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  • Articles  (1)
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  • München : Bayerisches Landesvermessungsamt
  • Springer Nature
  • Wien : Geolog. Bundesanst.
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    Springer Nature
    In:  EPIC3Biodiversity and Conservation, Springer Nature, 23(2), pp. 405-419, ISSN: 0960-3115
    Publication Date: 2023-09-22
    Description: One of the most controversially discussed topics in current biodiversity-ecosystem function research is the transfer of results from experimental and theoretical studies to natural ecosystems. At the same time, monitoring data on biodiversity are requested as key indicators for the state of an ecosystem in most environmental evaluation frameworks. We analyse two monitoring data sets comprising information on abundance and biomass of macrozoobenthos communities in the German Wadden Sea in order to evaluate how much information monitoring data on biodiversity provide concerning ecosystem functioning and what implications this information (or the lack thereof) has for future monitoring programmes. Our results show a positive correlation between number of species of macrozoobenthos and its standing stock. Despite differences in overall biomass and individual size in different functional groups, this correlation remained consistent for different feeding guilds and therefore is likely to be independent of certain species traits. Moreover, functional turnover analyses indicate that increasing species richness is needed to maintain biomass levels over increasing periods of time. Whereas our data thus corroborate predictions from theory, we could not determine any causal relationships, because monitoring data commonly include only vague proxies for very few functional parameters, in our case standing biomass as a proxy for production. As to the use of diversity as an indicator for ecosystem functioning, we advise that management decisions are to be based on verified causal relationships and therefore strongly suggest the general incorporation of unambiguous proxies for functional parameters in the measuring campaigns of monitoring programmes.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev
    Format: application/pdf
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