地理学报

地理学报 ›› 2010, Vol. 65 ›› Issue (7): 781-788.doi: 10.11821/xb201007002

• 自然地理 • 上一篇    下一篇

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

韩芳1,2, 张百平1, 谭靖1,2, 朱运海3, 姚永慧1   

  1. 1. 中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室，北京100101;
    2. 中国科学院研究生院，北京100049;
    3. 山东省科技发展战略研究所，济南250014
  • 收稿日期:2009-11-25 修回日期:2010-03-10 出版日期:2010-07-20 发布日期:2010-07-20
  • 通讯作者: 张百平(1963-),男，研究员, 博士生导师, 研究领域为山地生态与GIS应用。E-mail: zhangbp@lreis.ac.cn
  • 作者简介:韩芳(1981-), 女, 山东兖州人, 博士研究生, 主要研究方向为山地地理, GIS应用。E-mail: hanf@lreis.ac.cn
  • 基金资助:

    国家自然科学基金项目(40971064)

The Effect of Mountain Base Elevation on the Altitude of Timberline in the Southeastern Eurasia: A Study on the Quantification of Mass Elevation Effect

HAN Fang1,2, ZHANG Baiping1, TAN Jing1,2, ZHU Yunhai3, YAO Yonghui1   

  1. 1. Institute of Geographical Sciences and Natural Resourcesl Research, CAS, Beijing 100101, China;
    2. Graduate School of Chinese Academy of Science, Beijing 100039, China;
    3. Shandong Institute for Development Strategy of Science and Technology, Jinan 250014, China
  • Received:2009-11-25 Revised:2010-03-10 Online:2010-07-20 Published:2010-07-20
  • Supported by:

    National Natural Science Foundation of China, No.40971064

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被引次数

54

摘要：

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。

关键词: 欧亚大陆, 山体效应, 定量化, 山体基面高度, 林线, 纬度, 经度

Abstract:

This paper focuses on the method of quantifying the phenomenon of mass elevation effect (massenerhebungs effect). Geographers have taken notice of mass elevation effect and its influence on mountain altitudinal belts for more than 100 years. But so far, our knowledge on mass elevation effect has been very limited, let alone its quantitative effect on mountain altitudinal belts. Geographers and botanists have established many unitary or dibasic fitting models between mountain altitudinal belts' distribution and longitude or latitude, or both. But most of these models involve small scales and could not be expanded to other regions; while others are established for the northern hemisphere or the whole globe with very low precision. The reason is that these models neglect one of the most important factors controlling the distribution of altitudinal belts—mass elevation effect. It is well known that the higher the mountain range, the greater the mass elevation effect is. So, mountain's base altitude could be a represent of mass elevation effect. We collect 173 samples of forest line distribution, and use latitude, longitude and mountain base elevation (MBE) as independent variables to build a multiple linear regression equation for timberline altitude in the southeastern Eurasian continent. The result turned out that the contribution of latitude, longitude and mountain base elevation to timber line distribution reaches 30.60%, 26.53%, and 42.87%, respectively. North of northern latitude 32°, the contribution for each of the three factors amounts to 53.08%, 21.25%, and 25.67%, respectively; to the south, the contribution is 14.94%, 48.98%, and 36.08%, respectively. The results indicate that MBE, serving as a proxy indicator of mass elevation effect, is a significant factor determining the elevation of altitudinal belts. Compared with other factors, it is more stable and independent in affecting forest line elevation. Of course, mass elevation effect is also determined by other factors, including mountain's volume, the distance to the edge of a land mass, the structures of the mountains nearby, etc. They need to be included in the study of mass elevation effect in the future.

Key words: Eurasia, mass elevation effect, quantification, mountain base elevation (MBA), timberline, latitude, longitude