Effect of species richness and relative abundance on the shape of the species accumulation curve

Abstract We explain how species accumulation curves are influenced by species richness (total number of species), relative abundance and diversity using computer‐generated simulations. Species richness defines the boundary of the horizontal asymptote value for a species accumulation curve, and the shape of the curve is influenced by both relative abundance and diversity. Simulations with a high proportion of rare species and a few abundant species have a species accumulation curve with a low ‘shoulder’ (inflection point on the ordinate axis) and a long upward slope to the asymptote. Simulations with a high proportion of relatively abundant species have a steeply rising initial slope to the species accumulation curve and plateau early. Diversity (as measured by Simpson's and Shannon–Weaver indices) for simulations is positively correlated with the initial slope of the species accumulation curve. Species accumulation curves cross when one simulation has a high proportion of both rare and abundant species compared with another that has a more even distribution of abundance among species.     

Using species accumulation curves to estimate trapping effort in fauna surveys and species richness

Abstract The shape of species accumulation curves is influenced by the relative abundance and diversity of the fauna being sampled, and the order in which individuals are caught. We use resampling to show the variation in species accumulation curves caused by the order of trapping periods. Averaged species accumulation curves calculated by randomly assigning the order of trapping periods are smooth curves that are a better estimate of species richness and a more useful tool for determining the trapping effort required to adequately survey a site. We extend this concept of randomly resampling the trapping period to show that randomizing the number of individuals caught for each species over the number of collection periods (e.g. days) can provide an accurate estimate of the averaged species accumulation curve. This is particularly useful as it enables an accurate estimation of the proportion of the total number of species caught in an area during a survey from information on the number of individuals caught for each species and the number of trapping periods, and is not dependent on having knowledge of the trapping period in which each individual was caught. This calculation also enables an assessment to be made of the adequacy of fauna surveys to report a species inventory in environmental impact assessments when only a species list and relative abundance data are provided.     

Determining adequate trapping effort and species richness using species accumulation curves for environmental impact assessments

Abstract Environmental impact assessments (EIA) require that the proponent indicates the potential impact that a development will have on the biodiversity of the area. As part of this assessment it is normal practice to inventory the vertebrate species in the area. We show here how species accumulation curves can be used as a tool by environmental consultants to indicate the adequacy of their trapping effort and predict species richness for a disturbance site. The shape of a species accumulation curve is influenced by the number of species in an assemblage and the proportional number of singletons (rarely caught species) in the survey sample. We provide guidelines for the number of individuals that need to be caught in a trapping program to achieve 80% and 90% of the species in a habitat, and we indicate how this number can be adjusted to accommodate variations in relative species abundance.     

Assessing biodiversity with species accumulation curves; inventories of small reptiles by pit‐trapping in Western Australia

Abstract We examined 11 non‐linear regression models to determine which of them best fitted curvilinear species accumulation curves based on pit‐trapping data for reptiles in a range of heterogeneous and homogenous sites in mesic, semi‐arid and arid regions of Western Australia. A well‐defined plateau in a species accumulation curve is required for any of the models accurately to estimate species richness. Two different measures of effort (pit‐trapping days and number of individuals caught) were used to determine if the measure of effort influenced the choice of the best model(s). We used species accumulation curves to predict species richness, determined the trapping effort required to catch a nominated percentage (e.g. 95%) of the predicted number of species in an area, and examined the relationship between species accumulation curves with diversity and rarity. Species richness, diversity and the proportion of rare species in a community influenced the shape of species accumulation curves. The Beta‐P model provided the best overall fit (highest r²) for heterogeneous and homogeneous sites. For heterogeneous sites, Hill, Rational, Clench, Exponential and Weibull models were the next best. For homogeneous habitats, Hill, Weibull and Chapman–Richards were the next best models. There was very little difference between Beta‐P and Hill models in fitting the data to accumulation curves, although the Hill model generally over‐estimated species richness. Most models worked equally well for both measures of trapping effort. Because the number of individuals caught was influenced by both pit‐trapping effort and the abundance of individuals, both measures of effort must be considered if species accumulation curves are to be used as a planning tool. Trapping effort to catch a nominated percentage of the total predicted species in homogeneous and heterogeneous habitats varied among sites, but even for only 75% of the predicted number of species it was generally much higher than the typical effort currently being used for terrestrial vertebrate fauna surveys in Australia. It was not possible to provide a general indication of the effort required to predict species richness for a site, or to capture a nominated proportion of species at a site, because species accumulation curves are heavily influenced by the characteristics of particular sites.     

