Non-parametric Richness Estimators Research Articles

Exploring scale insects biodiversity in orange orchards: insights from Guelma province, Algeria

Scale insects are pests affecting citrus crops in the Mediterranean basin, but their significance is often overlooked in some countries due to insufficient information about the threat they pose to this type of cultivation. In Algeria, various studies have aimed to identify and highlight the most harmful species impacting citrus orchards. This research specifically focuses on compiling a list of species affecting orange orchards in three regions of Guelma province (northeast Algeria) which are Boumahra Ahmad, El Fedjoudj and Guelma. Branch samples with their leaves were collected from all cardinal directions of the trees as well as from the center of the canopy during the winter-spring period from 2014 to 2018 while examining the climatic influence on their presence. Seventeen species were identified, with Aonidiella aurantii (Maskell, 1879), Parlatoria ziziphi (Lucas, 1853) and Coccus pseudomagnoliarum (Kuwana, 1914) being dominant and Lepidosaphes beckii (Newman, 1869), Saissetia oleae (Olivier, 1791) and Saissetia coffeae (Walker, 1852) considered rare. Non-parametric richness estimators (Chao 1, Chao 2, Jack 1 and Boot) suggest the potential presence of additional species, reaching 20.15 ± 0.96, indicating that the count may extend to 21 scale insects in the surveyed orchards. Spearman correlation analysis applied to species and climatic conditions reveals their influence on species abundance, but not on their diversity. We observed a positive impact on relative humidity and a negative impact on average temperature.

Checklist, distribution, diversity, and rarity of mayflies (Ephemeroptera) in Slovakia.

Despite the essential role of mayflies (Ephemeroptera) in freshwater ecosystems and their long-term use in research and routine biomonitoring in the Carpathian and Pannonian ecoregions, their distribution data are fragmentary and outdated. All published and unpublished data on mayflies from Slovakia was gathered and a database of > 15,000 species records from 2206 localities built with the aims (i) to critically revise available data and assess the completeness of the species inventory, (ii) to identify hotspots of species diversity, and (iii) to provide a benchmark for assessment of species rarity and conservation status in the region. After the critical revision of the data covering more than 100 years, the occurrence of 109 mayfly species in Slovakia was confirmed. The species inventory appears to be nearly complete, as evidenced by the rarefaction curve and a nonparametric species richness estimator. The highest mayfly gamma diversity was recorded below 500 m a.s.l. and in streams of the fifth order, which can be considered hotspots of mayfly diversity in the region. Six species were last recorded before 1990 and thus can be considered extinct in Slovakia. Twenty-nine species could be classified as very rare, with their occurrence frequency decreasing with increasing altitude and most of them being restricted to large lowland rivers and stagnant water habitats in their floodplains. In conclusion, our study provides comprehensive data on key freshwater bioindicators and suggests increasing conservation priorities, especially in lowland river floodplains occupied by several very rare mayfly species.

Uneven species occurrence and richness of lowland snakes (Serpentes, Squamata) in Terengganu, Peninsular Malaysia, with new locality records.

This study documents information on the composition, diversity, richness, and temporal occurrence of snakes at Sekayu's lowland forest (SLF), Terengganu, Peninsular Malaysia for the first time. The snakes recorded within the SLF were sampled opportunistically from 2013 to 2019, employing the Visual Encounter Survey method (VES) and L-shape pitfall traps with drift fences. Forty-six snake species from 37 genera belonging to the nine families were recorded, of which 11 were new records to Terengganu. Individual-based rarefaction and extrapolation curves were not reaching asymptote, indicating that additional species can be recorded at the study area. Non-parametric species richness estimators estimated and produced a range between 51 and 57 species. ACE was the best estimator based on the quantitative evaluation. All species showed some variations of occurrence patterns across months. Fourteen species were only encountered once across the sampling years, and interestingly 11 of them were only detected during the rainy season (late October to January). In general, the number of species richness, abundance, and rare species were high during this season. Species richness of snakes is high at SLF but sampling effort should be intensified, especially during these rainy months, to obtain a robust estimated snake species richness in SLF. Terengganu harbor considerably high species richness of snakes with a total of 71 species to date (excluding marine snakes), but snake diversity is still underestimated as only a few localities were surveyed in the past years, primarily at the northern part. Future surveys should be commenced at the central and southern parts of Terengganu to complement the current investigation.

