Search

The overall water quality of urban rivers is closely related to the community structure and the physiochemical factors in them. In this study, the bacterial communities and physiochemical factors of the Qiujiang River, an important urban river in Shanghai, were explored. Water samples were collected from nine sites of the Qiujiang River on November 16, 2020. The water quality and bacterial diversity were studied through physicochemical detection, microbial culture and identification, luminescence bacteria method, and 16S rRNA Illumina MiSeq high-throughput sequencing technology. The water pollution of the Qiujiang River was quite serious with three water quality evaluation indexes, including Cd2+, Pb2+, and NH4+-N, exceeding the Class V standard set by the Environmental Quality Standards for Surface Water (China, GB3838-2002), while the luminescent bacteria test indicated low toxicity of nine sampling sites. Through 16S rRNA sequencing, a total of 45 phyla, 124 classes, and 963 genera were identified, in which Proteobacteria, Gammaproteobacteria, and Limnohabitans were the most abundant phylum, class, and genus, respectively. The Spearman correlation heatmap and redundancy analysis showed that the bacterial communities in the Qiujiang River were correlated with pH; the concentrations of K+, and NH4+-N, and the Limnohabitans were significantly correlated with the concentrations of K+, and NH4+-N in the Zhongyuan Road bridge segment. In addition, opportunistic pathogens Enterobacter cloacae complex and Klebsiella pneumoniae in the samples collected in the Zhongyuan Road bridge segment and Huangpu River segment, respectively, were successfully cultured. The Qiujiang River was a heavily polluted urban river. The bacterial community structure and diversity were greatly affected by the physiochemical factors of the Qiujiang River, and it displayed low toxicity while a relatively high infectious risk of intestinal and lung infectious diseases. [ABSTRACT FROM AUTHOR]

Background: Multi-omics technology provides a good tool to analyze the protein toxin composition and search for the potential pathogenic factors of Solenopsis invicta, under the great harm of the accelerated invasion in southern China. Methods: Species collection, functional annotation, toxin screening, and 3D modeling construction of three interested toxins were performed based on the successfully constructed transcriptome and proteome of S. invicta. Results: A total of 33,231 unigenes and 721 proteins were obtained from the constructed transcriptome and proteome, of which 9,842 (29.62%) and 4,844 (14.58%) unigenes, as well as 469 (65.05%) and 71 (99.45%) proteins were annotated against the databases of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, respectively. After comparing with the uniprot toxin database, a total of 316 unigenes and 47 proteins (calglandulin, venom allergen 3, and venom prothrombin activator hopsarin-D, etc.) were successfully screened. Conclusions: The update of annotations at the transcriptome and proteome levels presents a progression in the comprehension of S. invicta in China. We also provide a protein toxin list that could be used for further exploration of toxicity as well as its antagonistic strategy by S. invicta. [ABSTRACT FROM AUTHOR]

Heat waves (HWs) are one of the current topics of scientific research in the context of global warming, as they can have a disastrous impact on both environment and society. Therefore, detailed studies of variations of HWs that assess variability on spatiotemporal scales are becoming increasingly necessary. The main objective of this study is to detect and analyse variation in HWs and potential climate drivers across China based on Köppen climate classifications. Daily observation data (maximum and minimum temperature) from 1961 to 2016 were used in the study to define HWs based on excess heat factors (EHFs). Linear trend analysis, Bayesian change‐point analysis, cross‐wavelet transform method, and Pearson correlation analysis method were adopted to identify the trends, variability and resonance periodicity of EHFs in sub‐regional, and the possible links between EHFs and large‐scale climate patterns, respectively. Results show that there was an overall significantly increasing trend of EHFs over six climatic zones except for HWM in the Polar tundra (ET). The spatiotemporal characteristics of EHFs in mainland China vary considerably. The spatial patterns of the mean annual EHFs are similar to their change trend. The spatial pattern of the number of individual HWs, the number of days that contribute to HWs, and the length of the longest HW in arid (BB), semi‐arid (BS) and cold semi‐humid (DW) areas of study is the west exceeding the east; temperate humid (CF) is contrary to that, with the south exceeding the north in temperate semi‐humid (CW) and ET. In addition, the mean temperature of all heatwaves (HWM) and the peak daily value in the hottest HW appeared in parts of northern DW, CF and BS. Change point first occurs in the northern and then in the southern region across mainland China, excepting HWM. A dominant positive correlation was found for Multivariate ENSO Index (MEI) and Arctic Oscillation Index (AOI) with EHFs, while a dominant negative correlation was detected for Pacific Decadal Oscillation (PDO) and the North Atlantic Oscillation (NAO) across China. A common significant 2–4 year periodical oscillation was detected in the EHFs series at the nationwide scale. Strengthening anti‐cyclone circulation in the Mongolian Plateau, and weakening monsoon flow and speed have contributed to the changes in EHFs across China. [ABSTRACT FROM AUTHOR]

