Zhang Xinyi, Wang Xiaoyue, Zohner Constantin M, Peñuelas Josep, Li Yang, Wu Xiuchen, Zhang Yao, Liu Huiying, Shen Pengju, Jia Xiaoxu, Liu Wenbin, Tian Dashuan, Pradhan Prajal, Fandohan Adandé Belarmain, Peng Dailiang, Wu Chaoyang
The Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing, China.
University of the Chinese Academy of Sciences, 100049, Beijing, China.
Nat Commun. 2025 Jan 21;16(1):910. doi: 10.1038/s41467-025-56159-4.
Precipitation is an important factor influencing the date of foliar senescence, which in turn affects carbon uptake of terrestrial ecosystems. However, the temporal patterns of precipitation frequency and its impact on foliar senescence date remain largely unknown. Using both long-term carbon flux data and satellite observations across the Northern Hemisphere, we show that, after excluding impacts from of temperature, radiation and total precipitation by partial correlation analysis, declining precipitation frequency may drive earlier foliar senescence date from 1982 to 2022. A decrease in precipitation frequency intensifies drought stress by reducing root-zone soil moisture and increasing atmospheric dryness, and limit the photosynthesis necessary for sustained growth. The enhanced drought acclimation, showing a more rapid response to drought, also explains the positive relationship between precipitation frequency and foliar senescence date. Finally, we find 30 current state-of-art Earth system models largely fail to capture the sensitivity of DFS to changes in precipitation frequency and incorrectly predict the direction of correlations for approximately half of the northern global lands, in both historical simulations and future predictions. Our results therefore highlight the critical need to include precipitation frequency, rather than just total precipitation, into models to accurately forecast plant phenology under future climate change.
降水是影响叶片衰老日期的一个重要因素，而叶片衰老日期又会影响陆地生态系统的碳吸收。然而，降水频率的时间模式及其对叶片衰老日期的影响在很大程度上仍不为人知。利用北半球的长期碳通量数据和卫星观测资料，我们发现，通过偏相关分析排除温度、辐射和总降水量的影响后，降水频率下降可能会导致1982年至2022年叶片衰老日期提前。降水频率降低会通过减少根区土壤湿度和增加大气干燥度来加剧干旱胁迫，并限制持续生长所需的光合作用。增强的干旱适应性，即对干旱的响应更快，也解释了降水频率与叶片衰老日期之间的正相关关系。最后，我们发现，在历史模拟和未来预测中，目前30个最先进的地球系统模型在很大程度上未能捕捉到叶片衰老日期对降水频率变化的敏感性，并且大约对全球北半球一半陆地的相关性方向预测错误。因此，我们的研究结果凸显了在模型中纳入降水频率而非仅仅总降水量的迫切需求，以便在未来气候变化下准确预测植物物候。