Theory and application of an improved species richness estimator.

Species richness is an essential biodiversity variable indicative of ecosystem states and rates of invasion, speciation and extinction both contemporarily and in fossil records. However, limited sampling effort and spatial aggregation of organisms mean that biodiversity surveys rarely observe every species in the survey area. Here we present a non-parametric, asymptotic and bias-minimized richness estimator, Ω by modelling how spatial abundance characteristics affect observation of species richness. Improved asymptotic estimators are critical when both absolute richness and difference detection are important. We conduct simulation tests and applied Ω to a tree census and a seaweed survey. Ω consistently outperforms other estimators in balancing bias, precision and difference detection accuracy. However, small difference detection is poor with any asymptotic estimator. An R-package, Richness, performs the proposed richness estimations along with other asymptotic estimators and bootstrapped precisions. Our results explain how natural and observer-induced variations affect species observation, how these factors can be used to correct observed richness using the estimator Ω on a variety of data, and why further improvements are critical for biodiversity assessments. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Estimating total species richness: Fitting rarefaction by asymptotic approximation

AbstractEstimating the number of species in a community is important for assessments of biodiversity. Previous species richness estimators are mainly based on nonparametric approaches. Although parametric asymptotic models have been applied, they received limited attention due to specific limitations. Here, we introduce parametric models fitting the probability‐based rarefied species richness curve that allow us to estimate the “Total Expected Species” (TES) in a community based on species' abundance data. We develop two approaches to calculate TES (termed “TESa” and “TESb”), based on two slightly different mathematical assumptions regarding Expected Species (ES) models. We provide R functions to calculate both these estimation approaches and their standard deviation. The function also enables users to visualize the estimation. We test the performance of TESa, TESb, and their average (TESab) across simulated and empirical data, and compare their bias, precision, and accuracy with other commonly used, nonparametric species richness estimators: the bias‐corrected (bc‐)Chao1 and the abundance‐based coverage estimator (ACE). Simulation reveals that in small samples TESa shows a tendency to overestimate and TESb to underestimate overall species richness. TESab performs well in bias, precision, and accuracy when compared with (bc‐)Chao1 and ACE estimators. Results from empirical data show that the variance generated from TES estimates is comparable with that for (bc‐)Chao1 and ACE. Our study demonstrates that rarefaction theory in combination with parametric approximation models provides a valuable new approach to estimate the species richness of incompletely sampled communities. Robust estimates are likely to be obtained where the observed number of species is greater than half of the TES estimation. When the ratio of TESa to the observed richness is ≫2, we suggest the use of TESb or TESab. Although more comprehensive comparisons with other estimators are suggested, we encourage researchers to consider the TES approach in their biodiversity studies as a complement to current existing estimators.

Taxonomic uncertainty and the challenge of estimating global species richness

Taxonomic uncertainty and the challenge of estimating global species richness

A Universal Key to Rationally Select Which, Among Nonparametric Species Richness Estimators, Performs Best According to Each Particular Incomplete Sampling

