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.     

Quantification of mesocosm fish and amphibian species diversity via environmental DNA metabarcoding

Freshwater fauna are particularly sensitive to environmental change and disturbance. Management agencies frequently use fish and amphibian biodiversity as indicators of ecosystem health and a way to prioritize and assess management strategies. Traditional aquatic bioassessment that relies on capture of organisms via nets, traps and electrofishing gear typically has low detection probabilities for rare species and can injure individuals of protected species. Our objective was to determine whether environmental DNA (eDNA) sampling and metabarcoding analysis can be used to accurately measure species diversity in aquatic assemblages with differing structures. We manipulated the density and relative abundance of eight fish and one amphibian species in replicated 206‐L mesocosms. Environmental DNA was filtered from water samples, and six mitochondrial gene fragments were Illumina‐sequenced to measure species diversity in each mesocosm. Metabarcoding detected all nine species in all treatment replicates. Additionally, we found a modest, but positive relationship between species abundance and sequencing read abundance. Our results illustrate the potential for eDNA sampling and metabarcoding approaches to improve quantification of aquatic species diversity in natural environments and point the way towards using eDNA metabarcoding as an index of macrofaunal species abundance.     

Estimating the spawning activity of fish species using nuclear and mitochondrial environmental DNA concentrations and their ratios

1. During spawning activity, fish release large amounts of sperm and eggs into the water, which has been assumed to cause an increase in environmental DNA (eDNA) levels and nuclear DNA/mitochondrial DNA ratios. To test whether these assumptions are valid and whether nuclear and mitochondrial eDNA analysis can be used to monitor the spawning activity of freshwater fish, we conducted field eDNA surveys and traditional surveys using common carp (Cyprinus carpio), largemouth bass (Micropterus salmoides) and bluegill sunfish (Lepomis macrochirus) as model species.
2. Fish spawning periods were estimated based on age, as estimated using the body lengths of juveniles collected in the Miharu reservoir in Fukushima, Japan. The results showed that the main spawning periods of largemouth bass and bluegill sunfish were from April to July and from July to August, respectively.
3. Field eDNA surveys were conducted in the Hebisawagawa front reservoir, which is connected to the Miharu reservoir. From March to August 2019 and 2020, weekly eDNA sampling was conducted at three sites, and daily sampling was conducted at six sites from 23 June to 3 July 2020. The eDNA concentrations of the nuclear internal transcribed spacer 1 (ITS1) and mitochondrial cytochrome B (CytB), as well as the ITS1/CytB ratio, were measured for each of the three fish in each water sample. Water temperature had a statistically significant effect on eDNA concentration, probably reflecting the relationship between water temperature and spawning.
4. We created generalised additive mixed models to estimate spawning activity periods based on weekly eDNA data. The estimated periods of spawning activity for common carp, largemouth bass and bluegill sunfish were March to May, May to July, and May to August, respectively. The estimated spawning periods coincided with known fish ecology or the results of traditional methods. This method also has been applied to daily eDNA samples, showing the feasibility of high-resolution estimation of spawning activity.
5. For common carp and bluegill sunfish, we were able to estimate the spawning period using this method. Although the method is affected by biomass and the diffusion and degradation of eDNA, it has the potential to accurately estimating spawning activities. These then can be estimated without conducting laborious traditional surveys, facilitating the monitoring of reproduction by rare, invasive or important fishery species. Further research on the diffusion distance and degradation time of the eDNA concentration peak caused by fish spawning activity may improve the accuracy of monitoring.

     

环境DNA技术在淡水底栖大型无脊椎动物多样性监测中的应用

环境DNA (eDNA)是指生物有机体在环境中(例如土壤、沉积物或水体)遗留下的DNA片段。eDNA技术是指从环境中提取DNA片段进行测序以及数据分析来反映环境中的物种或群落信息。与传统方法相比, eDNA技术具有高灵敏度、省时省力、无损伤等优点。目前, eDNA技术已成为一种新的水生生物监测方法, 主要应用于水生生物的多样性研究、濒危和稀有动物的物种状态及外来入侵动物扩散动态的监测等。本文从eDNA技术在水生生物多样性监测应用领域的发展历程、eDNA技术的操作流程以及其在监测淡水底栖大型无脊椎动物方面的应用进展、技术优势和局限性五个方面进行了综述。最后, 本文对eDNA技术在淡水底栖大型无脊椎动物多样性监测应用的发展趋势和前景作出展望。     

Making environmental DNA count

The arc of reception for a new technology or method – like the reception of new information itself – can pass through predictable stages, with audiences’ responses evolving from ‘I don't believe it’, through ‘well, maybe’ to ‘yes, everyone knows that’ to, finally, ‘old news’. The idea that one can sample a volume of water, sequence DNA out of it, and report what species are living nearby has experienced roughly this series of responses among biologists, beginning with the microbial biologists who developed genetic techniques to reveal the unseen microbiome. ‘Macrobial’ biologists and ecologists – those accustomed to dealing with species they can see and count – have been slower to adopt such molecular survey techniques, in part because of the uncertain relationship between the number of recovered DNA sequences and the abundance of whole organisms in the sampled environment. In this issue of Molecular Ecology Resources, Evans et al. ( 2015 ) quantify this relationship for a suite of nine vertebrate species consisting of eight fish and one amphibian. Having detected all of the species present with a molecular toolbox of six primer sets, they consistently find DNA abundances are associated with species’ biomasses. The strength and slope of this association vary for each species and each primer set – further evidence that there is no universal parameter linking recovered DNA to species abundance – but Evans and colleagues take a significant step towards being able to answer the next question audiences tend to ask: ‘Yes, but how many are there?’     

