College of Urban and Environmental Sciences, Peking University, Beijing, China.
Glob Chang Biol. 2013 Apr;19(4):1275-84. doi: 10.1111/gcb.12095. Epub 2013 Jan 10.
Using first leaf unfolding data of Salix matsudana, Populus simonii, Ulmus pumila, and Prunus armeniaca, and daily mean temperature data during the 1981-2005 period at 136 stations in northern China, we fitted unified forcing and chilling phenology models and selected optimum models for each species at each station. Then, we examined performances of each optimum local species-specific model in predicting leaf unfolding dates at all external stations within the corresponding climate region and selected 16 local species-specific models with maximum effective predictions as the regional unified models in different climate regions. Furthermore, we validated the regional unified models using leaf unfolding and daily mean temperature data beyond the time period of model fitting. Finally, we substituted gridded daily mean temperature data into the regional unified models, and reconstructed spatial patterns of leaf unfolding dates of the four tree species across northern China during 1960-2009. At local scales, the unified forcing model shows higher simulation efficiency at 83% of data sets, whereas the unified chilling model indicates higher simulation efficiency at 17% of data sets. Thus, winter temperature increase so far has not yet significantly influenced dormancy and consequent leaf development of deciduous trees in most parts of northern China. Spatial and temporal validation confirmed capability and reliability of regional unified species-specific models in predicting leaf unfolding dates in northern China. Reconstructed leaf unfolding dates of the four tree species show significant advancements by 1.4-1.6 days per decade during 1960-2009 across northern China, which are stronger for the earlier than the later leaf unfolding species. Our findings suggest that the principal characteristics of plant phenology and phenological responses to climate change at regional scales can be captured by phenological and climatic data sets at a few representative locations.
利用来自中国北方 136 个站点的 1981-2005 年期间的柳属、杨属、榆属和李属植物第一叶片展开数据和逐日平均气温数据，我们拟合了统一的强迫和需冷量物候模型，并为每个物种在每个站点选择了最优模型。然后，我们检验了每个最优的局地种特异性模型在预测相应气候区内所有外部站点叶片展开日期的性能，并选择了 16 个具有最大有效预测的局地种特异性模型作为不同气候区的区域统一模型。此外，我们使用模型拟合时间段之外的叶片展开和逐日平均气温数据对区域统一模型进行了验证。最后，我们将网格化逐日平均气温数据代入区域统一模型，重建了 1960-2009 年期间中国北方四种树种叶片展开日期的空间格局。在局地尺度上，统一强迫模型在 83%的数据集中具有更高的模拟效率，而统一需冷量模型在 17%的数据集中具有更高的模拟效率。因此，到目前为止，冬季温度的升高尚未显著影响中国北方大部分地区落叶树的休眠和随后的叶片发育。时空验证证实了区域统一种特异性模型在预测中国北方叶片展开日期方面的能力和可靠性。重建的四种树种的叶片展开日期在 1960-2009 年期间显示出明显的提前，每十年提前 1.4-1.6 天，对于较早展开的物种而言，这种提前更为明显。我们的研究结果表明，通过少数有代表性的地点的物候和气候数据集，可以捕捉到区域尺度上植物物候的主要特征和对气候变化的物候响应。
