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Background:In rural China, many natural water bodies and farmlands have been converted into fish farming ponds as an economic developmental strategy. There is still a limited understanding of how the diversity and structure of microbial communities change in nature and become managed fish pond ecosystems.Objective:We aimed to identify the changes of the diversity and structure of microbial community and driving mechanism in pond ecosystems.Methods:The datasets of 16S rRNA amplicon sequencing and the concentrations of N and P fractions were achieved in water samples of pond ecosystems. Bioinformatics analysis was used to analyze the diversity and structure of the microbial communities.Results:Our results indicated that the diversity and structure of the microbial communities in the natural ponds were significantly different from ones in managed fish ponds. The nutrients of N and P and water environmental factors were responsible for 46.3% and 19.5% of the changes in the structure and diversity of the microbial community, respectively.Conclusion:The N and P fractions and water environmental factors influenced the microbial community structure and diversity in pond ecosystems. Fish farming indirectly affected the microbial community by altering the contents of N and P fractions in water bodies of ponds, when a natural pond was converted into a managed fish pond.

Background: The high permeability of Distributed Generation (DG) and the development of DC load represented by electric vehicle Battery Swapping Station (BSS) pose new challenges to the reliable and economic operation of DC distribution system. Methods: In order to improve the wind and solar absorption rate and the reliable operation of DC distribution network and coordinate the interests and demands of BSS and DC distribution company, the upper level takes the abandonment rate and the minimum variance of BSS charging and discharging net load as two objective functions, and the lower level takes the minimum operation cost of DC distribution network and BSS as the objective function. Secondly, this paper proposes a method that combines Genetic Algorithm (GA) with Wind-Driven Optimization algorithm (WDO). CPLEX and hybrid GA-WDO are used to solve the upper and lower models, respectively. Results: Finally, an example shows that the proposed optimization model can reduce the operation cost of DC distribution network with BSS and improve the utilization rate of wind and light, which shows the rationality and effectiveness of the optimization model. Conclusion: In this paper, considering the randomness and uncertainty of wind power generation and photovoltaic power generation, this paper establishes the upper objective function with the minimum abandonment rate and load variance and the lower objective function with the minimum operation cost of DC distribution network and BSS operators.

Over recent decades, Taihu Lake, the third largest freshwater lake in China, has borne the brunt of intensive human activities. Non-point source pollutants and discharges of domestic wastewater are now the main cause of eutrophication. To control non-point source pollution, it is useful to have a good understanding of the spatial and temporal distribution of N (nitrogen). In this study, we applied Export Coefficient Model (ECM) and the Net Anthropogenic Nitrogen Inputs (NANI) method to estimate the N loads in the Taihu Basin at county scale since 1980. We found that N inputs and exports had increased from 6432 and 3170 kg N km−2 yr−1 in 1980 to 9722 and 4582 kg N km−2 yr−1 in 2010, respectively. The 151% increase of N inputs, but 144% increase of riverine N outputs suggested the more N was retained within the Taihu Basin. Both the population density and the urban areas were strongly correlated with N inputs and exports. Approximately 38% of the N inputs were exported in 2010, but only 19% were exported in 1980. This ratio illustrated that human activities, especially urbanization and population growth, have upset N budget in the Taihu Basin. This study supported by empirical models provides a case to demonstrate the N cascade in the Taihu Basin and can also be used to support decision making and to facilitate the development of measures to control N in the future.