Since most samplings of local species communities are bound to remain substantially incomplete for practical reasons, a wide variety of nonparametric estimators of the number of unrecorded species have been proposed over the past fifty years. Unfortunately, the distinct formulations of each of these estimators naturally lead to substantially divergent estimates. The will to try to select, in each case, the estimator expected to be the more accurate has long been carried out only on a purely empirical, even arbitrary, basis (as is evident from the extensive consultation of much of the past literature on estimating species richness of incompletely sampled communities). So that extrapolating the true species richness of a community from its incomplete survey has long remained quite unsatisfactory. Indeed, the definition of a truly rational procedure for selecting the most accurate (least-biased) estimator actually requires a solidly established theoretical framework, involving to conform, as best as possible, to the general mathematical characteristics of the Species Accumulation Function. Accordingly, unveiling, first of all, these mathematical characteristics of the Species Accumulation Function was a decisive step forward in this perspective. Thereby making it now possible to propose an objective key to rationally select the one, within the series of various estimators, which, depending on each particular sampling, happens to be the least biased in this particular case, thus providing the most accurate estimate of the number of still unrecorded species. And, consequently, making it possible, now, to deliver the best estimate of the true species richness of a local community, despite its being incompletely surveyed.

Performance of richness estimators for invertebrate inventories in reservoirs.

Biological inventories combined with the estimation of species richness represent a useful tool for the analysis of the pattern of species distribution in different regions. This study aimed to (i) comparatively evaluate the performance of non-parametric richness estimators for invertebrate inventories in reservoirs between ecoregions and (ii) to assess whether the efficiency (bias, precision and accuracy indices) of the estimators is altered when applied to sites from different ecoregions. The study was conducted in the ecoregions Central Pediplano of the Borborema Plateau (Paraíba River basin) and Northern Sertaneja Depression (Piranhas-Assu River basin), semiarid region of Brazil. Six reservoirs were selected and benthic macroinvertebrates were sampled at 141 sites distributed along the littoral zone, in 4 periods (June, September, December 2014 and March 2015). The organisms were identified to the family level, except for Chironomidae, identified to the genus level. We comparatively analyzed six non-parametric richness estimators: Jackknife 1, Jackknife 2, Chao1, Chao 2, ICE, and Bootstrap, and three performance indicators: bias, precision, and accuracy. ICE and Jackknife 2 had more stable results for total species richness, but with different performance between ecoregions for bias, precision, and accuracy. Variation in performance of the estimators may be associated with differences in species richness and frequency between ecoregions. ICE and Jackknife 2 proved to be the best estimators for biological inventories of aquatic invertebrates in reservoirs in studies comparing data from different ecoregions, due to accuracy and precision, while Bootstrap is the least indicated, given greater bias and less accuracy and precision.

Pedigree accumulation analysis: Combining methods from community ecology and population genetics for breeding adult estimation

Abstract Estimates of the number of successfully breeding adults (NS) in a population can predict levels of recruitment. However, assessments of NS are often difficult to obtain because encounters with adults are limited due to life‐history characteristics, low abundance or other constraints associated with access to critical habitats. Alternatively, efforts to sample individuals at earlier ontogenetic stages can be more tractable, resulting in more comprehensive samples. To estimate NS, we describe, evaluate and apply two nonparametric species richness estimators to information associated with genetic pedigree reconstruction. Simulations compared bias and precision associated with Chao and Jackknife methods when estimating NS. We also evaluated NS estimation sensitivity to two sources of variation associated with species reproductive ecology (variance in reproductive success and sex ratio skew) and genetic pedigree assignment error. Finally, the application of our novel method was demonstrated in two different species and systems (Chinook Salmon in Oregon, USA and Lake Sturgeon in Michigan, USA). We found unbiased NS estimates were generated across a broad range of offspring sample sizes using the Chao method. Empirical results corroborated simulation‐based expectations and highlighted applications where parents and offspring are sampled, and when only offspring are sampled. When offspring sample sizes are adequate and pedigree reconstruction errors are low, the combination of established methods from community ecology and genetic pedigree reconstruction provides an accurate alternative method to estimate NS that can facilitate population assessments.

Effect of crop residue management on damage by Diatraea saccharalis (Lepidoptera: Crambidae), its egg parasitoids and the ants associated with sugarcane.

