Markov Chain Monte Carlo on optimal adaptive sampling selections

Under a Bayesian population model with a given prior distribution, the optimal sampling strategy with a fixed sample size n is an n-phase adaptive one. That is, the selection of the next sampling units should sequentially depend on the information obtained from the previously selected units, including the observed values of interest. Such an optimal strategy is in general not executable in practice due to its intensive computation. In many survey sampling situations, an important problem is that one would like to select a set of units in addition to a certain number of sampling units which have been observed. If the optimal strategy is an adaptive one, the selection of the additional units should take both the labels and the observed values of the already selected units into account. Hence, a simpler optimal two-phase adaptive sampling strategy under a Bayesian population model is proposed in this article for practical interest. A Markov chain Monte Carlo method is used to approximate the posterior joint distribution of the unobserved population units after the first phase sampling, for the optimal selection of the second phase sample. This approximation method is found to be successful to select the optimal second-phase sample. Finally, this optimal strategy is applied to a set of data from a study of geothermal CO₂ emissions in Yellowstone National Park as a practical illustrative example.     

Detecting Rare Species with Random or Subjective Sampling: a Case Study of Red-Listed Saproxylic Beetles in Boreal Sweden

Abstract:  Efficient sampling design in field studies is important for economical and statistical reasons. We compared two ways to distribute sampling effort over an area, either randomly or subjectively. We searched for red-listed saproxylic (wood-living) beetles in 30 spruce stands in boreal Sweden by sifting wood from dead trees. We randomly selected positions within each stand with a geographic positioning system and sampled the nearest dead tree (random sample). In the same stand we also sampled dead trees that, based on literature, were likely to host such species (subjective sampling). The subjective sampling (two to five samples per stand, depending on stand size) was compared with the higher, random sampling effort (fixed level of 12 samples/stand). Subjective sampling was significantly more efficient. Red-listed species were found in 36% of the subjective samples and in 16% of the random samples. Nevertheless, the larger random effort resulted in a comparable number of red-listed species per stand and in 13 detected species in total (vs. 12 species with subjective sampling). Random sampling was less efficient, but provided an unbiased alternative more suitable for statistical purposes, as needed in, for example, monitoring programs. Moreover, new species-specific knowledge can be gained through random searches.     

Spatially Explicit Power Analyses for Occupancy‐Based Monitoring of Wolverine in the U.S. Rocky Mountains

Conservation scientists and resource managers often have to design monitoring programs for species that are rare or patchily distributed across large landscapes. Such programs are frequently expensive and seldom can be conducted by one entity. It is essential that a prospective power analysis be undertaken to ensure stated monitoring goals are feasible. We developed a spatially based simulation program that accounts for natural history, habitat use, and sampling scheme to investigate the power of monitoring protocols to detect trends in population abundance over time with occupancy‐based methods. We analyzed monitoring schemes with different sampling efforts for wolverine (Gulo gulo) populations in 2 areas of the U.S. Rocky Mountains. The relation between occupancy and abundance was nonlinear and depended on landscape, population size, and movement parameters. With current estimates for population size and detection probability in the northern U.S. Rockies, most sampling schemes were only able to detect large declines in abundance in the simulations (i.e., 50% decline over 10 years). For small populations reestablishing in the Southern Rockies, occupancy‐based methods had enough power to detect population trends only when populations were increasing dramatically (e.g., doubling or tripling in 10 years), regardless of sampling effort. In general, increasing the number of cells sampled or the per‐visit detection probability had a much greater effect on power than the number of visits conducted during a survey. Although our results are specific to wolverines, this approach could easily be adapted to other territorial species. Poder de Análisis Espacialmente Explícito para el Monitoreo Basado en Ocupación del Glotón (Gulo gulo) en las Montañas Rocallosas de Estados Unidos     

Epigenetic effects of N-methyl-N′-nitro-N-nitrosoguanidine on Kazakh esophageal epithelial cells

