Monitoring bioaccumulation and toxic effects of hexachlorobenzene using the polyurethane foam unit method in the microbial communities of the Fuhe River, Wuhan

Hexachlorobenzene (HCB) is a chlorinated aromatic hydrocarbon that was widely used for seed dressing in prevention of fungal growth on crops, and also as a component of fireworks, ammunition, and synthetic rubbers. Because of its resistance to degradation and mobility, HCB is widely distributed throughout the environment and is accumulated through food chains in different ecosystems. In this study, a preliminary investigation was carried out on the bioaccumulation and the toxic effects of HCB in the microbial (protozoan in particular) communities in the Fuhe River, Wuhan, a water body receiving industrial wastewaters containing HCB and other pollutants, using the standardized polyurethane foam units (PFU) method. Field samples were taken from eight stations established along the Fuhe River in January and August 2006. The concentration ratios of HCB in microbial communities and in water were 9.66-18.64, and the microbial communities accumulated 13.29-56.88 mu g/L of HCB in January and 0.82-10.25 mu g/L HCB in August. Correlation analysis showed a negative correlation between the HCB contents in the microbial assemblage, and the number of species and the diversity index of the protozoan communities. This study demonstrated the applicability of the PFU method in monitoring the effects of HCB on the level of microbial communities.

Microsatellite diversity and population genetic structure of redfin culter (Culter erythropterus) in fragmented lakes of the Yangtze River

Redfin culter (Culter erythropterus) is a small lethic freshwater fish and widely distributed in the adjacent lakes of the Yangtze River of China. Five microsatellite loci were applied to investigate the genetic variation and population structure of redfin culter from seven lakes in the middle-and-lower reaches of the Yangtze River. The gene diversity was high among the populations (H > 0.9), the average number of alleles among seven populations was low with a range from 2.00 to 3.87. The mean observed (H-O) and expected (H-E) heterozygosity ranged from 0.111 to 0.419 and from 0.162 to 0.750, respectively. Significant deviations from Hardy-Weinberg Equilibrium expectation were found in 50% of the total locus-population combination tests in which heterozygote deficits were apparent. The analysis of molecular variance (AMOVA) indicated that the percentage of variance among and within these populations were 6.18 and 93.82, respectively. The Fst values (0.062, P < 0.001) among studied populations indicated that there were significant genetic differentiations among redfin culture populations from the scattered lakes with different connections to the Yangtze River. These results are useful for the evaluation and conservation of small freshwater fishes. The factors that may be involved in low intra-population polymorphism and the pattern of the population genetic structure of redfin culter from the Yangtze River were discussed.

Using the moving window incorporated neural network to forecast the population behavior of Nostocales spp. in the River Darling, Australia

The paper demonstrates the nonstationarity of algal population behaviors by analyzing the historical populations of Nostocales spp. in the River Darling, Australia. Freshwater ecosystems are more likely to be nonstationary, instead of stationary. Nonstationarity implies that only the near past behaviors could forecast the near future for the system. However, nonstionarity was not considered seriously in previous research efforts for modeling and predicting algal population behaviors. Therefore the moving window technique was incorporated with radial basis function neural network (RBFNN) approach to deal with nonstationarity when modeling and forecasting the population behaviors of Nostocales spp. in the River Darling. The results showed that the RBFNN model could predict the timing and magnitude of algal blooms of Nostocales spp. with high accuracy. Moreover, a combined model based on individual RBFNN models was implemented, which showed superiority over the individual RBFNN models. Hence, the combined model was recommended for the modeling and forecasting of the phytoplankton populations, especially for the forecasting.