Dynamics of the alpine timberline and its response to climate change in the Hengduan mountains over the period 1985-2015
Dynamics of the alpine timberline and its response to climate change in the Hengduan mountains over the period 1985-2015
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DOI：
10.1016/j.ecolind.2022.108589
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发表时间：
2022-01-28
影响因子：
6.9
通讯作者：
Wang，Lei
中科院分区：
文献类型：
--
作者：
Tian，Lei;Fu，Wenxue;Wang，Lei
作为生态系统交错带的高山林线的时空变化是研究气候变化的理想指标。为了定量了解高山林线对气候变化的响应，选择中国横断山区作为研究区域，收集了1985年，1995年，2005年和2015年获得的覆盖该地区的136张Landsat图像。首先，对高山林线进行了反演，并探讨了林线的时空动态。地形对高山林线位置的影响也进行了分析。结果表明：从1985年的3992.58 m到2015年的4047.60 m，林线平均高程增加了约55（±8.54）m，但这种变化存在明显的空间异质性。总的来说，阴坡（北方、东北和西北坡）的树带线平均海拔比阳坡（南坡、东南坡和西南坡）高出约160 m。研究还发现，在1985-2015年期间，高山树带线的上升趋势明显加速。最后，气候变量，驱动这一林带线移动的偏最小二乘（PLS）回归方法进行了确定和评估。结果表明，年平均气温（TEM_Year）、生长季总降水量（PRE_Grow）和生长季气温（TEM_Grow）是影响林线高度上升的显著正因子，而年总降水量（PRE_Year）则有意想不到的负效应。此外，其他气候因素（例如，强风）和非气候变量（例如，在今后的相关研究中还应包括森林植被与气候变化之间的联系（人类影响和土壤特性），以增进对极端条件下森林植被与气候变化之间联系的了解。
The spatiotemporal change in the alpine timberline, an ecosystem ecotone, is an ideal indicator for use in climate change research. In order to gain a quantitative understanding of the response of the alpine timberline to climate change, the Hengduan Mountains region of China was selected as a study area and a series of 136 Landsat images covering this area that were acquired in 1985, 1995, 2005 and 2015 were collected. First, the alpine timberline was retrieved and the spatiotemporal dynamics of the timberline were explored. The effect of topography on the location of the alpine timberline was also analyzed. The results indicate that the average elevation of the timberline increased by about 55 (±8.54) m from 3992.58 m in 1985 to 4047.60 m in 2015; however, there was obvious spatial heterogeneity in these changes. On the whole, the average elevation of the timberline on shaded slopes (northern, northeastern, and northwestern slopes) were found to be about 160 m higher than on sunward slopes (southern, southeastern, and southwestern slopes). It was also found that, over the period 1985–2015, there has been an obvious acceleration in the upward tendency of the alpine timberline. Finally, the climate variables that are driving this timberline shift were identified and evaluated using the partial least squares (PLS) regression method. The results indicate that the average annual temperature (TEM_Year), total precipitation during the growing season (PRE_Grow), and growing season temperature (TEM_Grow) were the significant positive factors driving the rise in the timberline elevation; the total annual precipitation (PRE_Year) was found to have an unexpected negative influence. Besides, other climatic factors (e.g., strong winds) and non-climate variables (e.g., human influence and soil properties) should be also included in future related studies to enhance the understanding of the link between forest vegetation and climate change under extreme conditions.