Assessment of methods to estimate aquatic macrophyte species richness in extrapolated sample sizes

We evaluated six methods to estimate species richness in extrapolated sample size using presence–absence data for aquatic macrophyte assemblages. Methods suitable for assemblages involving terrestrial and non-clonal (unitary) organisms may not be valid for aquatic macrophytes. The extrapolation of a species accumulation curve using a logarithmic function or using a linear model on the log of accumulated sampling units consistently overestimated species richness. The newly proposed Total-Species method gave similar results. The Negative Binomial and Logarithmic Series methods and the recently proposed Binomial Mixture Model were unbiased and accurate. We conclude that current extrapolation techniques are valid for estimation of species richness in macrophyte assemblages, and recommend the Logarithmic Series, Binomial Negative or Binomial Mixture Model methods.     

Modelling species richness and diversity in grassland communities of the Central Caucasus

In this study I used small squares (4 cm×4 cm) as a sampling technique within plots (128 cm×128 cm) of different elevation, aspect and slope angle in grassland communities (20 plots examined). Then I used a rectangular hyperbole equation (the Michaelis-Menten model) to describe species richness and the Inverse of Simpson Concentration (ISC) as functions of sample size. I checked robustness and precision of the model both by interpolation and extrapolation. Interpolation was similarly good in both cases, while extrapolation produced reliable predictions of ISC but underestimated species richness. Dominance analysis indicated that the underestimation of richness depends on the proportion of bottom species, and that the predicted values of richness roughly coincide with the numbers of dominant species found in plots. Therefore, the model may be used to assess number of dominant species when precision is less important than saving time during a survey. However, the rectangular hyperbole equation appears to be precise and robust in the prediction of ISC, at least in grassland communities. This property may also be employed for extrapolation of diversity indices with a limited sampling effort.     

The positive correlation between avian species richness and human population density in Britain is not attributable to sampling bias

Aim  To assess whether spatial variation in sampling effort drives positive correlations between human population density and species richness.
Location  British 10 × 10 km squares.
Methods  We calculated three measures of species richness from atlas data of breeding birds in Britain: total species richness, species richness standardised for sampling effort, and the number of species only recorded in supplementary casual records in a manner not standardised for survey effort. We then assessed the form of the relationship between these richness estimates and human population density, both with and without taking spatial autocorrelation into account.
Results  Both total and standardised species richness exhibit similar species richness–human population density relationships; species richness generally increases with human population density, but decreases at the very highest densities. Supplementary species richness is very weakly correlated with human population density.
Main conclusions  In this example, sampling effort only slightly influences the form of species richness–human population density relationships. The positive correlation between species richness and human population density and any resultant conservation conflicts are thus not artefactual patterns generated by confounding human density and sampling effort.     

Geographical variation in the 'bottom-up' control of diversity: fleas and their small mammalian hosts

Aim We searched for signs of the ‘bottom‐up’ diversity effect in the association between fleas (Siphonaptera) and their small mammalian hosts (Rodentia, Insectivora and Lagomorpha). We asked (1) whether a strong dependence of flea species richness on host species richness is characteristic for both Palaeoarctic and Nearctic realms; (2) if yes, whether the ratio of host species per flea species along the host diversity gradient is similar between the Palaeoarctic and Nearctic; and (3) whether factors other than host species richness (i.e. geographical position, climate and landscape) might better explain variation in flea species richness than host species richness. Location The study used previously published data on species richness of fleas and their small mammalian hosts from 26 Palaeoarctic and 19 Nearctic regions. Methods We regressed the number of flea species on the number of small mammal species across regions, separately for Palaeoarctic and Nearctic realms, using both non‐transformed data as well as data corrected for the confounding effects of host sampling effort and sampling area. To test whether flea species richness is determined by external factors unrelated to the host, we used stepwise multiple regressions of flea species richness against host species richness and parameters describing the geographical position, climate and relief of a region. Results When non‐transformed data were analysed, flea species richness was positively correlated with host species richness in both the Palaeoarctic and Nearctic, although the slopes of the two regressions differed significantly. After removal of the confounding effects of host sampling effort and sampling area, Palaeoarctic flea species richness remained strongly positively correlated with host species richness, whereas in the Nearctic, flea species richness appeared to be completely independent of host species richness. Results of the multiple regressions using corrected data demonstrated that in the Palaeoarctic, flea species richness was correlated with both the number of host species and the mean altitude of the region, whereas in the Nearctic, flea species richness only tended to be weakly correlated with latitude (however, this correlation turned out to be non‐significant after Bonferroni correction). Main conclusions We found evidence of bottom‐up control of flea diversity in the Palaeoarctic regions only, and not in the Nearctic. We explore several potential explanations for the different patterns observed in the two biogeographical realms, including differences in (1) levels of host specialization, (2) history of host–parasite associations and (3) landscape effects on flea diversification. We conclude that these factors combine to create different macroecological patterns in different biogeographical realms, and that diversity is not governed by the same forces everywhere.     

