Microsatellite data reveal fine genetic structure in male Guiana dolphins (<Emphasis Type="Italic">Sotalia guianesis)</Emphasis> in two geographically close embayments at south-eastern coast of Brazil

A large macrogeographic differentiation has been observed among Sotalia guianensis populations along the South American coast. However, no genetic structure has been detected so far in closely distributed populations of this species, even though it has been observed in other cetaceans. Here, we examined the fine scale population structure for the largest populations of S. guianensis inhabiting Sepetiba and Paraty embayments at the south-eastern coast of Rio de Janeiro, Brazil. Analysis of mitochondrial DNA (mtDNA) control region sequences failed to detect variability among sequences. Conversely, evidence of significant male population structure was found on the basis of ten nuclear microsatellite loci. Surprisingly, the microsatellite markers were able to distinguish between individuals from the two embayments located 60 km apart. The results suggest that differences in habitat type and behavioral specializations are likely to explain the patterns of genetic structure. These findings should provide baselines for the management of communities exposed to increasing human-driven habitat loss.     

Larval and Juvenile Fish Assemblage Structure of Inshore Habitats in the Middle Reaches of Li River,China: Spatial and Temporal Patterns in Relation to Abiotic Factors

To evaluate the effect of abiotic factors on larval and juvenile fish assemblage in shallow waters of middle reaches of Li River, Guilin, China. Samplings were taken monthly at 7 stations in the mainstream and 2 stations in 3 tributaries from May 2014 to April 2015. Synchronously, temperature, pH, turbidity, conductivity, dissolved oxygen rainfall and discharge were obtained. In all, 11.886 larval and juvenile fish from 18 species belonging to 8 families, 16 genera was captured. Principal Component Analysis (PCA) showed obvious significant difference between the environmental variables across sampling areas and months. The results of Canonical Correspondence Analysis (CCA) indicated that water temperature, turbidity, discharge and rainfall were dominant factors on larval and juvenile fish assemblage.     

Managing the nitrogen cycle to reduce greenhouse gas emissions from crop production and biofuel expansion

Public policies are promoting biofuels as an alternative to fossil fuel consumption in order to mitigate greenhouse gas (GHG) emissions. However, the mitigation benefit can be at least partially compromised by emissions occurring during feedstock production. One of the key sources of GHG emissions from biofuel feedstock production, as well as conventional crops, is soil nitrous oxide (N₂O), which is largely driven by nitrogen (N) management. Our objective was to determine how much GHG emissions could be reduced by encouraging alternative N management practices through application of nitrification inhibitors and a cap on N fertilization. We used the US Renewable Fuel Standards (RFS2) as the basis for a case study to evaluate technical and economic drivers influencing the N management mitigation strategies. We estimated soil N₂O emissions using the DayCent ecosystem model and applied the US Forest and Agricultural Sector Optimization Model with Greenhouse Gases (FASOMGHG) to project GHG emissions for the agricultural sector, as influenced by biofuel scenarios and N management options. Relative to the current RSF2 policy with no N management interventions, results show decreases in N₂O emissions ranging from 3 to 4 % for the agricultural sector (5.5–6.5 million metric tonnes CO₂?eq.?year^?1; 1 million metric tonnes is equivalent to a Teragram) in response to a cap that reduces N fertilizer application and even larger reductions with application of nitrification inhibitors, ranging from 9 to 10 % (15.5–16.6 million tonnes CO₂?eq.?year^?1). The results demonstrate that climate and energy policies promoting biofuel production could consider options to manage the N cycle with alternative fertilization practices for the agricultural sector and likely enhance the mitigation of GHG emissions associated with biofuels.     

