Can forest management be used to sustain water-based ecosystem services in the face of climate change?

Forested watersheds, an important provider of ecosystems services related to water supply, can have their structure, function, and resulting streamflow substantially altered by land use and land cover. Using a retrospective analysis and synthesis of long-term climate and streamfiow data (75 years) from six watersheds differing in management histories we explored whether streamflow responded differently to variation in annual temperature and extreme precipitation than unmanaged watersheds. We show significant increases in temperature and the frequency of extreme wet and dry years since the 1980s. Response models explained almost all streamflow variability (adjusted R2 > 0.99). In all cases, changing land use altered streamflow. Observed watershed responses differed significantly in wet and dry extreme years in all but a stand managed as a coppice forest. Converting deciduous stands to pine altered the streamflow response to extreme annual precipitation the most; the apparent frequency of observed extreme wet years decreased on average by sevenfold. This increased soil water storage may reduce flood risk in wet years, but create conditions that could exacerbate drought. Forest management can potentially mitigate extreme annual precipitation associated with climate change; however, offsetting effects suggest the need for spatially explicit analyses of risk and vulnerability.     

Rainfall trends in twentieth century over Kerala,India

Attempts were made to study temporal variation in monthly, seasonal and annual rainfall over Kerala, India, during the period from 1871 to 2005. Longterm changes in rainfall determined by Man-Kendall rank statistics and linear trend. The analysis revealed significant decrease in southwest monsoon rainfall while increase in post-monsoon season over the State of Kerala which is popularly known as the “Gateway of summer monsoon”. Rainfall during winter and summer seasons showed insignificant increasing trend. Rainfall during June and July showed significant decreasing trend while increasing trend in January, February and April. Hydel power generation and water availability during summer months are the concern in the State due to rainfall decline in June and July, which are the rainiest months. At the same time, majority of plantation crops are likely to benefit due to increase in rainfall during the post-monsoon season if they are stable and prolonged.     

Analysis of air pollution data at a mixed source location using boosted regression trees

This paper explores the use of boosted regression trees to draw inferences concerning the source characteristics at a location of high source complexity. Models are developed for hourly concentrations of nitrogen oxides (NO_X) close to a large international airport. Model development is discussed and methods to quantify model uncertainties developed. It is shown that good explanatory models can be developed and further, allowing for interactions between model variables significantly improves the model fits compared with non-interacting models. Methods are used to determine which variables exert most influence over predicted concentrations and to explore the NO_X dependency for each. Model predictions are used to estimate aircraft take-off contributions to total concentrations of NO_X and determine how these predictions are affected by annual variations in meteorological conditions and runway use patterns. Furthermore, the results relating to the aircraft contributions to total NO_X concentration are compared with those from a more detailed independent field campaign. Finally, we find empirical evidence that plumes from larger aircraft disperse more rapidly from the point of release compared with smaller aircraft. The reasons for this behaviour and the implications are discussed.     

Global sensitivity analysis of a process-based model for ammonia emissions from manure storage and treatment structures

The development of process-based models to estimate ammonia emissions from animal feeding operations (AFOSs) is sought to replace costly and time-consuming direct measurements. Critical to process-based model development is conducting sensitivity analysis to determine the input parameters and their interactions that contribute most to the variance of the model output. Global and relative sensitivity analyses were applied to a process-based model for predicting ammonia emissions from the surface of anaerobic lagoons for treating and storing manure. The objectives were to compare global sensitivity analysis (GSA) to relative (local) sensitivity analysis (RSA) on a process-based model for ammonia emissions. Based on the first-order coefficient, both GSA and RSA showed the model input parameters in order of importance in process model for ammonia emissions from lagoon surfaces were: (i) pH, (ii) lagoon liquid temperature, (iii) wind speed above the lagoon surface, and (iv) the concentration of ammoniacal nitrogen in the lagoon. The GSA revealed that interactions between model parameters accounted for over two-thirds of the model variance, a result that cannot be achieved using traditional RSA. Also, the GSA showed that parameter interactions involving liquid pH had more impact on the model output variance than the single parameters: (i) temperature, (ii) wind speed, or (iii) total ammoniacal nitrogen. This study demonstrates that GSA provides a more complete analysis of model input parameters and their interactions on the model output compared to RSA. A comprehensive tutorial regarding the application of GSA to a process model is presented.     

Pesticide toxicity towards microalgae increases with environmental mixture complexity

Environmental Science and Pollution Research - Effect-directed analysis (EDA) aims at identifying the compound(s) responsible for toxicity in a complex environmental sample where several dozens of...     

Prenatal diagnosis of spinal muscular atrophy in Russia

Ninety-two families with spinal muscular atrophy (SMA) applied for genetic counselling and further prenatal diagnosis. To minimize expenses, only one tightly linked informative marker was determined in the course of preliminary examination, and non-radioactive allele detection was preferably used. Four prenatal diagnoses of SMA type I, four of SMA type II, and one of SMA type III were made. This trial programme shows the considerable requirements, importance, and potential effectiveness of prenatal prediction of SMA in Russia.     

Effect of endosulfan on blood glucose

Endosulfan was administered to cats intravenously at different doses. The compound (3 and 4 mg/kg) showed marked rise in blood glucose level after 15 and 30 minutes of treatment with a gradual fall upto 4 hrs. No change in blood glucose was observed at 2.0 mg/kg dose. Adrenalectomy prevented this rise in glucose level.     

Microwave enhanced advanced oxidation process for treating dairy manure at low pH

This study investigated the treatment of dairy manure using the microwave enhanced advanced oxidation process (MW-AOP) at pH 2. An experimental design was developed based on a statistical program using response surface methodology to explore the effects of temperature, hydrogen peroxide dosage and heating time on sugar production, nutrient release and solids destruction. Temperature, hydrogen peroxide dosage and acid concentration were key factors affecting reducing sugar production. The highest reducing sugar yield of 7.4% was obtained at 160°C, 0 mL, 15 min heating time, and no H₂O₂ addition. Temperature was a dominant factor for an increase of soluble chemical oxygen demand (SCOD) in the treated dairy manure. The important factors for volatile fatty acids (VFA) production were microwave temperature and hydrogen peroxide dosage. Temperature was the most important parameter, and heating time, to a lesser extent affecting orthophosphate release. Heating time, hydrogen peroxide dosage and temperature were significant factors for ammonia release. There was a maximum of 96% and 196% increase in orthophosphate and ammonia concentration, respectively at 160°C, 0.5 mL H₂O₂ and 15 min heating time. The MW-AOP is an effective method in dairy manure treatment for sugar production, nutrient solubilisation, and solids disintegration.