جستجوی مقالات مرتبط با کلیدواژه "saurida tumbil" در نشریات گروه "علوم پایه"

This study investigated the age, population dynamics and some biological characteristics of Saurida tumbil inhabiting Hormozgan province from Kolahi to Dargahan. This study was based on the data obtained from commercial catches of shrimp trawl vessels in fishing seasons of 2019. The results of this study showed that the highest correlation was related to total length and fork length relationship with estimated coefficient of correlation (r2= 0.9988). Also the results showed a significantly correlated length-weight relationship with estimated coefficient of correlation (r= 0.9373). The value of the slope (b) was significantly different from 3 which shows a negative allometric growth for this species. The estimated age (based on vertebrae age reading method) variability were 1 to 7 years. The fish with age 2 showed the highest frequency among the age groups. Also the Bertalanffy growth equation for this species in the study area was estimated as Lt=50.02 (l-exp(-0.28 (t+0.27)). The mortality coefficients were 2.66, 0.67 and 1.99 for the total mortality "Z", natural mortality "M" and fishing mortality "F", respectively. Also, the estimated exploitation rate for this species was 0.75 which shows that this species is in overexploitation phase. Hence, to improve the present stock status in this area and sustainable capture of S. tumbil, it is recommended to decrease fishing effort and improve bottom trawl for reducing bycatch issues.

In conformity to study and predict the distribution pattern of lizardfish (Saurida tumbil) in the northern Persian Gulf (Hormuzgan province waters), the catch data of 2008 were collected and analyzed. The primary statistical analysis were done using Excel and then distribution maps were provided using GIS–software based on Catch Per Unit of Area index (CPUA). Then to forecast the distribution pattern, the maps of different physical and chemical parameters of sea water consist of temperature, turbidity, salinity, sigma T, oxygen, pH, chlorophyll a, electrical conductivity, sound speed, depth, distance from coast, geographical position and time of towing were prepared and were used as independent value to be assessed with CPUA of lizardfish as dependent value. These maps were used as input of Artificial Neural Networks (ANNs) software of which 60% of data for training, 20% for testing and 20% for validation were applied to prepare the best ANN model. With applying this model on catch and CPUA data, the distribution pattern with emphasize on fishing ground can be predicted for further fisheries management and leading the fishing activities to be concentrated in fishing grounds.