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A study of the contribution of mass elevation effect to the altitudinal distribution of timberline in the Northern Hemisphere

A study of the contribution of mass elevation effect to the altitudinal distribution of... Abstract Alpine timberline, as the “ecological transition zone,” has long attracted the attention of scientists in many fields, especially in recent years. Many unitary and dibasic fitting models have been developed to explore the relationship between timberline elevation and latitude or temperature. However, these models are usually on regional scale and could not be applied to other regions; on the other hand, hemispherical-scale and continental-scale models are usually based on about 100 timberline data and are necessarily low in precision. The present article collects 516 data sites of timberline, and takes latitude, continentality and mass elevation effect (MEE) as independent variables and timberline elevation as dependent variable to develop a ternary linear regression model. Continentality is calculated using the meteorological data released by WorldClim and mountain base elevation (as a proxy of mass elevation effect) is extracted on the basis of SRTM 90-meter resolution elevation data. The results show that the coefficient of determination (R2) of the linear model is as high as 0.904, and that the contribution rate of latitude, continentality and MEE to timberline elevation is 45.02% (p=0.000), 6.04% (p=0.000) and 48.94% (p=0.000), respectively. This means that MEE is simply the primary factor contributing to the elevation distribution of timberline on the continental and hemispherical scales. The contribution rate of MEE to timberline altitude differs in different regions, e.g., 50.49% (p=0.000) in North America, 48.73% (p=0.000) in the eastern Eurasia, and 43.6% (p=0.000) in the western Eurasia, but it is usually very high. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png "Journal of Geographical Sciences" Springer Journals

A study of the contribution of mass elevation effect to the altitudinal distribution of timberline in the Northern Hemisphere

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References (56)

Publisher
Springer Journals
Copyright
2014 Science Press and Springer-Verlag Berlin Heidelberg
ISSN
1009-637X
eISSN
1861-9568
DOI
10.1007/s11442-014-1084-4
Publisher site
See Article on Publisher Site

Abstract

Abstract Alpine timberline, as the “ecological transition zone,” has long attracted the attention of scientists in many fields, especially in recent years. Many unitary and dibasic fitting models have been developed to explore the relationship between timberline elevation and latitude or temperature. However, these models are usually on regional scale and could not be applied to other regions; on the other hand, hemispherical-scale and continental-scale models are usually based on about 100 timberline data and are necessarily low in precision. The present article collects 516 data sites of timberline, and takes latitude, continentality and mass elevation effect (MEE) as independent variables and timberline elevation as dependent variable to develop a ternary linear regression model. Continentality is calculated using the meteorological data released by WorldClim and mountain base elevation (as a proxy of mass elevation effect) is extracted on the basis of SRTM 90-meter resolution elevation data. The results show that the coefficient of determination (R2) of the linear model is as high as 0.904, and that the contribution rate of latitude, continentality and MEE to timberline elevation is 45.02% (p=0.000), 6.04% (p=0.000) and 48.94% (p=0.000), respectively. This means that MEE is simply the primary factor contributing to the elevation distribution of timberline on the continental and hemispherical scales. The contribution rate of MEE to timberline altitude differs in different regions, e.g., 50.49% (p=0.000) in North America, 48.73% (p=0.000) in the eastern Eurasia, and 43.6% (p=0.000) in the western Eurasia, but it is usually very high.

Journal

"Journal of Geographical Sciences"Springer Journals

Published: Apr 1, 2014

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