Effects of sampling protocol on the shapes of species richness curves

Aim Scheiner (Journal of Biogeography, 2009, 36 , 2005–2008) criticized several issues regarding the typology and analysis of species richness curves that were brought forward by Dengler (Journal of Biogeography, 2009, 36 , 728–744). In order to test these two sets of views in greater detail, we used a simulation model of ecological communities to demonstrate the effects of different sampling schemes on the shapes of species richness curves and their extrapolation capability. Methods We simulated five random communities with 100 species on a 64 × 64 grid using random fields. Then we sampled species–area relationships (SARs, contiguous plots) as well as species–sampling relationships (SSRs, non‐contiguous plots) from these communities, both for the full extent and the central quarter of the grid. Finally, we fitted different functions (power, quadratic power, logarithmic, Michaelis–Menten, Lomolino) to the obtained data and assessed their goodness‐of‐fit (Akaike weights) and their extrapolation capability (deviation of the predicted value from the true value). Results We found that power functions gave the best fit for SARs, while for SSRs saturation functions performed better. Curves constructed from data of 32² grid cells gave reasonable extrapolations for 64² grid cells for SARs, irrespective of whether samples were gathered from the full extent or the centre only. By contrast, SSRs worked well for extrapolation only in the latter case. Main conclusions SARs and SSRs have fundamentally different curve shapes. Both sampling strategies can be used for extrapolation of species richness to a target area, but only SARs allow for extrapolation to a larger area than that sampled. These results confirm a fundamental difference between SARs and area‐based SSRs and thus support their typological differentiation.     

Parasite richness/sampling effort/host range: the fancy three-piece jigsaw puzzle

In this article, Jean-Fran?ois Guégan and Clive Kennedy propose an alternative explanation for the confounding effects of host geographical range and sampling effort on parasite species richness using pathway analysis procedure. They suggest that much of the species richness revealed by sampling effort is also a reflection of host range. Thus, the total contribution of host range logically incorporates a contribution from sampling effort. The implications of indirect effects of host range on richness estimates have not previously been discussed, and the authors here attempt to redress the balance. The contribution of host range to richness, as derived from control of sampling effort on richness estimates, therefore, is a mathematical expression that does not take into account the cause-and-effect nature of things.     

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.     

生物群落多样性的测度方法 V.生物群落物种数目的估计方法

群落的物种数目,即物种丰富度,是最古老、同时也是最基本的一个多样性概念,从对它的估计中可以得到关于物种灭绝速率方面的信息,这对生物多样性保护是非常重要的。已经提出了很多方法来估计群落中的物种数目,这些方法可以分为两大类,即基于理论抽样的方法和基于数据分析的方法。前者包括经典估计方法和贝叶斯估计方法;后者包括对数正态分布的积分方法、再抽样方法和种－面积曲线的外推方法。发现：（１）有些方法适用于动物群落,如大多数基于理论抽样的方法;有些方法则适用于植物群落,如大多数基于数据分析的方法;（２）这些方法还没有经过全面而系统地比较;（３）还没有一个普遍认为比较好的方法。因此,建议采用野外调查与模拟研究相结合的方法对各种估计方法进行系统地评价。     

Matthew effect in counting the number of species

The number of species in an area is a fundamental parameter in species-area theory. Besides sampling size and statistical extrapolation, the inaccurate number of species can intensify the existing controversy on the species richness—productivity and extinction rate overestimate/underestimate. This problem can be caused by Matthew effect from sampling process and taxonomic identification: it is much easier to identify and record common species than rare species. Therefore, it is necessary to prevent and control the Matthew effect, which can distort the number of species (especially the rare species) and the individuals of each species.     

