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The distribution and abundance of emperor fishes (Lethrinidae) along the Arabian Sea  coast of Oman were analysed from commercial catch-per-unit-effort data for the periods 1996–2004 and 2005,  respectively. Two-stage generalized additive models (GAM) were used to detect trends in abundance  relative to environmental variables. The GAM that included month (positive in August and October),  sea surface temperature (SST; positive at 25–27˚C) and longitude (positive between 57°50’ E–58°50’  E) explained the highly variable distribution and abundance patterns best. ArcGIS-9 was used as an  auxiliary to visualize seasonal trends that could not be seen from the statistical GAM analysis. From the spatial grids, it appeared that abundance increased with warmer SST encountered in  August/September to January but was lower during the SW monsoon in June–August when the SST  decreased below 25°C. The results emanating from the analysis of the 2005 data confirmed those from  the original 1996–2004 data, suggesting that predictions from the original models were relatively  robust. The synthesis of methods used in this study is a major step towards developing  statistically robust and spatially explicit methods for predicting fisheries performance.

journal of agricultural and marine sciences

Predicting the Distribution and Abundance of Emperor Fishes (Lethrinus spp.) in the Arabian Sea Using Two-Stage Generalized Additive Models and a Geographic Information System