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滞后降水对陆地生物群落植物生产的影响。

Lagged precipitation effects on plant production across terrestrial biomes.

作者信息

He Lei, Wang Jian, Peltier Drew M P, Ritter François, Ciais Philippe, Peñuelas Josep, Xiao Jingfeng, Crowther Thomas W, Li Xing, Ye Jian-Sheng, Sasaki Takehiro, Zhou Chenghu, Li Zhao-Liang

机构信息

State Key Laboratory of Efficient Utilization of Arable Land in China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China.

The Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.

出版信息

Nat Ecol Evol. 2025 Jul 28. doi: 10.1038/s41559-025-02806-4.

Abstract

Precipitation effects on plant carbon uptake extend beyond immediate timeframes, reflecting temporal lags between rainfall and plant growth. Mechanisms and relative importance of such lagged effects are expected to vary across ecosystems. Here we draw on an extensive collections of productivity proxies from long-term ground measurements, satellite observations and model simulations to show that preceding-year precipitation exerts a comparable influence on plant productivity to current-year precipitation. Statistically supported lagged precipitation effects are detected in 13.4%-19.7% of the grids depending on the data source. In these sites, preceding-year precipitation positively controls current-year plant productivity in water-limited areas, while negative effects occur in some wet regions, such as tropical forests. While aridity emerges as the main driver of this spatial variability, machine learning-based spatial attribution also indicates interactions among plant traits, climatic conditions and soil properties. We also show that soil water dynamics, plant phenology and foliar structure might mediate lagged precipitation effects across time. Our findings highlight the role of preceding-year precipitation in global plant productivity.

摘要

降水对植物碳吸收的影响超出了即时时间框架,反映了降雨与植物生长之间的时间滞后。这种滞后效应的机制和相对重要性预计会因生态系统而异。在这里,我们利用来自长期地面测量、卫星观测和模型模拟的大量生产力代理数据集,表明前一年的降水对植物生产力的影响与当年降水相当。根据数据来源,在13.4%-19.7%的网格中检测到了统计学上支持的滞后降水效应。在这些地点,前一年的降水在水分有限的地区对当年植物生产力有正向控制作用,而在一些湿润地区,如热带森林,则会产生负面影响。虽然干旱是这种空间变异性的主要驱动因素,但基于机器学习的空间归因也表明了植物性状、气候条件和土壤性质之间的相互作用。我们还表明,土壤水分动态、植物物候和叶片结构可能会在不同时间介导滞后降水效应。我们的研究结果突出了前一年降水在全球植物生产力中的作用。

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