Bayesian analysis of Jolly-Seber type models

We propose the use of finite mixtures of continuous distributions in modelling the process by which new individuals, that arrive in groups, become part of a wildlife population. We demonstrate this approach using a data set of migrating semipalmated sandpipers (Calidris pussila) for which we extend existing stopover models to allow for individuals to have different behaviour in terms of their stopover duration at the site. We demonstrate the use of reversible jump MCMC methods to derive posterior distributions for the model parameters and the models, simultaneously. The algorithm moves between models with different numbers of arrival groups as well as between models with different numbers of behavioural groups. The approach is shown to provide new ecological insights about the stopover behaviour of semipalmated sandpipers but is generally applicable to any population in which animals arrive in groups and potentially exhibit heterogeneity in terms of one or more other processes.     

Estimating abundance: a non parametric mark recapture approach for open and closed systems

We present a novel, non-parametric, frequentist approach for capture-recapture data based on a ratio estimator, which offers several advantages. First, as a non-parametric model, it does not require a known underlying distribution for parameters nor the associated assumptions, eliminating the need for post-hoc corrections or additional modeling to account for heterogeneity and other violated assumptions. Second, the model explicitly deals with dependence of trials by considering trials to be dependent; therefore, cluster sampling is handled naturally and additional adjustments are not necessary. Third, it accounts for ordering, utilizing the fact that a system with a small population will have a greater frequency of recaptures “early” in the survey work compared to an identical system with a larger population. We provide mathematical proof that our estimator attains asymptotic minimum variance under open systems. We apply the model to a data set of bottlenose dolphins (Tursiops truncatus) and compare results to those from classic closed models. We show that the model has an impressive rate of convergence and demonstrate that there’s an inverse relationship between population size and the proportion of the population that need to be sampled, while achieving the same degree of accuracy for abundance estimates. The model is flexible and can apply to ecological situations as well as other situations that lend themselves to capture recapture sampling.     

Sparse PCA and investigation of multi-elements compositional repositories: theory and applications

The geochemistry of floodplain sediments is fundamental to monitor environmental changes and to quantify their contribution to natural and anthropic processes. A floodplain sediment composition is a vector of positive elements which sum to a fixed constant. The analysis of high-dimensional compositions requires methods that produce results involving only a small portion of the original variables. On the other hand, the analysis must take into account the additional constraints specific to compositions. With the purpose of studying these problems, a new procedure for sparse PCA is proposed on European floodplain sediment samples.     

Analysis and prediction of $$\mathrm{PM}_{10}$$ concentration levels in Tunisia using statistical learning approaches

Over the past years, the health impact of airborne particulate matter \(\mathrm{PM}_{10}\) has become a very topical subject. Thereby, a lot of research effort in the environmental sciences goes towards the modeling and the prediction of ambient \(\mathrm{PM}_{10}\) concentrations. In this paper, we are interested in the statistical classification of the daily mean \(\mathrm{PM}_{10}\) concentration in Tunisia according to the authority regulation. We consider two monitoring stations: a big industrial station and a traffic station. The main goal of this work is to determine the pertinent predictors of \(\mathrm{PM}_{10}\) concentration within a nonlinear multiclass framework. To do this, we used two popular statistical learning methods; the support vector machines (SVM) and the random forests (RF). The statistical results obtained on the real datasets, show that RF outperform SVM for the purpose of variable selection even with a reduced number of observations compared to the number of explicative variables. It was also demonstrated that the \(\mathrm{PM}_{10}\) concentration measured yesterday is the most relevant predictor of its present-day value. Moreover, we found that the more delayed values of \(\mathrm{PM}_{10}\) concentration may be crucial to get an accurate prediction.     

