The concept of mass elevation effect （massenerhebungseffect, MEE） was introduced by A. de Quervain about 100 years ago to account for the observed tendency for temperature-related parameters such as tree line and sn...The concept of mass elevation effect （massenerhebungseffect, MEE） was introduced by A. de Quervain about 100 years ago to account for the observed tendency for temperature-related parameters such as tree line and snowline to occur at higher elevations in the central Alps than on their outer margins. It also has been widely observed in other areas of the world, but there have not been significant, let alone quantitative, researches on this phenomenon. Especially, it has been usually completely neglected in developing fitting mod- els of timberline elevation, with only longitude or latitude considered as impacting factors. This paper tries to quantify the contribution of MEE to timberline elevation. Considering that the more extensive the land mass and especially the higher the mountain base in the interior of land mass, the greater the mass elevation effect, this paper takes mountain base elevation （MBE） as the magnitude of MEE. We collect 157 data points of timberline elevation, and use their latitude, longitude and MBE as independent variables to build a multiple linear regression equation for timberline elevation in the southeastern Eurasian continent. The results turn out that the contribution of latitude, longitude and MBE to timberline altitude reach 25.11%, 29.43%, and 45.46%, respectively. North of northern latitude 32°, the three factors＇ contribution amount to 48.50%, 24.04%, and 27.46%, respectively; to the south, their contribution is 13.01%, 48.33%, and 38.66%, respectively. This means that MBE, serving as a proxy indi- cator of MEE, is a significant factor determining the elevation of alpine timberline. Compared with other factors, it is more stable and independent in affecting timberline elevation. Of course, the magnitude of the actual MEE is certainly determined by other factors, including mountain area and height, the distance to the edge of a land mass, the structures of the mountains nearby. These factors need to be inctuded in the study of MEE quantification in the future. This paper could help build up a high-accuracy and multi-scale elevation model for alpine timberline and even other altitudinal belts.展开更多
Alpine timberline, as the ＂ecologica tion of scientists in many fields, especially in transition zone,＂ has long attracted the atten- recent years. Many unitary and dibasic fitting models have been developed to expl...Alpine timberline, as the ＂ecologica tion of scientists in many fields, especially in transition zone,＂ has long attracted the atten- 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 meteorological data released by WorldClim and model. Continentality is calculated using the 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 dif- fers 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.展开更多
The heating effect （or mass elevation effect, MEE） of the Tibetan Plateau （TP） is intense due to its massive body. Some studies have been undertaken on its role as the heat source in summer and its implications fo...The heating effect （or mass elevation effect, MEE） of the Tibetan Plateau （TP） is intense due to its massive body. Some studies have been undertaken on its role as the heat source in summer and its implications for Asian climate, but little has been known of the im- plications of its MEE for the distribution of mountain altitudinal belts （MABs）. Using air tem- perature data observed and remotely sensed data, MAB/treeline data, and ASTER GDEM data, this paper compares the height of MABs and alpine treelines in the main TP and the surrounding mountains/lowland and explains the difference from the point of view of MEE. The results demonstrate： 1） at same elevation, air temperature and the length of growing season gradually increase from the eastern edge to the interior TP, e.g., at 4500 m （corre- sponding to the mean altitude of the TP）, the monthly mean temperature is 3.58℃ higher （April） to 6.63℃ higher （June） in the interior plateau than in the Sichuan Basin; the 10℃ iso- therm for the warmest month goes upward from the edge to the interior of the plateau, at 4000 m in the Qilian Mts. and the eastern edges of the plateau, and up to 4600-5000 m in Lhasa and Zuogong; the warmth index at an altitude of 4500 m can be up to 15℃-month in the in- terior TP, but much lower at the eastern edges. 2） MABs and treeline follow a similar trend of rising inwards： dark-coniferous forest is 1000-1500 m higher and alpine steppe is about 700-900 m higher in the interior TP than at the eastern edges.展开更多
基金Foundation： National Natural Science Foundation of China, No.41030528 No.40971064 Innovation Project of State Key Laboratory of Resources and Environmental Information System （LREIS）
文摘The concept of mass elevation effect （massenerhebungseffect, MEE） was introduced by A. de Quervain about 100 years ago to account for the observed tendency for temperature-related parameters such as tree line and snowline to occur at higher elevations in the central Alps than on their outer margins. It also has been widely observed in other areas of the world, but there have not been significant, let alone quantitative, researches on this phenomenon. Especially, it has been usually completely neglected in developing fitting mod- els of timberline elevation, with only longitude or latitude considered as impacting factors. This paper tries to quantify the contribution of MEE to timberline elevation. Considering that the more extensive the land mass and especially the higher the mountain base in the interior of land mass, the greater the mass elevation effect, this paper takes mountain base elevation （MBE） as the magnitude of MEE. We collect 157 data points of timberline elevation, and use their latitude, longitude and MBE as independent variables to build a multiple linear regression equation for timberline elevation in the southeastern Eurasian continent. The results turn out that the contribution of latitude, longitude and MBE to timberline altitude reach 25.11%, 29.43%, and 45.46%, respectively. North of northern latitude 32°, the three factors＇ contribution amount to 48.50%, 24.04%, and 27.46%, respectively; to the south, their contribution is 13.01%, 48.33%, and 38.66%, respectively. This means that MBE, serving as a proxy indi- cator of MEE, is a significant factor determining the elevation of alpine timberline. Compared with other factors, it is more stable and independent in affecting timberline elevation. Of course, the magnitude of the actual MEE is certainly determined by other factors, including mountain area and height, the distance to the edge of a land mass, the structures of the mountains nearby. These factors need to be inctuded in the study of MEE quantification in the future. This paper could help build up a high-accuracy and multi-scale elevation model for alpine timberline and even other altitudinal belts.
基金National Natural Science Foundation of China,No.41030528No.40971064
文摘Alpine timberline, as the ＂ecologica tion of scientists in many fields, especially in transition zone,＂ has long attracted the atten- 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 meteorological data released by WorldClim and model. Continentality is calculated using the 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 dif- fers 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.
基金National Natural Science Foundation of China, No.41571099 No.41001278
文摘The heating effect （or mass elevation effect, MEE） of the Tibetan Plateau （TP） is intense due to its massive body. Some studies have been undertaken on its role as the heat source in summer and its implications for Asian climate, but little has been known of the im- plications of its MEE for the distribution of mountain altitudinal belts （MABs）. Using air tem- perature data observed and remotely sensed data, MAB/treeline data, and ASTER GDEM data, this paper compares the height of MABs and alpine treelines in the main TP and the surrounding mountains/lowland and explains the difference from the point of view of MEE. The results demonstrate： 1） at same elevation, air temperature and the length of growing season gradually increase from the eastern edge to the interior TP, e.g., at 4500 m （corre- sponding to the mean altitude of the TP）, the monthly mean temperature is 3.58℃ higher （April） to 6.63℃ higher （June） in the interior plateau than in the Sichuan Basin; the 10℃ iso- therm for the warmest month goes upward from the edge to the interior of the plateau, at 4000 m in the Qilian Mts. and the eastern edges of the plateau, and up to 4600-5000 m in Lhasa and Zuogong; the warmth index at an altitude of 4500 m can be up to 15℃-month in the in- terior TP, but much lower at the eastern edges. 2） MABs and treeline follow a similar trend of rising inwards： dark-coniferous forest is 1000-1500 m higher and alpine steppe is about 700-900 m higher in the interior TP than at the eastern edges.
