Fitting complex population models by combining particle filters with Markov chain Monte Carlo

We show how a recent framework combining Markov chain Monte Carlo (MCMC) with particle filters (PFMCMC) may be used to estimate population state-space models. With the purpose of utilizing the strengths of each method, PFMCMC explores hidden states by particle filters, while process and observation parameters are estimated using an MCMC algorithm. PFMCMC is exemplified by analyzing time series data on a red kangaroo (Macropus rufus) population in New South Wales, Australia, using MCMC over model parameters based on an adaptive Metropolis-Hastings algorithm. We fit three population models to these data; a density-dependent logistic diffusion model with environmental variance, an unregulated stochastic exponential growth model, and a random-walk model. Bayes factors and posterior model probabilities show that there is little support for density dependence and that the random-walk model is the most parsimonious model. The particle filter Metropolis-Hastings algorithm is a brute-force method that may be used to fit a range of complex population models. Implementation is straightforward and less involved than standard MCMC for many models, and marginal densities for model selection can be obtained with little additional effort. The cost is mainly computational, resulting in long running times that may be improved by parallelizing the algorithm.     

The use of well-defined biomarkers (such as blood lead) in risk assessment

Biomarkers have a number of different uses in risk assessment, including (1) a variety of applications as dosimeters, (2) as an aid in quantifying inter-individual variability in susceptibility; and (3) as intermediate effect parameters that can help the analyst predict outcomes that are difficult to measure directly. This paper focuses primarily on applications of the first and second types, which are most frequently found in assessing risks from inorganic compounds.     

Classification of occupations at risk in Thailand for lead exposure using blood lead levels as a biomarker

Lead (Pb) exposure is of particular concern because of the ongoing exposure of thousands of workers in industrial plants. Monitoring of Pb exposure among the at-risk workers is recommended and amongst various biomarkers, and it is well-established that blood lead (BPb) determination is utilized for biomonitoring. There are some previous reports on the BPb levels among several at-risk occupations in Thailand; however, there has been no comparison among these occupations with respect to metal levels in the blood. The aim of this study was to correlate at-risk occupations with Pb exposure and BPb levels. In order to compare between occupations, it was not possible to obtain a direct correlation as there are several confounding factors, especially for occupational conditions and lab measurement techniques. In this study, the exposure risk ratio from five previously available reports regarding BPb determination in at-risk occupations in Thailand is presented. Of interest, the high risk occupations are those in which individuals directly inhaled Pb in environmental ambient air. The cutoff median of exposure risk ratio was found to be 12.6 and this may be a useful value in determining whether exposed workers are at high risk in future studies.     

Low levels of lead and glutathione markers of redox status in human blood

Exposure to lead (Pb) is implicated in a plethora of health threats in both adults and children. Increased exposure levels are associated with oxidative stress in the blood of workers exposed at occupational levels. However, it is not known whether lower Pb exposure levels are related to a shift toward a more oxidized state. To assess the association between blood lead level (BLL) and glutathione (GSH) redox biomarkers in a population of healthy adults, BLL and four GSH markers (GSH, GSSG, GSH/GSSG ratio and redox potential E _h ) were measured in the blood of a cross-sectional cohort of 282 avid seafood-eating healthy adults living on Long Island (NY). Additionally, blood levels of two other metals known to affect GSH redox status, selenium (Se) and mercury (Hg), and omega-3 index were tested for effect modification. Regression models were further adjusted for demographic and smoking status. Increasing exposure to Pb, measured in blood, was not associated with GSSG, but was associated with lower levels of GSH/GSSG ratio and more positive GSH redox potential E _h , driven by its association with GSH. No effect modification was observed in analyses stratified by Hg, Se, omega-3 index, sex, age, or smoking. Blood Pb is associated with lower levels of GSH and the GSH/GSSG ratio in this cross-sectional study of healthy adults.     