In the American continent, the sugarcane borer Diatraea saccharalis (F.) is the main pest in sugarcane producing areas. The objective of this study was to assess the effect of crop residue management on damage by D. saccharalis, its egg parasitoids and the ants associated with sugarcane. The study was carried out during 2011-2012, 2012-2013 and 2013-2014 crop cycles, in three commercial fields located in different regions of Tucumán state, Argentina. Two types of crop residue management (= treatments) were compared: conservation of trash at the soil surface (CT) and trash burning (TB). In 'trash conservation' treatment, crop residue was allowed to remain over the soil surface during the whole sugarcane growing season, while the second treatment consisted of complete burning of trash blanket approximately 2 weeks after harvest. The injury level was measured by recording the number of stalks bored and internodes bored. Parasitism was estimated by counting the total number of eggs and number of black eggs (which indicates the occurrence of egg parasitoids). Ants (Formicidae) richness was calculated by two estimators; abundance-based coverage estimator and incidence-based coverage estimator, using the non-parametric richness estimators: Chao 2 and Jackknife. Finally, the indicator value was estimated through the measurement of specificity and fidelity. In all the parameters studied no significant difference was found between TB and CT treatments.

De artrópodos y plantas: Diversidad de la artropodofauna en un gradiente de vegetación en Los Llanos riojanos, Argentina

Given the fundamental role of arthropods and insects in the functioning of arid ecosystems, it is of key importance to understand their relationships with the environment, particularly for the development of future conservation efforts. Within the phytogeographic region of Chaco, in Los Llanos (La Rioja province, Argentina), great changes in vegetation occur within short distances, determining a pronounced gradient of plant heterogeneity. The aim of this study was to analyse the response of epigaeic arthropods to these changes. In this gradient, three environments were selected (Salinas, Interface and Monte), in which we collected arthropods and insects using fall traps during seven days during the warm season. Total abundance of arthropods and insects, and richness of insect species/morpho-species were determined. The association between the environments and the abundance and richness of species was evaluated by repeated measurements ANOVA. Nonparametric richness estimators (Chao1, Jackniffe1 and Bootstrap) and their species accumulation curves were used to test sampling completeness. To assess the structure of the insect community we used range-abundance curves and multivariate analysis. A total 8380 arthropods was collected, of which 5902 were insects grouped into 14 orders, 31 superfamilies, 35 families and 114 species/morphospecies. The environment with the greatest plant heterogeneity (Monte) presented the greatest abundance of arthropods and the greatest abundance and richness of insects. The most abundant and richest insect families were Formicidae (Hymenoptera) and Tenebrionidae (Coleoptera). Chao1 and Bootstrap were the best richness estimators. In this study, we found that the abundance, richness and composition of arthropod species, particularly insects, were associated to a vegetation gradient.https://doi.org/10.25260/EA.20.30.1.0.867

The study of hidden habitats sheds light on poorly known taxa: spiders of the Mesovoid Shallow Substratum.

The scarce and biased knowledge about the diversity and distribution of Araneae species in the Iberian Peninsula is accentuated in poorly known habitats such as the Mesovoid Shallow Substratum (MSS). The aim of this study was to characterize the spiders inventory of the colluvial MSS of the Sierra de Guadarrama National Park, and to assess the importance of this habitat for the conservation of the taxon.Thirty-three localities were selected across the high peaks of the Guadarrama mountain range and they were sampled for a year using subterranean traps specially designed to capture arthropods in the MSS. Species accumulation curves were built both for the observed species richness and for the non-parametric richness estimators. The literature was reviewed in order to update the distributional maps of the rarest species.Forty-two species were collected, of which four were species new to science. More than half were represented by one or two individuals which caused the accumulation curves to rise slowly and to end without reaching an asymptote. Almost half of the species showed significant increases in their Iberian distribution ranges. Two species were recorded for the first time in the Iberian Peninsula and 32 species were new additions to the spider checklist of the Sierra de Guadarrama National Park.

