Effect of Habitat Fragmentation and Isolation on the Population of Alpine Musk Deer

The alpine musk deer (Moschus chrysogaster) is a key species of some terrestrial ecosystems, it has an important economic and conservative significance as a kind of medical animal in China. Due to the interaction between natural forces and human disturbance, the habitats of alpine musk deer are fragmented and isolated in different mountains and the populations are confronted with many problems of survival. In this paper, we discuss the impact of habitat fragmentation and isolation on alpine musk deer populations based on the investigation on the population densities and sizes and environmental factors in different reserves, as well as on the analysis of its ecological adaptability. We found that the alpine musk deer has strong ecological adaptability; the population development of alpine musk deer may benefit from the reduction of the forest area and even from the fragmentation and isolation of the habitat to a certain extent. However, deforestion should not be encouraged only for the alpine musk deer population, but should also be based on the overall consideration of biodiversity conservation.     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

Trihalomethanes in Drinking Water of Greater Québec Region (Canada): Occurrence, Variations and Modelling

The levels of trihalomethanes (THMs) – the main species of by-product from water chlorination – were monitored in thedistribution systems of the five major drinking water utilitiesof the greater area of Québec City in order to investigate andmodel their occurrence on a spatial and seasonal basis. Data forTHMs and other water quality and operational parametersassociated with their formation were generated through a 16 monthsampling program involving several sites representing variablewater residence times, from the plant to the system extremity.The results demonstrate that the differences in measured THMlevels between the five utilities are mainly due to the variablequality of raw waters, the type of water treatment process beingused and the type and levels of applied disinfectant. Dependingon the utility, average THM levels were from 1.3 to 2.5 timeshigher in the system extremities than in the water leaving thetreatment plant. Also, average levels of THMs measured in summerat the distribution system extremities were, depending on theutility, from 2.5 to 5 times higher than the average levelsmeasured in winter. The seasonal differences were found to besignificantly greater than those observed by others in waterutilities in the United States and Europe and are explained inlarge part by the considerable changes, over the year, in thequality and temperature of surface waters in Southern Québec. Forthe five utilities under study, multivariate regression modelswere developed in order to predict spatial and seasonalvariations of THMs. Both residual chlorine demand and temperaturewere found to be better, statistically, as predictors for THMoccurrence. The usefulness of the developed models for routineand long term water quality management, as well as for assessmentof human exposure to THMs, are also discussed.     

linking various aspects of atmospheric change through a systems analysis of food

Although interdisciplinary collaboration to address a singleenvironmental problem is more common than in the past, all toooften the significant atmospheric problems of our day such asstratospheric ozone depletion, acidic deposition or climaticchange are addressed on a single issue basis. Systems analysis isa way of looking at a problem in a holistic, integrated fashionthrough including as many as practicable of the importantcomponents, and the linkages among them. Systems analysisoften begins with a conceptual model which, even if lackingquantification, is a useful means of changing ones thinking to amulti-issue approach. If possible, conceptual models areoperationalized by quantification (using the best availablescientific knowledge) of the stocks and flows of the relevantcomponents of the problem, and the processes that are involved.In this paper, a systems approach to food production is used tolink various atmospheric issues such as regional acidification andclimatic change. A spreadsheet model of food demand andproduction in various world regions examined the possible effectof atmospheric change on how much food we can grow, andwhether or not we may be able to meet the increased demand inthe year 2025. Using relatively modest changes in factors ofagricultural production, the spreadsheet model calculated globalshortfalls by the year 2025 of the order of 10 to 20% in someimportant agricultural crops, despite the improvements in cropproduction factors that are envisaged by the Food andAgricultural Organization from now until the year 2010, and thatwere extrapolated in this paper to 2025. The model alsocalculated that climatic change in combination with eithertropospheric ozone or increased UV-B radiation caused bydepletion of the stratospheric ozone layer may in general makethe situation worse than in the case of climatic change alone.Given the large uncertainties in the input data, the results in thispaper should not be viewed as predictions but rather as anexample of taking a relatively simple systems approach to foodproduction using a spreadsheet model, and calculating the effectsthat various aspects of atmospheric change might have upon it.Therefore, it is extremely important to know the effects uponcrop production factors of climatic change, tropospheric ozoneand increased UV-B radiation not only as individual issues, butalso of their combined effect since it is probable that in manyregions they will occur in combination.     

