“Green pointillism”: detecting the within-population variability of budburst in temperate deciduous trees with phenological cameras
“Green pointillism”: detecting the within-population variability of budburst in temperate deciduous trees with phenological cameras
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DOI：
10.1007/s00484-019-01855-2
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发表时间：
2019-09
影响因子：
3.2
通讯作者：
N. Delpierre;K. Soudani;D. Berveiller;E. Dufrene;G. Hmimina;G. Vincent
中科院分区：
文献类型：
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作者：
N. Delpierre;K. Soudani;D. Berveiller;E. Dufrene;G. Hmimina;G. Vincent
物候照相机十多年来一直用于识别植物物候标记（芽、叶衰老）和更普遍的森林冠层的绿色动态。分析通常是在整个相机视野范围内进行的，对树木之间物候标记的变异性没有特别的分析。本研究表明，物候照相机产生的图像可用于量化温带落叶林中芽芽（WPVbb）的种群内变异。通过7个站点年的图像分析，我们报告物候照相机测定的WPVbb与地面观测的量化之间存在很强的相关性（r2= 0.97）。我们表明，在给定的种群中，WPVbb每年都有很强的变化（4倍），这些变化与发芽期的温度条件有关，较冷的春天与树木之间的芽分化（较高的WPVbb）有关。在大陆尺度上部署我们的方法，即通过物候照相机网络，将提高对WPVbb的空间（跨种群）和时间（跨年份）变化的理解，这对森林功能、树木适应度和物候建模具有重要意义。
Phenological cameras have been used over a decade for identifying plant phenological markers (budburst, leaf senescence) and more generally the greenness dynamics of forest canopies. The analysis is usually carried out over the full camera field of view, with no particular analysis of the variability of phenological markers among trees. Here we show that images produced by phenological cameras can be used to quantify the within-population variability of budburst (WPVbb) in temperate deciduous forests. Using seven site-years of image analyses, we report a strong correlation (r2= 0.97) between the WPVbb determined with a phenological camera and its quantification through ground observation. We show that WPVbb varies strongly (by a factor of 4) from year to year in a given population and that those variations are linked with temperature conditions during the budburst period, with colder springs associated to a higher differentiation of budburst (higher WPVbb) among trees. Deploying our approach at the continental scale, i.e., throughout phenological cameras networks, would improve the understanding of the spatial (across populations) and temporal (across years) variations of WPVbb, which have strong implications on forest functioning, tree fitness and phenological modelling.