Estimating species richness using environmental DNA

The foundation for any ecological study and for the effective management of biodiversity in natural systems requires knowing what species are present in an ecosystem. We assessed fish communities in a stream using two methods, depletion‐based electrofishing and environmental DNA metabarcoding (eDNA) from water samples, to test the hypothesis that eDNA provides an alternative means of determining species richness and species identities for a natural ecosystem. In a northern Indiana stream, electrofishing yielded a direct estimate of 12 species and a mean estimated richness (Chao II estimator) of 16.6 species with a 95% confidence interval from 12.8 to 42.2. eDNA sampling detected an additional four species, congruent with the mean Chao II estimate from electrofishing. This increased detection rate for fish species between methods suggests that eDNA sampling can enhance estimation of fish fauna in flowing waters while having minimal sampling impacts on fish and their habitat. Modern genetic approaches therefore have the potential to transform our ability to build a more complete list of species for ecological investigations and inform management of aquatic ecosystems.     

The relationship between percentage of singletons and sampling effort: A new approach to reduce the bias of richness estimates

Estimate the richness of a community with accuracy despite differences in sampling effort is a key aspect to monitoring high diverse ecosystems. We compiled a worldwide multitaxa database, comprising 185 communities, in order to study the relationship between the percentage of species represented by one individual (singletons) and the intensity of sampling (number of individuals divided by the number of species sampled). The database was used to empirically adjust a correction factor to improve the performance of non-parametrical estimators under conditions of low sampling effort. The correction factor was tested on seven estimators (Chao1, Chao2, Jack1, Jack2, ACE, ICE and Bootstrap). The correction factor was able to reduce the bias of all estimators tested under conditions of undersampling, while converging to the original uncorrected values at higher intensities. Our findings led us to recommend the threshold of 20 individuals/species, or less than 21% of singletons, as a minimum sampling effort to produce reliable richness estimates of high diverse ecosystems using corrected non-parametric estimators. This threshold rise for 50 individuals/species if non-corrected estimators are used which implies in an economy of 60% of sampling effort if the correction factor is used.     

Species richness estimation of bird communities: how to control for sampling effort?

Since estimates of total species richness increase with sampling effort, methods to control for this sampling effect need to be tested and used. We present seven non-parametric and 12 accumulation curve methods that have been used recently in the ecological literature. To test their performance, we used data from bird communities in the Queen Charlotte Islands, Canada. The performance of each method was evaluated by calculating the bias and precision of its estimates against the known total species richness. For our data set, the two Chao estimators were the overall least biased and most precise estimation methods, followed by the two jackknife estimators, thus supporting results of previous studies. Nonparametric estimators tended to perform better than accumulation curve models. Most estimation methods had the problem that they tended to underestimate species richness for early samples, but slightly overestimated it for late samples. We briefly discuss the practical use of these methods which may greatly increase our ability to answer ecological questions and to guide conservation decisions, especially for species-rich tropical bird communities.     

Optimizing performance of nonparametric species richness estimators under constrained sampling

Understanding the functional relationship between the sample size and the performance of species richness estimators is necessary to optimize limited sampling resources against estimation error. Nonparametric estimators such as Chao and Jackknife demonstrate strong performances, but consensus is lacking as to which estimator performs better under constrained sampling. We explore a method to improve the estimators under such scenario. The method we propose involves randomly splitting species‐abundance data from a single sample into two equally sized samples, and using an appropriate incidence‐based estimator to estimate richness. To test this method, we assume a lognormal species‐abundance distribution (SAD) with varying coefficients of variation (CV), generate samples using MCMC simulations, and use the expected mean‐squared error as the performance criterion of the estimators. We test this method for Chao, Jackknife, ICE, and ACE estimators. Between abundance‐based estimators with the single sample, and incidence‐based estimators with the split‐in‐two samples, Chao2 performed the best when CV < 0.65, and incidence‐based Jackknife performed the best when CV > 0.65, given that the ratio of sample size to observed species richness is greater than a critical value given by a power function of CV with respect to abundance of the sampled population. The proposed method increases the performance of the estimators substantially and is more effective when more rare species are in an assemblage. We also show that the splitting method works qualitatively similarly well when the SADs are log series, geometric series, and negative binomial. We demonstrate an application of the proposed method by estimating richness of zooplankton communities in samples of ballast water. The proposed splitting method is an alternative to sampling a large number of individuals to increase the accuracy of richness estimations; therefore, it is appropriate for a wide range of resource‐limited sampling scenarios in ecology.     

