山体效应对北半球林线分布的影响分析

通过搜集整理了北半球516 个林线数据, 结合WorldClim 气象数据计算了林线数据点上的大陆度, 并依据SRTM高程数据提取了林线处的山体基面高度(作为山体效应的代用因子), 然后以纬度、大陆度和山体基面高度为解释变量, 建立三元回归模型。结果表明:线性回归模型的判定系数R²为0.904, 二次回归模型的R²高达0.912。相比先前不考虑基面高度的林线分布模型(R² = 0.79), 纳入了山体基面高度的林线分布模型能够更加有效的拟合半球尺度的林线分布; 结果还表明, 山体基面高度对北半球林线高度分布的贡献率达到了48.94% (p =0.000), 而纬度和大陆度分别为45.02% (p = 0.000) 和6.04% (p = 0.000)。这揭示了山体效应对半球尺度林线分布具有重要的影响。基面高度在北美洲地区对林线高度的贡献率最大(50.49%, p=0.000), 在欧亚大陆东部地区为48.73% (p = 0.000), 在欧亚大陆西部地区为43.6% (p=0.000)。这一结果说明山体效应对林线分布高度的影响虽有区域差异, 但都有较高的贡献率。     

山体基面高度对欧亚大陆东南部林线分布的影响——山体效应定量化研究

根据收集到173个林线数据,采用纬度、经度和基面高度的三元一次方程拟合欧亚大陆东南部林线分布,计算各自的标准回归系数和贡献率,以此来确定山体基面高度(山体效应的简明表达形式)对林线分布高度的影响。结果表明,纬度、经度和山体基面高度对林线分布高度的贡献率分别为30.60%、26.53%、42.87%。以北纬32o为界线,对其以北、以南区域也分别进行了分析,基面高度的贡献率达到24.10%和39.11%。分析不同尺度和区域山体基面高度作用于林线的贡献率不难发现:在欧亚大陆东南部以基面高度代表的山体效应对于林线高度的影响显著,明显地超过了纬度和经度。基面高度的作用受气候条件和海陆位置影响较小,不论大陆内部或沿海,基面高度分异对山地垂直带分异的影响都相对独立和稳定。该结果定量地表明了山体效应对林线分布高度的重要作用。     

山体基面高度对青藏高原及其周边地区雪线空间分布的影响

山体效应是地理地带性之外,在大尺度上影响垂直带分布的主要因素,山体基面高度则是山体效应的第一影响因子。青藏高原及其周边地区,雪线呈现出中心高、周围低,与山体基面高度相一致的环状分布模式。为分析山体基面高度对雪线分布的影响,本文共收集青藏高原及周边地区雪线数据142个,采用纬度、经度和基面高度为自变量的三元一次方程拟合研究区雪线分布,计算各自的标准回归系数和相对贡献率,再将基面高度划分成5个子集（0~1000 m、1001~2000 m、2001~3000 m、3001~4000 m和4001~5000 m）,分析基面高度不同的山地对雪线的影响差异。结果表明：① 在青藏高原,纬度、经度和基面高度对雪线高度分布的相对贡献率分别为51.49%、16.31%和32.20%;② 随着基面高度的增高,各子集模型的决定系数虽有逐渐降低的趋势,但仍保持在较高的值域（R²=0.895~0.668）,说明模型的有效性;③ 随基面高度的抬升,纬度和山体基面高度对雪线分布高度的相对贡献率分别表现出降低（92.6%~48.99%,R²=0.855）和增大（3.33%~31.76%,R²=0.582）的趋势,表明基面高度越高,其对雪线分布高度的影响越大。     