Cost-effective sampling for estimating species richness of ground beetles (Coleoptera: Carabidae) using pitfall traps: efficiency of non-parametric species richness estimators

Because it is extremely time-consuming and costly to evaluate species richness of highly diverse taxa such as insects, cost-effective sampling strategies to estimate species richness are needed, especially when long-term monitoring is conducted. We found a sampling method that reduced the number of traps per site when estimating species richness of ground beetles (Coleoptera: Carabidae) in six forest sites in Sorachi, Hokkaido, northern Japan. We set 40 pitfall traps per site and collected ground beetles for 1-week periods in June, July, and August 2013. We evaluated the performance of three non-parametric species richness estimators [Jackknife2, Chao1, and the abundance-based coverage estimator (ACE)] to estimate species richness. Rarefaction curves showed that ACE was the only valid estimator to estimate species richness for all sites. Using ACE, we can reduce the number of traps to 30 or 20 from 40 traps per site if we allow a bias of 5 or 10%, respectively. This study suggests that non-parametric species richness estimators are useful in estimating species richness of ground beetles with reduced sample size.

Does microhabitat influence the testate amoebae communities in the Nameri National Park, northeastern India? A tropical forest perspective

The community structure of testate amoebae inhabiting different microhabitats (soil and tree-moss) within a tropical forest biome in Nameri National Park, northeastern India, was investigated. A total of 33 testate amoebae species belonging to 13 genera were identified. Species belonging to the class Lobosea constituted 73% of total testate amoebae density in the soil habitat, whereas the class Filosea constituted the most dominant forms (58%) in the moist tree-moss habitat. The relative abundance of species was higher in the tree-moss habitat compared to the soil habitats of the forest. Although multivariate analysis suggested a significant difference in assemblage patterns between the habitats, the turnover in species (i.e., beta diversity) was insignificant. Species accumulation curves (SAC) constructed using both parametric and non-parametric species richness estimators revealed that the asymptote of species richness was achieved by a low number of sample replicates in both habitats. The temperature and pH of the substratum on testate amoebae distribution patterns suggest the importance of additional background factors on testate amoebae community structure. Further studies involving more biotopes, seasons, and trophic interactions are recommended to document a complete record of testate amoebae diversity and their interactions with environmental gradients in the tropical forest biomes of northeastern India.

Factors affecting aquatic beetle communities of Northern Western Ghats of India (Arthropoda: Insecta: Coleoptera)

We studied faunistic and ecological factors influencing distributions of aquatic beetles in the Northern Western Ghats (NWG) of India. In the period 2013–2017, we collected 213 samples from 105 localities within the area and obtained 66 species, the majority of which belong to Dytiscidae. Relative occurrence based on incidence data revealed that dytiscid water beetleLaccophilus inefficiensas the most widespread species. Non-parametric richness estimators Chao2, Jackknife1 and Bootstrap showed that 70–80% of the fauna was covered in the sampling efforts from different types of freshwater habitats. Sample-based rarefaction suggested that more sampling efforts within the region can yield additional species. Canonical correspondence analysis (CCA) revealed that altitude, salinity, hydroperiod and depth influenced the distribution of aquatic beetles. Further, CCA also revealed habitat preference and co-occurrence of various aquatic beetle species. For instance, while co-occurring species under Laccophilinae and Hydroporinae were eurytopic, other co-occurring speciesClypeodytes hemani,Microdytes sabitaeandLacconectus lambaiwere restricted to temporary habitats. Multiple correspondence analysis (MCA) showed a strong association between altitudinal classes and species distribution where many species were restricted within a particular altitudinal gradient. For example,M. sabitae,C. hemani,Hygrotus nilghiricus,L. lambaiandRhantus taprobanicuswith classes 900–1199 and 1200–1499 whileHyphydrus flavicans,Laccophilus ceylonicus,Lacconectus andrewesi,Sternolophus inconspicuusandCanthydrus laetabiliswith the class 300–599. The present work on aquatic beetles is the first attempt to study the influence of environmental factors on species diversity and distribution in the Northern Western Ghats of India.