Estimating species richness and catch per unit effort from boat electro‐fishing in a lowland river in temperate Australia

Abstract Biodiversity estimates are typically a function of sampling effort and in this regard it is important to develop an understanding of taxon‐specific sampling requirements. Northern hemisphere studies have shown that estimates of riverine fish diversity are related to sampling effort, but such studies are lacking in the southern hemisphere. We used a dataset obtained from boat electro‐fishing the fish community along an essentially continuous 13‐km reach of the Murrumbidgee River, Australia, to investigate sampling effort effects on fish diversity estimates. This represents the first attempt to investigate relationships between sampling effort and the detection of fish species in a large lowland river in Australia. Seven species were recorded. Species‐specific patterns in catch per unit effort were evident and are discussed in terms of solitary and gregarious species, recreational fishing and the monitoring of rare and threatened species. There was a requirement to sample substantial lengths of river to describe total species richness of the fish community in this river reach. To this end, randomly allocated sampling effort and use of species richness estimators produced accurate estimates of species richness without the requirement for excessive levels of effort. Twenty operations were required to estimate species richness at this site, highlighting the need for comparable studies of river fish communities in lowland rivers elsewhere in Australia and the southern hemisphere.     

The net result: evaluating species richness extrapolation techniques for littoral pond invertebrates

1. Total species richness for an assemblage or site is a valuable measure in conservation monitoring and assessment, but protocols for sampling and species richness determination in wetland habitats such as ponds, bogs or mires remain largely unrefined. 2. Techniques for estimation of total richness of an assemblage based upon replicated sampling offer the opportunity to derive useful estimates of total richness based upon small numbers of samples, and limit sampling‐derived disturbance which can be particularly problematic in small aquatic habitats. 3. We quantified the performance of eight of the most commonly encountered estimators of species richness for a variety of littoral zone macrofauna from ponds, comparing estimated richness to maximum richness derived from sampling. 4. Estimates using non‐parametric techniques based on species incidence provided the most accurate and precise estimates. The estimators Chao 2 and incidence‐based coverage estimator (ICE) from this category were reliable and consistent slight over‐estimators; the abundance‐based estimator Chao1 also performed well. 5. Species inventory based on relatively small numbers of samples might be significantly improved by use of non‐parametric estimators for quantification of species richness. 6. Use of non‐parametric estimators of species richness can assist biodiversity inventory by preventing erroneous rankings of habitat richness based upon observed species numbers from limited sampling.     

Fish species richness evaluation in Mexican coastal lagoons: a case study in the Gulf of Mexico

We analyze the origin of knowledge about fish species richness in the Tuxpan-Tampamachoco estuarine system, in Veracuz, México. A complete inventory of the fish species known to date for this system (N = 179) was elaborated from published lists and from sampling seagrass meadows of Tampamachoco Lagoon, which yielded 14 previously unknown species. When compared, the different lists showed a low similarity that may reflect differences in sampling methods and collecting strategies. Current data suggest that fish species richness in Mexican coastal lagoons (Gulf of Mexico) is not related with lagoon surface area, as has been suggested, but with the number of inventories available for each lagoon, being these a reflection of the sampling effort. A sampling design for the assessment of fish species richness in estuarine systems should consider: a) using the highest possible variety of sampling fishing gears, b) collecting in all microhabitat types and c) the preference of bimonthly or quarterly samplings for two or more years over monthly samplings in a single year.     

The influence of sampling intensity on the perception of the spatial distribution of tropical diversity and endemism: a case study of ferns from Bolivia

The distribution of tropical plant and animal diversity is still poorly documented, especially at spatial resolutions of practical use for conservation. In the present study, we evaluated the level to which geographical incomplete data availability of species occurrence affects the perception of biodiversity patterns (species richness and endemism) among pteridophytes in Bolivia. We used a data base of Bolivian pteridophytes (27,501 records), divided it into three time periods (1900–70, up to 1990 and up to 2006), and created grid-files at 15'-resolution for species richness and endemism. For each of these biodiversity properties we estimated the species richness (Chao 2) and the index of sampling completeness (C index) per grid, and then all these variables at both species richness and endemism were correlated. Patterns of richness were fairly consistent along all periods; the richest areas were placed along the humid-montane forest, even though they were strongly influenced by collecting intensity. Endemism had a lower degree of correlation with collecting intensity, but varied much more strongly through time than species richness. According to the C index, which gives the ratio between estimated (by Chao 2) and recorded values of species richness and endemism, both biodiversity properties tended to be undersampled in the richest grid cells. Inter-temporal correlations showed sharper differences of correlations for endemism than species richness. Consequently, already in 1970, botanists had a correct idea of the spatial distribution of pteridophyte richness in Bolivia (even though the magnitude was grossly underestimated). In contrast, patterns of endemism, which are of high conservation importance, may not even today be reliably known.     

