|Integrating information on marine species identification for fishery purposes|
Lleonart, J.; Taconet, M.; Lamboeuf, M. (2006). Integrating information on marine species identification for fishery purposes. Mar. Ecol. Prog. Ser. 316: 231-238
In: Marine Ecology Progress Series. Inter-Research: Oldendorf/Luhe. ISSN 0171-8630, more
Data collections; Fao; Identification; Species; Marine
|Authors|| || Top |
- Lleonart, J.
- Taconet, M.
- Lamboeuf, M.
Species identification for fishery purposes has been the subject of a major Food and Agriculture Organization (FAO) program since the 1960s. One of the main objectives is to improve catch statistics through accurate species identification. A number of guides (geographical), catalogues (taxonomic) and species synopses have been produced as hard copy, and, more recently, most of these publications have become freely available on the Internet. Species fact sheets are a new electronic product with a database structure integrated in the Fisheries Global Information System (FIGIS). FIGIS interconnects species information with many other types of information related to fisheries (statistics, stocks inventories and assessment reports, fisheries inventories, fishing techniques, fisheries management systems, introduced species, cultured species etc.) and with a wide range of services available from other FAO systems (virtual document library, mapping library, legislation library, scientific abstracts). FIGIS achieves these features thanks to a flexible 3-tier architecture based on open-source software (Java, XML, XSL, HTML), a metadata framework based on international standards, formal institutional partnerships for information sharing, and the exploitation and display of web services. Several gaps in geographical and taxonomical coverage have been determined; these are mainly located in South America and concern several taxa (particularly crustaceans) and some fish families of paramount importance to fisheries. Other species identification tools to address multispecies and ecosystem modeling are also needed. Finally, optimization of the worldwide community efforts in generating and sharing taxonomically related knowledge in a global network is a current challenge calling for an urgent solution.