Maximizing plant species inventory efficiency by means of remotely sensed spectral distances

Aim Inventorying plant species in an area based on randomly placed quadrats can be quite inefficient. The aim of this paper is to test whether plant species richness can be inventoried more efficiently by means of a spectrally‐based ordering of sites to be sampled. Location The study area was a complex wetland ecosystem, the Lake Montepulciano Nature Reserve, central Italy. This is one of the most important wetland areas of central Italy because of the diverse plant communities and the seasonal avifauna. Methods Field sampling, based on a random stratified sampling design, was performed in June 2002. Plant species composition was recorded within sampling units of 100 m² (plots) and 1 ha (macroplots). A QuickBird multispectral image of the same date was acquired and corrected both geometrically and radiometrically. Species accumulation curves based on spectral information were obtained by ordering sites to be sampled according to a maximum spectral distance criterion (i.e. by ordering sampling units based on the maximum distances among them in a four‐dimensional spectral space derived from the remotely sensed data). Different distance measures based on mean and maximum spectral distances among sampling units were tested. The performance of the species accumulation curve derived by the spectrally‐based ordering of sampling units was tested against a rarefaction curve obtained from the mean of 10,000 accumulation curves based on randomly ordered sampling units. Results The spectrally‐derived curve based on the maximum spectral distance among sampling units showed the most rapid accumulation of species, well above the rarefaction curve, at both the plot and the macroplot scales. Other ordering criteria of sampling units captured less richness over most of the species accumulation curves at both the spatial scales. The accumulation curves based on other measurements of distance were much closer to the random curve and did not show differences with respect to the species rarefaction curve based on random ordering of sampling units. Main conclusions The present investigation demonstrated that spectral‐based ordering of sites to be sampled can lead to the maximization of the efficiency of plant species inventories, an activity usually driven by the ‘botanist's internal algorithm’ (intuition), without any formalized rule to drive field sampling. The proposed approach can reduce costs of plant species inventorying through a more efficient allotment of time and sampling.     

A new relationship for rarefaction

All diversity indices are functions of the vector of the numbers of individuals in different species in a statistical population. So they are also functions of the number of species. It is well known, from the species-area curve and from collector's curves, that the number of species is a function of sampling effort. The rarefaction and Coleman functions are both functions that allow comparisons to be made at the same number of individuals, but have different mathematical forms. We show that the numerical difference between them, in the samples we have studied, is negligibly small. We show how to modify the Coleman function to allow for sampling without replacement, and show that the modified function is identical to the hypergeometric rarefaction function. Rarefaction should always be used, with any index, when comparing diversity in different size samples, but the number of species is the preferred index. Suggestions for comparing rarefaction curves from different samples are made.     

How many replicates to accurately estimate fish biodiversity using environmental DNA on coral reefs?

Quantifying fish species diversity in rich tropical marine environments remains challenging. Environmental DNA (eDNA) metabarcoding is a promising tool to face this challenge through the filtering, amplification, and sequencing of DNA traces from water samples. However, because eDNA concentration is low in marine environments, the reliability of eDNA to detect species diversity can be limited. Using an eDNA metabarcoding approach to identify fish Molecular Taxonomic Units (MOTUs) with a single 12S marker, we aimed to assess how the number of sampling replicates and filtered water volume affect biodiversity estimates. We used a paired sampling design of 30 L per replicate on 68 reef transects from 8 sites in 3 tropical regions. We quantified local and regional sampling variability by comparing MOTU richness, compositional turnover, and compositional nestedness. We found strong turnover of MOTUs between replicated pairs of samples undertaken in the same location, time, and conditions. Paired samples contained non‐overlapping assemblages rather than subsets of one another. As a result, non‐saturated localized diversity accumulation curves suggest that even 6 replicates (180 L) in the same location can underestimate local diversity (for an area <1 km). However, sampling regional diversity using ~25 replicates in variable locations (often covering 10 s of km) often saturated biodiversity accumulation curves. Our results demonstrate variability of diversity estimates possibly arising from heterogeneous distribution of eDNA in seawater, highly skewed frequencies of eDNA traces per MOTU, in addition to variability in eDNA processing. This high compositional variability has consequences for using eDNA to monitor temporal and spatial biodiversity changes in local assemblages. Avoiding false‐negative detections in future biomonitoring efforts requires increasing replicates or sampled water volume to better inform management of marine biodiversity using eDNA.     

