Thallium (Tl) is a trace element with extreme toxicity. Widespread Tl pollution in riverine systems, mainly due to escalating mining and smelting activities of Tl-bearing sulfide minerals, has attracted increasing attention. Insights into the function of the microbial communities with advanced characterization tools are critical for understanding the biogeochemical cycle of Tl. Herein, microbial communities and their adaptive evolution strategies in river sediments from a representative Tl-bearing pyrite mine area in southern China were profiled via 16S rRNA gene sequence analysis and shotgun metagenomic analysis. In total, 64 phyla and 778 genera of microorganisms were observed in the studied sediments. The results showed that pH, Tl, Pb, Zn and total organic carbon (TOC) had a significant influence on microbial community structure. Some important reductive microorganisms (such as Erysipelothrix, Geobacter, desulfatiferula, desulfatihabadium and fusibacter) were involved in the biogeochemical cycle of Tl. The ruv, rec, ars and other resistance genes enhanced the tolerance of microorganisms to Tl. The study suggested that relevant C, N and S cycle genes were the main metabolic paths of microorganisms surviving in the high Tl-polluted environment. The findings were critical for establishment, operation and regulation in the microbial treatment of Tl containing or related wastewater.Check dams are considered to be one of the most effective measures for conservation of the soil and water resources. However, identifying the most suitable sites for the installation of check dams remain quite demanding. This research investigates and compares five machine learning algorithms (MLAs) - boosted regression trees (BRT), multivariate adaptive regression spline (MARS), mixture discriminant analysis (MDA), random forest (RF), and support vector machine (SVM) - for generating check-dam site-suitability maps (CDSSMs) and assessing them in Firuzkuh County, Iran. First, the locations of 475 existing check dams were monitored, registered, and divided into calibration (70%) and testing datasets (30%) for training and validation of the models. Fourteen check-dam conditioning factors (CDCFs) were selected and checked for multicollinearity. The relative importance of the CDCFs assessed using the elastic net (ENET) algorithm. Results demonstrated that distance from river (DFR) and drainage density (DD) to be the most significant factors for mapping the suitable sites for the erection of check dams. This research revealed that all of five MLAs had excellent accuracy for predicting the check-dam site-suitability with high AUC values RF (0.966), SVM (0.878), MARS (0.878), MDA (0.844), and BRT (0.843). The most accurate model (RF) showed that 16.95%, 35.55%, 31.08%, and 16.42% of study area comes under low, moderate, high, and very high suitability classes. The outcome achieved by this research will be helpful to sustainability planners and managers in constructing check dams at suitable sites for better conservation of soil and water resources.Aquatic ecosystems are used for extensive rice-shrimp culture where the available water alternates seasonally between fresh and saline. Poor water quality has been implicated as a risk factor for shrimp survival; however, links between shrimp, water quality and their main food source, the natural aquatic biota inhabiting these ponds, are less well understood. We examined the aquatic biota and water quality of three ponds over an entire year in the Mekong Delta, Vietnam, where the growing season for the marine shrimp Penaeus monodon has been extended into the wet season, when waters freshen. The survival (30-41%) and total areal biomass (350-531 kg ha-1) of shrimp was constrained by poor water quality, with water temperatures, salinity and dissolved oxygen concentrations falling outside known optimal ranges for several weeks. Declines in dissolved oxygen concentration were matched by declines in both shrimp growth rates and lipid content, the latter being indicative of nutritional condition. Furthermore, as the dry season transitioned into the wet, shifts in the taxonomic composition of phytoplankton and zooplankton were accompanied by declines in the biomass of benthic algae, an important basal food source in these systems. Densities of the benthic invertebrates directly consumed by shrimp also varied substantially throughout the year. Overall, our findings suggest that the survival, condition and growth of shrimp in extensive rice-shrimp ecosystems will be constrained when poor water quality and alternating high and low salinity negatively affect the physiology, growth and composition of the natural aquatic biota. Changes in management practices, such as restricting shrimp inhabiting ponds to the dry season, may help to address these issues and improve the sustainable productivity and overall condition of these important aquatic ecosystems.Land use and cover change is an important concept in the study of ecosystem services, especially in ecologically fragile areas. This study generated three scenarios, namely historical trend (HT), national planning (NP), and windbreak and sand fixation (WS), by using the CLUMondo model and Bayesian belief network (BBN) to explore land use with diverse demands.  https://www.selleckchem.com/products/PD-98059.html  The CLUMondo model was utilized to simulate the land use probability surface of Horqin Sandy Land in 2025 under different scenarios. A BBN was constructed to investigate the net primary productivity (NPP), crop production (CP), and wind protection and sand fixation (WPSF) of Horqin Sandy Land in 2025 under uncertain land use to identify the short board areas of various services. The following results were obtained from the analysis. (1) The land use pattern of Horqin Sandy Land in 2025 under the HT scenario will be dominated by cultivated land expansion and grassland reduction. Under the NP scenario, forest will increase, and unused land and grassland will decrease considerably. Under the WS scenario, cultivated land will still maintain a similar growth state, but the difference is that forest and grassland will significantly increase. (2) NPP had the highest probability of being the Highest and the lowest probability of being Low, whereas CP and WPSF obtained the highest probability of being Medium and the lowest probability of being Higher. (3) Tuquan County and Wengniute Banner with a high probability of providing few ecosystem services should be regarded as key areas for ecological restoration. Kailu County and Horqin Left-wing Middle Banner can provide higher ecosystem services. The methodology adopted in this study establishes the connection between the land use probability surface and the optimized pattern of ecosystem services and can therefore be applied in areas where multi-objective comprehensive improvement of ecosystem services is expected.