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.

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 relativ...