A trait-based experimental approach to understand the mechanisms underlying biodiversity–ecosystem functioning relationships |
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| Institution: | 2. Institute of Biology, University Leipzig, Leipzig, Germany;3. Netherlands Institute of Ecology (NIOO), Wageningen, The Netherlands;4. Laboratory of Nematology, Wageningen University, Wageningen, The Netherlands;5. Department of Soil Quality, Wageningen University, Wageningen, The Netherlands;6. Institute of Evolutionary Biology and Environmental Studies, University of Zürich, Zürich, Switzerland;11. Terrestrial Ecology Research Group, Department of Ecology and Ecosystem Management, School of Life Sciences, Technische Universität München, Freising, Germany;12. Swiss Federal Institute of Aquatic Science and Technology (Eawag), Kastanienbaum, Switzerland;8. J. F. Blumenbach Institute of Zoology and Anthropology, University of Göttingen, Göttingen, Germany;9. Department of Biology, Lund University, Lund, Sweden;10. Agroecology, Department of Crop Sciences, University of Göttingen, Göttingen, Germany;1. Department of Plant Biology and Ecology, College of Life Science, Nankai University, No. 94 Weijin Road, Tianjin 300071, PR China;2. College of Agronomy & Resources and Environment, Tianjin Agricultural University, No. 22 Jinjing Road, Tianjin 300384, PR China |
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| Abstract: | Plant functional characteristics may drive plant species richness effects on ecosystem processes. Consequently, the focus of biodiversity–ecosystem functioning (BEF) experiments has expanded from the manipulation of plant species richness to manipulating functional trait composition. Involving ecophysiological plant traits in the experimental design might allow for a better understanding of how species loss alters ecosystem processes. Here we provide the theoretical background, design and first results of the ‘Trait-Based Biodiversity Experiment’ (TBE), established in 2010 that directly manipulates the trait composition of experimental plant communities.Analysis of six plant traits related to resource acquisition and use were analyzed using principal component analysis of 60 grassland species. The resulting two main axes describe gradients in functional similarity, and were used as the basis for designing plant communities with different functional and species diversity levels. Using such an approach allowed us to manipulate different levels of complementarity in spatial and temporal plant resource acquisition. In contrast to previous biodiversity experiments, the TBE is designed according to more realistic scenarios of non-random species loss along orthogonal axes of species trait dissimilarities. This allows us to tease apart the relative importance of selection and complementarity effects on multiple ecosystem processes, and to mechanistically study the consequences of plant community simplification. |
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| Keywords: | Functional diversity Species richness Plant traits Jena Experiment Selection effect Complementarity effect Redundancy Plant shoot biomass |
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