Evaluating sampling designs by computer simulation: a case study with the Missouri bladderpod

To effectively manage rare populations, accurate monitoring data are critical. Yet many monitoring programs are initiated without careful consideration of whether chosen sampling designs will provide accurate estimates of population parameters. Obtaining accurate estimates is especially difficult when natural variability is high, or limited budgets determine that only a small fraction of the population can be sampled. The Missouri bladderpod, Lesquerella filiformis Rollins, is a federally threatened winter annual that has an aggregated distribution pattern and exhibits dramatic interannual population fluctuations. Using the simulation program SAMPLE, we evaluated five candidate sampling designs appropriate for rare populations, based on 4 years of field data: (1) simple random sampling, (2) adaptive simple random sampling, (3) grid-based systematic sampling, (4) adaptive grid-based systematic sampling, and (5) GIS-based adaptive sampling. We compared the designs based on the precision of density estimates for fixed sample size, cost, and distance traveled. Sampling fraction and cost were the most important factors determining precision of density estimates, and relative design performance changed across the range of sampling fractions. Adaptive designs did not provide uniformly more precise estimates than conventional designs, in part because the spatial distribution of L. filiformis was relatively widespread within the study site. Adaptive designs tended to perform better as sampling fraction increased and when sampling costs, particularly distance traveled, were taken into account. The rate that units occupied by L. filiformis were encountered was higher for adaptive than for conventional designs. Overall, grid-based systematic designs were more efficient and practically implemented than the others. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Variables influencing one-zero and instantaneous time sampling outcomes

Previous studies have shown that instantaneous time sampling results are more highly correlated with true duration than are one-zero sampling results. One-zero results, however, reflected a composite of both duration and frequency better than did instantaneous results. It is shown in this analysis that these outcomes are the logical result of the definitions of the two sampling modes. When interval lengths meet specific requirements, correct frequency counts can be obtained with either mode and systematic duration error with one-zero sampling can be eliminated by subtracting frequency from the number of intervals scored ‘one.’     

Weaning of free-ranging infant baboons (Papio cynocephalus) as indicated by one-zero and instantaneous sampling of feeding

Weaning from the nipple and the use of solid foods were studied by one-zero and instantaneous sampling during the first year of life for 46 baboon infants. By the end of 1 year, infant baboons were nearing independence from the mother for nourishment and transportation and were competently foraging for insects and several plant foods. Using on-nipple as an index of waning dependence and the transition from riding on the mother to walking as a validity criterion, the two sampling methods yielded comparable scores which were valid indicants of developing independence.     

Beyond origami: using behavioural observations as a strategy to improve trap design

In contrast to ad hoc methods of developing traps for pest monitoring systems, a systematic approach using direct observation of animals allowed a greater understanding of the reasons why trap catch was significantly different in traps of basically similar design. The information gained using this approach could then be used to guide the further development of the trap. The same feature on two related designs of cockroach trap was varied: the slope of the ramp leading into the trap was either 60°, 30°, or 0°. The 30° ramp version of both traps caught significantly more Blattella germanica (L.) (Dictyoptera: Blattellidae). The 60° and 0° ramp versions both caught equal, lower, numbers but observation showed that these net catches were achieved by quite different means; few insects entered over the 60° ramps but none escaped, whereas all entered over the 0° ramps but half escaped. Similar approaches could be applied to other insect-trap systems.     

An empirical evaluation of instantaneous and one-zero sampling of chimpanzee behavior

The behavior category in progress at theend of every 15 seconds of observation of chimpanzee behavior was recorded (instantaneous sampling) as was the occurrence or nonoccurrence of all defined categoriesduring every 15 second observation interval (one-zero sampling). The scores obtained using the above procedures were then correlated with the percent of net observation time, hourly rate, and mean bout duration of the behavior categories. One-zero sampling scores correlated very strongly with percent of net observation time and moderately with hourly rate and mean bout duration. Instantaneous sampling scores correlated very strongly with percent of net observation time and moderately with hourly rate and mean bout duration.     

