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Differences in responses of tree-ring δ13C in angiosperms and gymnosperms to climate change on a global scale
Forest Ecology and Management ( IF 3.7 ) Pub Date : 2021-04-20 , DOI: 10.1016/j.foreco.2021.119247
Xiaozhen Li , Guo Chen , Wenyi Qin , Xiang Wang , Haitao Liu , Peng Wang

In the context of global warming, it is important to study how plants respond to climate change. The carbon isotope composition of tree-ring corrected to the value before the industrial revolution (δ13Cring) is an indicator of intrinsic water use efficiency (iWUE) that can provide information about the carbon and water balance of plants. However, it is challenging to elucidate the influence of different parameters on δ13Cring because of the interactions among environmental parameters and tree types. Additionally, the precise global isoscapes of δ13Cring have not been well established. In this study, we collected δ13Cring data published from 1948 to 2015 and investigated the relationship of these values with different environmental factors to evaluate how angiosperms and gymnosperms respond to environment parameters. Isoscapes based on three machine learning methods were used for the first time to predict the spatial distribution of δ13Cring. The results showed that the δ13Cring values of angiosperms and gymnosperms differed significantly. Moreover, the observed decreasing trend of corrected δ13C was not mainly caused by the fertilization effect of atmospheric concentration of CO2 (Ca). Instead, mean annual temperature (MAT) and annual precipitation (PRE) were the most important climatic parameters influencing the changes in angiosperms and gymnosperms, respectively. The random forest (RF) algorithm was the best model to establish the isoscapes and separate isoscapes for angiosperms and gymnosperms were necessary for years before 1960 and within 20° of latitude.



中文翻译:

在树木年轮的反应差异δ 13被子植物和裸子植物,以应对气候变化下在全球范围内

在全球变暖的背景下,研究植物如何应对气候变化非常重要。树环的碳同位素组合物的工业革命前修正为该值(δ 13 C ^)是固有水分利用效率(IWUE),其可以提供有关植物的碳和水余额信息的指示符。然而,它是具有挑战性的阐明δ不同的参数的影响13 Ç因为环境参数和树类型之间的相互作用的。此外,δ的精确全球isoscapes 13 Ç没有被很好地建立。在这项研究中,我们收集δ 13 C ^1948年至2015年发布的数据,研究了这些值与不同环境因素之间的关系,以评估被子植物和裸子植物对环境参数的反应。Isoscapes基于三个机器学习的方法用于在第一时间预测δ的空间分布13 Ç。该结果表明,δ 13 C ^被子植物和裸子植物的值显著不同。此外,校正δ所观察到的下降趋势13 ℃下不主要是由CO的大气浓度的施肥效果2(C)。相反,年平均温度(MAT)和年降水量(PRE)分别是影响被子植物和裸子植物变化的最重要的气候参数。随机森林(RF)算法是建立等值线的最佳模型,被子植物和裸子植物的等值线在1960年之前的几年内以及在纬度20度以内是必需的。

更新日期:2021-04-20
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