Application of species richness estimators for the assessment of fungal diversity

Species richness and distribution patterns of wood-inhabiting fungi and mycetozoans (slime moulds) were investigated in the canopy of a Central European temperate mixed deciduous forest. Species richness was described with diversity indices and species-accumulation curves. Nonmetrical multidimensional scaling was used to assess fungal species composition on different tree species. Different species richness estimators were used to extrapolate species richness beyond our own data. The reliability of the abundance-based coverage estimator, Chao, Jackknife and other estimators of species richness was evaluated for mycological surveys. While the species-accumulation curve of mycetozoans came close to saturation, that of wood-inhabiting fungi was continuously rising. The Chao 2 richness estimator was considered most appropriate to predict the number of species at the investigation site if sampling were continued. Gray's predictor of species richness should be used if statements of the number of species in larger areas are required. Multivariate analysis revealed the importance of different tree species for the conservation and maintenance of fungal diversity within forests, because each tree species possessed a characteristic fungal community. The described mathematical approaches of estimating species richness possess great potential to address fungal diversity on a regional, national, and global scale.     

基于环境DNA-宏条形码技术的底栖动物监测及水质评价研究进展

底栖动物是淡水生态系统中物种多样性最高的类群,也是应用最广泛的水质监测指示生物之一。传统的底栖动物监测以形态学为基础,耗时费力,无法满足流域尺度大规模监测的需求。环境DNA-宏条形码技术是一种新兴的生物监测方法,其与传统方法相比优势在于采样方法简单、低成本、高灵敏度,不受生物样本和环境状况的影响,不依赖分类专家和鉴定资料,能够快速准确地对多个类群进行大规模、高通量的物种鉴定。然而,在实际应用中该方法的效果受诸多因素的影响,不同的方法、流程往往会产生差异较大的结果。鉴于此,着重分析总结了应用环境DNA-宏条形码技术监测底栖动物的关键影响因素,包括样品采集与处理流程、分子标记选择、引物设计、PCR偏好性、参考数据库的完整性及相应的优化。并基于此探讨了提高环境DNA-宏条形码技术在底栖动物监测效率和准确率的途径,以期为底栖动物环境DNA-宏条形码监测方案的制定提供可靠的参考。最后对该技术在底栖动物监测和水质评价中的最新发展方向进行了展望。     

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.     

Estimating species richness using the jackknife procedure

An exact expression is given for the jackknife estimate of the number of species in a community and for the variance of this number when quadrat sampling procedures are used. The jackknife estimate is a function of the number of species that occur in one and only one quadrat. The variance of the number of species can be constructed, as can approximate two-sided confidence intervals. The behavior of the jackknife estimate, as affected by quadrat size, sample size and sampling area, is investigated by simulation.     

环境DNA metabarcoding及其在生态学研究中的应用

环境DNA metabarcoding(eDNA metabarcoding)是指利用环境样本(如土壤、水、粪便等)中分离的DNA进行高通量的多个物种(或高级分类单元)鉴定的方法。近年来,该方法引起了学者的广泛关注,逐渐应用于生物多样性研究、水生生物监测、珍稀濒危物种和外来入侵物种检测等生态学领域。介绍环境DNA metabarcoding的含义和研究方法;重点介绍环境DNA metabarcoding在物种监测、生物多样性研究和食性分析等生态学领域中的应用;总结环境DNA metabarcoding应用于生态学研究领域面临的挑战并对该方法的发展进行展望。     

Estimating species trees using multiple-allele DNA sequence data

Several techniques, such as concatenation and consensus methods, are available for combining data from multiple loci to produce a single statement of phylogenetic relationships. However, when multiple alleles are sampled from individual species, it becomes more challenging to estimate relationships at the level of species, either because concatenation becomes inappropriate due to conflicts among individual gene trees, or because the species from which multiple alleles have been sampled may not form monophyletic groups in the estimated tree. We propose a Bayesian hierarchical model to reconstruct species trees from multiple-allele, multilocus sequence data, building on a recently proposed method for estimating species trees from single allele multilocus data. A two-step Markov Chain Monte Carlo (MCMC) algorithm is adopted to estimate the posterior distribution of the species tree. The model is applied to estimate the posterior distribution of species trees for two multiple-allele datasets--yeast (Saccharomyces) and birds (Manacus-manakins). The estimates of the species trees using our method are consistent with those inferred from other methods and genetic markers, but in contrast to other species tree methods, it provides credible regions for the species tree. The Bayesian approach described here provides a powerful framework for statistical testing and integration of population genetics and phylogenetics.     

