Common Sampling Techniques Research Articles

Saliva as a diagnostic tool for COVID-19 (Novel Coronavirus)

The coronavirus disease (COVID-19) is an emerging illness that has rapidly spread across the globe. First identified in late December 2019, this new strain had not previously been detected in humans. The novel coronavirus isolated by researchers was subsequently named the 2019 novel coronavirus (2019-nCoV). COVID-19 can be diagnosed through various methods, with RT-PCR being the gold standard for these tests. The most common sampling techniques involve swabs from the nose, throat, or mouth. Saliva, a critical biological fluid containing several diagnostic biomarkers, plays an important role in detecting SARS-CoV-2 and other coronaviruses. Its use offers numerous benefits and helps researchers better distinguish between symptomatic and asymptomatic patients.

Sampling Strategies for Assessing Male Clients of Female Sex Workers in Public Health Research: A Compilation of Global Evidence.

Clients of Female Sex Workers (FSWs) are major bridge population in HIV transmission. Any research among them remains challenging because they are hidden within society. The objective of this review was tocompile the global evidence on different sampling strategies used to access male clients of female sex workers for research purpose, the challenges faced during the sampling process andpossible sources of bias. Original articles and reports published globally in last 10years, in English language and those with full text freely available online were included in this scoping review. A comprehensive search was carried out among the electronic peer-reviewed literature database (Pubmed and Web of Science) using a pre-designed peer reviewed search strategy. Narrative synthesis was applied out across all such articles. A total of 36 articles were finally included in this review. The common sampling techniques used include convenience sampling, referral by FSWs/ pimp/brothel manager/clients, time location cluster sampling, use of virtual network, anonymous telephone survey, referred by clinicians of STI clinic etc. Overall response rate varied between 35 and 90%. Major challenges in participant recruitment included non-response, feasibility issue specially to cater non-brothel-based clients, safety issue for investigators, over-representation of clients with lower socio-economic status, higher refusal rate for known HIV positive clients to provide biological sample etc. As different sampling techniques have comparable response rate, it can be recommended that a pilot study should be carried out in local context to finalise appropriate participant recruitment technique for a given population.

Impact of person-job fit and person-organization fit on employee engagement: Moderating role of supervisor support

Purpose: This study aimed to examine the impact of two fit concepts, namely, person-job fit (P-J) and person-organization fit (P-O), on employee engagement while taking supervisor support as the moderating variable. Research Methodology: The relationships among constructs were analyzed using correlation, and the study hypotheses were tested using regression. All employees of different mobile telecommunication companies in Bangladesh comprised the study population. The sample size was 100, which was taken using the judgmental sampling technique. Primary data were collected from a field-level survey using a structured questionnaire. Results: The results revealed a positive association between employee engagement and person-job fit, while person-organization fit had a similar association with engagement. The impact of these variables on employee engagement ultimately affects turnover intentions. This study also revealed that the association between person-organization fit and employee engagement is positively moderated by supervisor support. Limitations: The study used a common non-probability sampling technique and a small sample size, which is a limitation. Contribution: The insights will help managers to ensure a match between the job and organizational requirements and those of employees. The study will also inspire future research to connect Field Theory and social exchange theory (SET) with different concepts in different country and industry contexts. Novelty: For the first time in the relevant field, the study simultaneously connected field theory and SET theory with P-J and P-O fit with employee engagement.

Efficient Quality Diversity Optimization of 3D Buildings through 2D Pre-optimization.

Quality diversity algorithms can be used to efficiently create a diverse set of solutions to inform engineers' intuition. But quality diversity is not efficient in very expensive problems, needing 100.000s of evaluations. Even with the assistance of surrogate models, quality diversity needs 100s or even 1000s of evaluations, which can make it use infeasible. In this study we try to tackle this problem by using a pre-optimization strategy on a lower-dimensional optimization problem and then map the solutions to a higher-dimensional case. For a use case to design buildings that minimize wind nuisance, we show that we can predict flow features around 3D buildings from 2D flow features around building footprints. For a diverse set of building designs, by sampling the space of 2D footprints with a quality diversity algorithm, a predictive model can be trained that is more accurate than when trained on a set of footprints that were selected with a space-filling algorithm like the Sobol sequence. Simulating only 16 buildings in 3D, a set of 1024 building designs with low predicted wind nuisance is created. We show that we can produce better machine learning models by producing training data with quality diversity instead of using common sampling techniques. The method can bootstrap generative design in a computationally expensive 3D domain and allow engineers to sweep the design space, understanding wind nuisance in early design phases.

