ALLOMETRIC MODELS FOR ESTIMATING THE ROOT BIOMASS OF EURASIAN FOREST-FORMING GENERA BY REMOTE SENSING AS RELATED TO GLOBAL WARMING
Abstract
The climate system of the planet is gradually losing its stationarity, as a result of which climatic excesses are becoming more frequent, and climatic scenarios are becoming unpredictable. Predictive scenarios of vegetation change based on process-based models do not provide a clear understanding of whether the biota of the planet is a source or a carbon storage. Empirical modeling of the biomass of trees and stands by regression analysis based on “Big Data” has promising prospects, especially with the use of remote sensing technologies. The contribution of root biomass to the overall biological productivity of forest cover is the least studied. In this paper, statistically significant allometric models of root biomass depending on the tree height and the crown diameter have been developed on the basis of the compiled database on the harvest biomass of the roots of 897 sample trees of six forest-forming genera of Eurasia. The dependence of the root biomass of equal–sized trees on winter temperature, described by a descending curve for larches and firs, and an ascending curve for birches and beeches, has been established. The biomass of roots in pines and oaks is related only to the crown diameter and the tree height, and the change in zonal temperature does not affect this relationship. The contribution of crown diameter, tree height and January temperature to the explanation of root biomass variability is 38, 39 and 23 %, respectively. The proposed allometric models can be used to estimate the biomass of roots of forest-forming genera of Eurasia based on aerial laser sensing
About the Authors
V. A. Usoltsev
Ural State Forest Engineering University; Botanical Garden of the Ural Branch of the Russian Academy of Sciences
Russian Federation
Russian Federation
37, Siberian tract, Yekaterinburg, 620100
202a, 8 Marta Str., Yekaterinburg, 620144
I. S. Tsepordey
Botanical Garden of the Ural Branch of the Russian Academy of Sciences
Russian Federation
Russian Federation
202a, 8 Marta Str., Yekaterinburg, 620144
D. V. Noritsin
Sberbank PJSC, Analytics Competence Center
Russian Federation
Russian Federation
44, Gogol Str., Yekaterinburg, 620026
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For citations:
Usoltsev V.A., Tsepordey I.S., Noritsin D.V. ALLOMETRIC MODELS FOR ESTIMATING THE ROOT BIOMASS OF EURASIAN FOREST-FORMING GENERA BY REMOTE SENSING AS RELATED TO GLOBAL WARMING. Conifers of the boreal area. 2022;40(1):65-75. (In Russ.)
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