An empirical comparison of one-zero,focal-animal,and instantaneous methods of sampling spontaneous primate social behavior

InJ. Altmann's review of methods used to sample spontaneously occurring social behavior, the one-zero method, which has a history of over 40 years of use with human and animal research, was severely criticized and was the only technique for which no use whatsoever was recommended. Substantial justification for this recommendation would raise serious questions about widely cited primate research from laboratories at Cambridge, Wisconsin, and elsewhere, where one-zero sampling has been often used.Altmann's nonempirical consideration of one-zero sampling is based upon assumptions which are sometimes unnecessarily limiting or probably incorrect and which are not supported by any data. An empirical comparison of one-zero sampling with two techniques considered useful byAltmann reveals contradictions in her recommendations and suggests that the one-zero method is a convenient way to combine the actual rate and duration of a spontaneously occurring behavior into a single index of social relatedness.     

Properties of one-zero scores in observational studies of primate social behavior: The effect of assumptions on empirical analyses

Empirical analyses of techniques for observing spontaneous social behavior have been guided by implicit assumptions about the techniques’ validity, reliability, and comparability. The actual duration and actual frequency of a behavior have been used as intuitive standards of validity. Noncorrespondence among absolute values obtained from these measures and from one-zero scores has been taken to mean that one-zero scores are invalid. An analysis of macaque and gelada grooming relationships demonstrated how unjustified assumptions about absolute values can affect conclusions. A statistical comparison of four types of observation scores, and a multiple-regression analysis of one-zero scores, contradicted assumptions made previously about reliability and validity. The four methods were comparable and all were reasonably accurate.     

Closed testing with Globaltest,with application in metabolomics

The Globaltest is a powerful test for the global null hypothesis that there is no association between a group of features and a response of interest, which is popular in pathway testing in metabolomics. Evaluating multiple feature sets, however, requires multiple testing correction. In this paper, we propose a multiple testing method, based on closed testing, specifically designed for the Globaltest. The proposed method controls the familywise error rate simultaneously over all possible feature sets, and therefore allows post hoc inference, that is, the researcher may choose feature sets of interest after seeing the data without jeopardizing error control. To circumvent the exponential computation time of closed testing, we derive a novel shortcut that allows exact closed testing to be performed on the scale of metabolomics data. An R package ctgt is available on comprehensive R archive network for the implementation of the shortcut procedure, with applications on several real metabolomics data examples.     

Stipa tenacissima aerial biomass estimated at regional scale in an Algerian steppe, using geostatistical tools

Data from systematic sampling may be independent or autocorrelated. In the latter case geostatistical tools are used to identify the spatial patterns within the universe sampled. Special formulas have been derived by Russo & Bresler (1982) to estimate the variance of a value averaged over several transect samples. We applied these formulas to the green biomass of the dominant perennial steppe grass, Stipa tenacissima or alfa, in a 400 km² region in North-West Algeria; thirty years ago, this region was considered one of the best sites for alfa. A two-level sampling design was implemented with stratification of the region and systematic sampling within each stratum; globally the study included fifteen transects, representing 713 1 m² quadrats. Autocorrelation up to 500 meters was detected in five semi-variograms or correlograms, which were fitted to linear models with a sill. Biomass averaged only 165 (±55) kg ha^-1. We discuss the processes that have lead to the rapid degradation of alfa steppes in northern Algeria and the variation in spatial patterns of alfa stands. Ignoring autocorrelation in systematic sampling leads to biased estimates of variances and standard errors.     