An Interval-Parameter Waste-Load-Allocation Model for River Water Quality Management Under Uncertainty

A simulation-based interval quadratic waste load allocation (IQWLA) model was developed for supporting river water quality management. A multi-segment simulation model was developed to generate water-quality transformation matrices and vectors under steady-state river flow conditions. The established matrices and vectors were then used to establish the water-quality constraints that were included in a water quality management model. Uncertainties associated with water quality parameters, cost functions, and environmental guidelines were described as intervals. The cost functions of wastewater treatment units were expressed in quadratic forms. A water-quality planning problem in the Changsha section of Xiangjiang River in China was used as a study case to demonstrate applicability of the proposed method. The study results demonstrated that IQWLA model could effectively communicate the interval-format uncertainties into optimization process, and generate inexact solutions that contain a spectrum of potential wastewater treatment options. Decision alternatives can be generated by adjusting different combinations of the decision variables within their solution intervals. The results are valuable for supporting local decision makers in generating cost-effective water quality management strategies.     

Purification and Properties of Extracellular Poly(3-hydroxybutyrate) Depolymerase Produced by <Emphasis Type="Italic">Aspergillus fumigatus</Emphasis> 202

An extracellular poly(3-hydroxybutyrate) (PHB) depolymerase produced by a thermotolerant fungal soil isolate, Aspergillus fumigatus 202, was purified and characterized. Maximum PHB depolymerase production was obtained at the end of 48 h with initial medium pH 7.0 and 45 °C in Bushnell Haas Minerals medium containing PHB as sole source of carbon. The PHB depolymerase was purified using size exclusion chromatography to a fold purification of 20.62 and 61.62% yield. SDS-PAGE and isoelectric focusing revealed the molecular weight and pI of the purified enzyme as 63,744 Da and 4.2, respectively. N-terminal amino acid sequence of purified enzyme was HAXDAYLVK. This non-glycosylated enzyme was most active at pH 9.0 and 45 °C. Purified enzyme was inactivated by N-bromosuccinimide and dithiothreitol suggesting the involvement of tryptophan residues and disulfide bonds at its active site. Nonionic detergents like Tween 20, Tween 80 and Triton X-100 inhibited the enzyme activity. Ions like Ca⁺² and Mg⁺² (5 mM) increased the enzyme activity 1.5 times. Fe⁺² effectively inhibited the enzyme activity to 88% whereas Hg⁺² completely inhibited the enzyme.     

Modelling and Optimization of Uranium (VI) Ions Adsorption Onto Nano-ZnO/Chitosan Bio-composite Beads with Response Surface Methodology (RSM)

Nano-ZnO-chitosan bio-composite beads were prepared for the sorption of \({\text{UO}}_{2}^{{2+}}\) from aqueous media. The resulting nano-ZnO/CTS bio-composite beads were characterized by TEM, XRD etc. The sorption of \({\text{UO}}_{2}^{{2+}}\) by bio-composite beads was optimized using RSM. The correlation between four variables was modelled and studied. According to RSM data, correlation coefficients (R²?=?0.99) and probability F-values (F?=?2.24?×?10^??10) show that the model fits the experimental data well. Adsorption capacity for nano-ZnO/CTS bio-composite beads was obtained at 148.7 mg/g under optimum conditions. The results indicate that nano-ZnO/CTS bio-composite beads are appropriate for the adsorption of \({\text{UO}}_{2}^{{2+}}\) ions from aqueous media. Also, the suitability of adsorption values to adsorption isotherms was researched and thermodynamic data were calculated.     

Policy evaluation of vehicle exhaust standards in Japan from 1995 to 2005 based on two human health risk indices for air pollution and global warming