Evaluation of the influence of correcting for gillnet selectivity on the estimation of population parameters.

Gill nets are a common sampling technique in inland and marine fisheries. However, gill nets are size selective and may result in bias estimates of population parameters. As such, selectivity is commonly assessed using indirect estimation techniques. Indirect estimates of gillnet selectivity have been suggested to improve estimates of important populations metrics (e.g., total annual mortality), but this assertion has not been assessed. In the current study, we simulated hypothetical populations of channel catfish Ictalurus punctatus, lake trout Salvelinus namaycush, walleye Sander vitreus, and white crappie Pomoxis annularis and sampled the populations based on published gillnet encounter and retention probabilities. Total annual mortality and von Bertalanffy parameters were then estimated using unadjusted (not "correcting" for selectivity processes) and adjusted ("correcting" for selectivity processes) age and(or) length data to evaluate the value of accounting for gillnet selectivity when estimating these metrics. Our results indicate that adjusting for retention and encounter probabilities rarely leads to improved estimates of total annual mortality, K, and L∞. For instance, estimates of annual mortality of lake trout based on age data adjusted for retention probability resulted in an overestimate of A by 14.4%. As such, we suggest that analysis of gillnet selectivity only be used when specific questions are being addressed (e.g., catch-at-age models) or in situation when all processes contributing to gillnet selectivity (e.g., contact probability, size-specific availability) are known.

Three common sampling techniques in Pleistocene coral reefs of the Red Sea: a comparison.

Line Intercept Transects (LIT), Point Intercept Transects (PIT), and Photoquadrats (PQ) are the most common quantitative sampling techniques in modern and fossil coral reefs. Data from coral reefs obtained by the different methods are generally compared between various reef ages and localities. Quaternary reefs from warmer interglacial periods, which represent climate scenarios projected for the future, are particularly interesting for comparisons with modern reefs. Importantly, fossil reefs differ from modern reefs because they are diagenetically altered and time averaged. While several studies have compared different quantitative methods in modern reefs, very few have dealt with the comparability among fossil and between fossil and modern reefs. Here, we compare LIT, PIT at 10, 20 and 50 cm intervals, and PQ in two Pleistocene reef localities in Egypt. We find that alpha diversity, reef cover and community composition are dependent on the method. Results gained with plotless methods (LIT, PIT) differ strongly from results gained with plot methods (PQ). However, coral cover results are similar between LIT and PIT, and community composition is indistinguishable between the two, but alpha diversity depends on the interval used for PIT. We discuss the implications of our findings for comparing coral reefs of various ages and localities. We recommend surveying Pleistocene reefs with PIT at 20 cm intervals. This is because A) alpha diversity is well captured, B) the amount of time averaging recorded by PIT is reduced compared to PQ, C) the PIT results can be directly compared to reefs analyzed by LIT, and D) the method is less time consuming than LIT and PQ.

Trap Escape as a Driver of Capture Probability in Semiaquatic Snakes

Sampling biases resulting from capture methodology or animal behavioral responses can significantly skew our understanding of population size and structure. Behavioral responses to passive sampling with traps, such as trap-happy or trap-shy responses, can be accounted for in analyses using individual covariates but they require detailed understanding of the underlying behavioral mechanisms. We used a field experiment to investigate the impact of trap escape on capture rates and determine what traits influence trap escape rates between and within two species of semiaquatic snakes, Liodytes pygaea and Nerodia fasciata. We found that L. pygaea escaped significantly more often than did N. fasciata, smaller L. pygaea escaped at significantly higher rates than did larger conspecifics, and individual capture history significantly influenced escape rates in N. fasciata. Our findings highlight understudied sources of inter- and intraspecific capture heterogeneity in a common sampling technique, and we urge researchers to consider method-specific sampling biases when attempting to produce population parameter estimates for species that are difficult to detect.