Aeolian desertification is one of the most significant environmental and socio-economic problems, represents a major component of land degradation, and seriously harms the ecological environment, leading to adverse impacts on human society. Monitoring aeolian desertification and identifying the driving factors behind it are crucial for developing prevention and management strategies to combat this issue. The objectives of this study were to monitor the trends of aeolian desertification in Horqin Sandy Land by using time-series MODIS-NDVI remote sensing data for the period of 2000–2013. A dimidiate pixel model was chosen to calculate the Vegetation Coverage Index (VCI), while a unary linear regression analysis was used for a temporal trend analysis of the Aeolian Desertification Index (ADI) and selected climate factors. The Sen's slope estimator and the Mann-Kendall statistical test were used to analyze the spatial trends of the ADI. (1) The temporal trend of ADI showed three stages: reversion during the period of 2000–2005 and 2009–2013, and development during the period of 2005–2009. For the five classes of ADI, the areas of non-aeolian desertified lands (N) showed an increasing trend and the slight (SL), moderate (M), serious (S), and very serious aeolian desertified lands (VS) showed decreasing trends, with the decline in areas of SL and M contributing to the reversion of aeolian desertification. (2) The spatial distribution showed that the VS was mainly distributed in the southwestern portion, and the S was mainly distributed around the VS portion. The SL and M formed a straight line from the southwest to the northeast, bisecting the two areas of S. The N was mainly distributed in the northwestern portion and the eastern edges of the study area. (3) The spatial trends showed that areas of decreasing and significantly decreasing ADI trends occupied 78.44%, while areas with increasing and significantly increasing ADI trends only occupied 21.56% of the study area over the period of 2000–2013, indicating that aeolian desertification in Horqin Sandy Land is decreasing overall and advancing in certain portions. (4) The driving factors of aeolian desertification were analyzed from the perspectives of two groups: climate and anthropogenic factors. We found that the desertification control measures and favorable climate condition have played key roles in the process of desertification reversion; and climate fluctuations, reclamation and livestock pressure have led to the desertification development. The results can provide meaningful information for the prevention and control of aeolian desertification in Horqin Sandy Land. [ABSTRACT FROM AUTHOR]

Waterlogging disasters are one of the most destructive meteorological disasters, which lead to crop yield reduction and cause a great threat to humanity and economic structure. This study presents the methodology and procedure for dynamic risk assessment of waterlogging disasters for maize in Midwest of Jilin Province, China. We took the representative waterlogging disaster years of 1994, 2005, and 2010 as examples, the growth-stage waterlogging index was established to assess the waterlogging disaster hazard by using standard antecedent precipitation index and the relative humidity index. Maize growing data and maize planting area data were combined to assess the waterlogging disaster vulnerability of maize, in which the CERES-Maize model was used to simulate the growth of maize at a daily time step for each grid. Based on the theory of natural disaster risk, the dynamic risk assessment model of waterlogging disaster for maize was built. In this study, the risk indexes were divided into five classes by using an optimal partition method. The grid GIS technology was used to map the spatial distribution of data and the grade of waterlogging disaster risk at a resolution of 5000 × 5000 m. The results show that areas with very low waterlogging disaster risk are mainly located in western and northeastern regions; in contrast, very high and high waterlogging disaster risk levels are mainly located in southern and central regions. Meanwhile, high risk areas at different growth stages gradually spread from the southwestern to the Midwestern and southeastern regions. This study could help the government when they make strategic decisions regarding food security in China, and the method of dynamic waterlogging risk disaster assessment could also be applied for other crops to control and prevent the occurrence and development of waterlogging disasters and reduce their adverse influence. [ABSTRACT FROM AUTHOR]

