Impact of land-use and functional diversity on diversity and stability of grassland communities in fragmented landscapes

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With a dramatic decline in species richness, it becomes increasingly important to predict the long-term impact of global changes (climate change and land-use intensification on grassland plant community composition and services. However, to date, our ability for such predictions is very limited. To improve our predictive ability, we have to learn more about the interplay between components of community structure and ecosystem functioning. Motivated by a recent call to rebuild community ecology from functional traits, we propose a new approach to link the relationship between the response trait diversity of plant communities, i.e. diversity of life-history traits, and the long-term persistence of species diversity and ecosystem productivity in fragmented landscapes. Our approach consists of the combination of three complementary tools: an equation-based metacommunity simulation model, species distribution models, and Bayesian belief networks. Using this diverse toolbox, we seek to combine information concerning the life-history, dispersal, and geographic range of species with information about the distribution of suitable grassland habitats in space. This approach will be applied to grassland metacommunities in the Biodiversity Exploratories. Mechanistic models are an essential component of this project because of their ability to incorporate knowledge from disparate domains and different spatial scales. Specifically, using the framework proposed here, models link traits and performance measures such as persistence of species diversity and ecosystem productivity and this would not be possible without modelling. Ultimately, we seek to integrate both conceptual and empirical knowledge. Thus, we give an outlook towards the development of causal models scheduled for a follow-up phase. Causal models are easy to communicate and can be continually updated when new data or conceptual knowledge becomes available. However, the steps planned for the current project phase will already noticeably improve our predictive ability on metacommunity responses to global change.