Models and estimators linking individual-based and sample-based rarefaction,extrapolation and comparison of assemblages

Aims In ecology and conservation biology, the number of species counted in a biodiversity study is a key metric but is usually a biased underestimate of total species richness because many rare species are not detected. Moreover, comparing species richness among sites or samples is a statistical challenge because the observed number of species is sensitive to the number of individuals counted or the area sampled. For individual-based data, we treat a single, empirical sample of species abundances from an investigator-defined species assemblage or community as a reference point for two estimation objectives under two sampling models: estimating the expected number of species (and its unconditional variance) in a random sample of (i) a smaller number of individuals (multinomial model) or a smaller area sampled (Poisson model) and (ii) a larger number of individuals or a larger area sampled. For sample-based incidence (presence–absence) data, under a Bernoulli product model, we treat a single set of species incidence frequencies as the reference point to estimate richness for smaller and larger numbers of sampling units.Methods The first objective is a problem in interpolation that we address with classical rarefaction (multinomial model) and Coleman rarefaction (Poisson model) for individual-based data and with sample-based rarefaction (Bernoulli product model) for incidence frequencies. The second is a problem in extrapolation that we address with sampling-theoretic predictors for the number of species in a larger sample (multinomial model), a larger area (Poisson model) or a larger number of sampling units (Bernoulli product model), based on an estimate of asymptotic species richness. Although published methods exist for many of these objectives, we bring them together here with some new estimators under a unified statistical and notational framework. This novel integration of mathematically distinct approaches allowed us to link interpolated (rarefaction) curves and extrapolated curves to plot a unified species accumulation curve for empirical examples. We provide new, unconditional variance estimators for classical, individual-based rarefaction and for Coleman rarefaction, long missing from the toolkit of biodiversity measurement. We illustrate these methods with datasets for tropical beetles, tropical trees and tropical ants.Important findings Surprisingly, for all datasets we examined, the interpolation (rarefaction) curve and the extrapolation curve meet smoothly at the reference sample, yielding a single curve. Moreover, curves representing 95% confidence intervals for interpolated and extrapolated richness estimates also meet smoothly, allowing rigorous statistical comparison of samples not only for rarefaction but also for extrapolated richness values. The confidence intervals widen as the extrapolation moves further beyond the reference sample, but the method gives reasonable results for extrapolations up to about double or triple the original abundance or area of the reference sample. We found that the multinomial and Poisson models produced indistinguishable results, in units of estimated species, for all estimators and datasets. For sample-based abundance data, which allows the comparison of all three models, the Bernoulli product model generally yields lower richness estimates for rarefied data than either the multinomial or the Poisson models because of the ubiquity of non-random spatial distributions in nature.     

Comparing species richness among assemblages using sample units: why not use extrapolation methods to standardize different sample sizes?

Comparisons of species richness among assemblages using different sample sizes may produce erroneous conclusions due to the strong positive relationship between richness and sample size. A current way of handling the problem is to standardize sample sizes to the size of the smallest sample in the study. A major criticism about this approach is the loss of information contained in the larger samples. A potential way of solving the problem is to apply extrapolation techniques to smaller samples, and produce an estimated species richness expected to occur if sample size were increased to the same size of the largest sample. We evaluated the reliability of 11 potential extrapolation methods over a range of different data sets and magnitudes of extrapolation. The basic approach adopted in the evaluation process was a comparison between the observed richness in a sample and the estimated richness produced by estimators using a sub-sample of the same sample. The Log-Series estimator was the most robust for the range of data sets and sub-sample sizes used, followed closely by Negative Binomial, SO-J1, Logarithmic, Stout and Vandermeer, and Weibull estimators. When applied to a set of independently replicated samples from a species-rich assemblage, 95% confidence intervals of estimates produced by the six best evaluated methods were comparable to those of observed richness in the samples. Performance of estimators tended to be better for species-rich data sets rather than for those which contained few species. Good estimates were found when extrapolating up to 1.8-2.0 times the size of the sample. We suggest that the use of the best evaluated methods within the range of indicated conditions provides a safe solution to the problem of losing information when standardizing different sample sizes to the size of the smallest sample.     

