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Direct measurement of leaf area index in a deciduous needle-leaf forest, eastern Siberia
Polar Science ( IF 1.8 ) Pub Date : 2020-06-18 , DOI: 10.1016/j.polar.2020.100550
Nagai Shin , Ayumi Kotani , Tomonori Sato , Atsuko Sugimoto , Trofim C. Maximov , Aleksandr Nogovitcyn , Yumiko Miyamoto , Hideki Kobayashi , Shunsuke Tei

Accurate calculation of leaf area index (LAI) in boreal forests, which are vulnerable to climate change and have insufficient ground-truth data, is an important but challenging task when evaluating the spatio-temporal variability of ecosystem structures and functions (photosynthesis and evapotranspiration). By applying a direct method, we calculated the LAI of multiple forest layers (i.e., overstory of larch; understory of birch, willow, and alder; and floor vegetation) in a deciduous needle-leaf forest with a somewhat open canopy in eastern Siberia. We performed field studies that included logging one overstory larch tree, harvesting leaves of larch and floor vegetation (e.g., Vaccinium vitis-idaea), sampling leaves of understory trees, and measuring the architecture and morphology of overstory and understory trees and leaves. The plot-scale LAIs of larch overstory, understory trees, and floor vegetation were 1.30, 0.50, and 0.51, respectively, for a total of 2.31. Sum of our plot-scale LAI of larch overstory and understory trees was similar to previously reported results based on indirect methods. Our results indicate that LAI of understory trees and forest floor vegetation is important to improve the accuracy of total LAI of a deciduous needle-leaf forest with a somewhat open canopy in eastern Siberia.



中文翻译:

西伯利亚东部落叶针叶林叶面积指数的直接测量

在评估生态系统结构和功能(光合作用和蒸散量)的时空变化时,准确计算易受气候变化影响且缺乏真实数据的北方森林叶面积指数(LAI)是一项重要但具有挑战性的任务。 。通过采用直接方法,我们计算了西伯利亚东部一个略带开放冠层的落叶针叶林中多个森林层(即落叶松的上层;桦木,柳树和al木的下层;以及地上植被)的LAI。我们进行了实地研究,包括伐木一棵落叶松树,收获落叶松叶和地上植被(例如,越桔)),抽取林下树木的叶子,并测量林下和林下树木和树叶的结构和形态。落叶松上层林,下层林木和地上植被的样地规模LAI分别为1.30、0.50和0.51,总计2.31。落叶松上层林和下层林的地块规模LAI的总和与以前基于间接方法报告的结果相似。我们的结果表明,林下树木和林地植被的LAI对于提高西伯利亚东部冠层有些开放的落叶针叶林总LAI的准确性很重要。

更新日期:2020-06-18
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