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Projekt Druckansicht

Analyse von Diversitätseffekten auf die oberirdische Produktivität in Wäldern: vertieftes mechanistisches Verständnis der raum-zeitlichen Dynamik der Kronenraumbesetzung durch Einsatz des Mobilen Laserscannings

Fachliche Zuordnung Ökologie und Biodiversität der Pflanzen und Ökosysteme
Förderung Förderung von 2016 bis 2021
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 320926971
 
Erstellungsjahr 2020

Zusammenfassung der Projektergebnisse

Crown complementarity has been proposed as a fundamental mechanism underlying the enhanced canopy space-use efficiency and, thus, higher canopy space filling in mixed-species forest stands. Empirical evidence is, however, limited because the non-destructive, high-resolution and time-efficient quantification of 3D canopy space occupation patterns over large areas has long been logistically unfeasible. The use of mobile laser scanning (MLS) data has the potential to overcome these limitations. For this purpose, however, comprehensive methods are required for the automatic co-registration of the 3D-data, for the automatic individual-tree segmentation, and for the precise quantification of canopy space filling. The main goal of this cooperation project was to develop such methods and to analyse the impact of tree species richness on canopy space occupation in natural mature mixed-species forests using MLS data. We tested and validated the developed methods on the basis of a structurally complex mixed forest in northern Germany, in which MLS and terrestrial laser scanning (TLS) recordings were made in winter and summer. We developed a system-independent segmentation algorithm, which works with a 3D point cloud and a scan trajectory. Thus, MLS data sets of any system can be used. We found that trees with a diameter at breast height (DBH) > 7 cm and with a distance of up to 30 m from the MLS trajectory can generally be detected and segmented with sufficient accuracy. Analysing TLS data, we showed that local neighbourhood diversity has a significant influence on crown dimension and wood volume of individual trees. Moreover, we found a size-dependency of diversity effects on tree productivity (basal area and wood volume increment) with positive effects for large-sized trees and negative effects for small-sized trees. The MLS data analyses revealed that various relations between tree species richness (TSR) and crown space occupation (CSO) exist, depending on the definition of TSR and canopy space. Considering only the large trees of a patch for TSR determination, we observed a significant increase of CSO with TSR, whereas the opposite was found when including all trees > 7 cm DBH per patch. In addition to the MLS and TLS campaigns, forest stands were recorded with a new type of personal laser scanning (PLS) system. The additional PLS data provide a valuable database for the completion of the MLS data. In the course of the project an extensive and valuable dataset has been developed, which provides the basis for further research projects with regard to automatic tree species classification, e.g. with machine learning approaches. The results of the project have been published in leading scientific forestry journals.

Projektbezogene Publikationen (Auswahl)

 
 

Zusatzinformationen

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