Variation in mammal species richness and relative abundance in the Karoo

Understanding how climate change and land transformation may impact the distribution and diversity of wildlife species requires landscape-level foundational biodiversity surveys. The Karoo BioGaps Project aims to provide such data and to support the scientific assessment for shale gas development projects in the Karoo basin. In this paper we present the findings of the BioGaps mammal survey, which recorded medium and large mammals across twenty-five 1 km × 1 km sampling sites within the proposed fracking footprint using camera trapping techniques. We use sample rarefaction curves, non-parametric species richness estimators and non-metric multidimensional scaling plots to explore both species richness and community structure. We also used a generalised linear model to investigate how species diversity varies with both site-specific and landscape-level predictors. A total of 38 species were recorded at the majority of sites. Longitude (z = 4.018, p = 0.0005) emerged as the best predictor of species diversity across the study area, which we suggest is linked to the clear east–west aridity gradient. Together these results reveal the cosmopolitan distribution of the mammal taxa in the Karoo and could be used to inform decision-making linked to mining activities in the area.

Taxonomic diversity of bacteria from mangrove sediments of Goa: metagenomic and functional analysis.

The present study compared the taxonomic diversity and evaluated the functional attributes of the bacterial species from Mandovi and Zuari mangrove sediments, Goa, using paired-end amplicon sequencing of 16S rDNA and culture-based analyses, respectively. 16S rDNA sequencing revealed Proteobacteria, Firmicutes, and Actinobacteria as the dominant phyla in both the sediments. However, the abundance of these phyla significantly differed between the samples. Bacteroidetes from Mandovi sediment, and Acidobacteria and Gemmatimonadetes from Zuari sediment were the other exclusive major phyla. Chloroflexi, Cyanobacteria, Nitrospirae, Planctomycetes, Verrucomicrobia, and WS3 were the minor phyla observed in both. However, a significant difference in the distribution of minor phyla and lower bacterial taxa under each phylum was noted between the sediments, indicating that the resident microbial flora completely differed between them. This was further validated by high values from distance matrix analyses between the samples. In addition, the pathogenic Vibrio sp. was recorded exclusively in Mandovi sediment, while higher abundance of ecologically important bacterial classes including Gammaproteobacteria, Alphaproteobacteria, Deltaproteobacteria, and Bacilli was observed in Zuari sediment. Taken together, the data indicated that Zuari sediment was taxonomically richer than Mandovi sediment, while a greater incidence of anthropogenic activities occurred in the latter. This observation was further validated by non-parametric richness estimators which were found to be higher for Zuari sediment. The cultured bacterial isolates, all identified as Firmicutes, were tested for activities related to biofertilization and production of enzymes to be used for bioremediation and chemotherapeutic applications. Higher number of bacterial isolates from Mandovi was found to produce indole-acetic-acid, tannase, xylanase, and glutaminase enzymes, and could solubilize phosphate. In contrast, higher proportion of bacterial isolates from Zuari sediment were capable of producing amylase, cellulase, gelatinase, laccase, lipase, protease, and asparaginase enzymes, emphasizing the fact that the Zuari mangrove sediment is a rich reservoir for economically and biotechnologically important bacterial species.

Rarefaction and extrapolation of species richness using an area-based Fisher's logseries.