Active Learning Optimization for Boundary Identification Using Machine Learning-Assisted Method

<div class="section abstract"><div class="htmlview paragraph">Identifying edge cases for designed algorithms is critical for functional safety in autonomous driving deployment. In order to find the feasible boundary of designed algorithms, simulations are heavily used. However, simulations for autonomous driving validation are expensive due to the requirement of visual rendering, physical simulation, and AI agents. In this case, common sampling techniques, such as Monte Carlo Sampling, become computationally expensive due to their sample inefficiency. To improve sample efficiency and minimize the number of simulations, we propose a tailored active learning approach combining the Support Vector Machine (SVM) and the Gaussian Process Regressor (GPR). The SVM learns the feasible boundary iteratively with a new sampling point via active learning. Active Learning is achieved by using the information of the decision boundary of the current SVM and the uncertainty metric calculated by the GPR. The optimal sampling point is selected through multi-objective optimization so that the sampling point is close to the decision boundary of the current SVM as well as it has a high uncertainty metric. To illustrate the characteristics and effectiveness of the proposed approach, we apply the proposed approach to both simple problems with synthetic feasible regions and a complex industrial problem: autonomous driving path planning algorithm validation. With the proposed approach, edge cases are more effectively identified, so the classification accuracy of the resulting SVM is considerably higher than that of the SVM trained with conventional sampling techniques such as Monte Carlo Sampling and Latin Hypercube Sampling.</div></div>

Agglomerative clustering to improve the resolution of pseudo well stochastic seismic inversion: A case study

The Monte Carlo rejection and Monte Carlo Markov Chain methods are two common sampling techniques in Bayesian seismic inversion. Conventional methods of pseudo well stochastic seismic inversion for reservoir properties uses Monte Carlo rejection sampling of pseudo-wells to select those that best match seismic traces. The selected pseudo-wells do not influence the selection/rejection of subsequent pseudo-wells. The process requires a very large number of prior pseudo-wells to draw a reasonable outcome, which consumes a major part of the computation time. In conventional methods, the best-matched pseudo-wells often have dissimilarly shaped volume of shale logs, which can degrade the resolution of the outcome. Though Agglomerative clustering is well-known but the idea of grouping pseudo-wells based on similarly shaped volume of shale logs in pseudo well stochastic seismic inversion is unique. We propose an agglomerative clustering technique to group the prior pseudo-wells according to the shape of their volume of shale logs, before matching to seismic. The centroids of the pseudo-well clusters summarize the large number of prior pseudo-wells. The best-matched pseudo-well cluster centroid with seismic gives the most likely outcome while the two next best-matched cluster centroids give alternative results. The alternative results are useful to understand the uncertainty in the outcome. It has been observed that, the proposed method has reduced computation time (50–55% less than conventional pseudo well stochastic inversion). Meanwhile, the quantification of sand volume from the proposed method shows improvement over the conventional method. A comparison between the proposed and the conventional method has been shown on a synthetic wedge model and real seismic. In the wedge model (volume of sand is 0.65), the resultant volume of sand predicted in the modified method (0.7) is better than that predicted using the conventional method (0.8). The modified pseudo-well stochastic seismic inversion method has been applied on seismic data from deepwater Krishna-Godavari basin. The result shows an improvement in the characterization of thin shale layers within the reservoir.

Optimizing Sour Gas Qualification Testing: Determination and Verification of H2S Solubility from H2S/N2 Gas Mixtures up to 20,000 psig at 70°F

Traditionally, the H2S partial pressure (PH2S) of the gas/hydrocarbon phase has been used as the primary sour severity metric for material qualification and selection under ANSI/AMPP (NACE) MR0175/ISO 15156 guidelines. While the PH2S is appropriate for characterizing low total pressure systems, the strict, or ideal, Henry’s Law approach leads to over estimation of the dissolved H2S concentration (CH2S) for high-pressure, high-temperature (HPHT) wells by up to approximately 20 times at 70°F (21°C). Alternatively, the Ensemble Henry’s Law equation corrects for the non-ideal phase behavior of H2S at HPHT conditions and avoids over-estimation of CH2S. Given the industry’s reliance on using thermodynamic models to evaluate sour HPHT systems, an investigation was initiated to determine the accuracy of these model calculations. An empirical program was undertaken to verify CH2S predictions for the H2S-N2-H2O system. Multiple 2.7 L C-276 lined autoclaves were charged with a fixed inventory of H2S in N2 at multiple total pressure steps, with increasing N2 pressure, between 30 psig and 20,000 psig (3 bar and 1,380 bar) at 70±5°F (21±3°C). Per total pressure step, H2S levels in both the headspace gas and liquid phases were measured using common H2S sampling techniques (H2S-specific colorimetric tubes and iodometric titration, respectively), following ANSI/NACE TM0177-2016 guidelines. The results were used to calculate total pressure corrected (apparent) H2S solubility coefficients (AkH2S). Very good agreement was observed between empirically and computationally derived AkH2S values.

