trend with the transition to cold regions. The biomass increases with increasing temperature in humid regions, and decreases with the transition to dry climatic conditions. Inclusion of crown length as an additional independent variable in the allometric model practically did not improve its predictive ability. The contribution of inventory indices of trees, their species, and climatic variables to explaining the variability of biomass components is 72.9, 13.5 and 13.6 %, respectively. Climatic variables explain most of the variability in trunk and above-ground biomass (18 to 20 %), least of all in needles and branches (8 to 9 %). The findings can be useful for laser monitoring of forest biomass and predicting possible changes in tree biomass structure in case of climatic deviations.

Authors

Vladimir А. Usoltsev^1,2*, Doctor of Agriculture, Prof.; ResearcherID: M-8253-2018, ORCID: https://orcid.org/0000-0003-4587-8952
Ivan S. Tsepordey², Candidate of Agriculture, Research Scientist;
ResearcherID: AAC-5377-2020, ORCID: https://orcid.org/0000-0002-4747-5017
Igor M. Danilin³, Doctor of Agriculture, Prof.; ResearcherID: AAS-4960-2020, ORCID: https://orcid.org/0000-0001-9706-6927

Affiliation

¹Botanical Garden of the Ural Branch of the Russian Academy of Sciences, ul. 8 Marta, 202 а, Yekaterinburg, 620144, Russian Federation; usoltsev50@mail.ru*, ivan.tsepordey@yandex.ru
²Ural State Forest Engineering University, ul. Sibirskiy trakt, 37, Yekaterinburg, 620100, Russian Federation; usoltsev50@mail.ru, ivan.tsepordey@yandex.ru
³V.N. Sukachev Institute of Forest SB RAS, Akademgorodok, 50, Krasnoyarsk, 660036, Russian Federation; danilin@ksc.krasn.ru

Keywords

hydrothermal gradients, biomass components, LiDAR sensing of trees, allometric models, mean January temperature, annual precipitation, spruce, fir

Funding

The research was carried out within the framework of the state assignment FEUZ-2021-0014

For citation

Usoltsev V.А., Tsepordey I.S., Danilin I.M. Designing a Model of the Picea L. and Abies L. Biomass for Regional Climatic Conditions in Eurasia. Lesnoy Zhurnal = Russian Forestry Journal, 2022, no. 6, pp. 38–54. (In Russ.). https://doi.org/10.37482/0536-1036-2022-6-38-54

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