Ophiopholis mirabilis is a common species with a high population density on the western coasts of the northern Pacifi c Ocean.The number of O.mirabilis has been increasing recently in the scallop aquaculture zone(the Zhangzi Island area,northern Yellow Sea)in China.To explore the mechanism of its population variation,the reproductive cycle of O.mirabilis was investigated in this area(39°04′N;122°51′E)from February 2017 through January 2018 and determined by the monthly gonad index(GI),histological examinations of the gonads and the oocyte size-frequency distribution.O.mirabilis had a clear annual reproductive cycle that was synchronous between males and females.Sea temperature and food availability played important roles in O.mirabilis reproduction.The GI value was less reliable for determining reproductive activity in O.mirabilis because the nutritive tissues within the gonads may be utilized to synthesize gametes,leading to a decrease in GI during maturation.The histological results also show that abundant nutritive phagocytes were present in the gonads of O.mirabilis,which,together with the germ cells,aff ected the weight of the gonads.In addition,the mature oocytes of O.mirabilis were relatively small(75–150μm),indicating that the larval development was planktotrophic.This study provided insights into the reproductive patterns and biology of O.mirabilis and is an essential basis for the quantity control of this species in aquaculture areas. 相似文献
Mineral potential prediction is a process of establishing a statistical model that describes the relationship between evidence variables and mineral occurrences. In this study, evidence variables were constructed from geological, remote sensing, and geochemical data collected from the Lalingzaohuo district, Qinghai Province, China. Based on these evidence variables, a conjugate gradient logistic regression (CG-LR) model was established to predict exploration targets in the study area. The receiver operating characteristic (ROC) and prediction–area (P-A) curves were used to evaluate the effectiveness of the CG-LR model in mineral potential mapping. The difference between the vertical and horizontal coordinates of each point on the ROC curve was used to determine the optimal threshold for classifying the exploration targets. The optimal threshold corresponds to the point on the ROC curve where the difference between the vertical coordinate and the horizontal coordinate is the largest. In exploration target prediction in the study area, the CG algorithm was used to optimize iteratively the LR coefficients, and the prediction effectiveness was tested for different epochs. With increasing iterations, the prediction performance of the model becomes increasingly better. After 60 iterations, the LR model becomes stable and has the best performance in exploration target prediction. At this point, the exploration targets predicted by the CG-LR model occupy 14.39% of the study area and contain 93% of the known mineral deposits. The exploration targets predicted by the model are consistent with the metallogenic geological characteristics of the study area. Therefore, the CG-LR model can effectively integrate geological, remote sensing, and geochemical data for the study area to predict targets for mineral exploration.
Natural Resources Research - Some industrial activities, such as underground mining, hydraulic fracturing (HF), can cause microearthquakes and even damaging earthquakes. In recent years, with the... 相似文献