Using standardized sampling designs from population ecology to assess biodiversity patterns of therophyte vegetation across scales

Aim The analysis of diversity across multiple scales is hampered by methodological difficulties resulting from the use of different sampling methods at different scales and by the application of different definitions of the communities to be sampled at different scales. It is our aim to analyse diversity in a nested hierarchy of scales by applying a formalized sampling concept used in population ecology when analysing population structure. This concept involved a precise definition of the sampled vegetation type by the presence of a target species, in our case Hornungia petraea. We compared separate indices of inventory diversity (i.e. number of species) and differentiation diversity (i.e. extent of change in species composition or dissimilarity) with indices derived from species accumulation curves and related diversity patterns to topographical plot characteristics such as area and distance. Location Ten plots were established systematically over a distance of 100 km each in the distribution centre of H. petraea in Italy (i.e. Marche and Umbria) and in a peripheral exclave in Germany (i.e. Thuringia and Saxony‐Anhalt). Methods We used a nested sampling design of 10 random subplots within plots and 10 systematically placed plots within regions. Internal α‐diversity (species richness) and internal β‐diversity (dissimilarity) were calculated on the basis of subplots, α‐, β‐ and γ‐diversity on the basis of plots in Italy and Germany. In addition, indices of inventory diversity and differentiation diversity were derived by fitting species accumulation curves to the Michaelis–Menten equation. Results There was no significant difference in the internal α‐diversity between German and Italian plots but the α‐ and γ‐diversity were higher in Italy than in Germany. In Germany, the internal β‐diversity and β‐diversity were lower than in Italy. The differentiation diversity increased with increasing scale from subplots over plots to regions. The same results were obtained by calculating species accumulation curves. Significant positive correlations were encountered between the internal α‐diversity and α‐diversity in both countries, while the internal β‐diversity and internal α‐diversity showed a correlation only for the Italian plots. Similarity decay was found for German plots with respect to inter‐plot distance and for Italian plots with respect to altitudinal difference and to a smaller degree to distance between plots. Main conclusions The design chosen and the consistent analysis of species accumulation curves by the Michaelis–Menten equation yielded consistent results over different scales. The specific therophyte vegetation type in this study reflected diversity patterns also observed in other studies, e.g. a greater differentiation diversity in central than in peripheral habitats and a trend of increasing species richness towards lower altitudes. No asymptotic saturation of species richness between different scales was observed. Indications were found that the absolute level of inventory diversity at a particular scale and the completeness of the sampling procedure are the main clues for explaining the relationship between inventory and differentiation diversity at this particular scale.     

Ichthyoplankton metabarcoding: An efficient tool for early detection of invasive species establishment

Detection of invasive species is critical for management but is often limited by challenges associated with capture, processing and identification of early life stages. DNA metabarcoding facilitates large-scale monitoring projects to detect establishment early. Here, we test the use of DNA metabarcoding to monitor invasive species by sequencing over 5000 fishes in bulk ichthyoplankton samples (larvae and eggs) from four rivers of ecological and cultural importance in southern Canada. We were successful in detecting species known from each river and three invasive species in two of the four rivers. This includes the first detection of early life-stage rudd in the Credit River. We evaluated whether sampling gear affected the detection of invasive species and estimates of species richness, and found that light traps outperform bongo nets in both cases. We also found that the primers used for the amplification of target sequences and the number of sequencing reads generated per sample affect the consistency of species detections. However, these factors have less impact on detections and species richness estimates than the number of samples collected and analysed. Our analyses also show that incomplete reference databases can result in incorrectly attributing DNA sequences to invasive species. Overall, we conclude that DNA metabarcoding is an efficient tool for monitoring the early establishment of invasive species by detecting evidence of reproduction but requires careful consideration of sampling design and the primers used to amplify, sequence and classify the diversity of native and potentially invasive species.     