Random median sampling to enhance the precision of population estimates

We describe the characteristics of a sampling procedure called random median sampling that was proposed to enhance the precision of population estimates. In performing random median sampling, we first select a sampling item at random from the sampling area. We roughly compare the abundance of individuals in the selected item with that of the adjacent two items in order to identify the item that has median abundance, i.e., the item that has the second largest abundance among the three items. We count the number of individuals of the item having the median abundance. This procedure is repeated n times in the sampling area (i = 1, 2, ..., n). Let m _i be the ith median abundance. The estimates of the mean abundance per sampling item and the variance of estimates are given by Σm _i /n and Σ(m _i –Σm _i /n)²/n(n – 1), respectively. This method is a local application of the median ranked set sampling that was proposed by Muttlak (J Appl Stat Sci 6:245–255, 1997). Random median sampling is effective when the correlation coefficient between adjacent items is small. If the correlation coefficient is close to zero, random median sampling reduces the variance of estimates to 45 or 32% of that in simple random sampling when the distribution follows a normal distribution or a Laplace distribution, respectively. The sample size required to achieve a given precision of estimate decreases accordingly. The effectiveness of random median sampling, however, is small if the correlation coefficient is large. The condition in which random median sampling is superior to simple random sampling is also discussed.     

Harvest-based Bayesian estimation of sika deer populations using state-space models

We have estimated the number of sika deer, Cervus nippon, in Hokkaido, Japan, with the aim of developing a management program that will reduce the level of agricultural damage caused by these deer. A population index that is defined by the population divided by the population of 1993 is first estimated from the data obtained during a spotlight survey. A generalized linear mixed model (GLMM) with corner point constraints is used in this estimation. We then estimate the population from the index by evaluating the response of index to the known amount of harvest, including hunting. A stage-structured model is used in this harvest-based estimation. It is well-known that estimates of indices suffer from large observation errors when the probability of the observation fluctuates widely; therefore, we apply state-space modeling to the harvest-based estimation to remove the observation errors. We propose the use of Bayesian estimation with uniform prior-distributions as an approximation of the maximum likelihood estimation, without permitting an arbitrary assumption that the parameters fluctuate following prior-distributions. We are able to demonstrate that the harvest-based Bayesian estimation is effective in reducing the observation errors in sika deer populations, but the stage-structured model requires many demographic parameters to be known prior to running the analyses. These parameters cannot be estimated from the observed time-series of the index if there is insufficient data. We then construct a univariate model by simplifying the stage-structured model and show that the simplified model yields estimates that are nearly identical to those obtained from the stage-structured model. This simplification of the model simultaneously clarifies which parameter is important in estimating the population. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Addressing Temporal Variability in Bird Calling with Design and Estimation: A Northern Bobwhite Example

Imprecise or biased density estimates can lead to inadequate conservation action, overexploitation of game species, or lost recreational opportunities. Common approaches to estimating density of avian populations often either ignore the probability that an individual is present within the sampling area but is not available to be sampled (e.g., not vocalizing), or do not consider covariates that could influence availability. Additionally, management decisions made at the management unit scale are often informed by inadequate monitoring practices, such as limited sampling intensity. In such cases, management agencies calculate density by applying correction factors (e.g., detection probabilities estimated using empirical data from a different study system) to count data, rather than estimating a detection function directly using statistical models. We conducted a simulation study using northern bobwhite (Colinus virginianus; bobwhite) as a model species to quantify the consequences of mis-specifying avian point count models on bias and precision of density estimates. We compared bias and precision of estimates from a fully specified distance-sampling model that estimates availability and detection to 4 different mis-specified approaches, including 2 approaches to calculating density using correction factors. Using correction factors to calculate density produced estimates with low bias but relatively lower precision compared to the fully specified model (CV of density estimates at 35 sites over 5 years: fully specified = 10%, correction factors = 25% and 30%). Although the mean precision and bias of the fully specified model improved with more data (70 sites over 5 years, CV = 9%; 35 sites over 10 years, CV = 9%), precision of correction factors did not (70 sites over 5 years, CV = 22% and 27%; 35 sites over 10 years, CV = 24% and 29%). The fully specified model captured the underlying temporal variation in detection and availability. Increasing sampling duration from 5 to 10 years improved modeled estimates of growth rate, even for mis-specified models, but not derived growth rates using pre-determined detection functions. We demonstrated that conducting point counts 3 times/year at a feasible number of sites can produce relatively unbiased estimates of bobwhite density. Pre-determined detection functions can be fortuitously unbiased for certain years, but they are not a reliable method for determining density or identifying trends in density over time. © 2020 The Wildlife Society.     

