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、全年的太阳辐射量,同时以太阳辐射作为山体效应的代用因子,采用逐步回归分析方法构建了阿尔卑斯山林线分布模型,探究该山地的山体效应及其对林线的影响。研究结果表明：① 阿尔卑斯山具有明显的山体效应,山体内部的太阳辐射量远高于山体边缘地区,这也是山体内部气温和林线高度都高于山体边缘地区的主要原因。最热月、最冷月和全年总太阳辐射量在山体内部比边缘地区分别高10~20、20~40和200~400 kWh/m²。② 太阳辐射能更好地定量化山体效应,以太阳辐射为山体效应代用因子建立的林线分布模型具有更高的精度。与基于气温、降水构建的林线分布模型(R²= 0.522)相比,该模型具有更高的模拟精度(R² = 0.736),同时太阳辐射对林线分布的贡献率最大(1月、7月太阳辐射的贡献率分别为34.75%、27.82%),超过了气温和降水的贡献率(分别为26.24%和11.17%)。

Mountain elevation effect of the Alps and its implication for forest line

The Alps, a typical mountain in the Eurasia Continent with mountain elevation effect (MEE), plays an important role in determining the geo-ecological pattern of Europe. The cause of the MEE is that the uplifted plateau or mountain absorbs more solar radiation. Most of the previous studies used the difference of temperature at the same altitude or base height inside and outside the mountain to quantify the MEE. However, the above methods may have some errors. This study chose the Alps as the study area and analyzed the spatial distributions of the solar radiation, temperature, and forest line in the Alps based on the collected meteorological observation data, forest line data, and digital elevation data, as well as the solar radiation data calculated by the hemispheric horizon algorithm. For the purpose of exploring the implication of MEE for the forest line, this study used solar radiation as the representation of MEE to build a forest line distribution model. The results show that: 1) The Alps has great MEE, and solar radiations of the inner mountain are much higher than that on the edge of the mountain. It is also the main reason that the temperature and the height of forest line in the inner mountain are far higher than that in the mountain edge areas. The solar radiation in the warmest month, the coldest month, and the whole year is 10-20, 20-40 and 200-400 kWh/m² higher than that on the edge of the mountain, respectively. 2) Solar radiation can better quantify the MEE, and forest line distribution model established with solar radiations as the substitute factor of MEE has higher simulation accuracy. The accuracy of the forest line distribution model in this study (R² = 0.736) is higher than that of the model based on temperature and precipitation (R² = 0.522), and the contribution rate of solar radiation to forest line distribution is the highest (34.75% in January and 27.82% in July), which exceeds the contribution rates of temperature and precipitation (26.24% and 11.17%, respectively).