Integrating trophic data from the literature: The Danube River food web

In the era of bioinformatics and big data, ecological research depends on large and easily accessible databases that make it possible to construct complex system models. Open-access data repositories for food webs via publications and ecological databases (e.g. EcoBase) are becoming increasingly common, yet certain ecosystem types are underrepresented (e.g. rivers). In this paper, we compile the trophic connections (predator-prey relationships) for the Danube River ecosystem as gathered from globally available literature data. Data are analyzed by Danube regions separately (Upper, Middle, Lower Danube) as well as an integrated master network version. The master version has been aggregated into larger taxonomic categories. Local and global metrics were used to analyze and compare each network. We find disparity between regions (the Middle Danube having most nodes, but still quite heterogenous), we identify the most important trophic groups, and explain ways on evaluating missing data using each aggregation stage. This data-driven approach, summarizing our presently documented knowledge, can be used for preparing preliminary models and to further refine the Danube River food web in the future.

Automated summary

In the era of bioinformatics and big data, this study compiled trophic connections of the Danube River ecosystem from globally available literature data. Data were analyzed by region and an integrated master network version, identifying disparities between regions, determining the most important trophic groups, and explaining methods for evaluating missing data at each aggregation stage. This data-driven approach can be used to prepare preliminary models and refine the Danube River food web in the future.