When Is Rapid On-Site Evaluation Cost-Effective for Fine-Needle Aspiration Biopsy?

Background

Rapid on-site evaluation (ROSE) can improve adequacy rates of fine-needle aspiration biopsy (FNAB) but increases operational costs. The performance of ROSE relative to fixed sampling depends on many factors. It is not clear when ROSE is less costly than sampling with a fixed number of needle passes. The objective of this study was to determine the conditions under which ROSE is less costly than fixed sampling.

Methods

Cost comparison of sampling with and without ROSE using mathematical modeling. Models were based on a societal perspective and used a mechanistic, micro-costing approach. Sampling policies (ROSE, fixed) were compared using the difference in total expected costs per case. Scenarios were based on procedure complexity (palpation-guided or image-guided), adequacy rates (low, high) and sampling protocols (stopping criteria for ROSE and fixed sampling). One-way, probabilistic, and scenario-based sensitivity analysis was performed to determine which variables had the greatest influence on the cost difference.

Results

ROSE is favored relative to fixed sampling under the following conditions: (1) the cytologist is accurate, (2) the total variable cost ($/hr) is low, (3) fixed costs ($/procedure) are high, (4) the setup time is long, (5) the time between needle passes for ROSE is low, (6) when the per-pass adequacy rate is low, and (7) ROSE stops after observing one adequate sample. The model is most sensitive to variation in the fixed cost, the per-pass adequacy rate, and the time per needle pass with ROSE.

Conclusions

Mathematical modeling can be used to predict the difference in cost between sampling with and without ROSE.     

Estimating acridid densities in grassland habitats: a comparison between presence-absence and abundance sampling designs

Sampling methods to estimate acridid density per surface area unit in grassland habitats were compared using presence-absence data and count data. Sampling plans based on 6 yr of surveys were devised to estimate the density of Chorthippus spp., Euchorthippus spp., and Calliptamus italicus L. These acridids represented >90% of species in the study area. Sampling plans based on count data provided a reasonable tool when densities were >1/m(2) and when the level of precision was 0.20-0.30. A binomial sampling plan can be used to estimate C. italicus density with a level of precision >or=0.28. Sampling characteristics, i.e., estimated mean, actual precision, and sample size, were established on validation data sets with bootstrapping analysis. Sampling costs were also calculated according to density-dependent functions. Comparison between binomial sampling and enumerative sampling of C. italicus showed that binomial sampling required less time than enumerative sampling when densities were 0.35. Plot area had no significant effect on sample variances of counts.     

Atlantic bluefin tuna in the Gulf of Maine,II: precision of sampling designs in estimating seasonal abundance accounting for tuna behaviour

A primary challenge of animal surveys is to understand how to reliably sample populations exhibiting strong spatial heterogeneity. Building upon recent findings from survey, tracking and tagging data, we investigate spatial sampling of a seasonally resident population of Atlantic bluefin tuna in the Gulf of Maine, Northwestern Atlantic Ocean. We incorporate empirical estimates to parameterize a stochastic population model and simulate measurement designs to examine survey efficiency and precision under variation in tuna behaviour. We compare results for random, systematic, stratified, adaptive and spotter-search survey designs, with spotter-search comprising irregular transects that target surfacing schools and known aggregation locations (i.e., areas of expected high population density) based on a priori knowledge. Results obtained show how survey precision is expected to vary on average with sampling effort, in agreement with general sampling theory and provide uncertainty ranges based on simulated variance in tuna behaviour. Simulation results indicate that spotter-search provides the highest level of precision, however, measurable bias in observer-school encounter rate contributes substantial uncertainty. Considering survey bias, precision, efficiency and anticipated operational costs, we propose that an adaptive-stratified sampling alone or a combination of adaptive-stratification and spotter-search (a mixed-layer design whereby a priori information on the location and size of school aggregations is provided by sequential spotter-search sampling) may provide the best approach for reducing uncertainty in seasonal abundance estimates.

