Linking crown structure with tree ring pattern: methodological considerations and proof of concept

Author:

Pretzsch HansORCID,Ahmed ShamimORCID,Jacobs MartinORCID,Schmied GerhardORCID,Hilmers TorbenORCID

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

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3