中文摘要：

根据NDVI3g数据,本文定义了18种植被物候指标研究植被物候变化情况。根据1：100万植被区划,把青藏高原划分为8个植被区分。对物候变化比较显著的区域,采用最高温度、最低温度、平均温度、降水、太阳辐射数据,运用偏最小二乘法回归（PLS）研究物候变化的气候成因。结果表明：1青藏高原生长季初期物候指标,转折发生在1997-2000年,转折前初期物候指标平均提前2~3 d/10a;青藏高原末期物候指标转折发生在2004-2007年左右,生长季长度物候指标突变发生在2005年左右,转折前末期物候指标平均延迟1~2 d/10a、生长季长度平均延长1~2 d/10a;转折之后生长季初期物候指标推迟趋势的显著性水平仅为0.1,生长季末期物候指标、生长季长度指标趋势不显著。2高寒草甸与高寒灌木草甸是青藏高原物候变化最剧烈的植被分区。高寒草甸区生长季长度的延长主要是由生长季初期物候指标提前导致的。高寒灌木草甸区生长季长度的延长主要是由于初期物候指标的提前,以及末期物候指标的推迟共同作用导致的。3采用PLS进一步分析气象因素对高寒草甸与高寒灌木草甸物候剧烈变化的影响。表明,温度对物候的影响占主导地位,两植被分区均显示上年秋季、冬初温度对生长季初期物候具有正的影响,该时段温度一方面会导致上年末期物候指标推迟,间接推迟生长季开始时间;另一方面高温不利用冬季休眠。除夏季外,其余月份最小温度对植被物候的影响与平均温度、最高温度的影响类似。降水对植被物候的影响不同月份波动较大,上年秋冬季节降水对初期物候指标具有负的影响,春初降水对初期物候指标具有正的影响。8月份限制植被生长季的主要因素是降水,此时降水与末期物候指标模型系数为正。太阳辐射对植被物候的影响主要在夏季与秋初。PLS方法在物候变化研究中具有?

英文摘要：

Using NDVI3 g vegetation index, we defined 18 phenological metrics to investigate phenology change in the Tibetan Plateau（TP）. Considering heterogeneity of vegetation phenology, we divided TP into 8 vegetation clusters according to 1：1000000 vegetation cluster map. Using partial least regression（PLS） method, we investigated impacts of climate variables such as temperature, precipitation and solar radiation on vegetation phenology. Results indicated that：（1） Turning points of the date of the start of growing season（SOS） metrics are mainly observed during 1997-2000, before which SOS advanced 2-3 d/a. Turning points of the date of the end of growing season（EOS） and length of growing season（LOS） metrics are found during 2005 and 2004- 2007, respectively. Before the turning point, EOS has a delayed tendency of 1- 2 d/10 a, and LOS has a lengthening tendency of 1- 2 d/10 a. After the turning point, the tendency of SOS and EOS metrics is questionable. Meanwhile, lengthening of LOS is not statistically significant;（2） Alpine meadows and alpine shrub meadows are subject to the most remarkable changes. Lengthening LOS of alpine meadow is mainly due to advanced SOS and delayed EOS. Nevertheless, lengthening LOS of alpine shrub meadow is attributed mainly to advanced SOS;（3） Using PLS method, we quantified impacts of meteorological variables such as temperature, precipitation and solar radiation on phenology changes of alpine meadows and alpine shrub meadows, indicating that temperature is the dominant meteorological factor affecting vegetation phenology. In these two regions, autumn of last year and early winter temperature of last year have a positive effect on SOS. Firstly, increased temperature in this period would postpone last year’s EOS, and hence indirectly delay SOS of the current year;Secondly, warming autumn and early winter have the potential to negatively impact fulfilment of chilling requirements, leading to delay of SOS. Except summer, minimum temperature has a similar eff