Epigenetic change is a key factor for esophageal cancer progression. This study shows that upon exposure of primary cultures of human esophageal epithelial cells obtained from people of the Kazakh nationality in China to N-methyl-N′-nitro-N-nitrosoguanidine at concentrations of 0.75, 1.50, and 3.00 mg/L, (1) cell proliferation was inhibited, the percentages of cells in the G₀ and G₁ phases declined, and those in the S and G₂ + M phases increased at all concentrations, while apoptosis rates increased at medium and high concentrations; (2) the content of DNA-methyltransferases 3a and 3b and the activities of DNA-methyltransferase 1 and DNA-methyltransferase 3a increased at all concentrations while the content of DNA-methyltransferase 1 and the activity of DNA-methyltransferase 3b were increased only at the high concentration; (3) messenger RNA and protein levels of DNA-methyltransferases 1, 3a, and 3b were increased at all concentrations. Obviously, N-methyl-N′-nitro-N-nitrosoguanidine in the low mg/L range can inhibit the proliferation of normal Kazakh esophageal epithelial cells, can cause cell cycle arrest in the S and G₂ + M phases, promote apoptosis, and increase the activities of DNA-methyltransferases 1, 3a, and 3b.     

Adaptive two-stage one-per-stratum sampling

We briefly describe adaptive cluster sampling designs in which the initial sample is taken according to a Markov chain one-per-stratum design (Breidt, 1995) and one or more secondary samples are taken within strata if units in the initial sample satisfy a given condition C. An empirical study of the behavior of the estimation procedure is conducted for three small artificial populations for which adaptive sampling is appropriate. The specific sampling strategy used in the empirical study was a single random-start systematic sample with predefined systematic samples within strata when the initially sampled unit in that stratum satisfies C. The bias of the Horvitz-Thompson estimator for this design is usually very small when adaptive sampling is conducted in a population for which it is suited. In addition, we compare the behavior of several alternative estimators of the standard error of the Horvitz-Thompson estimator of the population total. The best estimator of the standard error is population-dependent but it is not unreasonable to use the Horvitz-Thompson estimator of the variance. Unfortunately, the distribution of the estimator is highly skewed hence the usual approach of constructing confidence intervals assuming normality cannot be used here.     

Contributions to composite sampling

The initial use of composite sampling involved the analysis of many negative samples with relatively high laboratory cost (Dorfman sampling). We propose a method of double compositing and compare its efficiency with Dorfman sampling. The variability of composite measurement samples has environmental interest (hot spots). The precision of these estimates depends on the kurtosis of the distribution; leptokurtic distributions (₂ > 0) have increased precision as the number of field samples is increased. The opposite effect is obtained for platykurtic distributions. In the lognormal case, coverage probabilities are reasonable for < 0.5. The Poisson distribution can be associated with temporal compositing, of particular interest where radioactive measurements are taken. Sample size considerations indicate that the total sampling effort is directly proportional to the length of time sampled. If there is background radiation then increasing levels of this radiation require larger sample sizes to detect the same difference in radiation.     

Ground water contamination with 238U, 234U, 235U, 226Ra and 210Pb from past uranium mining: cove wash,Arizona