Measures for vehicle exhaust emissions aimed at reducing either air pollution or global warming could have counterproductive effects on one another. Increasing diesel passenger vehicles, which generally have lower CO₂ emissions than gasoline counterparts, leads to increasing particulate matter (PM) emissions, while gasoline has lower PM emissions than diesel. It is said that stringent limits on PM emission factors discourages improved CO₂ emission factors. Without including both effects in a risk evaluation, one cannot evaluate whether the total risk is reduced or not. Hence, we evaluated representative exhaust emission measures based on risk evaluation for both air pollution and global warming. Considering consumer choice between diesel and gasoline passenger vehicles and emissions standards adopted in Japan from 1995 to 2005, we built five cases for vehicle policy evaluation. For each case, we estimated disability-adjusted life years (DALY) as an index of human health risk caused by lung cancer linked to inhalation exposure of elemental carbon in PM as well as due to global warming linked to CO₂. The results of our risk evaluation reveal that the case adopting the 2005 new long-term Japanese emission standard reduces the human health risk caused by lung cancer due to air pollution by 0.6 × 10³ DALY, but would increase the risk due to global warming by 31.9 × 10³ DALY compared with the case of adopting EURO 4, for the same conditions of passenger vehicle choice from 1995. These results suggest that the characteristics of Japanese emissions standards are mainly designed to reduce air pollution.     

Regulatory effects of dioxin-like and non-dioxin-like PCBs and other AhR ligands on the antioxidant enzymes paraoxonase 1/2/3

Paraoxonase 1 (PON1), an antioxidant enzyme, is believed to play a critical role in many diseases, including cancer. PCBs are widespread environmental contaminants known to induce oxidative stress and cancer and to produce changes in gene expression of various pro-oxidant and antioxidant enzymes. Thus, it appeared of interest to explore whether PCBs may modulate the activity and/or gene expression of PON1 as well. In this study, we compared the effects of dioxin-like and non-dioxin-like PCBs and of various aryl hydrocarbon receptor (AhR) ligands on PON1 regulation and activity in male and female Sprague-Dawley rats. Our results demonstrate that (i) the non-dioxin-like PCB154, PCB155, and PCB184 significantly reduced liver and serum PON1 activities, but only in male rats; (ii) the non-dioxin-like PCB153, the most abundant PCB in many matrices, did not affect PON1 messenger RNA (mRNA) level in the liver but significantly decreased serum PON1 activity in male rats; (iii) PCB126, an AhR ligand and dioxin-like PCB, increased both PON1 activities and gene expression; and (iv) even though three tested AhR ligands induced CYP1A in several tissues to a similar extent, they displayed differential effects on the three PONs and AhR, i.e., PCB126 was an efficacious inducer of PON1, PON2, PON3, and AhR in the liver, while 3-methylcholantrene induced liver AhR and lung PON3, and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), the most potent AhR agonist, increased only PON3 in the lung, at the doses and exposure times used in these studies. These results show that PCBs may have an effect on the antioxidant protection by paraoxonases in exposed populations and that regulation of gene expression through AhR is highly diverse.     

Visualizing dynamic capabilities as adaptive capacity for municipal water governance

This study seeks to expand empirical research on how municipalities have adapted and innovated (or not) their water systems as a result of climate change. We analyze characteristics of water governance at the municipal scale in Oklahoma, USA. ArcMap 10.3 was used to build a qualitative geographic information system (GIS) based on fieldwork, including interviews and site-observations, to compare dynamic capabilities that lead to innovation in 38 cities in the state. The GIS enables visualization of our digitalized research to understand the interconnections between drivers of innovativeness—the combination of dynamic capabilities and innovation rates—and state of water resource infrastructure in place specific and regional planning contexts. In particular, the GIS takes into consideration income level, the influence of state-level water policy (Water for 2060 Act), water manager certification levels, population, dynamic capabilities, and perceptions of risk and vulnerability to water system change. Digitizing this information provides a diverging perspective on the historical lack of innovation in the public sector, as different socio-cultural, socio-economic, and socio-political contexts occur throughout Oklahoma, a state notorious for its oil centered economy and its climate change deniers. The findings suggest that innovativeness is directly related to dynamic capabilities and indirectly related to population size, income level, and the educational backgrounds of water decision-makers. The visualizations also show that some cities have surplus capacity for adaptation, while others were able to more efficiently turn capacity into water management innovations. Seeing representations of water governance success and failure in communities affords the opportunity to educate citizens and decision-makers to adapt water infrastructures to the effects of climate change, showcasing the utility of digitalization in a quest for sustainable solutions.