Summer distribution of fish larvae in northern Aegean Sea

Larval fish and hydrographic data were collected in Kavala Gulf (northern Aegean Sea) across a fine scale grid of 17 stations in two surveys, carried out in the beginning of July 2002 and 2003. Despite the different taxonomic resolution and excluding the unidentified larvae, 22 taxa were caught in 2002 and 27 in 2003. Seventeen taxa were present in both years' collections. A total of 833 larvae were collected during the two samplings. The adults of several larvae caught, although sometimes at very low concentrations, are species with high commercial value or represent a major proportion of the captured production of the northern Aegean Sea. The larvae of European anchovy (Engraulis encrasicolus) were most abundant in both years followed by the brown comber (Serranus hepatus), the gobies (Gobius sp.) and, only for 2003, round sardinella (Sardinella aurita). Maximum anchovy larval densities reached 4145/10 m(2) and 13852/10 m(2) in the 2002 and 2003 surveys, respectively. The spatial extent Of anchovy larvae was also high as they were collected at 12 stations in 2002 and at 15 in 2003. Besides water circulation, the spatial distribution of fish larvae was largely influenced by temperature, salinity and dissolved oxygen

CHLfuzzy: a spreadsheet tool for the fuzzy modeling of chlorophyll concentrations in coastal lagoons

CHLFuzzy is a user-friendly, flexible, multiple-input single-output Takagi-Sugeno fuzzy rule based model developed in a MS-Excel (R) spreadsheet environment. The model receives a raw dataset consisting of four predictor variables, e.g., water temperature, dissolved oxygen content, dissolved inorganic nitrogen concentration, and solar radiation levels. It then defines fuzzy sets according to a collection of fuzzy membership functions, allowing for the establishment of fuzzy 'if-then' rules, and predicts chlorophyll-a concentrations, which highly compare to the measured ones. The performance of the model was tested against the Adaptive Neural Fuzzy Inference System (ANFIS), showing satisfactory results. An extensive dataset of environmental observations in Vassova Lagoon (Northern Greece), during the years 2001-2002, was used to train the model and an independent dataset collected during 2004 was used to validate CHLFuzzy and ANFIS models. Although both models showed a similar performance on the training dataset, with quite satisfactory agreement between observed and modeled chlorophyll-a values, the best results were obtained using the CHLfuzzy model. Similarly, the CHLfuzzy model depicted a fairly good ability to hindcast chlorophyll-a concentrations for the verification dataset, thus improving ANFIS model forecasts. Overall results suggest that CHLfuzzy can potentially be used as a lagoon water quality forecasting tool requiring limited computational cost