Geospatial Sciences Center of Excellence (GSCE), South Dakota State University, 1021 Medary Ave, Brookings, SD, 57007, USA.
Department of Geography & Geospatial Sciences, South Dakota State University, Brookings, SD, 57007, USA.
Sci Rep. 2020 Oct 21;10(1):17952. doi: 10.1038/s41598-020-74804-4.
Warming climate and its impact on vegetation phenological trends have been widely investigated. However, interannual variability in temperature is considerably large in recent decades, which is expected to trigger an increasing trend of variation in vegetation phenology. To explore the interannual phenological variation across the contiguous United States (CONUS), we first detected the onset of vegetation greenup using the time series of the daily two-band Enhanced Vegetation Index (EVI2) observed from the AVHRR Long-Term Data Record (1982-1999) and the MODIS Climate Modeling Grid (2000-2016). We then calculated the interannual variation in greenup onset during four decadal periods: 1982-1989, 1990-1999, 2000-2009 and 2010-2016. Further, the trend of interannual variation in greenup onset from 1982 to 2016 was analyzed at pixel and state levels. Extreme phenological events were also determined using a greenup onset anomaly for each pixel. Similar approaches were applied to spring temperatures to detect extreme years and to the temporal trend of interannual variation to explain the phenological variation. The results revealed that 62% of pixels show an increasing interannual variation in greenup onset, and in 44% of pixels, this variation could be explained by the temperature. Although extreme phenology occurred locally in different years, three nationwide extreme phenological years were distinguished. The extreme warm spring that occurred in 2012 resulted in the occurrence of greenup onset as much as 20 days earlier than normal in large parts of the CONUS. In contrast, greenup onset was much later (up to 30 days) in 1983 and 1996 due to cool spring temperatures. These findings suggest that interannual variation in spring phenology could be much stronger in the future in response to climate variation, which could have more significant impacts on terrestrial ecosystems than the regular long-term phenological trend.
气候变暖及其对植被物候趋势的影响已得到广泛研究。然而，近几十年来，温度的年际变化相当大，预计这将引发植被物候变化的趋势增加。为了探索整个美国大陆（CONUS）的年际物候变化，我们首先使用从 AVHRR 长期数据记录（1982-1999 年）和 MODIS 气候建模网格（2000-2016 年）观测到的每日两波段增强植被指数（EVI2）时间序列检测植被变绿的开始。然后，我们计算了四个十年期内的变绿开始的年际变化：1982-1989 年、1990-1999 年、2000-2009 年和 2010-2016 年。此外，还分析了 1982 年至 2016 年变绿开始的年际变化趋势。每个像素的变绿开始异常确定了极端物候事件。类似的方法也应用于春季温度，以检测极端年份，并解释物候变化的年际变化时间趋势。结果表明，62%的像素显示出变绿开始的年际变化增加，在 44%的像素中，这种变化可以用温度来解释。尽管极端物候在不同年份局部发生，但区分了三个全国性的极端物候年份。2012 年发生的异常温暖的春季导致 CONUS 大部分地区的变绿开始比正常情况早 20 天。相比之下，由于春季气温较低，1983 年和 1996 年的变绿开始较晚（最多 30 天）。这些发现表明，未来春季物候的年际变化可能会更强，以响应气候变化，这可能比常规的长期物候趋势对陆地生态系统产生更重大的影响。
