气候变化领域集成服务门户(CCPortal): Estimating architecture-based metabolic scaling exponents of tropical trees using terrestrial LiDAR and 3D modelling

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DOI	10.1016/j.foreco.2019.02.019
	Estimating architecture-based metabolic scaling exponents of tropical trees using terrestrial LiDAR and 3D modelling
	Lau A.; Martius C.; Bartholomeus H.; Shenkin A.; Jackson T.; Malhi Y.; Herold M.; Bentley L.P.
发表日期	2019
ISSN	0378-1127
起始页码	132
结束页码	145
卷号	439
英文摘要	The geometric structure of tree branches has been hypothesized to relate to the mechanical safety and efficiency of resource transport within a tree. As such, the topology of tree architecture links physical properties within a tree and influences the interaction of the tree with its environment. Prior work suggests the existence of general principles which govern tree architectural patterns across of species and bio-geographical regions. In particular, West, Brown and Enquist (WBE, 1997) and Savage et al. (2010) derive scaling exponents (branch radius scaling ratio α and branch length scaling ratio β) from symmetrical branch parameters and from these, an architecture-based metabolic scaling rate (θ) for the whole tree. With this key scaling exponent, the metabolism (e.g., number of leaves, respiration, etc.) of a whole tree, or potentially a group of trees, can be estimated allometrically. Until now, branch parameter values have been measured manually; either from standing live trees or from harvested trees. Such measurements are time consuming, labour intensive and susceptible to subjective errors. Remote sensing, and specifically terrestrial LiDAR (TLS), is a promising alternative, being objective, scalable, and able to collect large quantities of data without destructive sampling. In this paper, we calculated branch length, branch radius, and architecture-based metabolic rate scaling exponents by first using TLS to scan standing trees and then fitting quantitative structure models (TreeQSM) models to 3D point clouds from nine trees in a tropical forest in Guyana. To validate these TLS-derived scaling exponents, we compared them with exponents calculated from direct field measurements of all branches >10 cm at four scales: branch-level, cumulative branch order, tree-level and plot-level. We found a bias on the estimations of α and β exponents due to a bias on the reconstruction of the branching architecture. Although TreeQSM scaling exponents predicted similar θ as the manually measured exponents, this was due to the combination of α and β scaling exponents which were both biased. Also, the manually measured α and β scaling exponents diverged from the WBE's theoretical exponents suggesting that trees in tropical environments might not follow the predictions for the symmetrical branching geometry proposed by WBE. Our study provides an alternative method to estimate scaling exponents at both the branch- and tree-level in tropical forest trees without the need for destructive sampling. Although this approach is based on a limited sample of nine trees in Guyana, it can be implemented for large-scale plant scaling assessments. These new data might improve our current understanding of metabolic scaling without harvesting trees. © 2019 Elsevier B.V.
英文关键词	Architecture-based metabolic rate; Destructive harvesting; Quantitative structure models; Terrestrial LiDAR; WBE plant scaling exponent
语种	英语
scopus关键词	3D modeling; Architecture; Harvesting; Metabolism; Optical radar; Plants (botany); Remote sensing; Scaling laws; Seebeck effect; Surveying instruments; Tropics; Architectural pattern; Destructive sampling; Geometric structure; Metabolic rates; Quantitative structures; Scaling exponent; Terrestrial lidars; Tropical environments; Forestry; biogeographical region; estimation method; lidar; metabolism; plant architecture; reconstruction; three-dimensional modeling; tree; tropical environment; tropical forest; Data; Forestry; Guyana; Harvesting; Metabolism; Remote Sensing; Trees; Tropics; Guyana
来源期刊	Forest Ecology and Management
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156083
作者单位	Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, Droevendaalsesteeg 3, Wageningen, PB 6708, Netherlands; Center for International Forestry Research (CIFOR), P.O. Box 0113 BOCBD, Bogor, 16000, Indonesia; Environmental Change Institute, School of Geography and the Environment, South Parks Road, University of OxfordOX1 3QY, United Kingdom; Department of Biology, Sonoma State University, 1801 East Cotati Avenue, Rohnert Park, CA 94928, United States
推荐引用方式 GB/T 7714	Lau A.,Martius C.,Bartholomeus H.,et al. Estimating architecture-based metabolic scaling exponents of tropical trees using terrestrial LiDAR and 3D modelling[J],2019,439.
APA	Lau A..,Martius C..,Bartholomeus H..,Shenkin A..,Jackson T..,...&Bentley L.P..(2019).Estimating architecture-based metabolic scaling exponents of tropical trees using terrestrial LiDAR and 3D modelling.Forest Ecology and Management,439.
MLA	Lau A.,et al."Estimating architecture-based metabolic scaling exponents of tropical trees using terrestrial LiDAR and 3D modelling".Forest Ecology and Management 439(2019).