Spatial pattern and sequential sampling of squash bug (Heteroptera: Coreidae) adults in watermelon

Spatial distribution patterns of adult squash bugs were determined in watermelon, Citrullus lanatus (Thunberg) Matsumura and Nakai, during 2001 and 2002. Results of analysis using Taylor's power law regression model indicated that squash bugs were aggregated in watermelon. Taylor's power law provided a good fit with r2 = 0.94. A fixed precision sequential sampling plan was developed for estimating adult squash bug density at fixed precision levels in watermelon. The plan was tested using a resampling simulation method on nine and 13 independent data sets ranging in density from 0.15 to 2.52 adult squash bugs per plant. Average estimated means obtained in 100 repeated simulation runs were within the 95% CI of the true means for all the data. Average estimated levels of precision were similar to the desired level of precision, particularly when the sampling plan was tested on data having an average mean density of 1.19 adult squash bugs per plant. Also, a sequential sampling for classifying adult squash bug density as below or above economic threshold was developed to assist in the decision-making process. The classification sampling plan is advantageous in that it requires smaller sample sizes to estimate the population status when the population density differs greatly from the action threshold. However, the plan may require excessively large sample sizes when the density is close to the threshold. Therefore, an integrated sequential sampling plan was developed using a combination of a fixed precision and classification sequential sampling plans. The integration of sampling plans can help reduce sampling requirements.     

Cost/benefit and the effect of sample preservation procedures on quantitative patterns in benthic ecology

Some benthic assemblages studies have tested the effects of different preservation procedures on biomass, but their influence on quantitative patterns (number of species and abundance) is still unclear. We evaluated the influence of two sample preservation procedures on quantitative patterns in benthic ecology. Ten sampling points were systematically interspersed on two types of sediment (sandy and muddy). At each sediment type, samples from five sampling points were fixed in 10% formalin, and the other five points were preserved in 70% ethanol (without previous fixation). Three replicates were collected at each sampling point, and samples were washed in 0.5 mesh size and sorted in laboratory. A cost/benefit analysis was performed considering the washing time in laboratory and the costs of substances. A total of 1970 individuals were collected (muddy sediment: 132; sandy sediment: 1838), belonging to 121 taxa (muddy: 49; sandy: 83). Assemblages preserved in ethanol were composed of 795 individuals and 80 taxa, while those fixed with formalin had 1173 individuals and 94 taxa. Polychaeta predominated as the most abundant group for both preservation procedures. For the whole benthic community, significant differences occurred only between sediment types. Significant differences in the number of individuals of polychaetes were observed for the different preservation procedures in sandy sediment. Ethanol has the best cost/benefit ratio in both sediment types due to additional costs to attend safety requirements for formalin-fixed samples. Further studies should evaluate how quantitative patterns are affected by exposure time of preservation, anesthesia interaction, and morphological deformations (e.g. impossibility of identification).     

Fixed precision sequential sampling plans for the greenbug and bird cherry-oat aphid (Homoptera: Aphididae) in winter wheat

The numbers of greenbugs, Schizaphis graminum (Rondani), and bird cherry-oat aphids, Rhopalosiphum padi L., per wheat tiller (stem) were estimated in 189 production winter wheat (Triticum aestivum L.) fields located throughout Oklahoma. Taylor's power law regressions were calculated from these data and used to construct fixed precision sequential sampling schemes for each species. An evaluation data set was constructed from 240 samples taken during three growing seasons from winter wheat fields at four locations in Oklahoma. Wheat cultivar and growth stage were recorded for each field on the day of sampling. Taylor's power law parameters for evaluation fields differed significantly for both species among growing seasons, locations, and plant growth stages. Median precision achieved using the fixed precision sequential sampling schemes for each species departed <20% from expected precision over the range population intensity in the evaluation data. For the 10% of samples with greatest deviation between observed and expected precision, observed precision was 13.8-81.8% greater than that expected precision depending on aphid species and population intensity. For the greenbug, the distribution of the percentage deviation between observed and expected precision was positively skewed, so that the sampling scheme tended to over-predict precision. For the bird cherry-oat aphid, the distribution was more symmetric. Even though precision observed using the sampling schemes frequently varied from expected precision, because of the inevitable consequence of sampling error and environmental variation, the sampling schemes yielded median observed precision levels close to expected precision levels over a broad range of population intensity.     

