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.

Integrating trophic data from the literature: The Danube River food web / Patonai, K.; Jordan, F.. - In: FOOD WEBS. - ISSN 2352-2496. - 28:(2021), p. e00203.e00203. [10.1016/j.fooweb.2021.e00203]

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

Jordan F.
2021

Abstract

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.
Integrating trophic data from the literature: The Danube River food web / Patonai, K.; Jordan, F.. - In: FOOD WEBS. - ISSN 2352-2496. - 28:(2021), p. e00203.e00203. [10.1016/j.fooweb.2021.e00203]
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2915836
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 2
social impact