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Modeling and Forecasting the Dynamics of the Upper Forest Limit on the Zigalga Ridge (Southern Urals)

https://doi.org/10.18384/2712-7621-2025-3-32-51

Abstract

Aim. To assess the change in the area of forested lands at the upper limit of tree vegetation growth on the Zigalga Ridge (Southern Urals). To develop a justified forecast of the forest area expansion over the next century using data on the spatial position, age, and morphometric parameters of about 1004 trees.

Methodology. The dendrochronological method was used to derive the age of 411 trees growing on permanent study plots covering an area of 1.1 hectares. The studied plots are in the upper forest line ecotone and differ in exposure and altitude. The current above-ground woody biomass was measured in situ. Woody biomass formed in previous years was assessed using tree cores. Models predicting woody biomass at given locations were developed as functions combining the time of observation and geographic coordinates.

Results. The article presents data on the shift of the upper boundaries of woody vegetation into the mountain tundra communities, observed in the last century on the slopes of various exposures of the Zigalga Ridge in the Southern Urals, and also presents an analysis of how this shift is currently progressing. The paper proposes a model that predicts the accumulation of aboveground biomass of spruce stands and the movement of the upper forest boun-dary higher into the mountains in the coming years. The model forecasts that by 1965–2070, the pass between Mount Poperechnaya and Mount Lysaya will likely be covered with dense forest.

Research implications. The results of the study represent the first experience of modeling the advance of the upper forest boundary in the mountains of the Southern Urals and can be used in similar tasks in various mountain systems around the world. The obtained data on the spatial position of trees and their morphometric parameters can be used to monitor the condition of trees under various climate change scenarios in the future.

About the Authors

A. A. Grigoriev
Institute of Plant and Animal Ecology, Ural Branch of the Russian Academy of Sciences
Russian Federation

Andrey A. Grigoriev – PhD (Agriculture), Senior Researcher, Laboratory of Geoinformation Technologies

Ekaterinburg



G. I. Lozhkin
Kazan (Volga Region) Federal University; Institute of Geography, RAS
Russian Federation

Grigory I. Lozhkin – Assistant, Department of Ecosystem Modeling, Institute of Ecology, Biotechnology, and Nature Management; Research Engineer, Laboratory of Dendrochronology

Kazan;

Moscow



S. O. Vyukhin
Institute of Plant and Animal Ecology, Ural Branch of the Russian Academy of Sciences
Russian Federation

Sergey O. Vyukhin – Junior Researcher, Laboratory of Geoinformation Technologies

Yekaterinburg



N. A. Chizhikova
Kazan (Volga Region) Federal University
Russian Federation

Nelli A. Chizhikova – PhD (Biology), Assoc. Prof., Department of Ecosystem Modeling, Institute of Ecology, Biotechnology, and Nature Management

Kazan



P. P. Kudryavtsev
Taganay National Park
Russian Federation

Pavel P. Kudryavtsev – Departmentally Head, Research Department

Zlatoust



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