Mass Elevation Effect and Its Contribution to the Altitude of Timberline in the Northern Hemisphere
Qi Wenwen
Abstract
Qi Wenwen
Abstract
Alpine timberline,as the ecological transition zone, has long attracted attention of scientists in many fields of study,especially scientists of climatic change in recent years.Many unitary and dibasic fitting models have been developed between timberline and its influencing factors.It has been commonly believed that latitude or temperature is a decisive factor for the altitudinal distribution of timberline,and most of the fitting models involve the relationship between timberline and latitude or temperature.However,these models are usually on regional scale and could not be extended to other regions;on the other hand,hemispherical-scale and continental-scale models usually contain only about 100 timberline data and results in low precision.The present article has collected 516 data points of timberline,and takes latitude,continentality and mass elevation effect as independent variables and timberline elevation as dependent variables to set up a ternary linear regression model.Continentality is calculated using the meteorological data released by WorldClim and mountain base elevation(as alternative factor of the 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 mass elevation effect to timberline elevation is 45.02%(p = 0.000),6.04%(p = 0.000) and 48.94%(p = 0.000),respectively.This revealed that the influence of mountain mass elevation effect on timberline distribution exceeds that of latitude and continentality put together,and that mass mountain effect is the primary factor in determining the elevation distribution of timberline on continental and hemispherical scale.The contribution rate of the mass elevation effect to the timberlines is,although different in different regions,generally high,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.
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Alpine timberline,as the ecological transition zone, has long attracted attention of scientists in many fields of study,especially scientists of climatic change in recent years.Many unitary and dibasic fitting models have been developed between timberline and its influencing factors.It has been commonly believed that latitude or temperature is a decisive factor for the altitudinal distribution of timberline,and most of the fitting models involve the relationship between timberline and latitude or temperature.However,these models are usually on regional scale and could not be extended to other regions;on the other hand,hemispherical-scale and continental-scale models usually contain only about 100 timberline data and results in low precision.The present article has collected 516 data points of timberline,and takes latitude,continentality and mass elevation effect as independent variables and timberline elevation as dependent variables to set up a ternary linear regression model.Continentality is calculated using the meteorological data released by WorldClim and mountain base elevation(as alternative factor of the 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 mass elevation effect to timberline elevation is 45.02%(p = 0.000),6.04%(p = 0.000) and 48.94%(p = 0.000),respectively.This revealed that the influence of mountain mass elevation effect on timberline distribution exceeds that of latitude and continentality put together,and that mass mountain effect is the primary factor in determining the elevation distribution of timberline on continental and hemispherical scale.The contribution rate of the mass elevation effect to the timberlines is,although different in different regions,generally high,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.
Key concepts: Elevation (ballistics), Altitude (triangle), Latitude, Physical geography, Shuttle Radar Topography Mission, Geology, Digital elevation model, Scale (ratio)