Host longevity and parasite species richness in mammals

Hosts and parasites co-evolve, with each lineage exerting selective pressures on the other. Thus, parasites may influence host life-history characteristics, such as longevity, and simultaneously host life-history may influence parasite diversity. If parasite burden causes increased mortality, we expect a negative association between host longevity and parasite species richness. Alternatively, if long-lived species represent a more stable environment for parasite establishment, host longevity and parasite species richness may show a positive association. We tested these two opposing predictions in carnivores, primates and terrestrial ungulates using phylogenetic comparative methods and controlling for the potentially confounding effects of sampling effort and body mass. We also tested whether increased host longevity is associated with increased immunity, using white blood cell counts as a proxy for immune investment. Our analyses revealed weak relationships between parasite species richness and longevity. We found a significant negative relationship between longevity and parasite species richness for ungulates, but no significant associations in carnivores or primates. We also found no evidence for a relationship between immune investment and host longevity in any of our three groups. Our results suggest that greater parasite burden is linked to higher host mortality in ungulates. Thus, shorter-lived ungulates may be more vulnerable to disease outbreaks, which has implications for ungulate conservation, and may be applicable to other short-lived mammals.     

Host population density as the major determinant of endoparasite species richness in floodplain fishes of the upper Paraná River, Brazil

A comparative analysis of parasite species richness was performed across 53 species of fish from the floodplain of the upper Paraná River, Brazil. Values of catch per unit effort, CPUE (number of individuals of a given fish species captured per 1000 m(2) of net during 24 h) were used as a rough measure of population density for each fish species in order to test its influence on endoparasite species richness. The effects of several other host traits (body size, social behaviour, reproductive behaviour, spawning type, trophic category, feeding habits, relative position in the food web, preference for certain habitats and whether the fish species are native or exotic) on metazoan endoparasite species richness were also evaluated. The CPUE was the sole significant predictor of parasite species richness, whether controlling for the confounding influences of host phylogeny and sampling effort or not. The results suggest that in the floodplain of the upper Paraná River (with homogeneous physical characteristics and occurrence of many flood pulses), population density of different host species might be the major determinant of their parasite species richness.     

Efficiency of a Rapid Assessment of the Diversity of Ground Beetles and Ants, in Natural and Disturbed Habitats of the Nahuel Huapi Region (NW Patagonia, Argentina)

We use sample-based rarefaction curves to evaluate the efficiency of a rapid species richness assay of ground beetles and ants captured in pitfall traps in the Nahuel Huapi National Park (NW Patagonia, Argentina). We ask whether ant species richness patterns show some concordance with those of beetles, and use several extrapolation indices for estimating the expected number of species at a regional scale. A total of 342 pitfall traps were spread in groups, at an intensity of 9 traps/100 m², with two collection stations, at each of 19 sites representative of burned and unburned habitats in the forest, scrub and steppe, along a west-to-east transect of 63 km long. The high regional habitat heterogeneity along the west-to-east gradient is paralleled by a turnover of beetle and ant species, although different families of Coleoptera show idiosyncratic responses across habitat types. Spatial stratification of sampling over three major habitats along with the inclusion of burned and unburned environments may improve sampling efficiency. The observed and extrapolated species richness suggests that we captured a high proportion of the total number of species of beetles and ants known for the region. However, trends in species richness of ants may not indicate similar trends in beetles. Ants and beetles cannot be used as surrogate taxa for the analysis of species richness patterns. Instead, both taxa should be considered as focal as they may offer complementary information for the analysis of the effect of disturbance and regional habitat heterogeneity on species diversity patterns at a regional scale.     