山体基面高度对青藏高原及其周边地区雪线空间分布的影响简

山体效应是地理地带性之外,在大尺度上影响垂直带分布的主要因素,山体基面高度则是山体效应的第一影响因子。青藏高原及其周边地区,雪线呈现出中心高、周围低,与山体基面高度相一致的环状分布模式。为分析山体基面高度对雪线分布的影响,本文共收集青藏高原及周边地区雪线数据142个,采用纬度、经度和基面高度为自变量的三元一次方程拟合研究区雪线分布,计算各自的标准回归系数和相对贡献率,再将基面高度划分成5个子集（0~1000 m、1001~2000 m、2001~3000 m、3001~4000 m和4001~5000 m）,分析基面高度不同的山地对雪线的影响差异。结果表明：① 在青藏高原,纬度、经度和基面高度对雪线高度分布的相对贡献率分别为51.49%、16.31%和32.20%;② 随着基面高度的增高,各子集模型的决定系数虽有逐渐降低的趋势,但仍保持在较高的值域（R²=0.895~0.668）,说明模型的有效性;③ 随基面高度的抬升,纬度和山体基面高度对雪线分布高度的相对贡献率分别表现出降低（92.6%~48.99%,R²=0.855）和增大（3.33%~31.76%,R²=0.582）的趋势,表明基面高度越高,其对雪线分布高度的影响越大。     

青藏高原山体效应对近地表层垂直大气昼夜温差的影响

青藏高原巨大隆起不仅塑造了欧亚大陆的气候格局,也深远地影响了高原的地理生态格局。青藏高原巨大隆起而产生的山体效应不仅可对近地表温度产生显著影响,其对近地表层垂直大气亦可产生显著作用,然而目前仍缺乏这一方面的研究。因此,本研究基于MODIS大气廓线数据产品,以昼夜温差为切入点,分析了青藏高原不同季节、不同气压面（500～200hPa）的昼夜温差差异。结果表明：(1)青藏高原内部不同季节、不同气压面高度处的昼夜温差均大于外部地区,整体符合山体效应的格局。(2)青藏高原海拔越高,不同季节的垂直层昼夜温差越大。(3)随着气压面高度的增加（500～200 hPa）,海拔对冬季大气昼夜温差的影响逐渐降低,对春季、夏季和秋季的影响程度先升高后降低,作用最大处分别出现在300 hPa、250 hPa和300 hPa。     

阿尔卑斯山山体效应及其对林线的影响分析

阿尔卑斯山是欧亚大陆上著名的山地,对欧洲的地理生态格局具有重要的影响.山体效应产生的原因在于隆起的高原或山地吸收了更多的太阳辐射.因此,论文以阿尔卑斯山为研究对象,利用收集到的气象台站观测数据、林线、数字高程数据,以及基于半球视域算法计算得到的太阳辐射数据等,分析阿尔卑斯山气温的空间分布格局以及最热月、最冷月、全年的太...     

哀牢山西坡季风常绿阔叶林和湿性常绿阔叶林木质藤本植物的多样性与分布

分析比较了哀牢山西坡季风常绿阔叶林和湿性常绿阔叶林中木质藤本的物种组成与分布特征.在两类常绿阔叶林中各设置了10个20 m×20 m的样地,调查记录所有dbh≥0.2 cm和高度≥2 m木质藤本的种类、胸径和攀援类型.在季风常绿阔叶林中,共记录到木质藤本115株隶属于14科17属18种,湿性常绿阔叶林中有55株隶属于10科12属15种.季风常绿阔叶林中的木质藤本的物种丰富度、多度、Shannon和Simpson多样性指数显著高于湿性常绿阔叶林(p<0.05),基面积的差异则不显著.木质藤本物种最丰富的科是菝葜科(Smilacaceae,4种)、蔷薇科(Rosaceae,3种)、蝶形花科(Papilionaceae,3种)和葡萄科(Vitaceae,3种),物种组成上在季风常绿阔叶林和湿性常绿阔叶林中完全不同.径级分布上,两类常绿阔叶林中的木质藤本均以小藤本(dbh＜1.0 cm)的个体占优势,中等大小(1.0 cm＜dbh＜5.0 cm)的木质藤本在湿性常绿阔叶林中分布较少.此外,两类常绿阔叶林中均以茎缠绕类型木质藤本的种类为主,季风常绿阔叶林中以茎缠绕类型的藤本个体占优势,而湿性常绿阔叶林中则以根攀援类型的藤本个体为主.     

