- An ecosystem-based approach to assess the status of a Mediterranean ecosystem, the Posidonia oceanica seagrass meadow. doi link

Auteur(s): Personnic S., Boudouresque C.-F., Astruch P., Ballesteros Enric, Blouet Sylvain, Bellan-Santini Denise, Bonhomme P., Thibault-Botha Delphine, Feunteun E., Harmelin M., Pergent Gérard, Pergent-Martini Christine, Pastor Jérémy, Poggiale J.-C., Renaud Florent, Thibaut T., Ruitton S.

(Article) Publié: Plos One, vol. 9 p.e98994 (2014)

Ref HAL: hal-01148508_v1
PMID 24933020
DOI: 10.1371/journal.pone.0098994
Exporter : BibTex | endNote

Biotic indices, which reflect the quality of the environment, are widely used in the marine realm. Sometimes, key species or ecosystem engineers are selected for this purpose. This is the case of the Mediterranean seagrass Posidonia oceanica, widely used as a biological quality element in the context of the European Union Water Framework Directive (WFD). The good quality of a water body and the apparent health of a species, whether or not an ecosystem engineer such as P. oceanica, is not always indicative of the good structure and functioning of the whole ecosystem. A key point of the recent Marine Strategy Framework Directive (MSFD) is the ecosystem-based approach. Here, on the basis of a simplified conceptual model of the P. oceanica ecosystem, we have proposed an ecosystem-based index of the quality of its functioning, compliant with the MSFD requirements. This index (EBQI) is based upon a set of representative functional compartments, the weighting of these compartments and the assessment of the quality of each compartment by comparison of a supposed baseline. The index well discriminated 17 sites in the north-western Mediterranean (French Riviera, Provence, Corsica, Catalonia and Balearic Islands) covering a wide range of human pressure levels. The strong points of the EBQI are that it is easy to implement, non-destructive, relatively robust, according to the selection of the compartments and to their weighting, and associated with confidence indices that indicate possible weakness and biases and therefore the need for further field data acquisition.