Limited effects of dominant ants on assemblage species richness in three Amazon forests

1. Ants are highly interactive organisms and dominant species are considered to be able to control the species richness of other ants via competitive exclusion. However, depending on the scale studied, inter‐specific competition may or may not structure biological assemblages. To date, ant dominance–richness relationships have only been studied in small sample units, where a few dominant colonies could plausibly control most of the sample unit. 2. We conducted a comprehensive survey of terrestrial ant assemblages using bait, pitfall, and litter‐sorting methods in three sites in Brazilian Amazonia. Using a spatially structured rarefaction approach, based on sampling units with linear dimensions ranging from 25 to 250 m, the mesoscale patterns of ant dominance–richness relationships (sampling units covering hundreds of meters separated by kilometers) were investigated. 3. Interference–competition models (parabolic or negative linear relationships between species richness and the abundance of dominant ants) tended to be more frequent in smaller sample units or in assemblages sampled with interactive methods, such as baits. Using more inclusive sampling methods, the relationship was generally asymptotic rather than parabolic, with no reduction in species diversity because of the presence of dominants. Random co‐occurrence patterns of species within sites support the interpretation of a limited role for present‐day competition in structuring these assemblages. 4. Competition from dominant species may reduce species richness in small areas, especially when artificial baits are used, but appears to be less important than environmental constraints in determining ant species richness across scales of hectares and greater in these Amazon forests.     

Skipper Richness (Hesperiidae) Along Elevational Gradients in Brazilian Atlantic Forest

Hesperiidae are claimed to be a group of elusive butterflies that need major effort for sampling, thus being frequently omitted from tropical butterfly surveys. As no studies have associated species richness patterns of butterflies with environmental gradients of high altitudes in Brazil, we surveyed Hesperiidae ensembles in Serra do Mar along elevational transects (900–1,800 m above sea level) on three mountains. Transects were sampled 11–12 times on each mountain to evaluate how local species richness is influenced by mountain region, vegetation type, and elevational zones. Patterns were also analyzed for the subfamilies, and after disregarding species that exhibit hilltopping behavior. Species richness was evaluated by the observed richness, Jacknife2 estimator and Chao 1 estimator standardized by sample coverage. Overall, 155 species were collected, but extrapolation algorithms suggest a regional richness of about 220 species. Species richness was far higher in forest than in early successional vegetation or grassland. Richness decreased with elevation, and was higher on Anhangava mountain compared with the two others. Patterns were similar between observed and extrapolated Jacknife2 richness, but vegetation type and mountain richness became altered using sample coverage standardization. Hilltopping species were more easily detected than species that do not show this behavior; however, their inclusion did neither affect estimated richness nor modify the shape of the species accumulation curve. This is the first contribution to systematically study highland butterflies in southern Brazil where all records above 1,200 m are altitudinal extensions of the known geographical ranges of skipper species in the region.     

Using Museum Collections to Estimate Diversity Patterns along Geographical Gradients

Quantifying species-richness patterns along geographical gradients (typically latitude and elevation) has a long history in ecology and can be based on more-or-less complete censuses from a specified area (plot sampling), selective collection within a specified area (e.g. museum collections), or general information about species distributions (e.g. observations of extremes along the gradient, distribution maps). All these approaches require complete sampling to give the true richness in an area, but the richness pattern (i.e., the relative changes in richness along the gradient) may be estimated without complete sampling, although equal sampling between areas is necessary. This is relatively easy to do for fine-scale plot sampling, but rarely easy for other types of data. For data extracted from museum collections, a correct perception of the species richness pattern therefore depends on post-sampling treatment of data. Two commonly applied techniques for quantifying species richness patterns with these types of data are discussed, namely interpolation of species ranges and rarefaction. Such treatment may correct for unequal sampling in some instances, but may in other cases introduce artificial patterns. With incomplete sampling interpolation introduces an artificial humped pattern and rarefaction requires similar species abundance distributions to make unbiased comparisons among samples. One must therefore be cautious when applying these methods for estimating species richness patterns along geographical gradients.     

Biogeographical patterns of blood parasite lineage diversity in avian hosts from southern Melanesian islands