Application of CFD Methods for Modelling in Air Pollution Problems: Possibilities and Gaps

Different urban air pollution problems deal with complex structure of air flows and turbulence. For such problems the Computer Fluid Dynamics (CFD) methods become widely used. However, this approach despite a number of advantages has some problems. Experience of use of CFD tools for development of models and suggestions of their applications for a local scale air pollution over a complex terrain and stable stratification are discussed in this paper, including: Topography and complex geometry: choose of the co-ordinate system and computer grid; Turbulence closure for air pollution modelling: modified k- model for stable stratified ABL; Boundary conditions for vertical profiles of velocity for stable-stratified atmosphere; Effects of the radiation and thermal budget of inclined surfaces to dispersion of pollutants; Artificial sources of air dynamics and circulation.Some examples of CFD applications for air pollution modelling for a flat terrain, mountainous area, mining open cast and indoor ventilation are discussed. Modified k- model for stably-stratified ABL is suggested. Due to the isotropic character of the k- model a combination of it in vertical with the sub-grid turbulence closure in horizontal can be more suitable for ABL. An effective scheme of boundary conditions for velocity profiles, based on the developed similarity theory for stable-stratified ABL, is suggested. Alongside with the common studies of atmospheric dispersion, the CFD methods have also demonstrated a good potential for studying anthropogenic and artificial-ventilation sources of air dynamic and circulation in local-scale processes of air pollution.     

Multipoint source method in air pollution modelling of cold start emission

The paper presents a new method of air pollution modelling on a micro scale. For estimation of concentration of car exhaust pollutants, each car is treated as an instantaneous moving emission source. This approach enables us to model time and spatial changes of emission, especially during cold and cool start of an engine. These stages of engine work are a source of significant pollution concentration in urban areas. In this work, two models are proposed: one for the estimation of emission after cold start of the engine and another for the prediction of pollutant concentration. The first model (defined for individual exhaust gas pollutants) enables us to calculate the emission as a function of time after the cold or cool start, ambient temperature and average speed of motion. This model uses the HBEFA database. The second mathematical model is developed in order to calculate the pollutant dispersion and concentrations. The finite volume method is applied to discretise the set of partial differential equations describing wind flow and pollutant dispersion in the domain considered. Models presented in this paper can be called short-term models on a small spatial scale. The results of numerical simulation of pollutant emission and dispersion are also presented.     

Random walk modeling of wake dispersion for the exhaust tower of an underground tunnel in urban area

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Carbon isotope ratios in logged and unlogged boreal forests: Examination of the potential for determining wildlife habitat use

Due to assimilation of recycled CO₂ from litter decomposition and photosynthetic changes in carbon fractionation at low light levels, the foliage at the base of a forest is often more depleted in¹³C compared to that exposed to the atmosphere in either the canopy or in open clearings. This is referred to as the canopy effect. African research has indicated that these habitat differences in foliar ¹³C can be substantial enough to affect the carbon isotope ratios of resident fauna. Previous work documenting a 30-year chronology on moose teeth from Isle Royale National Park indicated a progressive depletion in¹³C and suggested that this could be due to forest regrowth following extensive burning. The present study examined the assumption implicit in this hypothesis that foliar ¹³C varies between open and closed boreal forest sites. I found a marginal canopy effect of 2 ¹³C difference between upper canopy and ground flora for a forest in northwestern Ontario and an average difference of 1.2 in under- and mid-story vegetation between closed forests and open clear-cuts. Because of these small differences, the utility of carbon isotope analysis in quantifying temporally integrated exploitation of deforested habitats will be low for northern boreal locations. In denser forests, such as those in the tropics or western North American where the canopy effect can be expected to be much greater, ¹³C analysis may still offer some promise for determining selection by wildlife of disturbed habitats.     

A Sensitivity Analysis of Nitrogen Losses from Dairy Farms

International attention has focused on agricultural production systems as non-point sources of pollution affecting the quality of streams, estuaries and ground water resources. The objective of the current study was to develop a model of nitrogen management on the dairy farm, and to perform sensitivity analyses in order to determine the relative importance of manipulating herd nutrition, manure management and crop selection in reducing nitrogen (N) losses from the farm. The importance of the method of N input to the farm (purchased feed, legume fixation, inorganic fertilizer, imported manure) was investigated, and the potential to reduce N losses from dairy farms was evaluated. Nitrogen balance equations were derived, and related efficiency coefficients were set to reference values representing common management practices. Total farm N efficiency (animal product N per N input), and N losses per product N were determined for different situations by solving the set of simultaneous equations. Improvements in animal diet and management that increase the conversion of feed N to animal product by 50% would increase total farm N efficiency by 48% and reduce N losses per product by 36 to 40%. In contrast, reducing losses from manure collection, storage and application to improve the percentage of manure N that becomes available in soil by 100% would only improve total farm N efficiency by 13% and reduce total N losses by 14%. Selecting crops and management that can use soil nutrients 50% more efficiently would improve total farm efficiency by up to 59% and reduce N losses by up to 41% depending on the predominant nitrogen sources to the farm. Legume production would reduce N losses per product compared with non-legumes. There was more than a five fold difference in N losses per animal product N between the most extreme scenarios suggesting considerable opportunity to reduce N losses from dairy farms.