Aboveground Biomass Of Mongolian Larch (Larix Sibirica Ledeb.) Forests In The Eurasian Region

Abstract

We used our database of tree biomass with a number of 433 sample trees of Larix from different ecoregions of Eurasia, involving 61 trees from Mongolia for developing an additive model of biomass tree components. Our approach solved the combined problem of additivity and regionality of the model. Our additive model of tree aboveground biomass was harmonized in two ways: first, it eliminated the internal contradictions of the component and of the total biomass equations, secondly, it took into account regional (and correspondingly species-specific) differences of trees in its component structure. A significant excess of larch biomass in the forest-tundra is found that may be explained by permafrost conditions, by tree growth in low-yielding stands with a high basic density of stem wood and relatively high developed tree crown in open stands. The aboveground biomass of larch trees in Mongolia does not stand out against the background of the most ecoregions of Eurasia. Based on our results, we conclude that the growing conditions of larch in Mongolia are not as tough as it was suggested earlier by other scientists. Biomass relations between regions may be explained by unknown and unaccounted factors and errors of measurements in all their phases (assessment of age, diameter, height of a tree, the selection of supposedly representative samples of component biomass, their drying, weighing, etc.). The question what explains the regional differences in the structure of biomass of trees with the same linear dimensions of their stems, remains open. Undoubtedly, the differences in tree age here play an important role. Also, important factor is the variation in the morphological structure of stands, which, in turn, is determined by both climatic and edaphic factors. The obtained models allow the determination of larch forest biomass in different ecoregions of Eurasia with the help of height and diameter data.

Biomass Estimation and Uncertainty Quantification From Tree Height

“…Our experiments employ a dataset collected from the opensource allometry databases [8], [36], [37]. Dataset provided by [8] consists of 4004 tree measurements at 58 sites in tropical forests over the globe.…”

“…Each measurement records the tree height, tree components' biomass, etc. The biomass data collected in [37] includes 6,604 records of trees in Eurasian forests (mainly in Russia). Then part of the measurements in the datasets were removed so that the left ones obey the following characteristics:…”

H/A/α Polarimetric Decomposition Of Dual Polarized Alos Palsar For Efficient Land Feature Detection And Biomass Estimation Over Tropical Deciduous Forest

“…Forest is an important component of the carbon cycle that reflects the state and health of our environment (Usoltsev et al 2019). The emerging climate change concept of reducing emissions from deforestation and forest degradation (REDD) comprises of the temporal change in the assessment of forest biomass/carbon stock (Sharma et al 2013).…”

Biomass Functions and Carbon Content Variabilities of Natural and Planted Pinus koraiensis in Northeast China

“…An individual tree biomass equation is widely known to be one of the most efficient techniques to estimate forest biomass since direct biomass measurements need tremendous resources (i.e., labor, time, equipment, and cost). Thousands of equations for stem, root, crown variables (i.e., branch and foliage), aboveground, and total biomass have been developed worldwide [ 7 , 8 , 9 , 10 ]. Most of them used the allometric function (Y = aX b ) to relate the required biomass (Y) with several easy-to-measure independent variables (X), in which tree diameter at breast height (D) is independently applied as the sole predictor.…”