Error estimation and global fitting in transverse-relaxation dispersion experiments to determine chemical-exchange parameters

Off-resonance effects can introduce significant systematic errors in R₂ measurements in constant-time Carr-Purcell-Meiboom-Gill (CPMG) transverse relaxation dispersion experiments. For an off-resonance chemical shift of 500 Hz, ¹⁵N relaxation dispersion profiles obtained from experiment and computer simulation indicated a systematic error of ca. 3%. This error is three- to five-fold larger than the random error in R₂ caused by noise. Good estimates of total R₂ uncertainty are critical in order to obtain accurate estimates in optimized chemical exchange parameters and their uncertainties derived from χ² minimization of a target function. Here, we present a simple empirical approach that provides a good estimate of the total error (systematic + random) in ¹⁵N R₂ values measured for the HIV protease. The advantage of this empirical error estimate is that it is applicable even when some of the factors that contribute to the off-resonance error are not known. These errors are incorporated into a χ² minimization protocol, in which the Carver–Richards equation is used fit the observed R₂ dispersion profiles, that yields optimized chemical exchange parameters and their confidence limits. Optimized parameters are also derived, using the same protein sample and data-fitting protocol, from ¹H R₂ measurements in which systematic errors are negligible. Although ¹H and ¹⁵N relaxation profiles of individual residues were well fit, the optimized exchange parameters had large uncertainties (confidence limits). In contrast, when a single pair of exchange parameters (the exchange lifetime, τ_ex, and the fractional population, p_a), were constrained to globally fit all R₂ profiles for residues in the dimer interface of the protein, confidence limits were less than 8% for all optimized exchange parameters. In addition, F-tests showed that quality of the fits obtained using τ_ex, p_a as global parameters were not improved when these parameters were free to fit the R₂ profiles of individual residues. Finally, nearly the same optimized global τ_ex, p_a values were obtained, when the ¹H and ¹⁵N data sets for residues in the dimer interface, were fit independently; the difference in optimized global parameters, ca. 10%, was of marginal significance according to the F-test.     

Brazilian red propolis reduces orange-complex periodontopathogens growing in multispecies biofilms

This study investigated the antimicrobial effects of the ethanolic extract of Brazilian red propolis (BRP) on multispecies biofilms. A seven-day-old subgingival biofilm with 32 species was grown in a Calgary device. Biofilms were treated with BRP (1,600, 800, 400 and 200?μg ml^?1) twice a day for 1?min, starting from day 3. Chlorhexidine (0.12%) and dilution-vehicle were used as positive and negative controls, respectively. On day 7, metabolic activity and the microbial composition of the biofilms by DNA-DNA hybridization were determined. The viability data were analyzed by one-way ANOVA followed by Tukey’s post hoc, whereas the microbial composition data were transformed via BOX-COX and analyzed using Dunnett’s post hoc. BRP (1,600?μg ml^?1) decreased biofilm metabolic activity by 45%, with no significant difference from chlorhexidine-treated samples. BRP (1,600?μg ml^?1) and chlorhexidine significantly reduced levels of 14 bacterial species compared to the vehicle control. Taken together, BRP showed promising antimicrobial properties which may be useful in periodontal disease control.     

