Alpine treeline, as a prominent ecological boundary between forested mountain slopes and alpine meadow/shrub, is highly complex in altitudinal distribution and sensitive to warming climate. Great efforts have been mad...Alpine treeline, as a prominent ecological boundary between forested mountain slopes and alpine meadow/shrub, is highly complex in altitudinal distribution and sensitive to warming climate. Great efforts have been made to explore their distribution patterns and ecological mechanisms that determine these patterns for more than 100 years, and quite a number of geographical and ecophysiological models have been developed to correlate treeline altitude with latitude or a latitude related temperature. However,on a global scale, all of these models have great difficulties to accurately predict treeline elevation due to the extreme diversity of treeline site conditions.One of the major reasons is that "mass elevation effect"(MEE) has not been quantified globally and related with global treeline elevations although it has been observed and its effect on treeline elevations in the Eurasian continent and Northern Hemisphere recognized. In this study, we collected and compiled a total of 594 treeline sites all over the world from literatures, and explored how MEE affects globaltreeline elevation by developing a ternary linear regression model with intra-mountain base elevation(IMBE, as a proxy of MEE), latitude and continentality as independent variables. The results indicated that IMBE, latitude and continentality together could explain 92% of global treeline elevation variability, and that IMBE contributes the most(52.2%), latitude the second(40%) and continentality the least(7.8%) to the altitudinal distribution of global treelines. In the Northern Hemisphere, the three factors' contributions amount to 50.4%, 45.9% and 3.7% respectively; in the south hemisphere, their contributions are 38.3%, 53%, and 8.7%, respectively. This indicates that MEE, virtually the heating effect of macro-landforms, is actually the most significant factor for the altitudinal distribution of treelines across the globe, and that latitude is relatively more significant for treeline elevation in the Southern Hemisphere probably due to fewer macro-landforms there.展开更多
Mass elevation effect (MEE) refers to the thermal effect of huge mountains or plateaus, which causes the tendency for tem- perature-related montane landscape limits to occur at higher elevations in the inner massifs...Mass elevation effect (MEE) refers to the thermal effect of huge mountains or plateaus, which causes the tendency for tem- perature-related montane landscape limits to occur at higher elevations in the inner massifs than on their outer margins. MEE has been widely identified in all large mountains, but how it could be measured and what its main forming-factors are still remain open. This paper, supposing that the local mountain base elevation (MBE) is the main factor of MEE, takes the Qinghai-Tibet Plateau (QTP) as the study area, defines MEE as the temperature difference (AT) between the inner and outer parts of mountain massifs, identifies the main forming factors, and analyzes their contributions to MEE. A total of 73 mountain bases were identified, ranging from 708 m to 5081 m and increasing from the edges to the central parts of the plateau. Climate data (1981-2010) from 134 meteorological stations were used to acquire ATby comparing near-surface air temperature on the main plateau with the free-air temperature at the same altitude and simi- lar latitude outside of the plateau. The AT for the warmest month is averagely 6.15 ~C, over 12~C at Lhatse and Baxoi. A multivariate linear regression model was developed to simulate MEE based on three variables (latitude, annual mean precipitation and MBE), which are all significantly correlated to AT. The model could explain 67.3% of MEE variation, and the contribution rates of three independent variables to MEE are 35.29%, 22.69% and 42.02%, respectively. This confirms that MBE is the main factor of MEE. The intensive MEE of the QTP pushes the 10~C isotherm of the warmest month mean temperature 1300-2000 m higher in the main plateau than in the outer regions, leading the occurrence of the highest timberline (4900 m) and the highest snowline (6200 m) of the Northern Hemisphere in the southeast and southwest of the plateau, respectively.展开更多
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
The varied altitudinal gradient of climate and vegetation is further complicated by mass elevation effect(MEE), especially in high and extensive mountain regions. However, this effect and its implications for mountain...The varied altitudinal gradient of climate and vegetation is further complicated by mass elevation effect(MEE), especially in high and extensive mountain regions. However, this effect and its implications for mountain altitudinal belts have not been well studied until recently. This paper provides an overview of the research carried out in the past 5 years. MEE is virtually the heating effect of mountain massifs and can be defined as the temperature difference on a given elevation between inside and outside of a mountain mass. It can be digitally modelled with three factors of intra-mountain base elevation(MBE), latitude and hygrometric continentality; MBE usually acts as the primary factor for the magnitude of MEE and, to a great extent, could represent MEE. MEE leads to higher treelines in the interior than in the outside of mountain masses. It makes montane forests to grow at 4800–4900 m and snowlines to develop at about 6000 m in the southern Tibetan Plateau and the central Andes, and large areas of forests to live above 3500 m in a lot of high mountains of the world. The altitudinal distribution of global treelines can be modelled with high precision when taking into account MEE and the result shows that MEE contributes the most to treeline distribution pattern. Without MEE, forests could only develop upmost to about 3500 m above sea level and the world ecological pattern would be much simpler. The quantification of MEE should be further improved with higher resolution data and its global implications are to be further revealed.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
