近50年中国典型木本植物展叶始期温度敏感度变化及原因

展叶始期的温度敏感度是指气温每变化1℃，物候期变化的天数。展叶始期对温度响应更敏感的植物能够在生长季初期占据更多的资源从而在种间竞争中占据优势，因此研究展叶始期的温度敏感度变化有助于评估植物对气候变化的适应能力。选择1963-2014年10个站点163种植物的展叶始期资料，利用滑动分析法计算了每15a各植物的展叶始期温度敏感度。在此基础上，分析了温度敏感度的变化趋势及空间格局，并讨论了导致展叶始期温度敏感度变化的可能原因。主要结论为：在全部313条展叶始期时间序列中，60.1%的序列温度敏感度呈升高趋势，其中显著升高的占40.0%（P < 0.05）；39.9%的序列温度敏感度降低，其中显著降低的占28.4%。在空间分布上，温带地区的6个站点展叶始期温度敏感度平均呈升高趋势。其中，北京地区植物展叶始期温度敏感度升高最为普遍，显著升高的物种比例达到75.0%（P < 0.05）。而亚热带站点（除合肥外）的展叶始期温度敏感度主要呈降低趋势。其中，长沙植物展叶始期温度敏感度显著降低的物种比例最高，达68.4%。冬季冷激量和春季气温变率是影响植物展叶始期温度敏感度随时间变化的主要因素。冬季冷激量降低将导致植物展叶始期温度敏感度降低，而春季气温变率降低将导致植物展叶始期温度敏感度升高。

Variations in temperature sensitivity of leaf unfolding date and their influencing factors for typical woody plants in China over the past 50 years

Temperature sensitivity (S_T) of the leaf unfolding date (LUD), which was defined as the shift of LUD per unit change in preseason temperature, was widely used to quantify phenological response to climate change. Species whose LUD responding to temperature more sensitively tended to have an earlier growing season, thus occupying more resources and obtaining competitive advantages in the community. Therefore, S_T could be used to assess the ability of species to cope with climate change. The temporal change in S_T and their driving forces have been studied for several plant species in Europe, but the long-term variation of S_T in China is still unclear. In this study, we selected the LUD data for 163 woody plants at 10 sites in China from the China Phenology Observation Network (CPON), as well as the corresponding meteorological data from the China Meteorological Data Service Center. First, S_T was calculated as the slope of the regression between LUD and the mean temperature during the optimum preseason, for each 15-year moving window during the period 1963-2014 for each species at each site. Second, we analyzed the temporal trends in S_T and calculated the average trend of S_T for each site to test the spatial patterns of S_T. Finally, we discussed the possible reasons for the changes in S_T. The conclusions were as follows:(1) Out of 313 LUD time series, 60.1% displayed increasing S_T, with 40.0% significantly (P < 0.05). S_T for the other 39.9% of time series exhibited a decreasing trend, with 28.4% significantly. (2) In terms of the spatial patterns, S_T of LUD showed increasing trends at 6 sites of temperate region. The most obvious one was Beijing, with 75% of species exhibiting significantly increasing S_T. On the contrary, S_T of LUD decreased over the past several decades at 4 sites of subtropical region except for Hefei. The most obvious one was Changsha, with 68.4% of species exhibiting significantly decreasing S_T. (3) Both the winter chilling and spring temperature variance affected the temporal variation in S_T. Reduced chilling days could lead to a lower S_T, while lower spring temperature variance could lead to a higher S_T.