Spatial heterogeneity of the relationship between vegetation dynamics and climate change and their driving forces at multiple time scales in Southwest China
Spatial heterogeneity of the relationship between vegetation dynamics and climate change and their driving forces at multiple time scales in Southwest China
复制标题
西南地区多时间尺度植被动态与气候变化关系及其驱动力的空间异质性
DOI：
10.1016/j.agrformet.2018.02.015
复制
发表时间：
2018-06-15
影响因子：
6.2
通讯作者：
Xu, Xiaojuan
中科院分区：
文献类型：
--
作者：
Liu, Huiyu;Zhang, Mingyang;Xu, Xiaojuan
在全球气候变化的背景下，植被动态与气候变化的关系对于脆弱生态系统的植被保护与恢复至关重要。然而，在多个时间尺度上的关系尚不清楚。基于EEMD方法，揭示了1982-2015年西南地区植被动态的空间异质性及其与气候变化的关系。植被动态可分为3年、6年、14年和32年的时间尺度振荡，并有增加的趋势。其中以3年时间尺度和增长趋势为主。在广西和贵州北部，植被动态主要是长期趋势，而在其他地区，植被动态主要是3年的时间尺度。随着时间尺度的增加，气候变化的影响变得更加明显。植被动态与生长季温度的关系在3年和6年时间尺度上由海拔和植被类型决定，但在长期趋势上仅由植被类型决定。植被动态与降水的关系在3 a时间尺度上受岩溶地貌和植被类型的驱动，在6 a时间尺度上受降水量的驱动，在长期趋势上受岩溶地貌和海拔的驱动。基于多时间尺度分析的多元回归分析，气候变化对54.1%的研究区植被动态有很好的解释。在广西和贵州北部，气候变化对植被动态的影响大于人类活动的影响。研究结果表明，多时间尺度分析有助于更好地理解植被动态的机制，为脆弱生态系统的植被恢复和保护提供科学依据。
Under global climate change, relationship between vegetation dynamics and climate change is vital for vegetation conservation and restoration in fragile ecological system. However, the relationships at multiple time scales are unclear. Based on the Ensemble empirical mode decomposition method (EEMD), we revealed the spatial heterogeneity of vegetation dynamics and its relationship with climate change at multiple time scales in Southwest China during 1982-2015. Vegetation dynamics can be divided into 3-, 6-, 14-, and 32-year time scale oscillations with an increasing trend. Hereinto, the 3-year time scale and the increasing trend are dominant. In Guangxi and north of Guizhou provinces, vegetation dynamics was dominated by the long-term trend, whereas in the other areas it was dominated by the 3-year time scale. With increasing time scale, the impact of climate change became more pronounced. The relationship between vegetation dynamics and temperature in growing season was determined by elevation and vegetation type at the 3-and 6-year time scales, but only by vegetation type over the long-term trend. The relationship between vegetation dynamics and precipitation was driven by karst landform and vegetation type at the 3-year time scale, by precipitation amount at the 6-year time scale, and by karst landform and elevation over the long-term trend. Based on multivariate regression analysis with multiple time scale analysis, climate change had a good and significant interpretation on vegetation dynamics in 54.1% of the study area. Specifically, in Guangxi and north of Guizhou provinces, the impact of climate change on vegetation dynamics was greater than that of human activities. Our findings showed that multiple time scale analysis might facilitate a better understanding of the mechanisms of vegetation dynamics, and provide scientific knowledge on vegetation restoration and conservation in fragile ecosystems.