Bohai Bay, a representative semi-enclosed bay of China, has been severely impacted in recent decades by rapid human development. Although the mantis shrimp Oratosquilla oratoria plays an important role in the Bohai Bay ecosystem and fishery, its feeding ecology and the impact of habitat changes on its feeding habits are poorly known. In this study, we sought to identify its feeding strategy through the separation of stomach contents, and to describe its trophic ecology during maturation in the Tianjin coastal zone of Bohai Bay by the DNA barcoding method using a fragment (about 690 bp) of the mitochondrial cytochrome oxidase I (CO I) gene. A total of 594 specimens were collected from March to July 2018, and 347 (58.42%) stomachs were found to have food remains. More than half of the O. oratoria individuals had poor feeding activity, and the degree of feeding of females was higher than that of males, but there was no significant difference in the visual fullness index and the fullness weight index (FWI) between sexes for each month. In addition, the feeding activity of O. oratoria was consistent across the months, suggesting in artificial breeding programs it is not worried too much about the accessional diet supplied to the female bloodstocks except maintaining their normal food. A total of 167 retrieved prey items yielded 187 readable sequences; 86.63% of these sequences could be assigned to the species level. Consequently, 25 different prey taxa covering all readable sequences were identified, showing O. oratoria is a generalist predator. In terms of percent composition by frequency of occurrences (%N), crustaceans and fishes accounted for the same and highest percentage (35.83%) in the mantis shrimp diet, followed by mollusks (24.59%) and the remaining marine organisms (3.73%) including Polychaeta (2.67%), Sagittoidea (0.53%), and Chromadorea (0.53%). The result shows the benthic fish Oxudercidae (family) appears to be an especially important food supply for O. oratoria during maturation. The degree of cannibalism decreased with an increase in diet species and the frequencies of cannibalism in this study was noticeably higher than that in previous studies, suggesting that cannibalism may be a significant feeding strategy in the mantis shrimp O. oratoria in the Tianjin coastal zone of Bohai Bay, and because of the frequently cannibalistic behavior, the high stocking density of broodstocks should be avoided. 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.