Approaching the binding between Cu(II) and aerobic granules by a modified titration and µ-XRF

Interactions between metals and activated sludge can substantially affect the fate and transport of heavy metals in wastewater treatment plants. Therefore, it is important to develop a simple, fast and efficient method to elucidate the interaction. In this study, a modified titration method with a dynamic mode was developed to investigate the binding of Cu(II), a typical heavy metal, onto aerobic granules. The titration results indicated that pH and ionic strength both had a positive effect on the biosorption capacity of the granular sludge. The µ-XRF results demonstrated that the distribution of metals on the granular surface was heterogeneous, and Cu showed strong correlations and had the same “hot spots” positions with other metal ions (e.g., Ca, Mg, Fe etc.). Ion exchange and complexing were the main mechanisms for the biosorption of Cu(II) by aerobic granules. These results would be beneficial for better understanding of Cu(II) migration and its fate in wastewater treatment plants.     

Improving simulations of sulfate aerosols during winter haze over Northern China: the impacts of heterogeneous oxidation by NO<Subscript>2</Subscript>

We implemented the online coupled WRF-Chem model to reproduce the 2013 January haze event in North China, and evaluated simulated meteorological and chemical fields using multiple observations. The comparisons suggest that temperature and relative humidity (RH) were simulated well (mean biases are–0.2K and 2.7%, respectively), but wind speeds were overestimated (mean bias is 0.5 m?s^–1). At the Beijing station, sulfur dioxide (SO₂) concentrations were overpredicted and sulfate concentrations were largely underpredicted, which may result from uncertainties in SO₂ emissions and missing heterogeneous oxidation in current model. We conducted three parallel experiments to examine the impacts of doubling SO₂ emissions and incorporating heterogeneous oxidation of dissolved SO₂ by nitrogen dioxide (NO₂) on sulfate formation during winter haze. The results suggest that doubling SO₂ emissions do not significantly affect sulfate concentrations, but adding heterogeneous oxidation of dissolved SO₂ by NO₂ substantially improve simulations of sulfate and other inorganic aerosols. Although the enhanced SO₂ to sulfate conversion in the HetS (heterogeneous oxidation by NO₂) case reduces SO₂ concentrations, it is still largely overestimated by the model, indicating the overestimations of SO₂ concentrations in the North China Plain (NCP) are mostly due to errors in SO₂ emission inventory.

Open image in new window

     

Photochemical indicators of ozone sensitivity: application in the Pearl River Delta,China

Surface O₃ production has a highly nonlinear relationship with its precursors. The spatial and temporal heterogeneity of O₃-NO _x -VOC-sensitivity regimes complicates the control-decision making. In this paper, the indicator method was used to establish the relationship between O₃ sensitivity and assessment indicators. Six popular ratios indicating ozone-precursor sensitivity, HCHO/NO _y , H₂O₂/ HNO₃, O₃/NO _y , O₃/NO _z , O₃/HNO₃, and H₂O₂/NO _z , were evaluated based on the distribution of NO_x- and VOC-sensitive regimes. WRF-Chem was used to study a serious ozone episode in fall over the Pearl River Delta (PRD). It was found that the south-west of the PRD is characterized by a VOCsensitive regime, while its north-east is NO _x -sensitive, with a sharp transition area between the two regimes. All indicators produced good representations of the elevated ozone hours in the episode on 6 November 2009, with H₂O₂/HNO₃ being the best indicator. The threshold sensitivity levels for HCHO/NO_y, H₂O₂/HNO₃, O₃/NO _y , O₃/NO _z , O₃/HNO₃, and H₂O₂/NO _z were estimated to be 0.41, 0.55, 10.2, 14.0, 19.1, and 0.38, respectively. Threshold intervals for the indicators H₂O₂/HNO₃, O₃/NO _y , O₃/NO _z , O₃/HNO₃, and H₂O₂/NO _z were able to identify more than 95% of VOC- and NO _x -sensitive grids. The ozone episode on 16 November 16 2008 was used to independently verify the results, and it was found that only H₂O₂/HNO₃ and H₂O₂/NO _z were able to differentiate the ozone sensitivity regime well. Hence, these two ratios are suggested as the most appropriate indicators for identifying fall ozone sensitivity in the PRD. Since the species used for indicators have seasonal variation, the utility of those indicators for other seasons should be investigated in the future work.

