To investigate the effect of chiral pesticide fenvalerate (FV) on the micro-ecological environment of aquaculture pond sediment, we used an indoor static experiment to observe the effects of FV added at different concentrations with different chiral isomers on the changes in the sediment bacterial community. The 16S rDNA high-throughput sequencing technique was used to conduct sequencing and analysis of the bacterial community structure as well as changes in aquaculture pond sediments after 4 weeks of cultivation. The results showed that the microbial alpha diversity indices (Sobs and Shannon indices) of the treated groups were significantly lower than those of the control group after 4 weeks (P < 0.05), and the values in the high-concentration group were significantly lower than those of the low-concentration group (P < 0.05). In terms of bacterial group composition, the proportion of abundance of Proteobacteria and Acidobacteria in the treated groups were greater than in the control group after 4 weeks, while the proportion of abundance of Bacteroidetes and Verrucomicrobia were lower. In the high-concentration FV treatment group, the proportion of abundance of Bacteroidetes, Acidobacteria, Chloroflexi, Nitrospinae, unclassified_k_norank, Ignavibacteriae, and Nitrospirae were significantly different from those of the other groups (P < 0.05). Principal coordinate analysis (PCoA) and ANONISIM/Adonis analysis showed that the cis-enantiomer had a stronger effect on the bacterial community as the concentration of FV increased. In addition, the linear discriminant analysis effect size (LEfSe) and linear discriminant analysis (LDA) results revealed differences in the level of enrichment of bacterial groups caused by FV at different concentrations and isomer levels. Collectively, this study showed that FV residue has a pronounced effect on bacterial communities in sediment, which becomes more significant with increasing exposure concentration. The effects of the cis- and trans-enantiomers of FV on the sediment environment are different; the cis-enantiomer has a stronger effect on the bacterial community.
The international community is paying more attention to climate change because a consensus has been reached that climate change has an adverse effect not only on the environment but also on agriculture. Therefore, in this study, present and future climate datasets (obtained from general circulation models) including atmospheric carbon concentration were used to assess the impact of climate change on grain production for an important base of China (Northeast). An empirical model has been developed using climate and other additional variables (effective irrigation area, fertilizer, and labor force) to assess the effect of climate change on grain production. The results revealed that maximum temperature is a key climate determinant in grain production of the study area. Atmospheric carbon concentration showed a significant impact on grain outputs in most of the cases. During the analysis, it was observed that precipitation displayed a declining trend while an effective irrigation area showed positive non-significant contribution to grain production. Analysis based on different representative concentration pathways exhibited that maximum temperature may contribute negatively to grain production in the future. Overall, the analysis showed that climate change has a significant contribution to grain production. In conclusion, the implications for future research and policymakers have been addressed. Particularly, the importance of considering regional differences in adaptation planning in agricultural regions was also considered.
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