Determination of biodiversity and spatial and temporal distribution pattern of demersal fishes in the Oman Sea

In this project, have been studied to determine the appropriate model to spatial, temporal and diversity of demersal fishes in the Sea of Oman, including Trichiuridae, Nemipteridae, Haemulidae, Arridae, Synodontidae, Batoidfishes, Carangidae, Scianidae, Carchariniformes and Serranidae. This research became operational from catch data during 2003 to 2013 (in 2007, due to the lack of ship failed). Processing and calculations was evaluated by using the software Excel, SPSS, Arc GIS and table curve 3D highest biomass and abundance was showed in strata A and C and 10-30 m depth layers was showed the best condition biomass. In other words, highest biomass was showed in the eastern region in the Oman Sea than the central and western regions. Batoidfishes and Trichiuridae had the highest biomass .Depth factors was showed a significant correlation with the biomass. Scianidae, Serranidae and Haemulidae were showed a large decline. Synodontidae was showed a very large increase. The largest of Shannon index belong to central and western region of the Oman Sea. The highest Shannon index was showed 10-20 and 50-100 m, respectively. The Distribution maps based on the biomass was analyzed by using Arc GIS software. So that were identified in the first time in a ten-year period and carefully catch stations any economic of aquatic group. In conclusion, the depth can be found in the pattern of distribution, abundance and diversity of fish from away the beach so that follow specific pattern.

The study of correlation between sea surface temperature (SST) by using the NOAA-AVHRR data and compare this data with temperature measurement in the Caspian Sea

The changes in time and location of surface temperature from a water body has an important effect on climate activities, marine biology, sea currents, salinity and other characteristics of the seas and lakes water. Traditional measurement of temperature is costly and time consumer due to its dispersion and instability. In recent years the use of satellite technology and remote sensing sciences for data acquiring and parameter and lysis of climatology and oceanography is well developed. In this research we used the NOAA’s Satellite images from its AVHRR system to compare the field surface temperature data with the satellite images information. Ten satellite images were used in this project. These images were calibrated with the field data at the exact time of satellite pass above the area. The result was a significant relation between surface temperatures from satellite data with the field work. As the relative error less than %40 between these two data is acceptable, therefore in our observation the maximum error is %21.2 that can be considered it as acceptable. In all stations the result of satellite measurements is usually less than field data that cores ponds with the global result too. As this sea has a vast latitude, therefore the different in the temperature is natural. But we know this factor is not the only cause for surface currents. The information of all satellites were images extracted by ERDAS software, and the “Surfer” software is used to plot the isotherm lines.