Atrazine contamination in agricultural soils from the Yangtze River Delta of China and associated health risks

Atrazine is one of the most widely applied and persistent herbicides in the world. In view of limited information on the regional contamination of atrazine in soils in China, this study investigated the spatial distribution and environmental impacts of atrazine in agricultural soils collected from the Yangtze River Delta (YRD) as an illustrative analysis of rapidly developing regions in the country. The results showed that the concentrations of atrazine in the YRD agricultural soils ranged from <1.0 to 113 ng/g dry weight, with a mean of 5.7 ng/g, and a detection rate of 57.7 % in soils. Pesticide factory might be a major source for the elevated levels of atrazine in Zhejiang Province. The contamination of atrazine was closely associated with land use types. The concentrations and detection rates of atrazine were higher in corn fields and mulberry fields than in rice paddy fields. There was no significant difference in compositions of soil microbial phospholipids fatty acids among the areas with different atrazine levels. Positive relationship (R = 0.417, p < 0.05, n = 30) was observed between atrazine and total microbial biomass. However, other factors, such as soil type and land management practice, might have stronger influences on soil microbial communities. Human health risks via exposure to atrazine in soils were estimated according to the methods recommended by the US EPA. Atrazine by itself in all the soil samples imposed very low carcinogenic risks (<10^?6) and minimal non-cancer risks (hazard index <1) to adults and children.     

Effect of rise in spring air temperature on the arrival dates and reproductive success of the Song Thrush, <Emphasis Type="Italic">Turdus philomelos</Emphasis> (C.L. Brehm, 1831) in the forest–steppe of the Russian Plain

The effect of rise in spring air temperature on the breeding phenology and reproductive success of the Song Thrush in the Voronezh Nature Reserve have been studied over the periods of 1987 to 1990 and 2008 to 2012. The results show that relatively high air temperatures provide for earlier arrival of the birds from wintering grounds, earlier and more synchronous breeding of the majority of nesting pairs, and an increase in clutch size and proportion of pairs producing two broods per season. Predation pressure on bird nests decreases under such conditions, which markedly improves reproductive success. Climate warming is conducive to increasing breeding productivity of the Song Thrush population as a whole.     

Siberian musk deer in the diets of tiger and bears in the Sikhote-Alin

The role of the Siberian musk deer in the diets of the Amur tiger, brown bear, and Asian black bear has been studied in the Sikhote-Alin State Biosphere Reserve in 1992 to 2016. Information has been collected from 763 tiger feeding sites, and the contents of tiger feces have been analyzed. Radiotelemetry has been used to evaluate tiger–musk deer relationships. The musk deer accounted for 0.26% of all animal species found to be eaten by the tiger. Musk deer remains in feces of the tiger, brown bear, and Asian black bear occurred with frequencies of 1.3, 0.2, and 0.3%, respectively. A case of musk deer avoiding the presence of brown bear is described.     

Carbon fluxes from coarse woody debris in southern taiga forests of the Valdai Upland

Studies in three typical forest biotopes of the Valdai Upland were performed to evaluate the stocks and surface area of coarse woody debris from spruce and birch (in linear transects), its colonization by xylotrophic fungi (during reconnaissance surveys), and CO₂ emission (by a chamber method). The stock and surface area were minimum in a paludal birch forest (46.4 m³/ha and 960 m²/ha) and maximum in a decay area of spruce forest (256.1 m³/ha and 3761 m²/ha, respectively). The assemblages of wood-decay fungi had a composition typically found in southern taiga forests. The total CO₂ flux varied from 145 kg C-CO₂/ha per year in the paludal birch forest to 462 kg C-CO₂/ha per year in small herb–green moss spruce forest. It is concluded that air temperature is an informative predictor of seasonal C-CO₂ flux rate from coarse woody debris.     

Building Greater Transparency in Supply Chains to Advance Sustainability

As company supply chains grow larger, more dispersed, and more complex, companies and their stakeholders are increasingly interested in knowing more about these supply chains and requesting greater transparency regarding them. This article examines several aspects that can assist companies in building greater transparency in supply chains, including supply chain mapping, traceability, third‐party certification, and goal setting, as well as reporting on their progress toward achieving these efforts. In addition, this article provides summaries of how several companies are building greater transparency in their supply chains, efforts that also help companies better manage the environmental impacts from their supply chains.     

Ultrasound effects on the activity of Aspergillus niger lipases in their application in dairy wastewater treatment

We evaluated the effect of ultrasound radiation on lipase activity. The experiments were conducted using a low‐cost crude enzyme extract. We then used this lipase to treat dairy effluent. The results of our study presented an increase of approximately 430% in the concentration of free fatty acids.     

How to Constrain Multi‐Objective Calibrations of the SWAT Model Using Water Balance Components

Accurate discharge simulation is one of the most common objectives of hydrological modeling studies. However, a good simulation of discharge is not necessarily the result of a realistic simulation of hydrological processes within the catchment. We propose an evaluation framework that considers both discharge and water balance components as evaluation criteria for calibration of the Soil and Water Assessment Tool (SWAT). In this study, we integrated average annual values of surface runoff, groundwater flow, and evapotranspiration in the model evaluation procedure to constrain the selection of good model runs for the Little River Experimental Watershed in Georgia, United States. For evaluating water balance and discharge dynamics, the Nash‐Sutcliffe efficiency (NSE) and percent bias (PBIAS) were used. In addition, the ratio of root mean square error and standard deviation of measured data (RSR) was calculated for individual segments of the flow duration curve to identify the best model runs in terms of discharge magnitude. Our results indicate that good statistics for discharge do not guarantee realistic simulations of individual water balance components. Therefore, we recommend constraining the ranges of water balance components to achieve a more realistic simulation of the entire hydrological system, even if tradeoffs between good statistics for discharge simulations and reasonable amounts of the water balance components are unavoidable. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

Evaluation of Existing and Modified Wetland Equations in the SWAT Model

The ability to accurately simulate flow and nutrient removal in treatment wetlands within an agricultural, watershed‐scale model is needed to develop effective plans for meeting nutrient reduction goals associated with protection of drinking water supplies and reduction of the Gulf of Mexico hypoxic zone. The objectives of this study were to incorporate new equations for wetland hydrology and nutrient removal in Soil and Water Assessment Tool (SWAT), compare model performance using original and improved equations, and evaluate the ramifications of errors in watershed and tile drain simulation on prediction of NO₃‐N dynamics in wetlands. The modified equations produced Nash‐Sutcliffe Efficiency values of 0.88 to 0.99 for daily NO₃‐N load predictions, and percent bias values generally less than 6%. However, statistical improvement over the original equations was marginal and both old and new equations provided accurate simulations. The new equations reduce the model's dependence on detailed monitoring data and hydrologic calibration. Additionally, the modified equations increase SWAT's versatility by incorporating a weir equation and an irreducible nutrient concentration and temperature coefficient. Model improvements enhance the utility of SWAT for simulating flow and nutrients in wetlands and other impoundments, although performance is limited by the accuracy of inflow and NO₃‐N predictions from the contributing watershed. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.