New perspectives on the ecology of tree structure and tree communities through terrestrial laser scanning. Issue 2 (16th February 2018)

• Record Type: Journal Article
• Authors: Malhi, Yadvinder; Jackson, Tobias; Patrick Bentley, Lisa; Lau, Alvaro; Shenkin, Alexander; Herold, Martin; Calders, Kim; Bartholomeus, Harm; Disney, Mathias I.
• Is Part Of: Interface focus. Volume 8:Issue 2(2018)
• Publication Date: 2018-02-16
• Subjects: terrestrial laser scanning -- tree architecture -- metabolic scaling theory -- wind speed -- tree surface area -- branching; Physical sciences -- Periodicals; Life sciences -- Periodicals; 500
• DOI: 10.1098/rsfs.2017.0052
• Languages: English
• ISSNs: 2042-8898

Abstract

Abstract : Terrestrial laser scanning (TLS) opens up the possibility of describing the three-dimensional structures of trees in natural environments with unprecedented detail and accuracy. It is already being extensively applied to describe how ecosystem biomass and structure vary between sites, but can also facilitate major advances in developing and testing mechanistic theories of tree form and forest structure, thereby enabling us to understand why trees and forests have the biomass and three-dimensional structure they do. Here we focus on the ecological challenges and benefits of understanding tree form, and highlight some advances related to capturing and describing tree shape that are becoming possible with the advent of TLS. We present examples of ongoing work that applies, or could potentially apply, new TLS measurements to better understand the constraints on optimization of tree form. Theories of resource distribution networks, such as metabolic scaling theory, can be tested and further refined. TLS can also provide new approaches to the scaling of woody surface area and crown area, and thereby better quantify the metabolism of trees. Finally, we demonstrate how we can develop a more mechanistic understanding of the effects of avoidance of wind risk on tree form and maximum size. Over the next few years, TLS promises to deliver both major empirical and conceptual advances in the quantitative understanding of trees and tree-dominated ecosystems, leading to advances in understanding the ecology of why trees and ecosystems look and grow the way they do.