The taxonomic distinctness of coastal bottom-dwelling fish communities of the North-east Atlantic

1. New techniques for identifying the average taxonomic range of species assemblages were applied to an extensive dataset of bottom-dwelling fish in the coastal waters of NW Europe. These taxonomic distinctness indices provided much greater resolution than traditional diversity indices as they incorporated information on taxonomic relationships into an index which measures species dominance. Unlike standard measures of species richness and diversity, the mean value of these statistics is independent of sampling effort, and this allows objective comparisons to be made between samples from studies where sampling effort is not standardized.
2. A reduction in the average taxonomic range between the fauna of western waters of the UK and that of the southern North Sea was consistent with the general decline in species richness observed between these regions, and suggests that these two factors may be spatially positively correlated. Indices calculated for individual samples of fish on a local scale, however, did not all fit this trend.
3. Much of the variability in taxonomic diversity within the coastal waters of NW Europe was caused by the variable geographical distribution of the elasmobranchs. Of all the families which comprise the fish communities, this group has life-history characteristics which make it most susceptible to impact by commercial trawl fisheries.
4. The use of taxonomic distinctness measures provided additional insights, of relevance to biodiversity assessment, suggesting that they might usefully be applied to other aquatic and terrestrial fauna.     

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.     

Limited sampling hampers “big data” estimation of species richness in a tropical biodiversity hotspot

Macro‐scale species richness studies often use museum specimens as their main source of information. However, such datasets are often strongly biased due to variation in sampling effort in space and time. These biases may strongly affect diversity estimates and may, thereby, obstruct solid inference on the underlying diversity drivers, as well as mislead conservation prioritization. In recent years, this has resulted in an increased focus on developing methods to correct for sampling bias. In this study, we use sample‐size‐correcting methods to examine patterns of tropical plant diversity in Ecuador, one of the most species‐rich and climatically heterogeneous biodiversity hotspots. Species richness estimates were calculated based on 205,735 georeferenced specimens of 15,788 species using the Margalef diversity index, the Chao estimator, the second‐order Jackknife and Bootstrapping resampling methods, and Hill numbers and rarefaction. Species richness was heavily correlated with sampling effort, and only rarefaction was able to remove this effect, and we recommend this method for estimation of species richness with “big data” collections.     

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.     

Evaluating the sampling bias in pattern of subterranean species richness: combining approaches

We investigated the pattern of species richness of obligate subterranean (troglobiotic) beetles in caves in the northwestern Balkans, given unequal and biased sampling. On the regional scale, we modeled the relationship between species numbers and sampling intensity using an asymptotic Clench (Michaelis–Menten) function. On the local scale, we calculated Chao 2 species richness estimates for 20 × 20 km grid cells, and investigated the distribution of uniques, species found in only one cave within the grid cell. Cells having high positive residuals, those with above average species richness than expected according to the Clench function, can be considered true hotspots. They were nearly identical to the observed areas of highest species richness. As sampling intensity in a grid cell increases the expected number of uniques decreases for any fixed number of species in the grid cell. High positive residuals show above average species richness for a certain level of sampling intensity within a cell, so further sampling has the most potential for additional species. In some cells this was supported by high numbers of uniques, also indicating insufficient sampling. Cells with low negative residuals have fewer species than would be expected, and some of them also had a low number of uniques, both indicating sufficient sampling. By combining different analyses in a novel way we were able to evaluate observed species richness pattern as well as identify, where further sampling would be most beneficial. Approach we demonstrate is of broad interest to study of biota with high levels of endemism, small distribution ranges and low catchability.     

Efficient sampling of plant diversity in arid deserts using non-parametric estimators

