Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/118870
Title: Patterns of intraspecific and intraindividual trait variation in trees along experimental diversity gradients
Author(s): Castro Sánchez-Bermejo, PabloLook up in the Integrated Authority File of the German National Library
Referee(s): Bruelheide, HelgeLook up in the Integrated Authority File of the German National Library
Haider, Sylvia Simone RebekkaLook up in the Integrated Authority File of the German National Library
Herrera Maliani, Carlos M.
Granting Institution: Martin-Luther-Universität Halle-Wittenberg
Issue Date: 2025
Extent: 1 Online-Ressource (227 Seiten)
Type: HochschulschriftLook up in the Integrated Authority File of the German National Library
Type: PhDThesis
Exam Date: 2025-03-07
Language: English
URN: urn:nbn:de:gbv:3:4-1981185920-1208286
Abstract: Phenotypic differences addressed from functional traits are widely used to study forest functioning. However, while ecological studies have traditionally focused on species-level trait differences, recent research emphasizes the need of considering intraspecific and intraindividual trait variation. Using leaf-level data collected in two large-scale forest biodiversity experiments in subtropical China and in Germany, I studied leaf trait variation along diversity gradients. The results show that trees change their leaf strategy and the leaf variability within the crown in response to diversity. Further, intraspecific trait variation is higher in monocultures to alleviate intraspecific competitive interactions and decreases with increasing tree species richness. Last, the results show how the organization of intraspecific and intraindividual trait variation lead to higher functional diversity of forest stands, which highlights their importance for understanding forest functioning.
URI: https://opendata.uni-halle.de//handle/1981185920/120828
http://dx.doi.org/10.25673/118870
Open Access: Open access publication
License: (CC BY-ND 4.0) Creative Commons Attribution NoDerivatives 4.0(CC BY-ND 4.0) Creative Commons Attribution NoDerivatives 4.0
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