Untitled - CNR

Fishery and Sea Resourcesmerge daily catch data with TPs and positiondata.Temperature and pressure data are seldommissing due to damaging or loss of the TPssensors. Besides, TPs data cannot be associatedwith geographic position, when theGPS does not receive the signal.5 ConclusionsFluctuations in the physical features of theenvironment may produce relevant changesin the marine ecosystem. The fish distributionis obviously influenced by these fluctuations.Therefore it is easy to understandthe relevance of appropriate observationaltools able to provide a better understandingof the links between environment andfish resources. The FOS discussed herebyrepresents a first and successful attempt towardthis goal. Thus an application ofsuch a monitoring system in other importantfishing areas of the Mediterranean Seawould be crucial in order to reach an effectivefishery management.At present time, one of the limits of theFOS is the deferred availability of the data:once a month the ISMAR-CNR operatorvisits the vessels in order to download theTPs data set. This time interval could befine for fishery management purposes but istoo long for operational applications. In avery next future, the TPs will be upgradedwith new sensors able to transmit the collecteddata directly to the EL at the end ofeach haul. The EL is already arranged to beable to send data by GPRS to a data center,thus the TPs upgrade will allow obtaininga complete data set in near real-time.The new TPs probes will also be able toproduce more reliable pressure and temperaturedata, and to collect salinity and possiblyother oceanographic (e.g., fluorescenceand/or turbidity) data.Another focal point in the FOS applicationis the collaboration of the fishermen.Hence the necessity to deepen the relationshipswith the fishery sector creatingstronger synergies. Interactions betweenthe research community and the fishing industry[15] as well as with the regulatoryauthorities would allow consistent step towardsthe institution of an operational fisheryand oceanographic framework aimed toa better management of the resources.References[1] G. Daskalov. Relating fish recruitment to stock biomass and physical environmentin the Black Sea using generalized additive models. Fishery Research, 41:1–23,1999.[2] R. Hedger, E. Mckenzie, M. Heath, P. Wright, B. Scott, A. Gallego, and J. Andrews.Analysis of the spatial distribution of mature code (Gadus morhua) andhaddock (Melanogrammus aeglefinus) abundance in the North Sea (1980-1999) usinggeneralized additive models,. Fishery Research, 70:17–25, 2004.[3] V. Denis, J. Lejeune, and J.P. Robin. Spatio-temporal analysis of the commercialtrawler data using general additive models: patterns of Loliginid squid abundancein the north-east Atlantic. ICES Journal of Marine Science, 59:633–648, 2002.1894