Semi-parametric statistical approaches for space-time process prediction

The problem of estimation and prediction of a spatial-temporal stochastic process, observed at regular times and irregularly in space, is considered. A mixed formulation involving a non- parametric component, accounting for a deterministic trend and the effect of exogenous variables, and a parametric component representing the purely spatio-temporal random variation is proposed. Correspondingly, a two-step procedure, first addressing the estimation of the non- parametric component, and then the estimation of the parametric component is developed from the residual series obtained, with spatial-temporal prediction being performed in terms of suitable spatial interpolation of the temporal variation structure. The proposed model formula-tion, together with the estimation and prediction procedure, are applied using a Gaussian ARMA structure for temporal modelling to space-time forecasting from real data of air pollution concentration levels in the region surrounding a power station in northwest Spain.     

Modelling and assessment of South African elephant Loxodonta africana population persistence

The use of a quantitative population growth model to investigate the persistence of South African elephant populations is explored. The model provides quantitative assessments of population persistence and confidence intervals for estimated parameters based purely on population size estimates. The analysis supports the view that most of the larger populations in the region are secure. This view is further supported by a lack of density dependent effects in most of the recovering populations and the high population rates of increase observed. This predominantly positive prognosis is in contrast with that emerging from most of the rest of the African continent where the populations are under greater threat because of habitat restriction and direct human conflict. This preliminary assessment of elephant population persistence suggests that “viable” populations may lie between 400 and 6000 individuals. Although not inconsistent with information-greedy genetic and demographic models, the relationship between population growth versus genetic and demographic models should be further investigated. The implementation of a metapopulation management strategy towards these smaller populations is advocated. In addition, as all of the populations included in this analysis have been afforded some degree of protection since the 1920s, continued protection would be a prerequisite for their continued survival.     

Major and trace elements of selected pedons in the USA

Few studies of soil geochemistry over large geographic areas exist, especially studies encompassing data from major pedogenic horizons that evaluate both native concentrations of elements and anthropogenically contaminated soils. In this study, pedons (n = 486) were analyzed for trace (Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Zn) and major (Al, Ca, Fe, K, Mg, Na, P, Si, Ti, Zr) elements, as well as other soil properties. The objectives were to (i) determine the concentration range of selected elements in a variety of U.S. soils with and without known anthropogenic additions, (ii) illustrate the association of elemental source and content by assessing trace elemental content for several selected pedons, and (iii) evaluate relationships among and between elements and other soil properties. Trace element concentrations in the non-anthropogenic dataset (NAD) were in the order Mn > (Zn, Cr, Ni, Cu) > (Pb, Co) > (Cd, Hg), with greatest mean total concentrations for the Andisol order. Geometric means by horizon indicate that trace elements are concentrated in surface and/or B horizons over C horizons. Median values for trace elements are significantly higher in surface horizons of the anthropogenic dataset (AD) over the NAD. Total Al, Fe, cation exchange capacity (CEC), organic C, pH, and clay exhibit significant correlations (0.56, 0.74, 0.50, 0.31, 0.16, and 0.30, respectively) with total trace element concentrations of all horizons of the NAD. Manganese shows the best inter-element correlation (0.33) with these associated total concentrations. Total Fe has one of the strongest relationships, explaining 55 and 30% of the variation in total trace element concentrations for all horizons in the NAD and AD, respectively.     

METHODOLOGIES FOR CALIBRATION AND PREDICTIVE ANALYSIS OF A WATERSHED MODEL1

ABSTRACT: The use of a fitted parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can lead to predictive nonuniqueness. The extent of model predictive uncertainty should be investigated if management decisions are to be based on model projections. Using models built for four neighboring watersheds in the Neuse River Basin of North Carolina, the application of the automated parameter optimization software PEST in conjunction with the Hydrologic Simulation Program Fortran (HSPF) is demonstrated. Parameter nonuniqueness is illustrated, and a method is presented for calculating many different sets of parameters, all of which acceptably calibrate a watershed model. A regularization methodology is discussed in which models for similar watersheds can be calibrated simultaneously. Using this method, parameter differences between watershed models can be minimized while maintaining fit between model outputs and field observations. In recognition of the fact that parameter nonuniqueness and predictive uncertainty are inherent to the modeling process, PEST's nonlinear predictive analysis functionality is then used to explore the extent of model predictive uncertainty.     

