Borges, M.F., Brind’Amour, A., Cardador, F., Chaves, C., Ellis, J. R., Gaudêncio, M. J., Guerra, M., Hille Ris Lambers, R., Narberhaus, I., Rumohr, Heye, Sapp, M., Schratzberger, M., Velasco, F. and Wlodarska-Kowalczuc, M. (2010) Practical issues affecting the utility of field survey data for biodiversity monitoring. [Paper] In: ICES Annual Science Conference. , 20.-24.09.2010, Nantes, France . ICES Council Meeting Papers, 2010 (Q:10).

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Abstract

There is growing emphasis on monitoring biodiversity in European waters not least due to the EC’s recent Marine Strategy Framework Directive (MSFD) listing biodiversity as one descriptor of ‘Good Environmental Status’ (GES). Member States already have various monitoring surveys in place, in particular groundfish and other fisheries surveys, which may provide a cost-effective way of assessing
some elements of biodiversity. The MSFD recognises the “need to ensure, as far as possible, compatibility with existing programmes”. Although existing field surveys are a potential source of quantitative data for
examining spatial and temporal biodiversity patterns, it must be acknowledged that such surveys were often not originally designed to monitor ‘biodiversity’, and long-term surveys may have had changes in survey design at some point, and/or subtle changes in survey protocols over time. Field surveys for infauna and plankton typically collect and preserve samples at sea, and subsequent laboratory work includes the use of reference collections, quality assurance and longer-term sample storage. Surveys with towed gears can collect large amounts of complex biological material which is typically processed at sea, and so
different forms of quality assurance are required. The taxonomic knowledge, experience and enthusiasm of sea-going staff can also influence the biodiversity information collected (e.g. time spent sorting complex
catches, species identification). Hence, matrices of species-station data can contain ‘artefacts’ that need to be understood and addressed before deriving biodiversity metrics, and may even necessitate some degree of data filtering. This paper uses field data from selected surveys to illustrate how various factors can affect ‘biodiversity information’.

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