Methods Of Studying The Alpine Treeline: A Systematic Review
https://doi.org/10.24057/2071-9388-2025-3735
Abstract
This paper provides a review and comparison of the methods for assessing trends in the dynamics of alpine treeline (ATL) in high mountains are presented in. The methods analyzed are contemporary, traditionally used (dendrochronological and paleocarpological methods, retrospective analysis of historical photographs and geodetic surveying, and multi-temporal aerial photography), and innovative ones developed in recent decades (semi-automatic and automatic methods of interpretation of high- and medium-resolution space imagery and methods of space imagery interpretation using different techniques, such as classification, segmentation, vegetation index analysis, and machine learning algorithms). Different interpretations of the concept of 'alpine treeline', which is currently established in geobotany and landscape sciences, are discussed. The attention to ATL dynamics is caused by global climate change's widespread forest increase and the decline in high mountain pastures. The ATL phenomenon's geographic map is condensed and displayed. There is an overview of the experience with different methods in varying mountain regions around the world. Each method is described in terms of its spatial scale, coverage, advantages, labor intensity, complexity, and limitations. It is shown that The effectiveness of the methods mainly depends on two key factors: the size of the area being studied and the time period over which changes are observed. The problem that still limits the use of remote sensing data is the contradiction between the accuracy of measurements and the coverage of the territories involved. To solve this problem, we suggest using a mix of methods that involve automatically classifying medium-resolution space images. This will be done by training on data collected from both fieldwork and lab experiments using different techniques.
Keywords
altitudinal treeline,
mountain treelines,
high-mountain landscapes,
GIS-modeling of landscape transformation
Supporting agencies: The reported research was funded by the State Assignment of the Institute of Geography, Russian Academy of Sciences, project no. АААА-А19-119021990093-8 (FMGE-2019-0007).
About the Authors
Andrey G. Purekhovsky
Institute of Geography, Russian Academy of Science
Russian Federation
Russian Federation
Staromonetniy lane, 29, Moscow, 119017
Alexey N. Gunya
Institute of Geography, Russian Academy of Science
Russian Federation
Russian Federation
Staromonetniy lane, 29, Moscow, 119017
Evgeniy Yu. Kolbowsky
Institute of Geography, Russian Academy of Science; Lomonosov Moscow State University
Russian Federation
Russian Federation
Staromonetniy lane, 29, Moscow, 119017; Leninskie Gory, 1, Moscow, 119991
Alexei A. Aleinikov
Institute of Geography, Russian Academy of Science
Russian Federation
Russian Federation
Staromonetniy lane, 29, Moscow, 119017
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Purekhovsky A.G., Gunya A.N., Kolbowsky E.Yu., Aleinikov A.A. Methods Of Studying The Alpine Treeline: A Systematic Review. GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY. 2025;18(1):105-116. https://doi.org/10.24057/2071-9388-2025-3735
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