Open image in new window

     

Modeling of Cr contamination in the agricultural lands of three villages near the leather industry in Kasur,Pakistan, using statistical and GIS techniques

Kasur is one of the hubs of leather industry in the Punjab, Pakistan, where chrome tanning method of leather processing is extensively being used. Chromium (Cr) accumulation levels in the irrigation water, soil, and seasonal vegetables were studied in three villages located in the vicinity of wastewater treatment plant and solid waste dumping site operated by the Kasur Tanneries Waste Management Agency (KTWMA). The data was interpreted using analysis of variance (ANOVA), clustering analysis (CA), and principal component analysis (PCA). Interpolated surface maps for Cr were generated using the actual data obtained for the 30 sampling sites in each of the three villages for irrigation water, soil, and seasonal vegetables. The level of contamination in the three villages was directly proportional to their distance from KTWMA wastewater treatment plant and the direction of water runoff. The highest level of Cr contamination in soil (mg kg^?1) was observed at Faqeeria Wala (37.67), intermediate at Dollay Wala (30.33), and the least in Maan (25.16). A gradational variation in Cr accumulation was observed in the three villages from contaminated wastewater having the least contamination level (2.02–4.40 mg L^?1), to soil (25.16–37.67 mg kg^?1), and ultimately in the seasonal vegetable crops (156.67–248.33 mg kg^?1) cultivated in the region, having the highest level of Cr contamination above the permissible limit. The model used not only predicted the current situation of Cr contamination in the three villages but also indicated the trend of magnification of Cr contamination from irrigation water to soil and to the base of the food chain. Among the multiple causes of Cr contamination of vegetables, soil irrigation with contaminated groundwater was observed to be the dominant one.     

Human parvovirus B19 infection and unbalanced translocation in a case of hydrops fetalis

In a case of hydrops fetalis, serological examination showed a recent maternal human parvovirus B19 infection. Amniocentesis revealed a unique unbalanced translocation between chromosomes 3 and 11 of the fetus. The mother proved to have a balanced reciprocal translocation between chromosomes 3 and 11. A grossly macerated hydropic male fetus was delivered with a flat nose and low implanted deformed ears. Histopathological examination revealed nuclear inclusion bodies in fetal erythroid cells, confirming human parvovirus B19 infection. Parvovirus B19 DNA was demonstrated by in situ hybridization in the nuclei of heart muscle cells. Our finding of two different disorders in one case illustrates the importance of a complete evaluation of every case of hydrops fetalis, especially concerning counselling on the outcome of future pregnancies. The human parvovirus B19 infection will not recur due to the acquired immunity of the mother, whereas the balanced reciprocal translocation will endanger future pregnancies.     

Incremental cost-effectiveness of incorporating oestriol evaluation in down syndrome screening programmes

As screening for Down syndrome becomes increasingly sophisticated, it is important to evaluate the newer technologies in terms of their cost-effectiveness. One recent addition to Down syndrome screening programmes is maternal serum unconjugated oestriol (uE₃), especially when used in conjunction with maternal serum α-fetoprotein and human chorionic gonadotropin. Using assumptions used in a California proposal to justify an expanded screening programme for Down syndrome, we calculated both the average and the incremental cost-effectiveness of adding uE₃. Using the base case assumptions, including an $8 fee for the uE₃, the incremental cost-effectiveness of adding uE₃ to the proposed California programme is $119 100 per case detected, a value that compares favourably with other Down syndrome screening programmes. The sensitivity analysis supports this conclusion over a wide range of assumptions. However, because of the uncertainty with some key data, it is still too early to fully support the inclusion of uE₃ in Down syndrome screening programmes.