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Early subtropical forest growth is driven by community mean trait values and functional diversity rather than the abiotic environment
Authors:Wenzel Kröber  Ying Li  Werner Härdtle  Keping Ma  Bernhard Schmid  Karsten Schmidt  Thomas Scholten  Gunnar Seidler  Goddert von Oheimb  Erik Welk  Christian Wirth  Helge Bruelheide
Affiliation:1. Martin Luther University Halle‐Wittenberg, Institute of Biology/Geobotany and Botanical Garden, Halle (Saale), Germany;2. Faculty of Sustainability, Institute of Ecology, Leuphana University Lüneburg, Lüneburg, Germany;3. Institute of Botany, CAS, Xiangshan, Beijing, China;4. University of Zurich, Zürich, Switzerland;5. Physical Geography and Soil Science, University of Tübingen, Tübingen, Germany;6. Institute of General Ecology and Environmental Protection, Technische Universit?t Dresden, Tharandt, Germany;7. University of Leipzig, Leipzig, Germany;8. German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig, Leipzig, Germany
Abstract:While functional diversity (FD) has been shown to be positively related to a number of ecosystem functions including biomass production, it may have a much less pronounced effect than that of environmental factors or species‐specific properties. Leaf and wood traits can be considered particularly relevant to tree growth, as they reflect a trade‐off between resources invested into growth and persistence. Our study focussed on the degree to which early forest growth was driven by FD, the environment (11 variables characterizing abiotic habitat conditions), and community‐weighted mean (CWM) values of species traits in the context of a large‐scale tree diversity experiment (BEF‐China). Growth rates of trees with respect to crown diameter were aggregated across 231 plots (hosting between one and 23 tree species) and related to environmental variables, FD, and CWM, the latter two of which were based on 41 plant functional traits. The effects of each of the three predictor groups were analyzed separately by mixed model optimization and jointly by variance partitioning. Numerous single traits predicted plot‐level tree growth, both in the models based on CWMs and FD, but none of the environmental variables was able to predict tree growth. In the best models, environment and FD explained only 4 and 31% of variation in crown growth rates, respectively, while CWM trait values explained 42%. In total, the best models accounted for 51% of crown growth. The marginal role of the selected environmental variables was unexpected, given the high topographic heterogeneity and large size of the experiment, as was the significant impact of FD, demonstrating that positive diversity effects already occur during the early stages in tree plantations.
Keywords:BEF‐China  community‐weighted mean traits  ecosystem functioning  plant functional traits  stomatal density  trees
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