Sampling Strategies in Antimicrobial Resistance Monitoring: Evaluating How Precision and Sensitivity Vary with the Number of Animals Sampled per Farm

Because antimicrobial resistance in food-producing animals is a major public health concern, many countries have implemented antimicrobial monitoring systems at a national level. When designing a sampling scheme for antimicrobial resistance monitoring, it is necessary to consider both cost effectiveness and statistical plausibility. In this study, we examined how sampling scheme precision and sensitivity can vary with the number of animals sampled from each farm, while keeping the overall sample size constant to avoid additional sampling costs. Five sampling strategies were investigated. These employed 1, 2, 3, 4 or 6 animal samples per farm, with a total of 12 animals sampled in each strategy. A total of 1,500 Escherichia coli isolates from 300 fattening pigs on 30 farms were tested for resistance against 12 antimicrobials. The performance of each sampling strategy was evaluated by bootstrap resampling from the observational data. In the bootstrapping procedure, farms, animals, and isolates were selected randomly with replacement, and a total of 10,000 replications were conducted. For each antimicrobial, we observed that the standard deviation and 2.5–97.5 percentile interval of resistance prevalence were smallest in the sampling strategy that employed 1 animal per farm. The proportion of bootstrap samples that included at least 1 isolate with resistance was also evaluated as an indicator of the sensitivity of the sampling strategy to previously unidentified antimicrobial resistance. The proportion was greatest with 1 sample per farm and decreased with larger samples per farm. We concluded that when the total number of samples is pre-specified, the most precise and sensitive sampling strategy involves collecting 1 sample per farm.     

淀山湖鱼类生物多样性调查样本量的优化设计

样本量大小影响估算鱼类种群动态和鱼类群落特征的准确性和精确度.本文以淀山湖渔业资源调查为例,研究估算淀山湖鱼类群落特征所需的样本量大小.2010年7月—2011年6月研究期间每月进行一次淀山湖渔业资源调查,共捕获14科45种鱼类.利用重采样方法,估算淀山湖渔业资源调查最优调查频次和最佳站点数.结果表明: 在淀山湖渔业资源调查中,站点数和调查频次呈负相关关系;保持95%的探测率探测90%的物种,每年调查11和12次相应需要设置21和19个站点.Shannon多样性指数随着每次调查站点数的增多而变大,增长到一定程度之后逐渐趋于稳定.淀山湖鱼类群落的物种多样性调查最佳站点数为21.本文的研究方法和结果可以为其他类似研究提供借鉴.     

The ‘standardized search’: An improved way to conduct bird surveys

Abstract Bird surveys are among the most widely used biodiversity inventories and serve as the basis for an increasing proportion of pure and applied ecological research. It is rarely possible to conduct exhaustive censuses of all individuals present at a particular site, so stopping rules are routinely used to determine when sampling should finish. Most bird survey methods use (implicit) effort‐based stopping rules, either fixed times, fixed sampling areas (quadrats) or both, to standardize samples of different sites. If between‐site variation is high, however, a fixed sampling effort will generate samples of variable completeness with samples from smaller, less complex sites being more representative and complete than samples from larger, more complex sites. More importantly, quadrat‐based methods shift the scope of the overall study from bird occurrence in sites to bird occurrence in quadrats within sites, diminishing the impact of the research given that results cannot be extrapolated to relevant biological and management scales. Here I advocate an alternative means of conducting bird surveys, whereby the entire site is sampled and a results‐based stopping rule is used to ensure sample completeness is uniform across all sites. For example, a researcher may decide to continue sampling each site until two or fewer previously unencountered species are recorded in a 40‐min period. Samples of different sites will vary in both area and duration but will all be equivalently accurate estimates of species richness. This approach allows the avifauna of entire sites (whether territories, woodland remnants or catchments) to be sampled and compared directly, generating results and implications at the appropriate scale. In addition to yielding reliable measures of species richness, data collected this way can be used to calculate estimates of sample completeness and species incidence, two valuable metrics for ecological studies. This paper includes detailed worked examples of how to conduct a ‘standardized search’ and calculate sample completeness and species incidence estimates. I encourage further research on bird survey methods, and suggest that most current methods are insufficient, inconsistent and unreliable.     