季风与地形对台湾降水的影响

本文以季风环流的季节变化及地形两大因子对台湾降水的影响进行了研究分析，结果显示：东北季风和地形共同影响，造成冬半年台湾东北部多雨和西南部干旱；夏半年由于受西南季风的影响，出现了岛西部降水略多于岛东部的现象，且由于西南季风的影响，缓解了西南部干旱．台湾地形对降水的影响居全国之冠，海拔高度每上升100m，年降水量递增值都大于100mm，海拔500mm左右的低层递增率更是高达266．5mm／100m．     

山体效应及其对林线分布的影响(英文)

The concept of mass elevation effect(massenerhebungseffect,MEE) was intro-duced 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 ar-eas 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 regres-sion 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’ contribu-tion 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 included 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.     

山体效应对北半球林线分布的影响(英文)

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.     

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

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.     

秦岭中部山地落叶阔叶林超级垂直带的发现与意义

山地垂直带谱是气候和植被水平地带变化和更替的缩影,垂直带的带幅、带间过渡方式、带内结构和垂直带组合方式都表现出高度的异质性和复杂性。本文发现在中国南北过渡带中部太白山发育了世界上最宽的山地垂直带——山地落叶阔叶林垂直带。该垂直带从基带到典型垂直带再到先锋性垂直带皆为山地落叶阔叶林,3种本来可以独立存在的垂直带,连续分布形成了包含3个栎林亚带、2个桦林亚带的“三层五亚带”超级垂直带,远远超过正常情况下山地垂直带1000 m的阈值,且其上限达到了海拔2800 m。它的形成与秦岭所处的过渡性地理位置、秦岭中部垂直带谱的完整性、丰富的落叶木本植物种群及其形成的强大群落竞争优势等因素紧密相关。超级垂直带的发现有多方面的意义：它是中国南北过渡带又一重要的标志性自然地理特征;它表明山地垂直带在特殊的山地环境中可以具有非常复杂的内部结构和宽大带幅,这扩展了我们对山地垂直带谱结构及机理认识的广度,对于创建山地垂直带谱结构理论具有十分重要的意义;超级垂直带的发现,也说明中国南北过渡带还有很多科学内容有待我们去探索和发现,希望本文能起到抛砖引玉的作用,引起学界对超级垂直带形成的气候和生物多样性因素、地理过渡带的结构和生态效应等重大问题进行深入研究。     

云南哀牢山西麓季风常绿阔叶林及思茅松林的群落学特征

在云南哀牢山西麓川河河谷残存有较大面积的季风常绿阔叶林,其周围分布着思茅松林.采用典型取样法,对季风常绿阔叶林及思茅松林的物种组成与群落结构进行了调查和分析,结果表明:季风常绿阔叶林乔木层的优势种主要是红木荷(Schima wallichii)、高山栲(Castanopsis delavayi)、密花树(Rapanea neriifolia),而思茅松成熟林以思茅松(Pinus kesiya var.langbianensis)为绝对优势.在季风常绿阔叶林的29株样树树干上共调查到附生植物共36种,但在思茅松林中几乎找不到附生植物.季风常绿阔叶林和思茅松成熟林的香农-威纳多样性指数分别为3.32和1.70;相对于思茅松林,季风常绿阔叶林物种组成和群落结构都更复杂,具有较高的生物多样性和稳定性.由于该区域的季风常绿阔叶林受到了较为严重的人为干扰和破坏,因此,需要进一步加强对山地森林植被的保护与管理,尽量减少人为干扰,并采取适当的人工抚育措施,促进该区山地森林资源的保护和恢复.     

Implications of mass elevation effect for the altitudinal patterns of global ecology

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.     

基于多源信息的区域尺度山地植被带数字化提取

山地植被带的提取及分析是地学和生态学研究的基础问题之一.利用野外点/线调查和历史文献资料,可以对局域尺度山体的植被带进行归纳和描绘,而在区域乃至全球尺度上更多依赖于学者的经验和知识.利用内蒙古大青山地区1∶100万植被图、1∶10万土地利用图、1∶25万DEM等,设计逻辑判别规则,提取典型的山地植被带斑块;然后基于贝叶斯识别算法,利用地形、水热和太阳辐射等因子对区域尺度山地植被带进行空间分布模拟,最终提取的植被带具有较高的精度,总体精度为74.53％,Kappa系数为0.69.研究表明,利用多源数据可以提取和模拟区域尺度山地植被带连续分布格局,中小比例尺空间数据的集成应用使得该方法的推广具有较大的可行性,为进一步获取大陆及全球尺度的山地植被带数据奠定了基础.