The role of temperature as a key driver for plant phenology is well established. However, an increasing lack of winter chilling may strongly slow down spring phenological advances in the course of warming. Along elevational gradients in the mountains, differential changes in winter chilling as well as more homogeneous leaf unfolding due to warming have been observed. In this study, we analyzed the elevation-linked lapse rates of phenological ground observations and remote sensing data in the pre-alpine and alpine regions of the Bavarian Alps, Germany. Seasonal start (SOS) and end of season (EOS) dates were extracted from time series data of 4-day maximum value composite Moderate Resolution Imaging Spectrometer (MODIS) sensor's Normalized Difference Vegetation Index (NDVI) for the years 2001-2016. Longer snow duration in the alpine region could be a possible reason of higher SOS elevational lapse rates as compared to the pre-alpine region. Significant and maximum differences in SOS rates between alpine and pre-alpine areas were observed in years with preceding warm winters with insufficient chilling. Minimum differences in SOS elevational lapse rates along the elevational gradients were found for cold spring and cold winter years. The MODIS-based SOS showed the highest correspondence when validated against the gridded German Meteorological Service (DWD) leaf unfolding data. However, EOS dates were in comparatively lower agreement with DWD data, and their lapse rates in the pre-alpine and alpine regions were difficult to validate. Contrary to the SOS, lower positive lapse rates of EOS were revealed in the alpine but not in the pre-alpine areas.

温度作为植物物候学的关键驱动因素的作用已得到很好的确立。但是，越来越少的冬季寒冷可能会大大减缓春季在变暖过程中的物候趋势。沿着山区的海拔梯度，观察到冬季寒冷的差异变化以及由于变暖而导致的叶片展开更加均匀。在这项研究中，我们分析了德国巴伐利亚阿尔卑斯山的前高山和高山地区物候地面观测和遥感数据与海拔相关的消失率。从4天最大值复合分辨率成像光谱仪（MODIS）传感器的归一化植被指数（NDVI）的时间序列数据中提取季节开始（SOS）和季节结束（EOS）日期（2001-2016年）。与高山前地区相比，高山地区更长的降雪持续时间可能是更高的SOS海拔高度下降率的可能原因。在先前温暖的冬季，寒冷不足的年份中，在高山地区和高山前地区之间的SOS率存在显着且最大的差异。在寒冷的春季和寒冷的冬季，沿海拔梯度的SOS海拔下降率差异最小。基于网格的德国气象局（DWD）展开数据进行验证时，基于MODIS的SOS显示出最高的对应性。但是，EOS日期与DWD数据相比相对较低，并且它们在高寒前和高寒地区的流失率很难验证。与SOS相反，