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  • 标题:Mass Elevation Effect and Its Contribution to the Altitude of Snowline in the Tibetan Plateau and Surrounding Areas
  • 本地全文:下载
  • 作者:Han Fang ; Zhang Baiping ; Yao Yonghui
  • 期刊名称:Arctic, Antarctic, and Alpine Research
  • 印刷版ISSN:1523-0430
  • 电子版ISSN:1938-4246
  • 出版年度:2011
  • 卷号:43
  • 期号:2
  • 页码:207-212
  • DOI:10.1657/1938-4246-43.2.207
  • 摘要:In exploring geographical distribution of mountain altitudinal belts (e.g., snowline, timber line, etc.), many unitary or dibasic fitting models have been developed to depict the relationship between altitudinal belts’ elevation and longitude or latitude, or both. However, most of these models involve small scales and could not be applied to other regions, while those established for the northern hemisphere or the whole globe, are of 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 ( massenerhebungseffect , short as MEE in the following text). This concept (MEE) was introduced more than 100 years ago by A. de Quervain 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. Although it has been widely observed and its effect on the elevation of mountain vegetation belts recognized, this phenomenon has not been quantitatively studied. We compiled 143 snowline descriptions from literature covering the Tibetan Plateau and its surrounding areas. Snowline elevation is related to longitude, latitude, and mountain base elevation (MBE), to construct a multivariate linear regression equation. These three factors could explain 83.5% of snowline elevation’s variation in the Tibetan plateau and its surrounding areas. Longitude, latitude, and MBE (representing MEE to some extent) contribute 16.14%, 51.64%, and 32.22%, respectively, to the variability of snowline elevation. North of latitude 32°N, the three factors’ contribution amounts to 18.72%, 44.27%, and 37.01%, respectively; to the south, their contribution is 28.12%, 15.37%, and 56.51%, respectively. A non-linear model was also constructed, but it only enhances the ability slightly in fitting of snowline’s distribution. Our analysis reveals that latitude and MBE are significant controlling factors of snowline elevation. Longitude, which stands for precipitation to a great extent, has limited impact on snowline’s distribution. MEE should be further studied, or directly quantified so that it can be adequately incorporated into the development of spatial models for altitudinal belts, whereby the precision of such models could be greatly enhanced.
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