Low blood lead levels and hemoglobin concentrations in preschool children in China

It is well known that lead (Pb) produces reduced haemoglobin (Hb) levels and risk of anemia when blood lead levels (BPb) are greater than 20?µg?dL^?1. Two recent studies reported an increased risk of anemia in children with BPb between 10–20?µg?dL^?1, but few studies examined the association between Hb levels or risk of anemia and BPb under 10?µg?dL^?1. In the present study this association was examined using data of 140 preschool children from a larger prospective cohort study in China. Data showed that compared to children with BPb <5?µg?dL^?1, children with BPb between 7.5–10?µg?dL^?1 had significantly lower Hb levels, but there were no marked differences for other groups. A linear regression model showed a negative relationship between BPb and Hb levels after controlling for age, gender, height, weight, and iron (Fe) deficiency. This finding, although limited by a small sample size, suggests it may be important to examine Pb-induced hemosynthesis effect at concentrations less than 10?µg?dL^?1.     

Testing the effectiveness of capture mark recapture population estimation techniques using a computer simulation with known population size

Estimation of small mammal population sizes is important for monitoring ecosystem condition and for conservation. Here, we test the accuracy of standard methods of population size estimation using Capture-Mark-Recapture (CMR) on a simulated population of agents. The use of a computer simulation allows complete control of population sizes and behaviors, thereby avoiding assumptions that may be violated in real populations. We find that the recommended protocol for CMR sampling, using uniformly distributed traps, consistently overestimates population sizes by as much as 100% when studies are conducted over only two trapping periods. More than 20 trapping periods are required before this method, or that of placing traps randomly, gives an accurate estimation of population size (i.e., within a 95% confidence limit of the actual value). Non-random sampling, by placing traps on runways used by small mammals, produces the most accurate, and least variable, estimates of population. However, we show that around 10 trapping periods are still required to produce an accurate population estimate using this method. Given that most real populations do not comply with the ‘ideal’ assumptions made by CMR, we suggest that population estimates based on CMR may be fundamentally flawed, and recommend that protocols for CMR population estimation methods may need revising.     

导致上西里西亚工业区儿童血铅水平升高环境和社会经济因素研究

本文集中在横向分析近期波兰儿童铅暴露和铅暴露增加背后的社会经济因素。在上西里西亚工业区,铅是分布最广泛的有毒重金属之一。儿童血铅水平升高关系儿童幸福,不断引起严重关切。本研究涉及在1999 - 2013年间,上西里西亚地区3岁到18岁的4 882名儿童。记录了每一个孩子血液中铅的浓度。孩子的父母被要求回答关于儿童接触铅的环境和家庭社会经济条件的问卷调查。铅暴露增加的因素包括：父母受教育程度较低,父母失业、父母的职业铅暴,家庭的贫穷社会经济地位,在家吸烟,生活在建筑物底层,食用本地种植的蔬菜和水果,在污染环境中长期进行户外活动和男性性别。铅的环境暴露仍然是导致上西里西亚地区儿童慢性铅中毒的主要因素。与儿童血铅浓度关系最大的社会经济因素是儿童父母的低教育水平。
精选自Wojciech Pelc, Natalia Pawlas, Micha? Dobrakowski, S?awomir Kasperczyk. Environmental and socioeconomic factors contributing to elevated blood lead levels in children from industrial area of Upper Silesia. Environmental Toxicology and Chemistry: Volume 35, Issue 10, pages 2597–2603, October 2016. DOI: 10.1002/etc.3429
详情请见http://onlinelibrary.wiley.com/doi/10.1002/etc.3429/full
     

Seasonal variation in paediatric blood lead levels in Syracuse,NY, USA

Venous blood lead values for 2,633 children aged 0–4 years in Syracuse, New York, collected between 1 April 1992 and 31 March 1993 were summarised by census tract for study of geographic variability. A demographic exposure model is presented showing housing stock and SES (socioeconomic status) parameters as the most significant predictor variables. A seasonal trend in blood lead levels was observed with late summer values about 40% higher than late winter values for census tracts with the highest geometric mean PbB levels. Seasonal variation is compared with a biokinetic uptake model to examine hypotheses about temporal variations in soil and dust lead exposure patterns.     

