Estimator bias and efficiency for adaptive cluster sampling with order statistics and a stopping rule

Practical problems facing adaptive cluster sampling with order statistics (acsord) are explored using Monte Carlo simulation for three simulated fish populations and two known waterfowl populations. First, properties of an unbiased Hansen-Hurwitz (HH) estimator and a biased alternative Horvitz-Thompson (HT) estimator are evaluated. An increase in the level of population aggregation or the initial sample size increases the efficiencies of the two acsord estimators. For less aggregated fish populations, the efficiencies decrease as the order statistic parameter r (the number of units about which adaptive sampling is carried out) increases; for the highly aggregated fish and waterfowl populations, they increase with r. Acsord is almost always more efficient than simple random sampling for the highly aggregated populations. Positive bias is observed for the HT estimator, with the maximum bias usually occurring at small values of r. Secondly, a stopping rule at the Sth iteration of adaptive sampling beyond the initial sampling unit was applied to the acsord design to limit the otherwise open-ended sampling effort. The stopping rule induces relatively high positive bias to the HH estimator if the level of the population aggregation is high, the stopping level S is small, and r is large. The bias of HT is not very sensitive to the stopping rule and its bias is often reduced by the stopping rule at smaller values of r. For more aggregated populations, the stopping rule often reduces the efficiencies of the estimators compared to the non-stopping-rule scheme, but acsord still remains more efficient than simple random sampling. Despite its bias and lack of theoretical grounding, the HT estimator is usually more efficient than the HH estimator. In the stopping rule case, the HT estimator is preferable, because its bias is less sensitive to the stopping level.     

Performance of adaptive cluster sampling estimators in a multivariate setting

Adaptive cluster sampling has been proven to perform well in a univariate setting, but it may not perform well when there are several parameters of interest. The efficiency of adaptive sampling when there are several variables of interest depends on the relationship of the variables with one another.     

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.     

Sequential male mate choice in a fish,the Pacific blue-eye<Emphasis Type="Italic"> Pseudomugil signifer</Emphasis>

Mate choice is not just a female preoccupation. Under some circumstances, males may also be choosy. However, studies of male mate choice have generally been confined to situations where males can make direct comparisons between potential partners. In contrast, sequential male mate choice has largely been overlooked despite its biologically importance, especially if current investment in mate attraction diminishes a males future mating opportunities. Using the Pacific blue-eye fish Pseudomugil signifer, we show that males are capable of exercising sequential mate choice. When presented sequentially with large and small females, males spent more effort courting the former. However, males did not appear to modify the time spent courting a given female based on the size of the female encountered previously. We suggest that greater attention to the sequential choice problem in males may help illuminate similarities and differences between the sexes when it comes to mating decisions.Communicated by T. Czeschlik     

Evaluation of US EPA Environmental Monitoring and Assessment Program's (EMAP)-Wetlands sampling design and classification

The United States Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP) will monitor the nation's resources by evaluating the status and trends of selected indicators of condition using a probability-based sampling design. The EMAP-Wetlands program will monitor the condition of the nation's wetlands. The EMAP classification system is an aggregation of the many subclasses of the US Fish and Wildlife Service's National Wetlands Inventory (NWI) classification system. This aggregation results in fewer wetland classes with more wetlands per class than the NWI system. Aggregation of the NWI classification was based primarily on dominant vegetation cover, flooding regimes, dominant water source, and adjacency to rivers and lakes. We evaluated the EMAP classification system and sampling design using NWI digital wetlands data for portions of Illinois, Washington, North Dakota, and South Dakata. Relative numbers of wetlands, total areas, average areas, and common versus rare classes were compared between the EMAP and NWI classification systems. As expected, the EMAP classification provided fewer wetland polygons, each with larger areas, without altering total wetland area. Summary statistics comparing sample estimates to true population parameters (represented by the NWI data) demonstrated the effectiveness of the EMAP sampling design with the exception of rare EMAP classes in the selected regions. Although simple random sampling is inadequate for both large and small wetlands, the EMAP sampling design is readily adapted to provide better estimates for these categories. Aggregating the NWI classification to the EMAP classification provides fewer wetland classes, with more wetlands per class, for EMAP's annual reports and statistical summaries. The research in this report has been funded by the United States Environmental Protection Agency (EPA) under contracts 68-C8-0006 to ManTech Environmental Technology, Inc. and 68-03-3532 to The Bionetics Corporation. Mention of trade names does not constitute endorsement or recommendation for use.     

Use of sequential sampling of amphipod abundance to classify the biotic integrity of acid-sensitive lakes

A sequential sampling program using previously published zoobenthos data is described for ubiquitous, cost-effective biomonitoring of the effects of lake acidification. Spring densities of the littoral amphipodHyalella azteca are quantitatively sorted into five abundance catagories. An essential step in the a priori definition of decision criteria is the stratification of proportional densities per unit macrophyte biomass in relation to aqueous total phosphorus concentrations. Density rankings were related to lake acidity and to detailed lake-specific information on patterns ofHyalella life history and acid tolerance. Incorporation ofHyalella abundance as a potential metric for the assessment of the biological integrity of acid-sensitive waters is recommended. The temporal integration of transient changes in spring meltwater chemistry is an important rationale for the development of such biomonitoring procedures.     

特殊天气过程对大气污染物浓度的影响

本文采用绵阳市１９８２年秋季－１９８９年秋季大气例行监测的ＳＯ２浓度值和采样时段的天气过程分析特殊天气过程对大气污染物浓度的影响。     

涪陵地区农田径流水体中三氮含量及分布特征

本文在涪陵地区大面积和定点采集了农田径流水样品，测定了径流水体中的三氮含量。探讨了径流水体三氮随产流时间的变化，分析了干旱时间，水体流动等因素对三氮含量的影响。结果表明，干旱时间，径流水体流动对三氮含量有一定的影响。经统计分析，涪陵地区农田径流水体中的ＮＨ３－Ｎ，ＮＯ３＾－－Ｎ，ＮＯ２＾－－Ｎ和Ｔ－Ｎ含量分别为０．８４０，０．９７０，０．１０７和２．０７ｍｇ／ｌ。     

A CLOSED SYSTEM SAMPLE TRANSFER DEVICE FOR VOLATILE ORGANIC COMPOUNI)S1

ABSTRACT: A sample transfer device was designed to provide a closed loop sampling system between a ground water sampling pump and a 40 ml volatile organic compound (VOC) vial. The same attachment can also be used with a bailer. The unit is constructed of a poly-tetrafluoroethylene (PTFE) body into which two stainless steel needles are press fitted. The needles puncture the Teflon septum of a vial; fluid flows through the longer needle into the vial and exits the vial from the shorter needle. The device eliminates sample transfer bias associated with head space, visible gas bubbles, and atmospheric contamination. Field sampling designed to determine differences in trichloroethylene (TCE) concentrations presumedly due to the device were statistically significant in one case, and insignificant in the second.