Species diversity in vertical, horizontal, and temporal dimensions of a fruit-feeding butterfly community in an Ecuadorian rainforest

To test the hypotheses that fruit-feeding nymphalid butterflies are randomly distributed in space and time, a community of fruit-feeding nymphalid butterflies was sampled at monthly intervals for one year by trapping 6690 individuals of 130 species in the canopy and understory of four forest habitats: primary, higraded, secondary, and edge. The overall species abundance distribution was well described by a lognormal distribution. Total species diversity (γ-diversity) was partitioned into additive components within and among community subdivisions (α-diversity and β-diversity) in vertical, horizontal and temporal dimensions. Although community subdivisions showed high similarity (1 —β-diversity/γ-diversity), significant β-diversity existed in each dimension. Individual abundance and observed species richness was lower in the canopy than in the understory. However, rarefaction analysis and species accumulation curves revealed that canopy had higher species richness than understory. Observed species richness was roughly equal in all habitats, but individual abundance was much greater in edge, largely due to a single, specialist species. Rarefaction analysis and species accumulation curves showed that edge had significantly lower species richness than all other habitats. Samples from a single habitat, height and time contained only a small fraction of the total community species richness. This study demonstrates the feasibility, and necessity, of large-scale, long-term sampling in multiple dimensions for accurately measuring species richness and diversity in tropical forest communities. We discuss the importance of such studies in conservation biology.     

Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness

Species richness is a fundamental measurement of community and regional diversity, and it underlies many ecological models and conservation strategies. In spite of its importance, ecologists have not always appreciated the effects of abundance and sampling effort on richness measures and comparisons. We survey a series of common pitfalls in quantifying and comparing taxon richness. These pitfalls can be largely avoided by using accumulation and rarefaction curves, which may be based on either individuals or samples. These taxon sampling curves contain the basic information for valid richness comparisons, including category–subcategory ratios (species-to-genus and species-to-individual ratios). Rarefaction methods – both sample-based and individual-based – allow for meaningful standardization and comparison of datasets. Standardizing data sets by area or sampling effort may produce very different results compared to standardizing by number of individuals collected, and it is not always clear which measure of diversity is more appropriate. Asymptotic richness estimators provide lower-bound estimates for taxon-rich groups such as tropical arthropods, in which observed richness rarely reaches an asymptote, despite intensive sampling. Recent examples of diversity studies of tropical trees, stream invertebrates, and herbaceous plants emphasize the importance of carefully quantifying species richness using taxon sampling curves.     

An approach based on the total‐species accumulation curve and higher taxon richness to estimate realistic upper limits in regional species richness

Most of accumulation curves tend to underestimate species richness, as they do not consider spatial heterogeneity in species distribution, or are structured to provide lower bound estimates and limited extrapolations. The total‐species (T–S) curve allows extrapolations over large areas while taking into account spatial heterogeneity, making this estimator more prone to attempt upper bound estimates of regional species richness. However, the T–S curve may overestimate species richness due to (1) the mismatch among the spatial units used in the accumulation model and the actual units of variation in β‐diversity across the region, (2) small‐scale patchiness, and/or (3) patterns of rarity of species. We propose a new framework allowing the T–S curve to limit overestimation and give an application to a large dataset of marine mollusks spanning over 11 km² of subtidal bottom (W Mediterranean). As accumulation patterns are closely related across the taxonomic hierarchy up to family level, improvements of the T–S curve leading to more realistic estimates of family richness, that is, not exceeding the maximum number of known families potentially present in the area, can be considered as conducive to more realistic estimates of species richness. Results on real data showed that improvements of the T–S curve to accounts for true variations in β‐diversity within the sampled areas, small‐scale patchiness, and rarity of families led to the most plausible richness when all aspects were considered in the model. Data on simulated communities indicated that in the presence of high heterogeneity, and when the proportion of rare species was not excessive (>2/3), the procedure led to almost unbiased estimates. Our findings highlighted the central role of variations in β‐diversity within the region when attempting to estimate species richness, providing a general framework exploiting the properties of the T–S curve and known family richness to estimate plausible upper bounds in γ‐diversity.     