单木生物量模型估计区域尺度生物量的不确定性

采用系统抽样体系江西省固定样地杉木连续观测数据和生物量数据,通过Monte Carlo法反复模拟由单木生物量模型推算区域尺度地上生物量的过程,估计了江西省杉木地上总生物量。基于不同水平建模样本量n及不同决定系数R~2的设计,分别研究了单木生物量模型参数变异性及模型残差变异性对区域尺度生物量估计不确定性的影响。研究结果表明:2009年江西省杉木地上生物量估计值为(19.84±1.27)t/hm~2,不确定性占生物量估计值约6.41%。生物量估计值和不确定性值达到平稳状态所需的运算时间随建模样本量及决定系数R~2的增大而减小;相对于模型参数变异性,残差变异性对不确定性的影响更小。     

A comparison of two tubificid oligochaete species as candidates for sublethal bioassay tests relevant to subtropical and tropical regions

Two tubificid oligochaetes, Branchiura sowerbyi and Tubifex tubifex, were evaluated as potential test organisms for sediment bioassays. We attempt to reproduce the sediment bioassay proposed by Reynoldson et al. (1991) using his strain of Tubifex tubifex and his reference sediment and to compare this technique using Branchiura sowerbyi. This species was chosen because it is more common and dominant in tropical and subtropical environments than Tubifex tubifex. Data on survival and reproduction were obtained for both species, and growth estimates were obtained for B. sowerbyi. The sublethal bioassay with T. tubifex confirmed earlier estimates of a test duration of 4 weeks at 22.5 °C. B. sowerbyi cultures can produce usable estimates in 21 days at 30 °C.     

Breeding dispersal in an isolated population of Spotted Owls Strix occidentalis: evidence for improved reproductive output

Breeding dispersal among territorial species is of interest to population biologists because leaving a territory carries fundamental risks to the dispersing individuals, and this may not outweigh the costs of maintaining the territory. Most studies of breeding dispersal have focused on species inhabiting spatially open populations, in which undetected emigration could impart a negative bias to estimates of dispersal. We studied breeding dispersal in an isolated (spatially closed) population of California Spotted Owl Strix occidentalis occidentalis in southern California for 12 years to assess factors that might correlate with breeding dispersal. Twenty‐nine per cent (n = 47) of territorial females and 19% (n = 35) of territorial males dispersed at least once during the study. Annually, 0–13% of the territorial females and 0–12% of the territorial males dispersed. Among a set of a priori and post hoc models related to breeding dispersal, the top a priori model indicated that birds having higher reproductive output relative to the population average were less likely to disperse. A post hoc model based on an index of territory quality was ranked higher than the top a priori model and indicated that birds occupying higher quality territories were less likely to disperse. These two models were correlated and represented short‐ and long‐term reproductive performance, respectively. Birds that dispersed also failed to fledge young in the year prior to dispersal, but the failure to fledge young did not, by itself, explain dispersal. Because Spotted Owls are long‐lived, they may ultimately improve their reproduction by dispersing given that they would have future opportunities to breed over the long term. Birds whose mates are likely to have died tended to improve their reproductive success, whereas the relationship between reproductive success of birds that divorced was less clear. Substantial variation in breeding dispersal was unexplained by our analysis so it is likely that the motivation to disperse was a complex process in this population.     