基金supported by the National Natural Science Foundation of China (Grant Nos. 41030528 and No. 40971064)
文摘Alpine treeline, as a prominent ecological boundary between forested mountain slopes and alpine meadow/shrub, is highly complex in altitudinal distribution and sensitive to warming climate. Great efforts have been made to explore their distribution patterns and ecological mechanisms that determine these patterns for more than 100 years, and quite a number of geographical and ecophysiological models have been developed to correlate treeline altitude with latitude or a latitude related temperature. However,on a global scale, all of these models have great difficulties to accurately predict treeline elevation due to the extreme diversity of treeline site conditions.One of the major reasons is that "mass elevation effect"(MEE) has not been quantified globally and related with global treeline elevations although it has been observed and its effect on treeline elevations in the Eurasian continent and Northern Hemisphere recognized. In this study, we collected and compiled a total of 594 treeline sites all over the world from literatures, and explored how MEE affects globaltreeline elevation by developing a ternary linear regression model with intra-mountain base elevation(IMBE, as a proxy of MEE), latitude and continentality as independent variables. The results indicated that IMBE, latitude and continentality together could explain 92% of global treeline elevation variability, and that IMBE contributes the most(52.2%), latitude the second(40%) and continentality the least(7.8%) to the altitudinal distribution of global treelines. In the Northern Hemisphere, the three factors' contributions amount to 50.4%, 45.9% and 3.7% respectively; in the south hemisphere, their contributions are 38.3%, 53%, and 8.7%, respectively. This indicates that MEE, virtually the heating effect of macro-landforms, is actually the most significant factor for the altitudinal distribution of treelines across the globe, and that latitude is relatively more significant for treeline elevation in the Southern Hemisphere probably due to fewer macro-landforms there.
基金National Natural Science Foundation of China(No.41571099,41030528)
文摘Mass elevation effect (MEE) refers to the thermal effect of huge mountains or plateaus, which causes the tendency for tem- perature-related montane landscape limits to occur at higher elevations in the inner massifs than on their outer margins. MEE has been widely identified in all large mountains, but how it could be measured and what its main forming-factors are still remain open. This paper, supposing that the local mountain base elevation (MBE) is the main factor of MEE, takes the Qinghai-Tibet Plateau (QTP) as the study area, defines MEE as the temperature difference (AT) between the inner and outer parts of mountain massifs, identifies the main forming factors, and analyzes their contributions to MEE. A total of 73 mountain bases were identified, ranging from 708 m to 5081 m and increasing from the edges to the central parts of the plateau. Climate data (1981-2010) from 134 meteorological stations were used to acquire ATby comparing near-surface air temperature on the main plateau with the free-air temperature at the same altitude and simi- lar latitude outside of the plateau. The AT for the warmest month is averagely 6.15 ~C, over 12~C at Lhatse and Baxoi. A multivariate linear regression model was developed to simulate MEE based on three variables (latitude, annual mean precipitation and MBE), which are all significantly correlated to AT. The model could explain 67.3% of MEE variation, and the contribution rates of three independent variables to MEE are 35.29%, 22.69% and 42.02%, respectively. This confirms that MBE is the main factor of MEE. The intensive MEE of the QTP pushes the 10~C isotherm of the warmest month mean temperature 1300-2000 m higher in the main plateau than in the outer regions, leading the occurrence of the highest timberline (4900 m) and the highest snowline (6200 m) of the Northern Hemisphere in the southeast and southwest of the plateau, respectively.
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.41421001,No.41571099,No.41030528
文摘The varied altitudinal gradient of climate and vegetation is further complicated by mass elevation effect(MEE), especially in high and extensive mountain regions. However, this effect and its implications for mountain altitudinal belts have not been well studied until recently. This paper provides an overview of the research carried out in the past 5 years. MEE is virtually the heating effect of mountain massifs and can be defined as the temperature difference on a given elevation between inside and outside of a mountain mass. It can be digitally modelled with three factors of intra-mountain base elevation(MBE), latitude and hygrometric continentality; MBE usually acts as the primary factor for the magnitude of MEE and, to a great extent, could represent MEE. MEE leads to higher treelines in the interior than in the outside of mountain masses. It makes montane forests to grow at 4800–4900 m and snowlines to develop at about 6000 m in the southern Tibetan Plateau and the central Andes, and large areas of forests to live above 3500 m in a lot of high mountains of the world. The altitudinal distribution of global treelines can be modelled with high precision when taking into account MEE and the result shows that MEE contributes the most to treeline distribution pattern. Without MEE, forests could only develop upmost to about 3500 m above sea level and the world ecological pattern would be much simpler. The quantification of MEE should be further improved with higher resolution data and its global implications are to be further revealed.
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.