Surveying plant diversity in arid desert areas is extremely difficult because of the harsh climate, hostile terrain, lack of roads, and insecurity, which is why it is particularly important to improve the sampling efficiency, but few relevant studies have been done. The performance of non-parametric estimators was assessed with first-hand field data to determine (a) the threshold of the proportion of uniques (number of species that occur in exactly one plot divided by the number of species sampled) that involves the least sampling effort and (b) the method of locating plots to obtain a more reliable estimate of species richness. The study area (Gurbantunggut desert, China) was divided into five sub-regions based on variation in physical environment and vegetation. The following common correction factors were selected: ACE, Chao1, Bootstrap, Chao2, ICE, Jack1, and Jack2. The estimates for each sub-region (partition) and for the entire region (without partition), the threshold of proportion of uniques, and the method of determining sampling locations (including prior sampling of plots that show large differences in habitats) were compared in terms of their ability to predict the number of species more accurately. We found that ACE and Chao1 (which use abundance data) showed more biased estimates than the other factors (incidence data), and best estimator is Jack1. Species richness was significantly underestimated for the region, but the non-parametric estimators could estimate the species richness for each sub-region reliably. Sampling locations affected the performance of non-parametric estimators significantly. The threshold of minimum sampling was 15% and that of uniques was 30%; the two were able to limit the bias within 5 and 10%, respectively. It is concluded that the non-parametric estimators can estimate the plant diversity of arid deserts reliably from the data on incidence. The study area (on the scale of a region) should be partitioned to improve the performance of the non-parametric estimators. The plots with larger differences in habitats should be sampled more extensively based on the threshold of the proportion of uniques.     

Constant tree species richness along an elevational gradient of Mt. Bokor,a table-shaped mountain in southwestern Cambodia

Some previous studies along an elevational gradient on a tropical mountain documented that plant species richness decreases with increasing elevation. However, most of studies did not attempt to standardize the amount of sampling effort. In this paper, we employed a standardized sampling effort to study tree species richness along an elevational gradient on Mt. Bokor, a table-shaped mountain in southwestern Cambodia, and examined relationships between tree species richness and environmental factors. We used two methods to record tree species richness: first, we recorded trees taller than 4 m in 20 uniform plots (5 × 100 m) placed at 266–1048-m elevation; and second, we collected specimens along an elevational gradient from 200 to 1048 m. For both datasets, we applied rarefaction and a Chao1 estimator to standardize the sampling efforts. A generalized linear model (GLM) was used to test the relationship of species richness with elevation. We recorded 308 tree species from 20 plots and 389 tree species from the general collections. Species richness observed in 20 plots had a weak but non-significant correlation with elevation. Species richness estimated by rarefaction or Chao1 from both data sets also showed no significant correlations with elevation. Unlike many previous studies, tree species richness was nearly constant along the elevational gradient of Mt. Bokor where temperature and precipitation are expected to vary. We suggest that the table-shaped landscape of Mt. Bokor, where elevational interval areas do not significantly change between 200 and 900 m, may be a determinant of this constant species richness.     

Biogeographical patterns of marine larval trematode parasites in two intermediate snail hosts in Europe

Aim We used published inventories of trematodes in Littorina littorea (L.) and Hydrobia ulvae (Pennant) in European seas to search for two basic biogeographical patterns in the spatial occurrence of various trematode species: (1) do parasite distribution and richness patterns in the two host snails overlap with known ecoregions of free‐living organisms; and (2) does trematode species richness in the snails follow latitudinal or longitudinal gradients? Location North East Atlantic. Methods We used multidimensional scaling (MDS), analysis of similarity (ANOSIM) and analysis of variance (ANOVA) to test whether there were overlaps of parasite distribution and richness with known ecoregions of free‐living organisms. In addition, we used linear regression analyses to test whether trematode richness in snails (corrected for sampling effort) was correlated with the latitude or longitude of the sampling sites. Results When corrected for sampling effort, mean trematode species richness per site did not differ among the different ecoregions in L. littorea. In contrast, in H. ulvae, mean species richness was much lower for sites from the Celtic Sea compared with sites from the Baltic Sea and the North Sea. Based on the results of MDS analyses, trematode species composition was distinct among ecoregions; in particular, communities from the Baltic Sea differed markedly from communities in the Celtic Sea, for both snail species. Latitude and longitude were not significantly correlated with parasite species richness in either snail species. Most trematode species had restricted distributions, and only three species in L. littorea and five species in H. ulvae occurred at more than 50% of the sites. Main conclusions There is more structure in the large‐scale distribution of trematodes in gastropods than one would expect from the large‐scale dispersal capabilities of their bird and fish final hosts. We propose mechanisms based both on limited dispersal via fish and bird final hosts and on gradients in environmental factors to explain the observed patterns.     

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.     

