Trait-Based Ecosystem Modeling: Integrating Community Assembly and Optimality Concepts into Dgvms

Tuesday, 16 December 2014
Simon Scheiter, Senckenberg Research Institute, Biodiversity and Climate Research Centre (BiK-F), Frankfurt am Main, Germany, Liam Langan, Goethe University Frankfurt, Physical Geography, Frankfurt, Germany and Steven I. Higgins, University of Otago, Department of Botany, Dunedin, New Zealand
Dynamic global vegetation models (DGVMs) are a central component of Earth system models, and our ability to understand and simulate past, present and future changes in the Earth system is linked to the quality of DGVMs. A major limitation of most DGVMs is that they represent vegetation by a fixed number of static functional types that do not allow plants and plant communities to dynamically adjust to the biotic and abiotic conditions. Here, we present the aDGVM2, a novel individual- and trait-based dynamic vegetation model. The aDGVM2 simulates growth, reproduction and mortality of single plants as a function of the plant-specific combination of trait values. Concepts from genetic optimization are used to simulate trait inheritance, crossover and mutation. These processes ensure that well-performing plants can pass their traits to the next generation and that vegetation can adjust to potentially changing environmental conditions. Thereby, the model iteratively assembles plant communities that are adapted to the environment. The aDGVM2 simulates responses of plant traits along climate, soil and disturbance gradients and associated responses in community structure, diversity and biome types. More specifically, we show that rooting strategies emerging in model simulations are related to soil characteristics and rainfall regimes and that community assembly processes can buffer impacts of disturbances on vegetation. The aDGVM2 model approach integrates aspects of community assembly theory, Earth system modeling and optimality theory and it has a high potential to improve our understanding of ecosystem responses to environmental changes.