Climate warming triggers increased frequency and intensity of extreme climate events, and due to disequilibrium precipitation at spatial and temporal scales, droughts or floods may occur frequently. Therefore, it is necessary to assess spatiotemporal variation of precipitation concentration and its potential impact on drought. The study calculated the Concentration Index (CI) and Precipitation Concentration Index (PCI) of 780 stations during 1961–2016 in mainland China, and monthly temperature and precipitation data were adapted to calculate the Standardized Precipitation Evapotranspiration Index (SPEI). Changepoint method was used to determine the turn and change points of CI and PCI, and Sen's slope method was used to calculate the trend before and after the year of turn points (YTPs) and the overall trend of drought was also analyzed. The Pearson correlation method was employed to evaluate the correlation between CI/PCI and SPEI to explore potential influence of precipitation concentration on drought from qualitative and quantitative perspectives. The results demonstrate that the annual CI ranges from 0.56 to 0.75, and the 25% rainiest days account for 68.35%–85.92% of total precipitation. The summer CI was the largest and the winter CI was the smallest among all seasons. 9.74% and 9.62% of stations were observed with change points for annual CI and PCI, respectively. Meanwhile, 80.13% and 69.36% of stations for annual CI and PCI showed a decreasing trend, respectively, and 73.21% of stations exhibited a trend of drought. Annual SPEI was positively correlated with CI and PCI, accounting for 88.59% and 70.77% of stations in mainland China, respectively, indicating that the variation of drought was more sensitive to CI than to PCI. The results can provide a basis for decision-making in water resources and drought risk management in China. • The precipitation and drought characteristics were systematically investigated based on CI, PCI and SPEI. • The Sen's slope and change point method were applied to the research. • CI and PCI had different impacts on annual drought of Sub-basin across mainland China. [ABSTRACT FROM AUTHOR]

• Introducing the DPSIRM model to establish an evaluation indicator system. • Utilize the Extension Cloud Model to assess the health status of the water cycle. • Introduced the Degree of Obstacle Model to analyze the main obstacle factors in 11 provinces and cities. • Utilized the ARIMA model to forecast the future health of water circulation. • Put forward relevant suggestions according to the evaluation results. The regional water cycle reflects the dual processes of nature and society. A healthy and benign water cycle is a fundamental guarantee for achieving regional sustainable development.The Yangtze River Economic Belt, as a densely populated urban cluster with abundant water resources in China, plays a crucial role in promoting the sustainable development of Chinese urban clusters. It is of significant importance to optimize the water cycle health of the Yangtze River Economic Belt and explore its primary obstacles.This study integrates the natural-social attributes of the water cycle and selects 25 evaluation indicators from six dimensions: Drivers (D), Pressures (P), States (S), Impacts (I), Responses (R), and Management (M), to construct the water cycle evaluation system for the Yangtze River Economic Belt.Combining Analytic Hierarchy Process (AHP), Decision-Making Trial and Evaluation Laboratory (DEMATEL), and the Criteria Importance Through Intercriteria Correlation (CRITIC) method, the comprehensive weights of subjective and objective factors are obtained based on the principle of minimum relative entropy.Based on this, an Extended Cloud Model is constructed to evaluate the water cycle health status of the region from 2012 to 2022.Furthermore, the Obstacle Degree Model is introduced to identify the primary obstacles affecting the water cycle health in the region. Finally, the ARIMA model is applied to forecast the water cycle health status in the region from 2023 to 2030.The results indicate that the comprehensive water cycle health level in the region improved gradually from initially sub-pathological to sub-healthy status from 2012 to 2022.Per capita GDP, industrial water consumption per ten thousand yuan of industrial value added, per capita water consumption, forest coverage rate, sediment transport module, proportion of environmental protection investment to GDP, and proportion of water resources management investment to GDP are the primary obstacles affecting the improvement of health in this region.The forecast indicates that the overall water cycle health status in the region will remain at a sub-healthy level from 2023 to 2030.The research results can provide a scientific reference for further promoting the high-quality development of the Yangtze River Economic Belt, better supporting and serving China's modernization, and providing scientific reference basis. [ABSTRACT FROM AUTHOR]

Foxtail millet (Setaria italica) is an important grain crop that is grown in arid regions. Here we sequenced 916 diverse foxtail millet varieties, identified 2.58 million SNPs and used 0.8 million common SNPs to construct a haplotype map of the foxtail millet genome. We classified the foxtail millet varieties into two divergent groups that are strongly correlated with early and late flowering times. We phenotyped the 916 varieties under five different environments and identified 512 loci associated with 47 agronomic traits by genome-wide association studies. We performed a de novo assembly of deeply sequenced genomes of a Setaria viridis accession (the wild progenitor of S. italica) and an S. italica variety and identified complex interspecies and intraspecies variants. We also identified 36 selective sweeps that seem to have occurred during modern breeding. This study provides fundamental resources for genetics research and genetic improvement in foxtail millet.

The contamination levels of 10 main kinds of foodstuffs in 11 provinces and cities were monitored by the national food contamination monitoring system from 2000-2001. About 45 thousand data were obtained in strict quality control. The data indicated that the contamination level of lead was increased in 10 years in meat, eggs, milk-based products especially in preserved eggs, but the contamination levels of arsenic, cadmium and hydrargyrum were not serious by adopting the national standards. Organochlorine pesticides residues (666, DDT) maintained downtrend and organophosphorus pesticides residues met the national associated criteria except methyl parathion in cereals.