文章基本信息

标题：Spatial patterning among savanna trees in high-resolution, spatially extensive data
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作者：A. Carla Staver ; A. Carla Staver ; Gregory P. Asner 等
期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2019
卷号：116
期号：22
页码：10681-10685
DOI：10.1073/pnas.1819391116
出版社：The National Academy of Sciences of the United States of America
摘要：In savannas, predicting how vegetation varies is a longstanding challenge. Spatial patterning in vegetation may structure that variability, mediated by spatial interactions, including competition and facilitation. Here, we use unique high-resolution, spatially extensive data of tree distributions in an African savanna, derived from airborne Light Detection and Ranging (LiDAR), to examine tree-clustering patterns. We show that tree cluster sizes were governed by power laws over two to three orders of magnitude in spatial scale and that the parameters on their distributions were invariant with respect to underlying environment. Concluding that some universal process governs spatial patterns in tree distributions may be premature. However, we can say that, although the tree layer may look unpredictable locally, at scales relevant to prediction in, e.g., global vegetation models, vegetation is instead strongly structured by regular statistical distributions.
关键词：savanna ; spatial pattern ; LiDAR ; heterogeneity