Topological Phenotypes Constitute a New Dimension in the Phenotypic Space of Leaf Venation Networks
Topological Phenotypes Constitute a New Dimension in the Phenotypic Space of Leaf Venation Networks
复制标题
拓扑表型构成了叶脉网络表型空间的新维度
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
E. Katifori
中科院分区：
文献类型：
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作者：
Henrik Ronellenfitsch;J. Lasser;D. Daly;E. Katifori
被子植物的叶子包含高度复杂的脉网络，由递归嵌套的、分层组织的回路组成。我们描述了一种基于嵌套环拓扑结构的网状血管网络的新表型特征。该表型性状编码的信息与广泛使用的几何表型性状正交，从而构成了叶脉表型空间的一个新的维度。我们将我们的度量应用于代表137个物种的186个叶片和小叶的数据库，主要来自Burseraceae家族，揭示了即使在这个单一家族中也有不同的拓扑网络特征。我们表明，通过计算拓扑和几何的“叶脉指纹”，拓扑信息显著提高了从碎片中识别叶子的能力。此外，我们提出了一个现象学模型，表明拓扑特征可以用每片叶子发育过程中标本特有的噪声效应来解释，这些噪声效应会在最终的网络中留下印记。这项工作为新的叶片定量识别技术开辟了道路，这些技术超越了简单的几何特征，如静脉密度，并直接适用于其他平面或亚平面网络，如大脑中的血管。
The leaves of angiosperms contain highly complex venation networks consisting of recursively nested, hierarchically organized loops. We describe a new phenotypic trait of reticulate vascular networks based on the topology of the nested loops. This phenotypic trait encodes information orthogonal to widely used geometric phenotypic traits, and thus constitutes a new dimension in the leaf venation phenotypic space. We apply our metric to a database of 186 leaves and leaflets representing 137 species, predominantly from the Burseraceae family, revealing diverse topological network traits even within this single family. We show that topological information significantly improves identification of leaves from fragments by calculating a “leaf venation fingerprint” from topology and geometry. Further, we present a phenomenological model suggesting that the topological traits can be explained by noise effects unique to specimen during development of each leaf which leave their imprint on the final network. This work opens the path to new quantitative identification techniques for leaves which go beyond simple geometric traits such as vein density and is directly applicable to other planar or sub-planar networks such as blood vessels in the brain.
影响因子：
3.5
作者：
VANPELT, J;UYLINGS, HBM;WOLDENBERG, MJ
通讯作者：
WOLDENBERG, MJ