Prediction Model of Jellyfish Blooms based on Sea Surface Temperature and Salinity and Other Water Qualities
Laura Moreno-Patricio(1), Cristina Martin-Puig(1) and Laia Romero(1)
(1) Starlab SL Barcelona, Cami de l'Observatori s/n, 08035 barcelona, Spain
The problem of jellyfish massive population near the coasts of the Mediterranean Sea seams to have increased during the last years. This jellyfish population can generate a social alert with bad repercussions on costal related activities. Alarmed by these repeating jellyfish events, the Spanish Environmental authorities financed last year the first known national study of jellyfish habitat. That study resulted into a monitoring network and warning chain for the Spanish coast, with the collaboration of regional institutions, ONGs and trained observers to survey the coast.
Following this first effort at national level, Starlab, with the economical support of the regional Catalan Government (CIDEM), has started an eighteen months project named DASO aiming to predict the probability of occurrence and expected concentration of jellyfish as a function of, mainly, sea surface temperature and salinity. This project will result in a pioneer operational service in Spain and it counts with the collaboration of the Catalan Agency of Waters (ACA) who will contribute with the provision of in situ data for the validation of the algorithms to be developed.
Although salinity and temperature are known to be the more determinant factors influencing the habitat of jellyfish (Decker et al. ), other parameters (such as chlorophyll concentration and total suspended matter (TSM)) are suspected to have an influence, and therefore will be taken into account in this study. The jellyfish habitat models based on all these physical parameters will provide information on likelihood thresholds of each of them for the probability of occurrence and the expected concentration of jellyfish.
The occurrence model is based on a logistic regression analysis which applies maximum likelihood to quantitative relationship among the selected parameters. The jellyfish concentration will be analysed empirically with the support of the ACA in situ measurements. Particularly, temperature versus salinity table will be provided and it will gather the jellyfish concentrations measured by ACA for each threshold during the last few years.
Sea Surface Temperature (SST) data used in this project will be acquired by the Advanced Along-Track Scanning Radiometer (AATSR) on board ENVISAT, which is able to acquire SST with an accuracy of 0.3 Cº. Sea Surface Salinity (SSS) data will be simulated using the MERCATOR salinity model.
The Chlorophyll and the TSM will be acquired by processing MERIS data with known techniques proposed by Ruddick et Al. .
Validation activities will consist of two subsequent phases. First, the SST, the Chlorophyll and the TSM will be verified with in situ data provided by ACA. Second, the model for jellyfish occurrence and concentration will be validated with a field campaign, foreseen tentatively for summer 2009, with the collaboration of ACA.
In this paper we present the DASO project and the progress to date. The success of DASO will have strong impacts on the capacity of monitoring and managing the ecosystem of the Catalan Coast, of the activities related to this environment and of preventing possible negative impacts on its related economy. Of course, not only Catalan coasts will benefit from this service, but it could be applicable to other coasts where enough historical in situ data is available.
 M. B. Decker et Al. ,Predicting the distribution of the scyphomedusa Chrysaora quinquecirrha in Chesapeake Bay, Mar Ecol Prog Vol. 329: 99–113, 2007 Jan 2007.
 K. Ruddick , Y. Park and B. Nechad. MERIS imagery of Belgian Coastal Waters: Mapping Suspended Matter and Chlorophyll-a, MERIS Users workshop held in Frascati, 10-13 November 2003
Keywords: ESA European
Space Agency - Agence spatiale europeenne,
observation de la terre, earth observation,
satellite remote sensing,
teledetection, geophysique, altimetrie, radar,
chimique atmospherique, geophysics, altimetry, radar,