Bayesian spatial modeling of moose count data: increasing estimator efficiency and exploring ecological hypotheses

Moose management throughout much of Alaska and Canada relies on aerial count data, which are commonly collected using the geospatial population estimator (GSPE) protocol. The GSPE uses a model-based analytical approach and finite-population block kriging to estimate abundance from a collection of sampled survey units. Widespread implementation and well-documented analytical software have resulted in reliable estimates of moose abundance, density, and composition across a large proportion of their range. Analysis is conducted almost exclusively using the GSPE software, which fits a fixed model structure to data collected within a single year. The downside of this approach to analysis is that the fixed model structure is inefficient for estimation, leading to more field effort than would otherwise be necessary to achieve a desired level of estimator precision. We developed a more easily modified and flexible Bayesian spatial general additive model approach (BSG) that accommodates spatial and temporal covariates (e.g., habitat characteristics, trend), multiple survey events, prior information, and incomplete detection. Using a series of 6 GSPE surveys conducted in Yukon-Charley Rivers National Preserve, Alaska, USA, from 2003–2019, we established the equivalence of the 2 approaches under similar model structures. We then extended the BSG to demonstrate how a more comprehensive approach to analysis can affect estimator precision and be used to assess ecological relationships. The precision of annual abundance estimators from the BSG were improved by an average of 43% over those based on the standard GSPE analysis, highlighting the very real costs of assuming a fixed (i.e., suboptimal) model structure. The population increased at a rate of 2.3%/year (95% CrI = 0.8–3.8%), and the increase was largely explained by a parallel increase in wildfire extent (i.e., high quality moose habitat). These results suggest that our approach could be used to increase estimator efficiency or decrease future survey costs without any modifications to the basic protocol. While modification of the GSPE software is possible, practitioners may find the BSG approach more convenient for quickly developing model structures for a particular application, thereby allowing them to extract more information from existing and future datasets.     

Parameter Estimation in Stratified Cluster Sampling under Randomized Response Models for Sensitive Question Survey

Randomized response is a research method to get accurate answers to sensitive questions in structured sample survey. Simple random sampling is widely used in surveys of sensitive questions but hard to apply on large targeted populations. On the other side, more sophisticated sampling regimes and corresponding formulas are seldom employed to sensitive question surveys. In this work, we developed a series of formulas for parameter estimation in cluster sampling and stratified cluster sampling under two kinds of randomized response models by using classic sampling theories and total probability formulas. The performances of the sampling methods and formulas in the survey of premarital sex and cheating on exams at Soochow University were also provided. The reliability of the survey methods and formulas for sensitive question survey was found to be high.     

Measuring and controlling data quality in biological assemblage surveys with special reference to stream benthic macroinvertebrates

1. Biological assemblage surveys primarily aim to characterise species composition and relative abundance at one or more spatial or temporal scales. Data interpretation and conclusions are dependent on how well samples characterise the assemblage of interest. 2. Conventional measures of data quality, e.g. standard deviations or coefficients of variation, were designed for single variable estimation, and they are either insufficient or invalid for assessing the quality of data describing entire assemblages. Similarity indices take species composition and relative abundance into account and may be used to effectively measure and control the quality of data used to characterise assemblage structure. 3. The average Jaccard coefficient (JC) calculated across multiple pairs of replicate samples, i.e. autosimilarity JC (AJC), is conceptually and numerically related to the average coefficient of variation in the densities of all species recorded, a measure of sampling precision, and to the proportion of total species richness sampled, a measure of sampling accuracy. 4. We explored how AJC can be used to assess the effect of different potential sources of error on the quality of assemblage survey data, including the sampling effort used both within regions and at individual sites, the individuals collecting samples, sub‐sampling procedures, and consistency of taxon identification. 5. We found that the autosimilarity‐based approach overcomes most weaknesses associated with conventional measures of data quality and can be used to effectively measure and control the quality of assemblage survey data.     

