In order to provide basic data for biological control of water quality,to improve of fishery potential and economic benefits,we characterized the fish community and measured growth rates of H.molitrix and A.nobilis in Jinhu Reservoir.Making use of mixed gill nets,a systematic fishery investigation was conducted in Janurary,April,July,and October of 2022,respectively.A total of 32 fish species were collected,belonging to 26 genera,8 families and 3 orders.Cypriniformes was the largest order,which accounted for 75.0%.The ecological type analysis revealed that the community was dominated by carnivorous and omnivorous fish.Four dominant fish species were identified based on the index of relative importance,which were H.molitrix,A.nobilis,Xenocypris microlepis and Culter dabryi dabryi.The growth equation of body length and body mass for H.molitrix,they were L_t=74.52×[1-e^{-0.26(t+0.35)}];W_t=6 925.48×[1-e^{-0.26(t+0.35)}]^{2.906 9},respectively,and for A.nobilis were L_t= 68.35×[1-e^{-0.19(t+0.82)}];W_t = 5 669.32×[1-e^{-0.19(t+0.82)}]^{2.973 0},respectively.The highest body mass growth rate for H.molitrix occurred during the age of 1-4,and then decreased gradually,with the growth inflexion points at the age of 3.75.And infection point for A.nobilis was 4.91.As a result,the most appropriate catching age were 4-year-old for H.molitrix and 5-year-old for A.nobilis in order to get the best effect on algal bloom control and economic benefit.The results provided important scientific evidence for rational utilization of H.molitrix and A.nobilis resources and ecological environment restoration in Jinhu Reservoir of Taining,Fujian Province,China.

Dissolved oxygen is an important environmental factor that affects the growth of aquatic organisms and water environment. Accurate prediction of dissolved oxygen is beneficial to the healthy development of aquaculture. This study was based on the water quality data and meteorological data of online buoys SK11 and SK18 in Shuikou reservoir area of Minjiang River in Fujian from January to June, 2022. Then, back propagation(BP) neural network prediction model and MIC-BP neural network measurement model were used for machine learning, and the prediction results are given. At the same time, the prediction results of the two dissolved oxygen prediction models were compared and verified. The results showed that after the identification and screening of MIC (Maximum information coefficient), among the 13 input factors, the factors that had great correlation with dissolved oxygen include pH, water temperature, chlorophyll, electrical conductivity, turbidity, ammonia nitrogen concentration and nitrite nitrogen concentration. The effect of the mixed MIC-BP neural network model was obviously better than that of the independent BP neural network model. After the candidate factors were identified and screened by MIC, the performance of the model could be obviously improved. Compared with the independent BP neural network model, the results showed that the performance of MIC-BP neural network model at SK11 station decreased by 29.29%, RMSE decreased by 60.09%,and NSE increased by 27.63%,respectively. At station SK18, MAE decreased by 17.16%, RMSE decreased by 16.23%, and NSE increased by 12.77%,respectively.