Using citizen science butterfly counts to predict species population trends

Citizen scientists are increasingly engaged in gathering biodiversity information, but trade‐offs are often required between public engagement goals and reliable data collection. We compared population estimates for 18 widespread butterfly species derived from the first 4 years (2011–2014) of a short‐duration citizen science project (Big Butterfly Count [BBC]) with those from long‐running, standardized monitoring data collected by experienced observers (U.K. Butterfly Monitoring Scheme [UKBMS]). BBC data are gathered during an annual 3‐week period, whereas UKBMS sampling takes place over 6 months each year. An initial comparison with UKBMS data restricted to the 3‐week BBC period revealed that species population changes were significantly correlated between the 2 sources. The short‐duration sampling season rendered BBC counts susceptible to bias caused by interannual phenological variation in the timing of species’ flight periods. The BBC counts were positively related to butterfly phenology and sampling effort. Annual estimates of species abundance and population trends predicted from models including BBC data and weather covariates as a proxy for phenology correlated significantly with those derived from UKBMS data. Overall, citizen science data obtained using a simple sampling protocol produced comparable estimates of butterfly species abundance to data collected through standardized monitoring methods. Although caution is urged in extrapolating from this U.K. study of a small number of common, conspicuous insects, we found that mass‐participation citizen science can simultaneously contribute to public engagement and biodiversity monitoring. Mass‐participation citizen science is not an adequate replacement for standardized biodiversity monitoring but may extend and complement it (e.g., through sampling different land‐use types), as well as serving to reconnect an increasingly urban human population with nature.     

基于QSAR模型的蒙特卡洛方法分析有机化学物质对大型蚤(Daphnia magna)的毒性

本文建立一系列758种有机化合物对大型蚤(Daphnia magna)毒性的定量结构-活性关系(QSARs)。用简化的分子线性输入系统(SMILES)代表分子结构。用CORAL(关联和逻辑)软件作为工具来开发QSAR模型。这些模型使用蒙特卡罗方法建立,依据的原理是QSAR是一个“随机事件”,假设检验一组随机数据分布在可见的训练集和不可见的验证集。检验了三组分布于可见的训练、校准、测试集中的数据以及不可见的验证集。最佳模型的预测潜能,也就是其不可见的验证集的统计特征如下:n = 87,r² = 0.8377,RMSE = 0.564。建议和讨论了所构建模型的机械解释和适用领域。
精选自Alla P. Toropova, Andrey A. Toropov, Aleksandar M. Veselinovi?, Jovana B. Veselinovi?, Danuta Leszczynska, Jerzy Leszczynski. Monte Carlo based QSAR models for toxicity of organic chemicals to Daphnia magna. Environmental Toxicology and Chemistry: Volume 35, Issue 11, pages 2691–2697, November 2016. DOI: 10.1002/etc.3466
详情请见http://onlinelibrary.wiley.com/doi/10.1002/etc.3466/full
     

Use of the ouput of a lead risk assessment model to establish soil lead cleanup levels

Three general methods to calculate soil contaminant cleanup levels are assessed: the truncated lognormal approach, Monte Carlo analysis, and the house-by-house approach. When these methods are used together with a lead risk assessment model, they yield estimated soil lead cleanup levels that may be required in an attempt to achieve specified target blood lead levels for a community. The truncated lognormal approach is exemplified by the Society for Environmental Geochemistry and Health (SEGH) model, Monte Carlo analysis is exemplified by the US EPA's LEAD Model, and the house-by-house approach is used with a structural equation model to calculate site-specific soil lead cleanup levels. The various cleanup methods can each be used with any type of lead risk assessment model. Although all examples given here are for lead, the cleanup methods can, in principle, be used as well with risk assessment models for other chemical contaminants to derive contaminant-specific soil cleanup levels.     

Evidence of a fall in cord blood lead levels in South Wales 1984–85

A monitoring scheme for blood lead was based on cord blood samples and maternal blood samples taken in Swansea, South Wales. A fall of around 20% during 1984–85 is described. During this period there was virtually no change in petrol sales in the area and no overall change in air lead levels. Air lead showed large seasonal changes but these were not reflected in blood lead. Water lead levels gave no evidence of changes of any importance during the period of monitoring. These results suggest that petrol lead was at most a minor contributor to blood lead.     

High blood lead levels amongst Hinayana Buddhist monks: A possible effect due to daily exposure to joss stick and candle smoke

Lead (Pb) has no relevant biological functions and is one of the most toxic metals. Among several other heavy metals, monitoring of Pb is an important focus in occupational medicine. In exposure and risk evaluation, monitoring Pb biologically has several advantages over technical exposure assessment. In this study, a high blood level of Pb was found amongst Hinayana Buddhist monks, who constitute a new forgotten high-risk population. The high blood Pb levels amongst this population might be due to prolonged exposure to joss stick and candle smoke.     