Empirically simulated study to compare and validate sampling methods used in aerial surveys of wildlife populations

This paper compares the distribution, sampling and estimation of abundance for two animal species in an African ecosystem by means of an intensive simulation of the sampling process under a geographical information system (GIS) environment. It focuses on systematic and random sampling designs, commonly used in wildlife surveys, comparing their performance to an adaptive design at three increasing sampling intensities, using the root mean square errors (RMSE). It further assesses the impact of sampling designs and intensities on estimates of population parameters. The simulation is based on data collected during a prior survey, in which geographical locations of all observed animals were recorded. This provides more detailed data than that usually available from transect surveys. The results show precision of estimates to increase with increasing sampling intensity, while no significant differences are observed between estimates obtained under random and systematic designs. An increase in precision is observed for the adaptive design, thereby validating the use of this design for sampling clustered populations. The study illustrates the benefits of combining statistical methods with GIS techniques to increase insight into wildlife population dynamics.     

Temporal Patterns of Species Accumulation in a Survey of Lepidoptera in a Beech-Maple Forest

One of the most significant challenges to insect conservation is lack of information concerning species diversity and distribution. Because a complete inventory of all species in an area is virtually impossible, interest has turned to developing statistical techniques to guide sampling design and to estimate total species richness within a site. We used two such techniques, diversity partitioning and non-parametric richness estimation, to determine how variation in sampling effort over time affected species accumulation for a survey of Lepidoptera in an old-growth beech-maple forest. Temporal scaling of sampling effort had significant effects on two measures of species diversity. Increases in species richness were primarily driven by changes in species occurrences with season, while Shannon diversity was largely determined at the scale of individual sampling units (i.e. by spatial effects). Variation in sampling effort affected the values of the two most widely regarded richness estimators (ICE and Chao 2); neither diversity estimator achieved stable values across a range of sampling efforts. Even after 52 trap-nights and accounting for seasonality, rare species (singletons and uniques) remained a significant component of the moth community. To the extent that moth communities in other forest systems are similarly comprised of many rare species, non-parametric richness estimators should be expected to yield variable estimates with increased effort and should only be used to provide a minimum benchmark for predicting the number of species remaining to be sampled. Our results suggest the best strategy for a short-term survey of forest Lepidoptera should emphasize spreading sampling intervals throughout a given year rather than focusing on intensive sampling during a short time period or prolonged sampling over many years.     

Monitoring population size of mammals using a spotlight-count-based abundance index: How to relate the number of counts to the precision?

Abundance indices are widely used to study changes in population size in wildlife management. However, a truly appropriate measure of precision is often lacking in such studies. Statistically, the two crucial issues regarding the use of an abundance index are sampling and observability, which lead one to consider two kinds of errors, namely sampling and observation errors. The purpose of this methodological paper is to relate the number of counts to the precision of an abundance index by introducing the Hansen–Hurwitz–Bershad model which takes into account both sampling and observation errors. We illustrate this statistical approach in the case of a European rabbit (Oryctolagus cuniculus) abundance index based on spotlight counts, for two fixed spatial sampling units located in different ecological contexts. We show (i) that the usual sampling variance estimator is a downward-biased estimator of the total variance of the abundance index, (ii) that the bias of the usual variance estimator does not decrease when increasing the sampling size, (iii) that correlated observation errors may have a dramatic impact on the total variance, especially when the sampling size increases. The acknowledgement that the (pure) sampling variance underestimates the total variance because of observation errors is a statistical result that is neither widely known nor appreciated by most wildlife ecologists. The magnitude of this underestimation may be important and, therefore, observation errors cannot be always considered as a priori negligible in assessing the precision of a count-based abundance index.     

Sequential sampling plans to Orthezia praelonga Douglas (Hemiptera: Sternorrhyncha, Ortheziidae) in citrus

The sequential sampling is characterized by using samples of variable sizes, and has the advantage of reducing sampling time and costs if compared to fixed-size sampling. To introduce an adequate management for orthezia, sequential sampling plans were developed for orchards under low and high infestation. Data were collected in Mat?o, SP, in commercial stands of the orange variety 'Pêra Rio', at five, nine and 15 years of age. Twenty samplings were performed in the whole area of each stand by observing the presence or absence of scales on plants, being plots comprised of ten plants. After observing that in all of the three stands the scale population was distributed according to the contagious model, fitting the Negative Binomial Distribution in most samplings, two sequential sampling plans were constructed according to the Sequential Likelihood Ratio Test (SLRT). To construct these plans an economic threshold of 2% was adopted and the type I and II error probabilities were fixed in alpha = beta = 0.10. Results showed that the maximum numbers of samples expected to determine control need were 172 and 76 samples for stands with low and high infestation, respectively.     

