Trait-based modelling to explore processes underlying diversity-functioning relationships

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Current problems in confidently predicting individual, community and ecosystem performance in the Jena Experiment point to our limited understanding of how plant traits translate into functioning. Our general objective is to link plant species traits to the functioning of grassland ecosystems in the context of the Jena Experiment. We propose three complementary modelling approaches that are apt to use the abundantly available information on traits and functions in the context of the Jena experiment to elucidate mechanisms underlying diversity-functioning relationships: (1) We will develop a statistical framework that explores the effect of traits and trait correlations on processes operating at different levels of integration. To this aim, we will estimate functional tradeoffs using non-linear dimensionality reductions and use the resulting manifolds to calculate complementarity, identity and distinctiveness of mixtures. The relationships to functions emerging at the individual, community and ecosystem level will be explored using variance partitioning and hierarchical Bayesian modelling. (2) We will explore how the structure of interaction networks characterized by interaction and connectivity matrices in Lotka-Volterra models parameterized from trait information and experimental data evoke different diversity-functioning mechanisms and (3) will apply a mechanistic model (GEMINI) in order to develop a system of predictions how traits translate into patterns of functioning and how trait correlations respond plastically along complementarity gradients. The design of the new experiment was tailored to support these three approaches.