High throughput automated allele frequency estimation by pyrosequencing

Pyrosequencing is a DNA sequencing method based on the principle of sequencing-by-synthesis and pyrophosphate detection through a series of enzymatic reactions. This bioluminometric, real-time DNA sequencing technique offers unique applications that are cost-effective and user-friendly. In this study, we have combined a number of methods to develop an accurate, robust and cost efficient method to determine allele frequencies in large populations for association studies. The assay offers the advantage of minimal systemic sampling errors, uses a general biotin amplification approach, and replaces dTTP for dATP-apha-thio to avoid non-uniform higher peaks in order to increase accuracy. We demonstrate that this newly developed assay is a robust, cost-effective, accurate and reproducible approach for large-scale genotyping of DNA pools. We also discuss potential improvements of the software for more accurate allele frequency analysis.     

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.     

On the estimation of species richness based on the accumulation of previously unrecorded species

Estimation of species richness of local communities has become an important topic in community ecology and monitoring. Investigators can seldom enumerate all the species present in the area of interest during sampling sessions. If the location of interest is sampled repeatedly within a short time period, the number of new species recorded is typically largest in the initial sample and decreases as sampling proceeds, but new species may be detected if sampling sessions are added. The question is how to estimate the total number of species. The data collected by sampling the area of interest repeatedly can be used to build species accumulation curves: the cumulative number of species recorded as a function of the number of sampling sessions (which we refer to as “species accumulation data”). A classic approach used to compute total species richness is to fit curves to the data on species accumulation with sampling effort. This approach does not rest on direct estimation of the probability of detecting species during sampling sessions and has no underlying basis regarding the sampling process that gave rise to the data. Here we recommend a probabilistic, nonparametric estimator for species richness for use with species accumulation data. We use estimators of population size that were developed for capture‐recapture data, but that can be used to estimate the size of species assemblages using species accumulation data. Models of detection probability account for the underlying sampling process. They permit variation in detection probability among species. We illustrate this approach using data from the North American Breeding Bird Survey (BBS). We describe other situations where species accumulation data are collected under different designs (e.g., over longer periods of time, or over spatial replicates) and that lend themselves to of use capture‐recapture models for estimating the size of the community of interest. We discuss the assumptions and interpretations corresponding to each situation.     

Diversity of predaceous arthropods in the almond tree canopy in Northeastern Portugal: A methodological approach

The almond tree is an economically important crop in Mediterranean regions. However, knowledge about the biodiversity of natural enemies that may be useful as biocontrol agents is scarce. The objectives of this work were: (i) to study the diversity of predaceous arthropods; and (ii) to establish a suitable sampling protocol for arthropods of the almond tree canopy. Between April and October of 2007 and 2008, 25 randomly selected trees were sampled in an organic almond grove located in the north‐east of Portugal using the beating technique. The specimens collected were counted and identified and the sampling protocol was established by using the accumulation curves and the seasonal richness peaks of the most abundant groups of natural enemies. A total of 1856 and 1301 arthropods were captured, respectively, in 2007 and 2008, where Araneae, Coccinellidae and Formicidae were the most abundant groups. A total of 14 families and 29 species of spiders were identified as Linyphiidae, Philodromidae, Thomisidae, Araneidae and Oxyopidae, the five most abundant families in both years. In the Coccinellidae and Formicidae communities 15 and 13 species were identified, respectively. According to taxa accumulation curves, the minimum sampling effort that provided a reliable picture of the biodiversity was established in 11 samples. Moreover, considering the seasonal richness distribution, it would be advisable to concentrate the sampling period from the beginning of July to the harvesting of almonds. This protocol might generate accurate replicate samples to estimate species richness when the effect of agricultural management is studied.     

