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Molecular Signal Processing
Bioorganic Chemistry
Biochemistry of Plant Interactions
Cell and Metabolic Biology
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Global change exposes forest ecosystems to many risks including novel climatic conditions, increased frequency of climatic extremes and sudden emergence and spread of pests and pathogens. At the same time, forest landscape restoration has regained global attention as an integral strategy for climate change mitigation. Owing to unpredictable future risks and the need for new forests that provide multiple ecosystem services, mixed-species forests have been advocated for this purpose. However, the successful establishment of mixed forests requires intrinsic knowledge of biodiversity\'s role for forest ecosystem functioning. In this respect, a better understanding of tree-tree interactions and how they contribute to observed positive tree species richness effects on key ecosystem functions is critical. Here, we review the current knowledge of the underlying mechanisms of tree-tree interactions and argue that positive net biodiversity effects at the community scale may emerge from the dominance of positive over negative interactions at the local neighbourhood scale. In a second step, we demonstrate how tree-tree interactions and the immediate tree neighbourhood\'s role can be systematically assessed in a tree diversity experiment. The expected results will improve predictions about the effects of tree interactions on ecosystem functioning based on general principles. We argue that this knowledge is urgently required to guide the design of tree species mixtures for the successful establishment of newly planted forests.
Publications
In plants, secondary metabolite profiles provide a unique opportunity to explore seasonal variation and responses to the environment. These include both abiotic and biotic factors. In field experiments, such stress factors occur in combination. This variation alters the plant metabolic profiles in yet uninvestigated ways. This data set contains trait and mass spectrometry data of thirteen grassland species collected at four time points in the growing season in 2017. We collected above-ground vegetative material of seven grass and six herb species that were grown in plant communities with different levels of diversity in the Jena Experiment. For each sample, we recorded visible traits and acquired shoot metabolic profiles on a UPLC-ESI-Qq-TOF-MS. We performed the raw data pre-processing in Galaxy-W4M and prepared the data for statistical analysis in R by applying missing data imputation, batch correction, and validity checks on the features. This comprehensive data set provides the opportunity to investigate environmental dynamics across diverse neighbourhoods that are reflected in the metabolomic profile.