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Comparative analysis of the mass elevation effect and its implication for the treeline between the Tibetan and Bolivian plateaus based on solar radiation

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Journal of Mountain Science 2022年第4期19卷 1082-1094页

作者： YAO Yong-hui SUO Nan-dong-zhu ZHANG Yi-chi State Key Laboratory of Resource and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Qinghai National Park Scientific Research Monitoring and Evaluation CenterXining 810000China

As one of the main non-zonal factors,the mass elevation effect(MEE)has significant impacts on both regional climates and mountain ecological *** recent years,with the development of quantitative techniques and methods,quantitative studies on the MEE and its implication on mountain altitudinal belts have developed ***,some issues have not been solved yet,such as high errors in spatial temperature estimations and difficulties in the definition and extraction of intramountain base ***,there is still a lack of comparative studies on the MEE and its influence on treelines and snowlines as most studies were conducted on specific mountains or *** compare the MEE magnitudes of the Tibetan Plateau(TP)and the Bolivian Plateau(BP),we estimated the correspondent air temperatures and simulated the solar radiations based on MODIS surface temperature,station observation,and treeline ***,we analyzed the elevation of the 10℃isotherms on the two plateaus,the temperatures at the same elevation,and the solar *** to the mechanism of the MEE and the relationship of solar radiation and treeline,we constructed treeline models for the two plateaus through a stepwise regression analysis by considering several influencing factors of the MEE(e.g.,air temperature and precipitation)and using solar radiation as its *** results showed that:(1)the MEE magnitude on the TP is equivalent to that on the BP although the former is slightly higher than the latter;(2)the MEE strongly influences the highest treelines in the northern and southern hemispheres,which both occur on the two ***,the treeline distribution models based on solar radiation had higher accuracies than those models with parameters of temperature and precipitation(the adjusted R^(2) values were 0.76 for the TP and 0.936 for the BP),indicating that solar radiation can be used to quantify the MEE and its implications on ***,the results of this

关键词： Tibetan Plateau Bolivian Plateau mass elevation effect Solar radiation Treeline Temperature

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mass elevation effect and its forcing on timberline altitude

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Journal of Geographical Sciences 2012年第4期22卷 609-616页

作者： HAN Fang YAO Yonghui DAI Shibao WANG Chun SUN Ranhao XU Juan ZHANG Baiping Geographic Information and Tourism College Chuzhou UniversityChuzhou 239000AnhuiChina State Key Laboratory of Resource and Environment Information System Institute of Geographic Sciences and Natural Resources ResearchCASBeijing 100101China State Key Laboratory of Urban and Regional Ecology Research Center for Eco-Environmental ScienceCASBeijing 100085China Institute of Environment and Sustainable Development in Agriculture Chinese Academy of Agricultural Sciences(CAAS)Beijing 100081China

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 qu

关键词： mass elevation effect mountain base elevation altitudinal belts quantification Eurasia

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The implication of mass elevation effect of the Tibetan Plateau for altitudinal belts

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Journal of Geographical Sciences 2015年第12期25卷 1411-1422页

作者： YAO Yonghui XU Mei ZHANG Baiping State Key Laboratory of Resource and Environmental Information System Institute of Geographic Sciences and Natural Resources Research CAS Beijing 100101 China China Institute of Water Resources and Hydropower Research Beijing 100044 China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023 China

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.

关键词： Tibetan Plateau mass elevation effect mountain altitudinal belt treeline the warmth index the 10℃ isotherm in the warmest month

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

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Journal of Geographical Sciences 2014年第2期24卷 226-236页

作者： ZHAO Fang ZHANG Baiping PANG Yu YAO Yonghui Institute of Geographic Sciences and Natural Resources Research CAS Beijing 100101 China University of Chinese Academy of Sciences Beijing 100049 China College of Resources Environment and Tourism Anyang Normal University Anyang 455000 Henan China

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.

关键词： Northern Hemisphere altitudinal distribution of timberline mass elevation effect mountain base elevation multiple linear regression

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What factors determine the mass elevation effect of the Tibetan Plateau?

