Assessment of benthic ecological status and heavy metal contamination in an estuarine intertidal mudflat in the Northern Bohai Sea.

Evaluating the ecological quality and pollution status of coastal mudflats is crucial for environmental protection and management, particularly when these areas serve as major shellfish production hotspots. In this study, we assessed the benthic ecological quality and heavy metals pollution in Geligang, located in the Northern Bohai Sea using the macrobenthos diversity index and the heavy metal pollution index. The Shannon-Wiener index (H'), AZTI marine biotic index (AMBI), multivariate AMBI (M-AMBI) showed that the benthic ecological quality in Geligang is either good or high. The potential ecological risk index and geoaccumulation index highlighted that cadmium (Cd) and mercury (Hg) as the primary heavy metal pollutants in Geligang. Surprisingly, the biomass of the two dominant species other than these indices serve as reliable indicators of heavy metal pollution. This suggests that the biomass of Mactra veneriformis and Potamocorbula laevis could be used to assess heavy metal pollution levels in Geligang.

The effect of total alkalinity on growth performance and calcification in juvenile Pacific abalone Haliotis discus hannai.

A 45-day trial was conducted to study the effect of seawater total alkalinity (TA) level up- and downregulation on the growth performance and calcification of Haliotis discus hannai Ino, while seawater pH was maintained at pHNBS = 8.1. Although seawater was not acidified, the results showed that TA downregulation caused a significant reduction (P < 0.05) in the somatic tissue growth of juvenile abalone, while TA upregulation significantly increased growth performance (P < 0.05). Similar to the impacts of pH reduction, TA downregulation also induces a decline in CO2 buffering capacity, which may be the reason why somatic tissue growth was reduced, as lowered CO2 buffering capacity was reported to shift the acid-base balancing of abalone. Parts of the periostracum layer weremissing and exposed the inner shell layers of the individuals from the TA-downregulated group. Scanning electron microscopy (SEM) results showed calcium carbonate densely deposited onto the inner shell in the control and TA-upregulated groups, while sparsely deposited calcium carbonate was observed in the TA-downregulated group. The C: N ratio in the shell of individuals from the TA-downregulated group was significantly lower than that of the other two groups, indicating that less inorganic carbon was added to the shell. As a result, abalone grew lighter and thinner shells in TA-downregulated seawater. Although seawater was not acidified, TA downregulation also caused a reduction in the calcium carbonate saturation state (Ω), which induced the erosion of the surface shell and the interruption of calcium carbonate generation. In conclusion, although seawater pH remained at ambient levels, the lowered CO2 buffering capacity and Ω induced by seawater TA downregulation also showed a detrimental effect on the growth and calcification of Pacific abalone. The impact of ocean acidification on the growth of abalone should not be assessed using only seawater pH and/or pCO2 but rather taking into account all of carbonate chemistry, particularly the CO2 buffering capacity. Abalone cultivation is suggested to be carried out in seawater with a higher level of CO2 buffering capacity and Ω, which can be achieved through integrated culture with seaweed or increasing the seawater TA level.

Quantitative Proteomics Reveal the Inherent Antibiotic Resistance Mechanism against Norfloxacin Resistance in Aeromonas hydrophila.

Recently, the prevalence of Aeromonas hydrophila antibiotic-resistant strains has been reported in aquaculture, but its intrinsic antibiotic resistance mechanisms are largely unknown. In the present study, a label-free proteomics technology was used to compare the differential protein abundances in response to norfloxacin (NOR) stress in A. hydrophila. The results showed that there were 186 proteins decreasing and 220 proteins increasing abundances in response to NOR stress. Bioinformatics analysis showed that the differentially expressed proteins were enriched in several biological processes, such as sulfur metabolism and homologous recombination. Furthermore, the antibiotic sensitivity assays showed that the deletion of AHA_0904, cirA, and cysI significantly decreased the resistance against NOR, whereas ΔAHA_1239, ΔcysA, ΔcysD, and ΔcysN significantly increased the resistance against NOR. Our results provide insights into NOR resistance mechanisms and indicate that AHA_0904, cirA, AHA_1239, and sulfur metabolism may play important roles in NOR resistance in A. hydrophila.

A new hybrid prediction model of air quality index based on secondary decomposition and improved kernel extreme learning machine.

Air quality index (AQI) prediction is important to control air pollution. To improve its accuracy, a new hybrid prediction model of AQI based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), multivariate multiscale dispersion entropy (mvMDE), variational mode decomposition optimized by bald eagle search (BES) algorithm (BVMD) and kernel extreme learning machine optimized by rat swarm optimizer (RSO) algorithm (RSO-KELM), named CEEMDAN-mvMDE-BVMD-RSO-KELM, is proposed. Firstly, AQI series is decomposed by CEEMDAN to obtain multiple intrinsic mode function (IMF) components, and each IMF component's complexity is calculated by mvMDE. Secondly, VMD optimized by BES algorithm, named BVMD, is proposed to solve the problem of choosing the decomposition level K and penalty factor α of VMD, and BVMD is used to perform the secondary decomposition of high complexity components. Thirdly, the penalty coefficient and kernel parameter of KELM optimized by RSO algorithm, named RSO-KELM, is proposed, and all IMF components are predicted by RSO-KELM. Finally, the final prediction results are obtained by reconstructing the prediction results of all IMF components. The objective of this study is to propose a new hybrid prediction model of AQI based on secondary decomposition and improved KELM. Taking Shanghai, Beijing and Xi'an as examples, the results show that compared with the comparison models, the proposed model has the highest prediction accuracy.