Abstract
Abstract
Key message
Structural characteristics of tree crowns obtained by TLidar scanning can be used for estimating the course of the stem diameter growth in the past.
Abstract
To improve human well-being through sustainable management of ecosystems, particular attention is given to the structures, functions, and services of forest trees and stands. The classical timber provision has become only one of many other forest ecosystem services. At the same time, the methods of ecosystem observation, analysis, and modelling have enormously improved. Here, we fathomed the information potential of the tree crown structure. Our overarching hypothesis was that the crown structure reflects essential characteristics of the tree ring pattern. The empirical part of this study was based on sample trees from the combined spacing-thinning trial in Norway spruce (Picea abies [L.] Karst.) Fürstenfeldbruck 612 in Southern Germany. First, we showed that the external characteristics of tree crowns and the internal stem structure are functionally linked. Second, we derived metrics for the tree ring pattern and crown shape, and found especially close relationships between the level and bending of the growth curve and the size and stereometric shape of the crown. Third, we investigated how the derived statistical relationships between tree ring pattern and crown structure can be applied to derive the course of tree growth from the crown structure. We showed how measures such as size and variability of the crown could be used to estimate the course of diameter growth. Finally, we showed that the revealed link could be used to assess past and future growth and life expectancy of trees. These findings can be used to monitor the stress defence potential, resistance, and resilience of trees.
Funder
H2020 Marie Skłodowska-Curie Actions
Deutsche Forschungsgemeinschaft
Bayerisches Staatsministerium für Ernährung, Landwirtschaft und Forsten
Technische Universität München
Publisher
Springer Science and Business Media LLC
Subject
Plant Science,Ecology,Physiology,Forestry
Reference99 articles.
1. Abdullahi S, Schardt M, Pretzsch H (2017) An unsupervised two-stage clustering approach for forest structure classification based on X-band InSAR data—a case study in complex temperate forest stands. Int J Appl Earth Obs Geoinf 57:36–48
2. Alonzo M, Bookhagen B, Roberts DA (2014) Urban tree species mapping using hyperspectral and lidar data fusion. Remote Sens Environ 148:70–83
3. Alvites C, Santopuoli G, Maesano M, Chirici G, Moresi FV, Tognetti R, Marchetti M, Lasserre B (2021) Unsupervised algorithms to detect single trees in a mixed-species and multilayered Mediterranean forest using LiDAR data. Can J for Res 51:1766–1780. https://doi.org/10.1139/cjfr-2020-0510
4. Assmann E (1970) The principles of forest yield study. Pergamon Press, Oxford, p 506
5. Assmann E, Franz F (1963) Vorläufige Fichten-Ertragstafel für Bayern. Institut für Ertragskunde der Forstlichen Forschungsanstalt München, Germany. 104 p
Cited by
9 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献