Carbon Storage by Siberian Larch in the Upper Treeline Ecotone in the Polar Urals

In the ecotone of the upper tree line, the relationships between the values of biometric parameters of Siberian larch (average radius of the horizontal projection of the crown, the diameter of the tree at the root collar and its height) were studied using ground-based measurements on circular sample plots and ultra-high spatial resolution aerial photographs obtained by an unmanned aerial vehicle. A nonlinear regression model, a model using the random forest method, and an ensemble of models using machine learning methods were created to establish a relationship between the values of the root collar diameter and the crown radius of a Siberian larch specimen. The obtained models have a high level of adequacy both qualitatively and quantitatively (R2 more than 0.95) levels. The predictive capabilities of the nonlinear regression model outside the training set were better than those of the machine learning models, so it was used together with allometric equations to quantify the phytomass of Siberian larch based on the root collar diameter and carbon sequestration in the study area using data obtained from crown decoding of 88.6 thousand Siberian larch specimens. It was found that in the upper treeline ecotone over an area of 7.32 km2 the value of aboveground and underground phytomass of Siberian larch is 1355.2 tons of dry mass, which contains 677.6 tons of carbon, or 2484.5 tons of CO2-equivalent.

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Publication Details

Journal
Russian Journal of Ecology
Published
2025-06-01
DOI
https://doi.org/10.1134/s1067413624603695
Primary Topic
Geochemistry and Geologic Mapping
Type
article
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article

Carbon Storage by Siberian Larch in the Upper Treeline Ecotone in the Polar Urals

Russian Journal of Ecology
Geochemistry and Geologic Mapping
article

Carbon Storage by Siberian Larch in the Upper Treeline Ecotone in the Polar Urals

article en

Abstract

In the ecotone of the upper tree line, the relationships between the values of biometric parameters of Siberian larch (average radius of the horizontal projection of the crown, the diameter of the tree at the root collar and its height) were studied using ground-based measurements on circular sample plots and ultra-high spatial resolution aerial photographs obtained by an unmanned aerial vehicle. A nonlinear regression model, a model using the random forest method, and an ensemble of models using machine learning methods were created to establish a relationship between the values of the root collar diameter and the crown radius of a Siberian larch specimen. The obtained models have a high level of adequacy both qualitatively and quantitatively (R2 more than 0.95) levels. The predictive capabilities of the nonlinear regression model outside the training set were better than those of the machine learning models, so it was used together with allometric equations to quantify the phytomass of Siberian larch based on the root collar diameter and carbon sequestration in the study area using data obtained from crown decoding of 88.6 thousand Siberian larch specimens. It was found that in the upper treeline ecotone over an area of 7.32 km2 the value of aboveground and underground phytomass of Siberian larch is 1355.2 tons of dry mass, which contains 677.6 tons of carbon, or 2484.5 tons of CO2-equivalent.

Russian Journal of EcologyVol. 56(3)
Ural Federal University (RU), Ural State Forestry Engineering University (RU), Ural Branch of the Russian Academy of Sciences (RU), Institute of Plant and Animal Ecology (RU)
Life in Land
Openalex Percentile: Top 26%
Geochemistry and Geologic Mapping
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