How to obtain a precise and representative estimate for parameters in LCA

Background, Aim and Scope  Quite often there is need for precise and representative parameters in LCA studies. Probably the most relevant have direct influence on the functional unit, whose definition is crucial in the conduct of any LCA. Changes in the functional unit show directly in LCI and LCIA results. In comparative assertions, a bias in the functional unit may lead to a bias in the overall conclusions. Since quantitative data for the functional unit, such as geometric dimensions and specific weight, often vary, the question arises how to determine the functional unit, especially if a comparative assertion shall be representative for a region or market. Aim and scope of the study is to develop and apply methods for obtaining precise and representative estimates for the functional unit as one important parameter in an LCA study. Materials and Methods  Statistical sampling is applied in order to get empirical estimates for the weight of yoghurt cups, as a typical parameter for the functional unit. We used a two-stage sampling design, with stratified sampling in the first stage and three different sampling designs in the second stage, namely stratified, clustered, and a posteriori sampling. Sampling designs are motivated and described. In a case study, they are each used to determined a representative weight for 150 g yoghurt cups in Berlin, at the point of sale and within a specific time. In the first sampling stage, food markets are randomly selected, while in the second stage, yoghurt cups in these food markets are sampled. The sampling methods are applicable due to newly available internet data. These data sources and their shortcomings are described. Results  The random sampling procedure yields representative estimates, which are compared to figures for market leaders, i.e. yoghurt cups with very high occurrence in the supermarkets. While single types of yoghurt cups showed moderate uncertainty, representative estimates were highly precise. Discussion results show, for one, the performance of the applied statistical estimation procedures, and they show further that adding more information in the estimation procedure (on the shape of the cup, on the type of plastic, on the specific brand) helps reducing uncertainty. Conclusions  As conclusions, estimates and their uncertainty depend on the measurement procedure in a sensitive manner; any uncertainty information should be coupled with information on the measurement procedure, and it is recommended to use statistical sampling in order to reduce uncertainty for important parameters of an LCA study. Recommendations and Perspectives  Results for market leaders differed considerably from representative estimates. This implies to not use market leader data, or data with a high market share, as substitute for representative data in LCA studies. Statistical sampling has been barely used for Life Cycle Assessment. It turned out to be a feasible means for obtaining highly precise and representative estimates for the weight of yoghurt cups in the case study, based on empirical analysis. Further research is recommended in order to detect which parameters should best be investigated in LCA case studies; which data sources are available and recommended, and which sampling designs are appropriate for different application cases. ESS-Submission Editor: Seungdo Kim. PhD (kimseun@msu.edu)     

Predicting and correcting bias caused by measurement error in line transect sampling using multiplicative error models

Line transect sampling is one of the most widely used methods for animal abundance assessment. Standard estimation methods assume certain detection on the transect, no animal movement, and no measurement errors. Failure of the assumptions can cause substantial bias. In this work, the effect of error measurement on line transect estimators is investigated. Based on considerations of the process generating the errors, a multiplicative error model is presented and a simple way of correcting estimates based on knowledge of the error distribution is proposed. Using beta models for the error distribution, the effect of errors and of the proposed correction is assessed by simulation. Adequate confidence intervals for the corrected estimates are obtained using a bootstrap variance estimate for the correction and the delta method. As noted by Chen (1998, Biometrics 54, 899-908), even unbiased estimators of the distances might lead to biased density estimators, depending on the actual error distribution. In contrast with the findings of Chen, who used an additive model, unbiased estimation of distances, given a multiplicative model, lead to overestimation of density. Some error distributions result in observed distance distributions that make efficient estimation impossible, by removing the shoulder present in the original detection function. This indicates the need to improve field methods to reduce measurement error. An application of the new methods to a real data set is presented.     

A correction for allele frequency estimates derived from isofemale lines

Isofemale lines are commonly used inDrosophila and other genera for the purpose of assaying genetic variation. Isofemale lines can be kept in the laboratory for many generations before genetic work is carried out, and permit the confirmation of newly discovered alleles. A problem not realized by many workers is that the commonly used estimate of allele frequency from these lines is biased. This estimation bias occurs at all times after the first laboratory generation, regardless of whether single individuals or pooled samples are used in each well of an electrophoretic gel. This bias can potentially affect the estimation of population genetic parameters, and in the case of rare allele analysis it can cause gross overestimates of gene flow. This paper provides a correction for allele frequency estimates derived from isofemale lines for any time after the lines are established in the laboratory. When pooled samples are used, this estimator performs better than the standard estimator at all times after the first generation. The estimator is also insensitive to multiple inseminations. After the lines have drifted oneN _e generations, multiple inseminations actually make the new estimator perform better than it does in singly inseminated females. Simulations show that estimates made using either estimator after the lines have drifted to fixation have a much greater error associated with their use than do those estimates made earlier in time using the correction. In general it is better to use corrected estimates of gene frequency soon after lines are established than to use uncorrected estimates made after the first laboratory generation. This work was supported by an NSERC fellowship to A.D.L.