Neural Network-Based Undersampling Techniques

Machine learning models have gained popularity nowadays for their potential to solve real-life issues when trained on pertinent data. In many cases, the real-life data are class imbalanced and hence the corresponding machine learning models trained on the data tend to perform poorly on metrics like precision, recall, AUC, F1, and G-mean score. Since class imbalance issue poses serious challenges to the performance of trained models, a multitude of research works have addressed this issue. Two common data-based sampling techniques have mostly been proposed-undersampling the data of the majority class and oversampling the data of the minority class. In this article, we focus on the former approach. We propose two novel algorithms that employ neural network-based approaches to remove majority samples that are found to reside in the vicinity of the minority samples, thereby undersampling the former to remove (or alleviate) the imbalance issue. We delineate the proposed algorithms and then test the proposed algorithms on some publicly available imbalanced datasets. We then compare the performance of our proposed algorithms to other popular undersampling algorithms. Finally, we conclude that our proposed algorithms outperform most of the existing undersampling approaches on most performance metrics.

Diversity and distribution patterns of ants along elevational gradients

Ants are one of the most successful groups of organisms present in almost all terrestrial habitats on the Earth. The published papers on ants with various sampling techniques were reviewed focusing on species richness along the elevational gradients to explain distribution patterns of ants and their potential drivers in the world. Pitfall trapping, hand collection, Winkler extractor and bait traps were found common sampling techniques for ant studies. Based upon literature, five broad distributional patterns were identified viz. mid-elevation peaks, decreasing, increasing, low plateaus, and constant patterns along the elevation ranging from 0 to 4800 m above sea level. The mid-elevation peak was a common pattern. However, ant species richness of Nepal follows a decreasing pattern based on the available records. Temperature was found as the major predictor of species richness patterns of ants.

Strategies for Autonomic Nervous System Mapping of Fiber Composition and Neural Circuitry Using Transmission Electron Microscopy in Support of SPARC Projects

The optimization of neuromodulation strategies is important for a development and refinement of therapies. The design of customized tools, such as electrical stimulating devices, depends on the detailed knowledge of nerve fiber composition and inter‐relationships between target organs, nerve populations, and synaptic circuitry. The autonomic nervous system gives support to organs and are composed by myelinated and unmyelinated fibers as well as pre‐ and post‐ganglionic neurons. Mapping an autonomic nerve such as the pelvic or vagus nerve that innervates peripheral tissues and understanding the synaptology of neurons in the cardiac and stellate ganglia may provide advanced knowledge for improved neuromodulation strategies. Transmission electron microscopy (TEM) is a high‐level technology that helps to identify and characterize axonal myelination and ultrastructure of unmyelinated fibers. TEM also allows for fine structural analysis of neural circuitry and innervation of autonomic targets. Immunogold detection techniques using TEM permits the identification and characterization of neuronal tracers in the nervous system. With the support from the Stimulating Peripheral Activity to Relieve Conditions (SPARC) program at NIH, we developed customized ultrastructural studies of the autonomic nervous system to facilitate refinement of neuromodulation strategies related to the autonomic control of cardiac, gastrointestinal, and lower urinary tract systems. Morphometric analysis is performed by automatic segmentation, and the development of a new strategy to calculate measurements of axon diameter, fiber diameter, myelin thickness, and G‐ratio provides a better understanding of fiber size for modelling studies. Both males and females from different species, including humans, are analyzed and compared. Implementation of common sampling techniques for nerves and ganglia across species provides increased rigor and reproducibility. TEM studies promote an improved understanding of functional studies and provide critical ultrastructural information for the development of new neuromodulation strategies.Support or Funding InformationSPARC/NIH 1OT2OD026585‐01 and Dr Miriam and Sheldon G. Adelson Medical Research Foundation (AMRF)

An Under-Ice Hyperspectral and RGB Imaging System to Capture Fine-Scale Biophysical Properties of Sea Ice

