School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China.
School of Public Policy and Management, China University of Mining and Technology, Xuzhou 221116, China.
Int J Environ Res Public Health. 2020 Jul 6;17(13):4865. doi: 10.3390/ijerph17134865.
Since the Silk-road Economic belt initiatives were proposed, Xinjiang has provided a vital strategic link between China and Central Asia and even Eurasia. However, owing to the weak and vulnerable ecosystem in this arid region, even a slight climate change would probably disrupt vegetation dynamics and land cover change. Thus, there is an urgent need to determine the Normalized Difference Vegetation Index (NDVI) and Land-use/Land-cover (LULC) responses to climate change. Here, the extreme-point symmetric mode decomposition (ESMD) method and linear regression method (LRM) were applied to recognize the variation trends of the NDVI, temperature, and precipitation between the growing season and other seasons. Combining the transfer matrix of LULC, the Pearson correlation analysis was utilized to reveal the response of NDVI to climate change and climate extremes. The results showed that: (1) Extreme temperature showed greater variation than extreme precipitation. Both the ESMD and the LRM exhibited an increased volatility trend for the NDVI, with the significant improvement regions mainly located in the margin of basins. (2) Since climate change had a warming trend, the permanent snow has been reduced by 20,436 km. The NDVI has a higher correlation to precipitation than temperature. Furthermore, the humid trend could provide more suitable conditions for vegetation growth, but the warm trend might prevent vegetation growth. Spatially, the response of the NDVI in North Xinjiang (NXC) was more sensitive to precipitation than that in South Xinjiang (SXC). Seasonally, the NDVI has a greater correlation to precipitation in spring and summer, but the opposite occurs in autumn. (3) The response of the NDVI to extreme precipitation was stronger than the response to extreme temperature. The reduction in diurnal temperature variation was beneficial to vegetation growth. Therefore, continuous concentrated precipitation and higher night-time-temperatures could enhance vegetation growth in Xinjiang. This study could enrich the understanding of the response of land cover change and vegetation dynamics to climate extremes and provide scientific support for eco-environment sustainable management in the arid regions.
自“丝绸之路经济带”倡议提出以来，新疆一直是中国与中亚乃至欧亚大陆之间的重要战略纽带。然而，由于该干旱地区生态系统脆弱，即使是轻微的气候变化也可能扰乱植被动态和土地覆盖变化。因此，迫切需要确定归一化植被指数（NDVI）和土地利用/土地覆盖（LULC）对气候变化的响应。本研究采用极值对称模态分解（ESMD）方法和线性回归方法（LRM）来识别生长季和其他季节的 NDVI、温度和降水的变化趋势。结合 LULC 的转移矩阵，利用 Pearson 相关分析揭示了 NDVI 对气候变化和气候极值的响应。结果表明：（1）极端温度的变化大于极端降水。ESMD 和 LRM 都显示出 NDVI 的波动性增加趋势，显著改善区域主要位于流域边缘。（2）由于气候变化呈变暖趋势，永久积雪减少了 20436km。NDVI 与降水的相关性高于温度。此外，潮湿趋势为植被生长提供了更适宜的条件，但温暖趋势可能会阻碍植被生长。空间上，北疆（NXC）的 NDVI 对降水的响应比对温度的响应更敏感。季节上，NDVI 与春、夏两季降水的相关性更大，而与秋、冬两季降水的相关性相反。（3）NDVI 对极端降水的响应强于对极端温度的响应。日温差减小有利于植被生长。因此，持续集中的降水和较高的夜间温度可能会增强新疆的植被生长。本研究丰富了对土地覆盖变化和植被动态对气候极值响应的认识，为干旱地区生态环境可持续管理提供了科学支持。