Aim (1) To describe the species–area relationships among communities of Plasmodium and Haemoproteus parasites in different island populations of the same host genus (Aves: Zosterops). (2) To compare distance–decay relationships (turnover) between parasite communities and those with potential avian and dipteran hosts, which differ with respect to their movement and potential to disperse parasite species over large distances. Location Two archipelagos in the south‐west Pacific, Vanuatu and New Caledonia (c. 250 km west of Vanuatu) and its Loyalty Islands, with samples collected from a total of 16 islands of varying sizes (328–16,648 km²). Methods We characterized parasite diversity and distribution via polymerase chain reaction (PCR) from avian (Zosterops) blood samples. Bayesian methods were used to reconstruct the parasite phylogeny. In accordance with recent molecular evidence, we treat distinct mitochondrial DNA lineages as equivalent to species in this study. Path analysis and parasite lineage accumulation curves were used to assess the confounding effect of inadequate sampling on the estimation of parasite richness. Species–area and species–distance relationships were assessed using linear regression: distance–decay relationships were assessed using Mantel tests. Results Birds and mosquito species and Plasmodium lineages exhibited significant species–area relationships. However, Plasmodium lineages showed the weakest ‘species–area’ relationship; no relationship was found for Haemoproteus lineages. Avian species richness influenced parasite lineage richness more than mosquito species richness did. Within individual avian host species, the species–area relationship of parasites showed differing patterns. Path analysis indicated that sampling effort was unlikely to have a confounding effect on parasite richness. Distance from mainland (isolation effect) showed no effect on parasite richness. Community similarity decayed significantly with distance for avifauna, mosquito fauna and Plasmodium lineages but not for Haemoproteus lineages. Main conclusions Plasmodium lineages and mosquito species fit the power‐law model with steeper slopes than found for the avian hosts. The lack of species–distance relationship in parasites suggests that other factors, such as the competence of specific vectors and habitat features, may be more important than distance. The decay in similarity with distance suggests that the sampled Plasmodium lineages and their potential hosts were not randomly distributed, but rather exhibited spatially predictable patterns. We discuss these results in the context of the effects that parasite generality may have on distribution patterns.     

Tropical paradox: a multi-scale analysis of the invasion paradox within Miami Rock Ridge tropical hardwood hammocks

The invasion paradox describes the scale dependence of native-exotic richness relationships (NERRs), where NERRs are negative at neighborhood scales and positive at landscape scales. However, a lack of tropical surveys and past failures to isolate potential confounding variables contribute to significant gaps in our understanding of the processes producing these patterns. We surveyed the vascular flora of 13 tropical hardwood hammocks for community characteristics (e.g., native and exotic species richness, vegetative cover) with a hierarchical sampling design. Using model selection, we determined which variables best predicted patterns of exotic species richness at each spatial scale of consideration. We found that native and exotic species richness were positively correlated at neighborhood scales, but negatively correlated at landscape scales. The latter result stands in stark opposition to the patterns published in the literature thus far. We found that natural disturbance history (as approximated by vegetative cover) was positively correlated with exotic species richness at intermediate and landscape scales only. Overall, hammock identity was the most important factor driving exotic species richness patterns at all spatial scales. Hammocks with highly-disturbed hydrologies, brought about by water management, had fewer native species and more exotic species than hammocks with more natural hydrological conditions. Our results are among the first from examination of subtropical communities, and may support the hypothesis that tropical and subtropical communities are subject to more intense biotic interactions. However, given our unique sampling design, our results do not reject the hypothesis that environmental heterogeneity drives the relationship between native and exotic species richness patterns.     

Assessing bee species richness in two Mediterranean communities: importance of habitat type and sampling techniques

The decline of bees has raised concerns regarding their conservation and the maintenance of ecosystem services they provide to bee-pollinated wild flowers and crops. Although the Mediterranean region is a hotspot for bee species richness, their status remains poorly studied. There is an urgent need for cost-effective, reliable, and unbiased sampling methods that give good bee species richness estimates. This study aims: (a) to assess bee species richness in two common Mediterranean habitat types: semi-natural scrub (phrygana) and managed olive groves; (b) to compare species richness in those systems to that of other biogeographic regions, and (c) to assess whether six different sampling methods (pan traps, variable and standardized transect walks, observation plots and trap nests), previously tested in other European biogeographic regions, are suitable in Mediterranean communities. Eight study sites, four per habitat type, were selected on the island of Lesvos, Greece. The species richness observed was high compared to other habitat types worldwide for which comparable data exist. Pan traps collected the highest proportion of the total bee species richness across all methods at the scale of a study site. Variable and standardized transect walks detected the highest total richness over all eight study sites. Trap nests and observation plots detected only a limited fraction of the bee species richness. To assess the total bee species richness in bee diversity hotspots, such as the studied habitats, we suggest a combination of transect walks conducted by trained bee collectors and pan trap sampling.