Sea-ice biophysical properties are characterized by high spatio-temporal variability ranging from the meso- to the millimeter scale. Ice coring is a common yet coarse point sampling technique that struggles to capture such variability in a non-invasive manner. This hinders quantification and understanding of ice algae biomass patchiness and its complex interaction with some of its sea ice physical drivers. In response to these limitations, a novel under-ice sled system was designed to capture proxies of biomass together with 3D models of bottom topography of land-fast sea-ice. This system couples a pushbroom hyperspectral imaging (HI) sensor with a standard digital RGB camera and was trialed at Cape Evans, Antarctica. HI aims to quantify per-pixel chlorophyll-a content and other ice algae biological properties at the ice-water interface based on light transmitted through the ice. RGB imagery processed with digital photogrammetry aims to capture under-ice structure and topography. Results from a 20 m transect capturing a 0.61 m wide swath at sub-mm spatial resolution are presented. We outline the technical and logistical approach taken and provide recommendations for future deployments and developments of similar systems. A preliminary transect subsample was processed using both established and novel under-ice bio-optical indices (e.g., normalized difference indexes and the area normalized by the maximal band depth) and explorative analyses (e.g., principal component analyses) to establish proxies of algal biomass. This first deployment of HI and digital photogrammetry under-ice provides a proof-of-concept of a novel methodology capable of delivering non-invasive and highly resolved estimates of ice algal biomass in-situ, together with some of its environmental drivers. Nonetheless, various challenges and limitations remain before our method can be adopted across a range of sea-ice conditions. Our work concludes with suggested solutions to these challenges and proposes further method and system developments for future research.

Kernel density estimation for hierarchical data

Multistage sampling is a common sampling technique employed in many studies. In this setting, observations are identically distributed but not independent, thus many traditional kernel smoothing techniques, which assume that the data are independent and identically distributed (i.i.d.), may not produce reasonable density estimates. In this paper, we sample repeatedly with replacement from each cluster, create multiple i.i.d. samples containing one observation from each cluster, and then create a kernel density estimate from each i.i.d. sample. These estimates will then be combined to form an estimate of the marginal probability density function of the population.

Sampling baseline androgens in free-living passerines: Methodological considerations and solutions

Obtaining baseline hormone samples can be challenging because circulating hormone levels often change rapidly due to the acute stress of capture. Although field protocols are established for accurately sampling baseline glucocorticoid concentrations, fewer studies have examined how common sampling techniques affect androgens levels. Indeed, many studies focused on understanding the functional significance of baseline androgen levels use sampling methods known to activate the endocrine responses to stress. To understand how different field sampling protocols affect plasma androgen levels, we measured the androgen response to two types of capture stressors in a free-living tropical bird, the wire-tailed manakin (Pipra filicauda). First, we subjected males to a standardized capture and restraint protocol lasting either 15 or 30 min. Second, males were passively captured in nets that were filmed (to establish exact duration of time between capture and blood sampling) and checked every 30 min. The first study showed that circulating plasma androgen levels decreased significantly following both 15 and 30 min of restraint in a cloth bag, with a trend for the 30 min samples to be lower than the 15 min samples. Further, the change in androgen levels was dependent on an individual’s initial androgen levels, with the individuals with the highest initial levels registering the largest declines. The results of the second study suggest that hanging in a mist net for extended periods of time also leads to a decrease in circulating androgen levels, but this effect was weaker than that of capture and restraint in a cloth bag. Our findings demonstrate that, overall, circulating androgen levels decrease in response to common sampling techniques; a finding that has important implications for studies measuring baseline androgen levels in free-living birds. Future studies should prioritize sampling individuals immediately upon removal from the mist net, as handling and restraint have a strong negative effect on circulating androgen levels. When constant monitoring of the mist net is not possible, investigators should use video cameras to record the amount of time an individual spends in the net prior to blood sampling and then statistically control for the effect of this variable in analyses.

Evaluating the microbiome of two sampling locations in the nasal cavity of cattle with bovine respiratory disease complex (BRDC).

Bovine respiratory disease complex (BRDC) is a multifactor disease, and disease incidence may be associated with an animal's commensal bacterial populations (microbiome) in the upper nasal cavity. Identifying these commensal bacterial populations in the upper nasal cavity may help us to understand the impact of the microbiome on incidence of BRDC in cattle. Various sampling techniques have previously been utilized to evaluate the microbiome of different locations of the upper nasal cavity in cattle. Therefore, our objective was to determine whether bacterial populations of the nasal cavity vary based on these sampling locations. Two common sampling techniques were evaluated, including 6-inch nasal swabs and deep nasopharyngeal swabs. Nasal swabs from calves were collected when the animal was diagnosed with BRDC after weaning in the feedlot in addition to collection of samples from asymptomatic cohorts. Samples were pooled in groups based on year the animal was in the feedlot (2015 or 2016), when the animal was diagnosed with BRDC (1 to 5 weeks after weaning), type of sample (6-inch nasal swab or deep nasopharyngeal swab), and health status (diagnosis with BRDC or control). Variable regions 1 through 3 along the 16S rRNA gene were amplified by PCR and sequenced using next-generation sequencing (Illumina MiSeq) for identification of the bacterial taxa present. Overall, sampling site did not consistently influence diversity of the bacterial populations of the upper nasal cavity. However, the effect of disease incidence on the microbiome was depended on sampling time after weaning (P = 0.0462) for 2015, while the main effects of sampling time after weaning (P = 0.00992) and disease phenotype (P = 0.012) were significant for 2016. These data for 2016 demonstrate that in addition to bacterial profiles changing throughout weaning, calves diagnosed with BRDC have different bacterial profiles compared to their control cohorts. In addition, evaluation of the microbiome identified predominant bacteria genera in the upper nasal cavity included those previously reported to be associated with cattle diagnosed with BRDC including Mycoplasma sp., Psychrobacter sp., and Mannheimia sp. In summary, these results demonstrate that shorter, less invasive 6-inch nasal swabs produce similar results to deep nasopharyngeal swabs.

