Perspectives in Meiobenthology by Olav Giere

Author:Olav Giere
Language: eng
Format: epub
ISBN: 9783030139667
Publisher: Springer International Publishing

(2)Compared with morphological taxonomy, identification by meta-barcoding seems less accurate at low taxonomic ranks, while it works well in discriminating units at higher ranks (Leasi et al. 2018). Moreover, this comprehensive study disclosed that, depending on the method applied, the various meiofaunal taxa become differently resolved. In some groups, the recorded alpha-diversity was higher when identifying by traditional morphological taxa compared to the use of barcoding methods.

Oftentimes, studies on dominant meiofauna groups (e.g. nematodes), from marine and freshwater, from shallow and deep sites try to assess a potential relation between biodiversity (alpha-diversity) and functional diversity or even ‘efficacy’ of an ecosystem. It turns out that many of these complex concepts are scale dependent, i.e. factors relevant for smaller-scale investigations may change at greater scales (Dümmer et al. 2016; Rosli et al. 2017). Comparing alpha-diversity and functional diversity among nematodes at different depths in the Mediterranean, Baldrighi and Manini (2015) could not find a consistent relationship, but rather a varying dependence on size class within the taxon. Also in studies that compared meio- and macrobenthos, a parallel trend between alpha-diversity and functional diversity was rarely found (see Discussion in Baldrighi and Manini 2015). Since functional diversity, among other factors, strongly depends on the trophic spectrum, differences between meio- and macrofauna with their different composition of trophic types (e.g. scarce filter feeders in meiobenthos) are to be expected.

The frequently cited bathymetric gradient, typically found in sampling profiles from the surface towards the deep-sea, denotes an exponential decline in functional diversity compared to the more linear decline in numerical biodiversity (see Danovaro et al. 2008). While the dwindling food supply will be responsible for the general decrease in biodiversity, the exponentially diminishing functional diversity and the dropping of other ‘ecosystem functions’ are probably not to be explained by unifactorial influences and not valid for all diversity levels (Pusceddu et al. 2016).

The question is: Does a generally definable relation between numerical diversity and functional diversity exist? In nematodes, high species diversity did not relate to a greater functional diversity (Baldrighi and Manini 2015). Strong competition (niche overlap) as well as functional redundancy, typical for shallow sites, might reduce numerical biodiversity of assemblages but promote their functional diversity.

Altogether, many of the postulated relations, how ecological parameters influence biodiversity, have to be put into perspective (Leduc et al. 2013). Biodiversity depends on the spatial scale; it is strongly influenced by the maturity of the ecosystem, the prevailing limitations and by the abiotic situation. There may be loose ties only as well as direct interdependences. In essence, the entire ecological context, both abiotic and biotic, is of influence and hardly definable by a general relationship (Danovaro et al. 2013).

Scrutiny of data by complex mathematical models seems to be a promising approach when analysing these relations. Again, this requires cooperation of teams, sometimes disciplines, particularly when studying large areas. Analyses of biodiversity in large regions not only reveal distributional patterns and their influencing factors. They often allow for conclusions on the connectivity of communities and help to designate metacommunities.

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