The objectives of the study are to present a critical review of the ²³⁸U, ²³⁴U, ²³⁵U, ²²⁶Ra and ²¹⁰Pb levels in water samples from the EPA studies (U.S. EPA in Abandoned uranium mines and the Navajo Nation: Red Valley chapter screening assessment report. Region 9 Superfund Program, San Francisco, 2004, Abandoned uranium mines and the Navajo Nation: Northern aum region screening assessment report. Region 9 Superfund Program, San Francisco, 2006, Health and environmental impacts of uranium contamination, 5-year plan. Region 9 Superfund Program, San Franciso, 2008) and the dose assessment for the population due to ingestion of water containing ²³⁸U and ²³⁴U. The water quality data were taken from Sect. “Data analysis” of the published report, titled Abandoned Uranium Mines Project Arizona, New Mexico, Utah–Navajo Lands 1994–2000, Project Atlas. Total uranium concentration was above the maximum concentration level for drinking water (7.410–1 Bq/L) in 19 % of the water samples, while ²³⁸U and ²³⁴U concentrations were above in 14 and 17 % of the water samples, respectively. ²²⁶Ra and ²¹⁰Pb concentrations in water samples were in the range of 3.7 × 10^?1 to 5.55 × 102 Bq/L and 1.11 to 4.33 × 102 Bq/L, respectively. For only two samples, the ²²⁶Ra concentrations exceeded the MCL for total Ra for drinking water (0.185 Bq/L). However, the ²¹⁰Pb/²²⁶Ra ratios varied from 0.11 to 47.00, and ratios above 1.00 were observed in 71 % of the samples. Secular equilibrium of the natural uranium series was not observed in the data record for most of the water samples. Moreover, the ²³⁵U/^totalU mass ratios ranged from 0.06 to 5.9 %, and the natural mass ratio of ²³⁵U to ^totalU (0.72 %) was observed in only 16 % of the water samples, ratios above or below the natural ratio could not be explained based on data reported by U.S. EPA. In addition, statistical evaluations showed no correlations among the distribution of the radionuclide concentrations in the majority of the water samples, indicating more than one source of contamination could contribute to the sampled sources. The effective doses due to ingestion of the minimum uranium concentrations in water samples exceed the average dose considering inhalation and ingestion of regular diet for other populations around the world (1 μSv/year). The maximum doses due to ingestion of ²³⁸U or ²³⁴U were above the international limit for effective dose for members of the public (1 mSv/year), except for inhabitants of two chapters. The highest effective dose was estimated for inhabitants of Cove, and it was almost 20 times the international limit for members of the public. These results indicate that ingestion of water from some of the sampled sources poses health risks.     

Comparison between Hansen-Hurwitz and Horvitz-Thompson estimators for adaptive cluster sampling

Thompson (1990) introduced the adaptive cluster sampling design. This sampling design has been shown to be a useful sampling method for parameter estimation of a clustered and scattered population (Roesch, 1993; Smith et al., 1995; Thompson and Seber, 1996). Two estimators, the modified Hansen-Hurwitz (HH) and Horvitz-Thompson (HT) estimators, are available to estimate the mean or total of a population. Empirical results from previous researches indicate that the modified HT estimator has smaller variance than the modified HH estimator. We analytically compare the properties of these two estimators. Some results are obtained in favor of the modified HT estimator so that practitioners are strongly recommended to use the HT estimator despite easiness of computations for the HH estimator.     

Estimating total abundance of a large temperate-reef fish using visual strip-transects

Total abundance estimates for the large, common, reef fish Cheilodactylus spectabilis (Hutton) were obtained for a marine reserve and adjacent section of coast in north-eastern New Zealand during 1985. Visual strip-transects were used to estimate abundance and size structure in both areas. The accuracy, precision and cost efficiency of five transect sizes (500, 375, 250, 100, 75 m²) were examined over three times per day (dawn, midday and dusk), by simulating transects over mapped C. spectabilis populations. Two transect sizes showed similarly high efficiency. The smaller of the two (20x5 m) was chosen for the survey because of the general advantages attributable to small sampling units. Biases related to strip-transect size are discussed. Preliminary sampling indicated that C. spectabilis was distributed heterogeneously, and that density was habitat-related. An optimal stratified-random design was employed in both locations, to obtain total abundance and size-structure estimates. This reduced the between-habitat source of variability in density. The total number of sampling units used was governed by the time available. The resulting total abundance estimates obtained were 18 338±2 886 (95% confidence limit) for the 5 km marine reserve, compared to 3 987±1 117 for an adjacent, heavily fished 4 km section of coast. When corrected for total area and habitat area sampled, this represented a 2.3-fold difference in abundance. If sampling had been designed to detect an arbitrary 10% difference in abundance within each habitat, an infeasible 440 h of sampling would have been required. Size-frequency distributions of C. spectabilis at the reserve had a larger model size class than distributions from the adjacent area. The data suggest that reserve status is causal in these differing abundance and size structure estimates.     