Fisher's logseries is widely used to characterize species abundance pattern, and some previous studies used it to predict species richness. However, this model, derived from the negative binomial model, degenerates at the zero‐abundance point (i.e., its probability mass fully concentrates at zero abundance, leading to an odd situation that no species can occur in the studied sample). Moreover, it is not directly related to the sampling area size. In this sense, the original Fisher's alpha (correspondingly, species richness) is incomparable among ecological communities with varying area sizes. To overcome these limitations, we developed a novel area‐based logseries model that can account for the compounding effect of the sampling area. The new model can be used to conduct area‐based rarefaction and extrapolation of species richness, with the advantage of accurately predicting species richness in a large region that has an area size being hundreds or thousands of times larger than that of a locally observed sample, provided that data follow the proposed model. The power of our proposed model has been validated by extensive numerical simulations and empirically tested through tree species richness extrapolation and interpolation in Brazilian Atlantic forests. Our parametric model is data parsimonious as it is still applicable when only the information on species number, community size, or the numbers of singleton and doubleton species in the local sample is available. Notably, in comparison with the original Fisher's method, our area‐based model can provide asymptotically unbiased variance estimation (therefore correct 95% confidence interval) for species richness. In conclusion, the proposed area‐based Fisher's logseries model can be of broad applications with clear and proper statistical background. Particularly, it is very suitable for being applied to hyperdiverse ecological assemblages in which nonparametric richness estimators were found to greatly underestimate species richness.

An Analysis of Malaise-Trap Effectiveness in Assessing Robber Fly (Diptera: Asilidae) Species Richness

Abstract Little quantitative information is available on the effectiveness of Malaise traps in estimating insect species richness. I used the Chao1 nonparametric species richness estimator to evaluate the effectiveness of Malaise traps in assessing species richness of robber flies in west-central Illinois burned and unburned deciduous forest and tallgrass prairie habitats. Two of 12 traps yielded asymptotic species richness values, with remaining traps requiring fold increases ranging from 3.1 to 20.9 to reach asymptotic richness. Overall, observed species richness was over 85% of estimated species richness, but a 3.9-fold sample-size increase would have been required to reach asymptotic species richness. For individual habitats, estimated fold increases in sample size ranging from 1.9 to 9.7 would have been needed to reach asymptotic species richness. These results show that Malaise traps are effective in sampling robber flies, but asymptotic species richness would be difficult to achieve. Lower target c...

Characterization of Macroinvertebrate Communities in the Hyporheic Zone of River Ecosystems Reflects the Pump-Sampling Technique Used.

The hyporheic zone of river ecosystems provides a habitat for a diverse macroinvertebrate community that makes a vital contribution to ecosystem functioning and biodiversity. However, effective methods for sampling this community have proved difficult to establish, due to the inaccessibility of subsurface sediments. The aim of this study was to compare the two most common semi-quantitative macroinvertebrate pump-sampling techniques: Bou-Rouch and vacuum-pump sampling. We used both techniques to collect replicate samples in three contrasting temperate-zone streams, in each of two biogeographical regions (Atlantic region, central England, UK; Continental region, southeast France). Results were typically consistent across streams in both regions: Bou-Rouch samples provided significantly higher estimates of taxa richness, macroinvertebrate abundance, and the abundance of all UK and eight of 10 French common taxa. Seven and nine taxa which were rare in Bou-Rouch samples were absent from vacuum-pump samples in the UK and France, respectively; no taxon was repeatedly sampled exclusively by the vacuum pump. Rarefaction curves (rescaled to the number of incidences) and non-parametric richness estimators indicated no significant difference in richness between techniques, highlighting the capture of more individuals as crucial to Bou-Rouch sampling performance. Compared to assemblages in replicate vacuum-pump samples, multivariate analyses indicated greater distinction among Bou-Rouch assemblages from different streams, as well as significantly greater consistency in assemblage composition among replicate Bou-Rouch samples collected in one stream. We recommend Bou-Rouch sampling for most study types, including rapid biomonitoring surveys and studies requiring acquisition of comprehensive taxon lists that include rare taxa. Despite collecting fewer macroinvertebrates, vacuum-pump sampling remains an important option for inexpensive and rapid sample collection.