1982—2009年基于卫星数据的北半球中高纬地区植被春季物候动态及其与气候的关系

深入认识北半球植被物候在全球变暖背景下的动态变化特征,对于评估和预测生态系统结构和功能对气候变化的响应有重要的指示作用.遥感技术是获取北半球植被春季物候的最重要方法,但是由于物候提取算法的差异,目前还存在较大的不确定性.本文利用5种方法,基于卫星获取的归一化植被指数估算了北半球中高纬地区1982—2009年植被春季物候开始日期,分析了该日期的多年动态变化的时空特征,并探讨了气候变化对春季物候变化的影响.结果表明: 研究区植被春季物候开始日期呈现提前趋势,研究期间提前(4.0±0.8) d,其中,欧亚大陆提前速率为(0.22±0.04) d·a^-1,显著高于北美大陆的变化速率(0.03±0.02 d·a^-1);不同植被类型的变化趋势不同,5种方法都显示草地表现为显著提前趋势,而林地的提前趋势不显著.区域平均的植被春季物候开始日期的年际波动主要受春季温度的变化所驱动(r² =0.61,P<0.001), 温度每上升1 ℃,可以导致春季物候提前(3.2±0.5) d,而春季降水影响不显著(P>0.05).

Variation of satellite-based spring vegetation phenology and the relationship with climate in the Northern Hemisphere over 1982 to 2009.

In-depth understanding the variation of vegetation spring phenology is important and nece-ssary for estimation and prediction of ecosystem response to climate change. Satellite-based estimation is one of the important methods for detecting the vegetation spring phenology in Northern Hemisphere. However, there are still many uncertainties among different remote sensing models. In this study, we employed NDVI satellite product from 1982 to 2009 to estimate vegetation green-up onset dates in spring across Northern Hemisphere, and further analyzed the phenology spatio-temporal variation and the relationship with climate. Results showed that spatial mean spring phenology significantly advanced by (4.0±0.8) days during this period in the Northern Hemisphere, while spring phenology advanced much faster in Eurasia (0.22±0.04 d·a^-1) than in North America (0.03±0.02 d·a^-1). Moreover, phenology of different vegetation types changed inconstantly during the period. All five methods consistently indicated that grassland significantly advanced, while forests didn’t advance robustly among methods. In addition, the interannual change of spring phenology was mainly driven by spring temperature. The spring phenology advanced (3.2±0.5) days with 1 ℃ increase in temperature. On the contrary, we did not find significant relationship between vegetation spring phenology and spring accumulative precipitation across the Northern Hemisphere (P>0.05) in this study.