Respiration and lipid content of the Arctic copepod<Emphasis Type="Italic"> Calanus hyperboreus</Emphasis> overwintering 1 m above the seafloor at 2,300 m water depth in the Fram Strait

In August 2000 high concentrations of the dominant herbivorous copepod Calanus hyperboreus were detected in the Arctic Fram Strait, west of Spitsbergen, 1 m above the seafloor at 2,290 m water depth. Individuals from that layer were sampled by a hyper-benthic net attached to the frame of an epi-benthic sledge. For comparison, the vertical distribution of C. hyperboreus in the water column was studied simultaneously by a multiple opening/closing net haul from 2,250 m depth to the surface. Maximum abundance was found close to the surface with 6.6 and 10.0 ind. m^?3 at 0–50 m and 50–100 m depth, respectively. However, the major fraction of the population (>40%) occurred between 1,000 and 1,500 m depth. In the deepest layer (2,000–2,250 m) abundance measured 2.2 ind. m^?3 and was twice as high as between 100 and 1,000 m depth. In comparison to individuals from surface waters, copepods from the hyper-benthic layer were torpid and did not react to mechanical stimuli. Stage CV copepodids and females from the deep sample contained 4–10% less lipid and showed significantly reduced respiration rates of 0.24 and 0.26 ml O₂ h^?1 g^?1 dry mass (DM) as compared to surface samples (0.49 and 0.43 ml O₂ h^?1 g^?1 DM). All these observations indicate that the hyper-benthic part of the population had already started a dormant overwintering phase at great depth. Based on the lipid deposits and energy demands, the potential maximum duration of the non-feeding dormant phase was estimated at 76–110 days for females and at 98–137 days for CV copepodids, depending on what indispensable minimum lipid content was assumed. In any case, the estimated times could not meet the necessary requirements for a starvation period of >6 months until the next phytoplankton bloom in the following spring. The ecological implications of these results are discussed with respect to the life cycle and eco-physiological adaptations of C. hyperboreus to its high-Arctic habitat.     

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.     

Sleepiness among night-time drivers: relationship to blood alcohol concentration and other factors

OBJECTIVE: The study aimed to explore the distribution and correlates of subjective sleepiness among the general night-time driving population. METHODS: The survey took place in three British Columbia communities in June 2003 between 21:00 hours to 03:00 hours. Sites and vehicles were selected randomly. Surveyors obtained information on several demographic and situational variables including self-assessed degree of sleepiness and self-reported hours asleep and awake, as well as an objective measure of blood alcohol concentration obtained from a hand-held breath-testing device. RESULTS: The total compliance rate among intercepted drivers was 85%. Among the 2335 drivers responding to the questionnaire, 68.4% indicated that they were wide awake, 27.6% were somewhat sleepy, and 4.1% were very sleepy. Logistic regression quantified the independent contributions of the various factors to subjective sleepiness. Male drivers with positive blood alcohol concentrations under 50 mg% were more likely to report feeling sleepy than those with either higher or with zero blood alcohol concentration. Greater relative risk of sleepiness was also associated with being female, being under age 55, and advanced hour of night. Driving with passengers of the same gender was associated with lower reported sleepiness. CONCLUSIONS: A substantial proportion of night-time drivers are driving while sleepy, especially at late night and early morning hours. The combination of alcohol and sleepiness compounds impairment in experimental studies and deserves greater attention in crash risk studies and as a topic for public education and awareness.     

Control chart for monitoring occupational asthma

INTRODUCTION: Work-related asthma has become the most prevalent occupational respiratory disease in the developed world. Occupational asthma is thought to affect 5%-10% of people worldwide. The first step in the diagnosis of occupational asthma is to establish work-relatedness. Although considerable research has been conducted in the area of occupational asthma, no simple, effective, and statistically sound method has been developed that can be used as an initial step to effectively identify the workers at risk for occupational asthma. The purpose of this research was to investigate whether Shewhart control chart method can be used as an effective method to detect occupational asthma. METHOD: Forty-five workers who completed the study and provided usable peak expiratory flow (a lung function marker) recordings while at work and away from work were included in this study. Control charts were developed using Shewhart's Method. The lower control limit of at work control chart (LCL(W)) was compared to each subject's Personal Best (PB) value. RESULTS: Reviewing the results of this comparison showed LCL(W)<60% PB to have a sensitivity of 85.71%, specificity of 87.50%, and an error rate of 13.33%. When the subjects suspected for false positive and false negative diagnoses were identified, the test produced a sensitivity of 95.24%, a specificity of 95.83% and an error rate of 4.44%. CONCLUSIONS: Our results were as good as, and in some cases better than, published clinical guidelines. IMPACT ON INDUSTRY: Our research showed that the control chart method is an effective, simple, and inexpensive tool for early intervention in workers suspected for occupational asthma.