Changes in blood lead and water lead in Edinburgh. An eight year follow-up to the Edinburgh lead study

This study aimed to measure changes in household water lead and blood lead in young people living in Edinburgh over a period of 8 years. Two hundred and twenty-three families were eligible and 207 (93%) agreed to participate. A half-hour stagnation sample of kitchen cold water was taken from each household, and 171 young people (aged 14–17 years) provided a blood sample for lead analysis. Information on plumbing changes, exposure to other sources of lead and factors which might influence blood lead was collected by questionnaire. Edinburgh is supplied with water treated in one of two treatment plants. There was a different programme of water treatment in each plant. In one (A) lime and orthophosphate was introduced in the interval between the original and follow-up studies. In the other (F) lime treatment began before the original study and orthophosphate was introduced subsequently. In water from treatment plant A, mean water lead levels fell from 34 to 4.3 gL-1 (87%). In water supplied from treatment plant F the corresponding values were 9.3 to 3.6 gL-1 (61%). These reductions were due to both water treatment and removal of lead plumbing. Houses with no lead plumbing have water lead levels 89% lower than houses with lead tanks, and 47% lower than houses with lead pipes. About one-third of households with lead tanks are predicted to have water lead levels above the current EC limit of 50 gL- 1, though only 3% or less of the remaining households would exceed this limit. If the proposed 10 gL-1 limit were introduced, 34% of households supplied from plant A and 25% from plant F would breach the limit. Blood lead levels fell from an average of 11.0 gdL-1 to 4.0 gdL-1. Males had higher values than females and the main factors influencing levels were water lead and age of house. Our results show substantial reductions in household water lead and blood lead in our sample over a period of 8 years and represent an important achievement in public health. However, more progress will be required if the proposed new limit of 10 gL-1 for water lead is to be met. There is a need for the continuing surveillance of household water lead and blood lead levels in representative samples of the population.     

An Integrated Monte Carlo Methodology for the calibration of water quality models

This paper proposes an Integrated Monte Carlo Methodology (IMCM) to solve the parameter estimation problem in water quality models. The methodology is based on Bayesian approach and Markov Chain Monte Carlo techniques and it operates by means of four modules: Markov Chain Monte Carlo (MCMC), Moving Feasible Ranges (MFR), Statistical Analysis of the Joint Posterior Distribution (SAD) and Uncertainty Propagation Analysis (UPA). The main innovation of the new proposal lies in the combination of MCMC and MFR modules which provides the joint posterior distribution of the calibrated parameters following the classical Bayesian approach. While MCMC module, based on Shuffled Complex Evolution Metropolis (SCEM-UA) algorithm, is specially designed to sample complex joint posterior shapes within certain parameter ranges, the MFR readjusts these ranges until the coverage of the feasible parameter space is guaranteed. Once the joint posterior distribution is properly defined, the SAD provides the parameter statistics and the UPA performs an analysis of the uncertainty propagation through the model. The possibilities of the new proposal have been tested on the basis of a simple model featuring different activated sludge batch experiments. IMCM has been implemented in Matlab and it is prepared to be easily connected to any software package.     

The relationship between surface dust lead loadings on carpets and the blood lead of young children

The final clean-up of residential lead abatement projects in federally-supported housing, as well as in other housing in a number of states, must meet surface dust lead clearance levels expressed as g of lead per square foot. These clearance levels were established because hand-to-mouth ingestion of lead-contaminated dust is recognised as a major pathway through which many children are exposed. A dilemma exists because many floors in housing undergoing abatement are carpeted and the established clearance levels are generally not recommended for use on carpets. These clearance levels are also used as 'action levels' to determine whether exposure reduction activities are needed. The US Environmental Protection Agency is currently in the process of issuing standards for hazardous levels of lead in interior dust and bare soil under Title X of the Housing and Community Development Act of 1992, The Residential Lead-Based Paint Hazard Reduction Act of 1992. An effort to develop a potential surface dust lead clearance level for carpets was made using an existing vacuum dust collection method that has previously been shown to be a reliable indicator of childhood lead exposure. This method was designed for use on carpeted and non-carpeted surfaces. Using data from the Cincinnati Soil Lead Abatement Demonstration Project, the suggested floor-dust lead level where an estimated 95% of the population of children would be expected to have blood lead values below the national goal of 10 g dL^–1, was more than an order of magnitude lower than the current floor-dust lead clearance level of 1080 g m^–2 (100 g ft^–2). Further comparisons of blood lead and carpet lead levels in other parts of the country should be performed before a risk-based lead loading clearance level is established.     