Stack sampling for organic emissions

Along with increased activity in source sampling for organics, there have been many improvements in the methods of acquiring samples. Much has been learned about how best to proceed, and a number of potentially serious pitfalls have been discovered, characterized, and circumvented. Unfortunately, communication of all of this new technology has not always been effective.

This paper reviews some of the more important fundamental principles involved in stack sampling for organics, briefly describes and discusses recently developed equipment, and points out a few of the more serious pitfalls to be avoided. Extensive references are provided, many of which are often overlooked by newcomers to the field. The conclusion is reached that it is possible to consistently obtain high‐quality samples of organic materials from stationary source stacks, even though knowledge and caution are necessary.     

Using the bootstrap with two-phase adaptive stratified samples from multiple populations at multiple locations

Recently the two-phase adaptive stratified sampling design proposed by Francis (1984) has been extended by Manly et al. (2002) for situations where several biological populations are sampled simultaneously, and where this is done at several different geographical locations in order to estimate population totals or means. The method uses the results from a first phase sample to decide how best to allocate a second phase sample to locations and strata, in order to maximise a criterion (based on estimated coefficients of variation) that measures the accuracy of estimation for population totals, for all variables at all locations. One potential problem with this method is bias in the estimators of the population totals and means. In this paper bootstrapping is considered as a means of overcoming these biases. It is shown using model populations of Pacific walrus and shellfish, based on real data, that bootstrapping is a useful tool for removing about half of the bias. This is also confirmed from some simulations using artificial data.     

Degradation of dibutyl phthalate in refuse from different phases of landfill by its dominant bacterial strain,Enterobacter sp. T1

A facultative bacterial strain isolated from municipal solid waste (MSW) obtained from a simulated landfill bioreactor was found to have the ability to use dibutyl phthalate (DBP) as its sole source of carbon and energy. Based on its morphology, physiochemical characteristics, and 16S rDNA sequence, the strain was identified as Enterobacter sp. T1. Evaluation of the degradation of DBP in refuse collected during the initial, acidic, and methanogenic phases of landfill before and after inoculation with Enterobacter sp. T1 revealed that the degradation fits first-order kinetic models for refuse from all phases. The removal rate of DBP in the refuse of the methanogenic phase increased from 59.3% to 74.5% when Enterobacter T1 was added. The half-life of DBP in refuse from the methanogenic phase that was inoculated with Enterobacter T1 decreased by 36.7% relative to uninoculated samples, and the intermediate products monobutyl phthalate (MBP) and phthalic acid were detected in all samples. These results provide new evidence for the potential of applying Enterobacter sp. for phthalic acid ester-polluted area remediation.     

Soleidae macroparasites along the Portuguese coast: latitudinal variation and host–parasite associations