Automatic vehicle classification using linked visual words

An improvement in the method of automatic vehicle classification is investigated. The challenges are to correctly classify vehicles regardless of changes in illumination, differences in points of view of the camera, and variations in the types of vehicles. Our proposed appearance-based feature extraction algorithm is called linked visual words (LVWs) and is based on the existing technique bag-of-visual word (BoVW) with the addition of spatial information to improve accuracy of classification. In addition, to prevent over-fitting due to a large number of LVWs, four common sampling techniques with LVWs are investigated. Our results suggest that the sampling of LVWs using TF-IDF with grouping improved the accuracy of classification for the test dataset. In summary, the proposed system is able to classify nine types of vehicles and work with surveillance cameras in real-world scenarios. The classification accuracy of the proposed system is 5.58% and 4.27% higher on average for three datasets when compared with BoVW + SVM and Lenet-5, respectively.

Impression Smear Agreement with Acetate Tape Preparation for Cytologic Sampling.

Cutaneous cytologic sampling techniques are used to detect bacteria, yeast, and inflammatory cells for diagnosis and therapeutic monitoring. Studies have examined slide evaluation techniques, ear swab cytology staining methods, and observer variations; few studies compare common clinical sampling techniques. The primary aim of this study was to measure detection of microorganisms and neutrophils by impression smear compared to acetate tape preparation; comparison of agreement between two acetate tape staining methods was a secondary aim. Thirty lesions consistent with superficial pyoderma were sampled via impression smear and acetate tape preparation. Acetate tape preparations were either stained with modified Romanowksy stain solutions two and three or solution three alone. Impression smears were stained in the standard manner. Bacteria, yeast, and neutrophils were evaluated using a semi-quantitative scale [0-4]. Quantities were aggregated and compared using Cohen's kappa to measure agreement between methods. When impression smears were compared to acetate tape, the lowest agreement occurred for neutrophils, with impression smears detecting more neutrophils. Comparison of acetate tape staining methods had the highest agreement for yeast detection. Sampling technique and staining method did not differ for detection of bacteria. Impression smears detected more neutrophils, and yeast detection appeared equivalent for acetate tape staining methods.

Characterization of the density and body size of a Gammarus pulex (Crustacea: Amphipoda) population in subsurface sediments reflects the sampling technique used

The hyporheic zone and its invertebrate fauna play vital roles in the functioning of lotic ecosystems. However, although sampling invertebrates from subsurface sediments is recognized as challenging, few studies have quantified the effectiveness of common sampling techniques. We conducted laboratory experiments to compare two common, semi-quantitative pump-sampling techniques—Bou–Rouch and vacuum-pump sampling. We determined the proportion of a Gammarus pulex (Crustacea: Amphipoda) population sampled by each method in five sediment treatments comprising coarse (16–32 mm), medium (8–16 mm), and fine (4–8 mm) gravel and combinations thereof. We compared the body size of individuals sampled and not sampled by each technique to the population mean. Density estimates obtained using both methods were low: 33 ± 5 and 5 ± 1% of the population present for Bou–Rouch and vacuum-pump samples, respectively. Density estimates were significantly higher for Bou–Rouch than for vacuum-pump samples in four sediment treatments, but were comparable in coarse gravel. The body size of organisms captured by the Bou–Rouch technique was comparable to the population mean, whereas those in vacuum-pump samples were smaller. With hyporheic invertebrates suggested as future biomonitors of ecosystem health, we recommend Bou–Rouch sampling as the more effective pump-sampling method for community characterization.