Sequential sampling plan for Cameraria ohridella (Lepidoptera: Gracillariidae) on horse chestnut tree

A fixed precision sequential sampling plan for estimating the density of the horse chestnut, Aesculus hippocastanum L., leafminer Cameraria ohridella Deschka & Dimic (Lepidoptera: Gracillariidae) was developed. Data were collected from 2002 to 2004 in Turin, northwestern Italy, with the aim of developing a sampling strategy for estimating populations of C. ohridella mines. Taylor's power law was used as a regression model. Sampling parameters were estimated from 216 data sets, and an additional 110 independent data sets were used to validate the fixed precision sequential sampling plan with resampling software. Covariance analysis indicated that there were not significant differences in the coefficient of Taylor's power law between heights of the foliage, months, and years. Dispersion patterns of C. ohridella were determined to be aggregated. The parameters of the Taylor's power law were used to calculate minimum sample sizes and sampling stop lines for different precision levels. Considering a mean density value of five mines per leaf, an average sample number of only 49 leaves was necessary to achieve a desired precision level of 0.25. As the precision level was increased to 0.10, the average sample size increased to 303 leaves. The sequential sampling plan should provide an effective management of C. ohridella in the urban areas, minimizing sampling time and cost, and at the same should be an effective tool to reduce insecticide applications and prevent the esthetic damage.     

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.     

Spatial distribution of nymphs of Scaphoideus titanus (Homoptera: Cicadellidae) in grapes, and evaluation of sequential sampling plans

The spatial distribution of the nymphs of Scaphoideus titanus Ball (Homoptera Cicadellidae), the vector of grapevine flavescence dorée (Candidatus Phytoplasma vitis, 16Sr-V), was studied by applying Taylor's power law. Studies were conducted from 2002 to 2005, in organic and conventional vineyards of Piedmont, northern Italy. Minimum sample size and fixed precision level stop lines were calculated to develop appropriate sampling plans. Model validation was performed, using independent field data, by means of Resampling Validation of Sample Plans (RVSP) resampling software. The nymphal distribution, analyzed via Taylor's power law, was aggregated, with b = 1.49. A sample of 32 plants was adequate at low pest densities with a precision level of D0 = 0.30; but for a more accurate estimate (D0 = 0.10), the required sample size needs to be 292 plants. Green's fixed precision level stop lines seem to be more suitable for field sampling: RVSP simulations of this sampling plan showed precision levels very close to the desired levels. However, at a prefixed precision level of 0.10, sampling would become too time-consuming, whereas a precision level of 0.25 is easily achievable. How these results could influence the correct application of the compulsory control of S. titanus and Flavescence dorée in Italy is discussed.     

Sampling considerations for garden symphylans (Order: Cephalostigmata) in western Oregon

Sampling recommendations were developed for a potato bait sampling method used to estimate garden symphylan (Scutigerella immaculata Newport) densities in western Oregon. Sample size requirements were developed using Taylor's power law to describe the relationship between sample means and variances. Developed sampling recommendations performed well at sample sizes of 30 and greater, when validated by resampling a cohort of 40 independent data sets. Sample size requirements for the bait sampling method were 1.5 times greater than the requirements for the soil sampling method over densities from 1 to 20 S. immaculata per sample unit. As S. immaculata densities increased from April to May, sample size requirements decreased by 36% for fixed precision levels. For sampling in April, decreasing the damage threshold from 20, to 10 and five S. immaculata per sample unit, required a 1.6 and 2.5 times greater sample size requirement, respectively, for a fixed precision level (c) appropriate for pest management (c = 0.25). The bait sampling method provides an efficient reliable alternative to the standard soil sampling method used to monitor garden symphylan populations.