The scent of dominance: female field crickets use odour to predict the outcome of male competition

Pheromones may convey information about mate quality and social status. In the field cricket Gryllus integer, females mount the males for copulation, such that males cannot coerce females to mate. We examined whether virgin G. integer females preferred the scent of potentially dominant males to that of subordinate males. First, we collected pheromones by confining males on filter paper. Next, we offered filter paper from each of two size-matched males and control paper to females that had never been exposed to males, and measured the time spent by the female on each kind of paper. Finally, dominance status of the males in each size-matched pair was determined by pitting the two males against one another in agonistic contests. When offered filter paper from subsequently dominant versus subsequently subordinate males, females spent more time on the paper from the dominant male than the subordinate male, and much less time on control paper. Thus, pheromones may inform female G. integer about a male's potential to achieve dominant social status. Male pheromones were also associated with the female's tendency to mount a male. In contrast to cockroaches, where females prefer the scent of subordinate males (presumably to avoid risk of injury), female crickets prefer the scent of potentially dominant males and are more likely than males to wound their mating partners.     

Modelling with uncertainty: Introducing a probabilistic framework to predict animal population dynamics

Predictive population models designed to assist managers and policy makers require an explicit treatment of inherent uncertainty and variability. These are particular concerns when modelling non-native and reintroduced species, when data have been collected within one geographical or ecological context but predictions are required for another, or when extending models to predict the consequences of environmental change (e.g., climate or land-use). We present an aspatial, probabilistic framework of hierarchical process models for predicting population growth even when data are sparse or of poor quality. Insight into the factors affecting population dynamics in real landscapes can be provided and Kullback–Leibler distances are used to compare the relative output of models. This flexible yet robust framework gives easily interpretable results, allowing managers as well as modellers to invalidate anomalous models and apply others to real-life scenarios.We illustrate the framework’s power with a meta-analysis of European wild boar (Sus scrofa) data. We test hypotheses about the effect of geographic region, hunting and mast years on wild boar population growth, to build models of wild boar dynamics for the UK. The framework quantifies the importance of hunting pressure as a driver of population growth, and confirms that reproductive success is greatly decreased in poor mast years, suggesting that the key to predicting wild boar dynamics is to ascertain local hunting pressure and to better understand changing food availability. Geography had no significant effect, indicating that it is not a good proxy for modelling the impact of change in climate or land-use on wild boar populations at the European scale. We use the framework to predict population abundance 9 years after an isolated population of wild boar established in the UK; in a comparison with the only field data and two independent modelling exercises, our framework provides the most robust and informative results.     

Social network analysis and valid Markov chain Monte Carlo tests of null models

Analyses of animal social networks derived from group-based associations often rely on randomisation methods developed in ecology (Manly, Ecology 76:1109–1115, 1995) and made available to the animal behaviour community through implementation of a pair-wise swapping algorithm by Bejder et al. (Anim Behav 56:719–725, 1998). We report a correctable flaw in this method and point the reader to a wider literature on the subject of null models in the ecology literature. We illustrate the importance of correcting the method using a toy network and use it to make a preliminary analysis of a network of associations among eagle rays.

Organochlorine levels in human blood from residents in areas of limited pesticide use in Sudan

Ninety-nine human blood samples were collected from the riverine region of northern Sudan and the traditional and mechanized rain-fed areas of western and eastern Sudan, representing areas of limited pesticide use in Sudan. Blood samples were analyzed for organochlorine pesticides by gas liquid chromatography (GLC) followed by electron-capture detection (ECD). p,p′-DDE (a metabolite of DDT), heptachlor epoxide, β-hexachlorocyclohexane (β-HCH), and dieldrin were detected in all locations surveyed. The level of total organochlorine burden was highest in the traditional rain-fed area, followed by the mechanized rain-fed area, and the riverine area. A highly significant correlation was observed between total organochlorine blood burden and the age of the donors (r = 0.608**).