Parasite assemblages are increasingly being used as indicators of their hosts’ biology and ecology, especially for economically important marine species such as the Soleidae. In this study, seven species inhabiting Portuguese coastal waters were examined for external and internal macroparasite infections using standard procedures: Dicologlossa cuneata, Microchirus azevia, Microchirus variegatus, Solea lascaris, Solea senegalensis, Solea solea and Synaptura lusitanica. Despite being closely related, these species present different life history patterns and ecological preferences which were expected to be mirrored by their macroparasite assemblages. The aim of the study was, therefore, to study the variation of these assemblages, within and between host species, along the Portuguese coast in order to evaluate the importance of the hosts’ features and environmental factors in the assemblage compositions. Flatfish were obtained seasonally from commercial fishing vessels operating in three areas (northern, central and southern) along the Portuguese coast. Prevalence and mean abundance were calculated and tested for differences between host sex, areas and seasons. The host specificity index and the importance of the host–parasite relationship were computed based on mean abundance. The total number of parasite individuals, species richness, total prevalence, total mean abundance, diversity and evenness were also calculated. A canonical correspondence analysis (CCA) was performed using prevalence and mean abundance data. A total of 44 macroparasite species were found. No significant differences were observed in prevalence and mean abundance between sexes and sampling seasons but, for three of the parasite species, significant differences were found between areas. The highest values of the parasitological and ecological indices were generally registered in the hosts S. lascaris and S. senegalensis and in the southern area. The CCA using the prevalence data revealed the differentiation of S. lascaris samples, which was mainly related to the total prevalence and to the number of important species of macroparasites. When using mean abundance data, the CCA revealed the differentiation of D. cuneata from the south, S. lascaris from the three areas and S. senegalensis from the south, mainly related to total prevalence and richness. The differences found between infection levels and assemblages’ composition were mainly due to differences in hosts’ diet, namely prey type consumption, given that most macroparasites found were transmitted through the food web. However, environmental factors were also important given that they regulate the distribution of ectoparasites and the availability of prey, and therefore the infections’ pattern. These findings were in agreement with the ones from similar studies performed in other species, revealing the importance of parasites as indicators of their hosts’ ecology.     

Optimal Marking of Threatened Species to Balance Benefits of Information with Impacts of Marking

Abstract: Marking animals so that they are uniquely identifiable provides information that may assist conservation efforts. Nevertheless, some methods used to mark animals can be harmful. We used mathematical methods to assess the trade‐off between the impact of marking threatened species and the value of the information gained. We considered the case where 2 management strategies, each aiming to improve a species' survival rate, are implemented in an experimental phase. The results of the experiment were applied in a postexperimental management phase. We expressed the expected number of survivors in both phases mathematically, accounting for any mortality caused by the experiment, and determined the proportion of animals to mark to maximize this number. The optimal number of animals to mark increased with the number of individuals available for the experiment and with the number of individuals to be managed in the future. The optimal solution was to mark only 25% of the animals when there were 1000 individuals available for the experiment, the results were used to manage 2000 individuals, and marking caused mortality of 1%. Fewer animals were marked when there were fewer animals in either phase or when marking caused higher mortality. In the case of the Helmeted Honeyeater (Lichenostomus melanops cassidix), the optimal proportion to mark was <1 if the mortality rate was >0.15%–1%, with the threshold depending on the number of animals in the experimental and postexperimental phases. The trade‐off between gaining more information about a species and possibly harming individuals of that species by marking them is difficult to assess subjectively. We show how to determine objectively the optimal proportion of animals to mark to enhance the management of threatened species.     

Restricted adaptive cluster sampling

Adaptive cluster sampling can be a useful design for sampling rare and patchy populations. With this design the initial sample size is fixed but the size of the final sample (and total sampling effort) cannot be predicted prior to sampling. For some populations the final sample size can be quite variable depending on the level of patchiness. Restricted adaptive cluster sampling is a proposed modification where a limit is placed on the sample size prior to sampling and quadrats are selected sequentially for the initial sample size. As a result there is less variation in the final sample size and the total sampling effort can be predicted with some certainty, which is impor- tant for many ecological studies. Estimates of density are biased with the restricted design but under some circumstances the bias can be estimated well by bootstrapping. © Rapid Science 1998     

极性有机物整合采样技术在监测水环境中农药的应用

明确水环境中农残的污染状况对研究其环境行为和生态风险至关重要。传统主动采样法耗能、耗力且单次采样仅获得瞬时浓度值。被动采样节能、方便且为时间加权平均浓度,利于大规模采样。极性有机物整合采样技术(polar organic chemical integrative sampler,POCIS)是针对极性有机物的被动采样技术,近年来在水环境中农药监测的运用越来越广泛。本文概述了POCIS结构、原理和校正方法,探讨了环境因素(如水流速率、温度、p H、溶解性有机质、盐度和膜污染)、化合物性质及POCIS结构对农药采样速率(Rs)的影响。此外,综述了POCIS在监测水环境中农药的应用,展望了POCIS在该领域中的问题、解决方式及前景。     

