Synergies and processing of data for an understanding of biodiversity and functioning across trophic levels and networks

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Wider research context: Ecological research is generating data faster and in larger volumes than ever before. Thus, data management and synthesis have become key elements driving successful integrative projects. Objectives: First, we will ensure efficient data management and promote synergies in the processing of data among MultiTroph’s subprojects through extensive services provided by training courses and the maintenance and ongoing development of the BEF-China data portal, as well as by supporting data and code open access publication strategies. Second, we will develop early synthesis connecting MultiTroph’s subprojects based on available and newly generated data which links network structure, multidiversity and multifunctionality. Multidiversity assembly and trophic interactions need time to establish. For this reason, including previous data from BEF-China is essential. Methods: We will provide data management along the entire data lifecycle, specifically by optimizing the functionality of the BEFdata portal, by providing reproducible computational workflows and training on data integration, and by managing paper proposals that guarantee a safe environment for data sharing. For synthesis across networks we will use linear mixed models and structural equation modelling to analyse the relative effects of direct and indirect pathways between tree diversity, the structure of mutualistic and antagonistic networks, and the associated multitrophic diversity of higher trophic levels. Moreover, we will relate diversity and network data to individual ecosystem functions and multifunctionality. Several functions can be followed over time from the establishment of the experiment to the current closed-canopy stands. Structural equation modelling on distance matrices will be used to assess the relative strength of space and the abiotic environment vs. tree species diversity and biomass on these functions over the course of ecosystem development. Finally, we will make use of network characteristics and multidiversity metrics to analyse their contribution to overall ecosystem functioning, i.e. multifunctionality. This will be achieved with generalized multilevel path analysis and by quantifying total energy flow and storage across trophic levels, based on extensive data on ecosystem process rates, stoichiometric data and the calculation of metabolic rates. Innovation: We provide data management and synthesis—both of which are mandatory for an interdisciplinary consortium such as MultiTroph—in a unique framework allowing us to combine new research ideas with legacy data from past observations over different spatial and temporal scales.Primary researchers involved: Andreas Schuldt (PI, Uni Göttingen), Helge Bruelheide (Co-PI, Uni Halle-Wittenberg), in collaboration with our Chinese partners Huijie Qiao and Xiaojuan Liu (Chinese Academy of Sciences).