Abundance and species richness as a function of food resources and vegetation structure: juvenile fish assemblages in rivers

Availability of food and habitat complexity are two factors generally invoked to explain the high density of fish in vegetated habitats. The role of food resources (zooplankton) and habitat complexity (expressed by a vegetation structural index) in determining juvenile fish abundance and fish species richness in three morphologically contrasted macrophyte types (Sagittaria, Ceratophyllum and Nuphar) was studied for a large, lowland river.
Our results showed that fish abundance increased with food availability, and was maximal for intermediate values of vegetation complexity. Food resources and vegetation complexity did not, however, explain the higher juvenile fish abundance observed in Sagittaria beds. We suggested that plant growth form, acting on fish foraging success and risk of predation, might influence patterns of juvenile fish distribution.
Species‐abundance relationships were similar among the three macrophyte types, but relationships between number of fish species (fish richness) and number of samples differed. Fish richness in terms of total number of fish species found at each sampling point showed the same pattern as for fish abundance: it increased with food availability and was highest at intermediate vegetation complexities. However, since both fish abundance and fish richness responded in the same manner to food availability and vegetation complexity, we were not able to distinguish statistically any effect for the specific fish richness formulated by the number of fish species per unit fish abundance. The current paradigm that structural complexity of vegetation provides a wider range of niches, increasing species diversity, was thus not verified. This finding indicates a simple species‐abundance relationship (the passive sampling hypothesis), and suggests that no special mechanism acts directly on fish species richness.     

Influences of interpolation of species ranges on elevational species richness gradients

Interpolation of species ranges has been a common approach to compensate for the unevenness or incompleteness in sampling effort in studies of geographic species richness gradients. However, potential biases introduced by this estimation method remain unclear. Here, we presented an explicit examination of the influences of one‐dimensional interpolation on elevational species richness gradients, and discussed potential causes and processes of these influences. We conducted intensive surveys of birds along the elevational gradients of the Ailao Mountains, southwestern China, and compared richness patterns based on interpolation with raw data as well as estimated data from rarefaction and Chao1 non‐parametric estimator; we also compared results of multiple linear regressions and hierarchical partitioning analyses explaining these four measures of richness. Actual evapotranspiration (AET) and the mid‐domain effect (MDE) were highly correlated and separately provided a good potential explanation for the unimodal richness pattern in the Ailao Mountains, with modifying and suppressive effects of other variables such as area. Interpolation consistently and significantly increased the effects of AET/MDE, while it reduced contributions of area and human disturbance. Our results demonstrated that while compensating for biases in sampling effort, interpolation may also spuriously fill genuine distribution gaps, and tend to underestimate the effects of the non‐monotonic or discontinuous influencing factors that are responsible for these gaps, and overestimate the effects of other factors actually suppressed by these factors. These influences were most strong for species with relatively medium elevational ranges. We conclude that at the regional scale, interpolation method is a potential source of bias in identifying and explaining species richness gradients and should be used with careful consideration. It may be advantageous to adopt other robust estimation methods besides interpolation to gain a more accurate assessment of species richness and a more objective understanding of their underlying mechanisms.     

Quantifying rotifer species richness in temperate lakes

1. Biodiversity assessments of lakes depend on the ability to identify the complement of species present, although the degree of sampling required is often uncertain. We utilise long‐term data to predict rotifer species richness in three habitats in three Polish lakes using rarefaction sampling methods. 2. Richness in littoral and psammon habitats did not saturate, even with up to 130 samples. Highest richness was observed in psammon habitat (119 species) in Lake Mikolajskie, followed by littoral habitat in Lakes ?uknajno (114 species) and Kuc (110 species). Littoral habitats in Lakes ?uknajno (56%) and Kuc (51%) had the most species not shared with other habitats in the same lake. 3. Species richness (Chao2) estimates ranged between 44 for pelagic and 135 for psammon habitat in Lake Mikolajskie, to 100 for psammon and 137 for littoral habitat in Lake Kuc, and 65 for pelagic and 162 for littoral habitat in Lake ?uknajno. Whole lake estimates were 167, 205 and 171 species, respectively, for these lakes, higher than the 150 to 160 species predicted by Dumont and Segers (Hydrobiologia, 1996, 341 , 125). 4. Using standardised sampling, richness was significantly higher in littoral than either pelagic or psammon habitats. Contrasts of standardised rarefaction curves revealed that richness in Lakes Kuc and Mikolajskie was described as well by littoral‐only or psammon‐only samples, respectively, as by those randomly drawn from across all habitats in the lake. 5. Species richness estimates for Lake Mikolajskie were highest in summer, followed by autumn and spring. Interannual estimates differed by up to 427%, nearly an order of magnitude greater than maximal seasonal variation of 70%. 6. Results indicate that much higher sampling intensity is required to establish species richness than is presently carried out in most lakes. Because many species can be detected only with very intensive sampling, conservation programmes must consider sampling intensity when designing studies.