Minimum sample sizes for population genomics: an empirical study from an Amazonian plant species

High‐throughput DNA sequencing facilitates the analysis of large portions of the genome in nonmodel organisms, ensuring high accuracy of population genetic parameters. However, empirical studies evaluating the appropriate sample size for these kinds of studies are still scarce. In this study, we use double‐digest restriction‐associated DNA sequencing (ddRADseq) to recover thousands of single nucleotide polymorphisms (SNPs) for two physically isolated populations of Amphirrhox longifolia (Violaceae), a nonmodel plant species for which no reference genome is available. We used resampling techniques to construct simulated populations with a random subset of individuals and SNPs to determine how many individuals and biallelic markers should be sampled for accurate estimates of intra‐ and interpopulation genetic diversity. We identified 3646 and 4900 polymorphic SNPs for the two populations of A. longifolia, respectively. Our simulations show that, overall, a sample size greater than eight individuals has little impact on estimates of genetic diversity within A. longifolia populations, when 1000 SNPs or higher are used. Our results also show that even at a very small sample size (i.e. two individuals), accurate estimates of F_ST can be obtained with a large number of SNPs (≥1500). These results highlight the potential of high‐throughput genomic sequencing approaches to address questions related to evolutionary biology in nonmodel organisms. Furthermore, our findings also provide insights into the optimization of sampling strategies in the era of population genomics.     

Hybridization ddRAD‐sequencing for population genomics of nonmodel plants using highly degraded historical specimen DNA

Species’ responses at the genetic level are key to understanding the long‐term consequences of anthropogenic global change. Herbaria document such responses, and, with contemporary sampling, provide high‐resolution time‐series of plant evolutionary change. Characterizing genetic diversity is straightforward for model species with small genomes and a reference sequence. For nonmodel species—with small or large genomes—diversity is traditionally assessed using restriction‐enzyme‐based sequencing. However, age‐related DNA damage and fragmentation preclude the use of this approach for ancient herbarium DNA. Here, we combine reduced‐representation sequencing and hybridization‐capture to overcome this challenge and efficiently compare contemporary and historical specimens. Specifically, we describe how homemade DNA baits can be produced from reduced‐representation libraries of fresh samples, and used to efficiently enrich historical libraries for the same fraction of the genome to produce compatible sets of sequence data from both types of material. Applying this approach to both Arabidopsis thaliana and the nonmodel plant Cardamine bulbifera, we discovered polymorphisms de novo in an unbiased, reference‐free manner. We show that the recovered genetic variation recapitulates known genetic diversity in A. thaliana, and recovers geographical origin in both species and over time, independent of bait diversity. Hence, our method enables fast, cost‐efficient, large‐scale integration of contemporary and historical specimens for assessment of genome‐wide genetic trends over time, independent of genome size and presence of a reference genome.     

Revised and annotated checklist of aquatic and semi-aquatic Heteroptera of Hungary with comments on biodiversity patterns

A basic knowledge of regional faunas is necessary to follow the changes in macroinvertebrate communities caused by environmental influences and climatic trends in the future. We collected all the available data on water bugs in Hungary using an inventory method, a UTM grid based database was built, and Jackknife richness estimates and species accumulation curves were calculated. Fauna compositions were compared among Central-European states. As a result, an updated and annotated checklist for Hungary is provided, containing 58 species in 21 genera and 12 families. A total 66.8% of the total UTM 10 × 10 km squares in Hungary possess faunistic data for water bugs. The species number in grid cells numbered from 0 to 42, and their diversity patterns showed heterogeneity. The estimated species number of 58 is equal to the actual number of species known from the country. The asymptotic shape of the accumulative species curve predicts that additional sampling efforts will not increase the number of species currently known from Hungary. These results suggest that the number of species in the country was estimated correctly and that the species accumulation curve levels off at an asymptotic value. Thus a considerable increase in species richness is not expected in the future. Even with the species composition changing the chance of species turn-over does exist. Overall, 36.7% of the European water bug species were found in Hungary. The differences in faunal composition between Hungary and its surrounding countries were caused by the rare or unique species, whereas 33 species are common in the faunas of the eight countries. Species richness does show a correlation with latitude, and similar species compositions were observed in the countries along the same latitude. The species list and the UTM-based database are now up-to-date for Hungary, and it will provide a basis for future studies of distributional and biodiversity patterns, biogeography, relative abundance and frequency of occurrences important in community ecology, or the determination of conservation status.