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Journal of Mountain Science 2020年第11期17卷 2742-2749页

作者： HAN Fang WAN Li WU Hong-zhi ZHANG Bai-ping GAO Lan SONG Ge School of Civil Engineering and Architecture Shandong University of TechnologyZibo 255000China Sub-Institute of High and New Technology Standardization China National Institute of StandardizationBeijing 100191China Institute for Development Strategy of Science and Technology Qilu University of TechnologyShandong Academy of SciencesJinan 250014China Institute of Geographic Sciences and Natural Resources Research State Key Laboratory of Resources and Environmental Information SystemBeijing 100101China

The mass elevation effect(MEE)of the Tibetan Plateau(TP)has attracted the attention of geographers because of its significant influence on the Asian climate,snow line,timberline,and other important climate-ecological boundaries of the plateau and on global ecological *** recent years,much progress has been made in quantifying the MEE of ***,factors that affect the size of MEE have not been examined in depth,and the key factors still remain *** on quantification of MEE for each mountain basal elevation plot,this study identifies the factors that contribute significantly to MEE of the *** factors are considered,including mountain basal elevation,distance from the core zone of MEE,thermal continentality,maximum elevation,height difference,area,and difference of underlying surface(with the yearly max"Normalized Difference Vegetation Index"(NDVI)serving as a quantitative indicator).We also used these seven factors as independent variables to develop a multiple linear regression model for MEE of the *** show that:(1)the determination coefficient(R2)of the model reaches as high as 0.877,and the contributions of mountain basal elevation,distance from the core zone of MEE,thermal continentality,maximum elevation,topographical height difference,area,and NDVI are 39.77%,23.02%,14.48%,5.78%,11.41%,2.92%,and 2.62%,respectively,with mountain basal elevation and the distance from the core of MEE as the most important factors;(2)thermal continentality and MEE are significantly correlated,and maximum elevation only has a coupling relationship with MEE,with height difference and NDVI contributing little to *** study deepens our understanding of MEE and its forming factors in the Tibetan Plateau.

关键词： Tibetan Plateau mass elevation effect Mountain basal elevation Influencing factors

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中国天山山体效应评估及空间分异归因

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地理学报:英文版 2023年第10期33卷 2031-2051页

作者：张明羽张正勇刘琳张雪莹康紫薇陈泓瑾高煜王统霞余凤臣 School of Science Shihezi UniversityShihezi 832000XinjiangChina Key Laboratory of Oasis Town and Mountain-basin System Ecology of Xinjiang Bingtuan Shihezi 832003XinjiangChina Xinjiang Institute of Ecology and Geography CASUrumqi 830011China School of Water Conservancy&Architectural Engineering Shihezi UniversityShihezi 832000XinjiangChina

The mass elevation effect(MEE)is a thermal effect,in which heating produced by long wave radiation on a mountain surface generates atmospheric uplift,which has a profound impact on the hydrothermal conditions and natural geographical processes in mountainous *** on multi-source remote sensing data and field observations,a spatial downscaling inversion of temperature in the Tianshan Mountains in China was conducted,and the MEE was estimated and a spatio-temporal analysis was *** Geo Detector model(GDM)and a geographically weighted regression(GWR)model were applied to explore the spatial and temporal heterogeneity of the study *** key results can be obtained.(1)The temperature pattern is complex and diverse,and the overall temperature presented a pattern of high in the south and east,but low in the north and *** were clear zonal features of temperature that were negatively correlated with altitude,and the temperature difference between the internal and external areas of the mountains.(2)The warming effect of mountains was prominent,and the temperature at the same altitude increased in steps from west to east and north to *** units,such as large valleys and intermontane basins,weakened the latitudinal zonality and altitudinal dependence of temperature at the same altitude,with the warming effect of mountains in the southern Tianshan Mountains.(3)The dominant factors affecting the overall pattern of the MEE were topography and location,among which the difference between the internal and external areas of the mountains,and the absolute elevation played a prominent *** interaction between factors had a greater influence on the spatial differentiation of mountain effects than single factors,and there was a strong interaction between terrain and climate,precipitation,nthe normalized difference vegetation index(NDVI),and other factors.(4)There was a spatial heterogeneity in the direction and intensity of the spatial vari

关键词： mass elevation effect spatial downscaling GeoDetector GWR Tianshan Mountains

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