A review of adaptive cluster sampling: 1990–2003

Adaptive cluster sampling (ACS) is an adaptive sampling scheme which operates under the rule that when the observed value of an initially selected sampling unit satisfies some condition of interest, C, other additional units in some pre-defined accompanying neighborhood are also added to the sample. In turn, if any of these additional units satisfy C, then their corresponding unit neighborhoods are added to the sample as well, and so on. This process stops when no additional units satisfying C are encountered. This paper will provide a review of the major developments and issues in ACS since its introduction by Thompson (1990) [Journal of the American Statistical Association, 85, 1050–1059].     

Relating environmental modeling to policy issues and decisions

This paper describes a linear program-based computer model which has been developed to identify the most effective spending patterns for environmental cleanup based on public preferences and spending limitations. The inputs to the model include the costs of removing each residual studied from its various sources. The objective function is the total “value of removal”. The factor added for each residual consists of a value for the residual multiplied by the quantity or fraction removed.Results of the analysis relate to and support current and projected policy decisions by the U.S. Environmental Protection Agency (EPA) for air and water programs. In addition, the results of the analysis suggest that EPA undertake a redirection of the Nation's resources among residual control programs.     

Geographic sampling of urban soils for contaminant mapping: how many samples and from where

Properly sampling soils and mapping soil contamination in urban environments requires that impacts of spatial autocorrelation be taken into account. As spatial autocorrelation increases in an urban landscape, the amount of duplicate information contained in georeferenced data also increases, whether an entire population or some type of random sample drawn from that population is being analyzed, resulting in conventional power and sample size calculation formulae yielding incorrect sample size numbers vis-à-vis model-based inference. Griffith (in Annals, Association of American Geographers, 95, 740–760, 2005) exploits spatial statistical model specifications to formulate equations for estimating the necessary sample size needed to obtain some predetermined level of precision for an analysis of georeferenced data when implementing a tessellation stratified random sampling design, labeling this approach model-informed, since a model of latent spatial autocorrelation is required. This paper addresses issues of efficiency associated with these model-based results. It summarizes findings from a data collection exercise (soil samples collected from across Syracuse, NY), as well as from a set of resampling and from a set of simulation experiments following experimental design principles spelled out by Overton and Stehman (in Communications in Statistics: Theory and Methods, 22, 2641–2660). Guidelines are suggested concerning appropriate sample size (i.e., how many) and sampling network (i.e., where).

Use of the “Acetylene blockage” technique for assaying denitrification in a salt marsh

The acetylene blockage technique was evaluated for measurement of denitrification in salt-marsh sediments (near Halifax, Nova Scotia, Canada). N₂O in the gas phase of closed Spartina alterniflora marsh-sediment systems was analyzed with use of a thermal conductivity gas chromatograph sensitive to approximately 0.1 nmoles ml^-1 gas. No N₂O was detected for unfertilized sediment samples taken through the growing season and incubated in sealed buckets with 10% C₂H₂. For sediment samples amended with nitrate and for enrichments, initial rates of N₂O evolution were higher in the presence of 10% C₂H₂ than in the absence of C₂H₂, but after longterm incubation N₂O was consumed in some samples containing C₂H₂ as well as in samples without C₂H₂. In addition, total gaseous nitrogen (N₂ and N₂O) production in the absence of C₂H₂ was higher than in the presence of C₂H₂. Acetylene appears to be an inconsistent inhibitor of N₂O reduction in salt-marsh sediments. The usefulness of the acetylene-denitrification technique in this habitat is, therefore, questionable.