Abundance and dominance become less predictable as species richness decreases

Aim To test the hypothesis that communities with higher diversity have more predictable properties by examining patterns of community structure along a species richness gradient. Location Trinidad and Tobago (11°00 N, 61°00 W), on the South American continental shelf, opposite the Orinoco River delta, north‐east Venezuela. Methods We used quantile regressions to investigate how three total abundance, absolute and relative dominance measures – numerical abundance, biomass and energy use, respectively – change across a species richness gradient. We investigated which allocation rule best mimics community assembly in this species richness gradient by examining the abundance of the dominant species and comparing it with predictions of niche apportionment models. Results All measures of total abundance increase on average across the gradient, but the upper limit remains constant. On average, absolute dominance is constant, but the distance between the upper and lower limits decreases along the gradient. Relative dominance decreases with species richness. Observed dominance patterns are best described by Tokeshi's random fraction model. Main conclusions Our results show that both total abundance and absolute dominance become increasingly variable as biodiversity decreases. Consequently, our study suggests that ecosystem properties are less predictable when biodiversity is lower.     

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.     

Functional diversity (FD), species richness and community composition

Functional diversity is an important component of biodiversity, yet in comparison to taxonomic diversity, methods of quantifying functional diversity are less well developed. Here, we propose a means for quantifying functional diversity that may be particularly useful for determining how functional diversity is related to ecosystem functioning. This measure of functional diversity “FD” is defined as the total branch length of a functional dendrogram. Various characteristics of FD make it preferable to other measures of functional diversity, such as the number of functional groups in a community. Simulating species' trait values illustrates how the relative importance of richness and composition for FD depends on the effective dimensionality of the trait space in which species separate. Fewer dimensions increase the importance of community composition and functional redundancy. More dimensions increase the importance of species richness and decreases functional redundancy. Clumping of species in trait space increases the relative importance of community composition. Five natural communities show remarkably similar relationships between FD and species richness.     

Detection of invasive freshwater fish species using environmental DNA survey

Invasive species are one of the most significant problem in freshwater ecosystems. Most common non-native freshwater species in Turkish freshwater fish fauna are Prussian Carp (Carassius gibelio), North African Catfish (Clarias gariepinus), Nile Tilapia (Oreochromis niloticus) and Topmouth Gudgeon (Pseudorasbora parva).Recent studies showed that environmental DNA could be used to detect target species inhabiting the ecosystem with higher precision and less effort compared to traditional field surveys. In this study, eDNA approach was used to investigate non-native freshwater fish species from fifteen different locations of Upper Sakarya Basin. eDNA was successfully extracted from the water samples of locations where the species were visually observed. Mean amplification rate of eDNA was calculated as 77.03%.This study is the first environmental DNA study used in detection of four of the most common invasive freshwater fish species. Results clearly indicating that eDNA surveys could be used as an important molecular tool to monitor invasive fish species in freshwater ecosystems.     

Performance of nonparametric species richness estimators in a high diversity plant community

Abstract. The efficiency of four nonparametric species richness estimators — first‐order Jackknife, second‐order Jackknife, Chao2 and Bootstrap — was tested using simulated quadrat sampling of two field data sets (a sandy ‘Dune’ and adjacent ‘Swale’) in high diversity shrublands (kwongan) in south‐western Australia. The data sets each comprised > 100 perennial plant species and > 10 000 individuals, and the explicit (x‐y co‐ordinate) location of every individual. We applied two simulated sampling strategies to these data sets based on sampling quadrats of unit sizes 1/400th and 1/100th of total plot area. For each site and sampling strategy we obtained 250 independent sample curves, of 250 quadrats each, and compared the estimators’ performances by using three indices of bias and precision: MRE (mean relative error), MSRE (mean squared relative error) and OVER (percentage overestimation). The analysis presented here is unique in providing sample estimates derived from a complete, field‐based population census for a high diversity plant community. In general the true reference value was approached faster for a comparable area sampled for the smaller quadrat size and for the swale field data set, which was characterized by smaller plant size and higher plant density. Nevertheless, at least 15–30% of the total area needed to be sampled before reasonable estimates of S_t (total species richness) were obtained. In most field surveys, typically less than 1% of the total study domain is likely to be sampled, and at this sampling intensity underestimation is a problem. Results showed that the second‐order Jackknife approached the actual value of S_t more quickly than the other estimators. All four estimators were better than S_obs (observed number of species). However, the behaviour of the tested estimators was not as good as expected, and even with large sample size (number of quadrats sampled) all of them failed to provide reliable estimates. First‐ and second‐order Jackknives were positively biased whereas Chao2 and Bootstrap were negatively biased. The observed limitations in the estimators’ performance suggests that there is still scope for new tools to be developed by statisticians to assist in the estimation of species richness from sample data, especially in communities with high species richness.     

Assessment of fish communities using environmental DNA: Effect of spatial sampling design in lentic systems of different sizes

Freshwater fish biodiversity is quickly decreasing and requires effective monitoring and conservation. Environmental DNA (eDNA)‐based methods have been shown to be highly sensitive and cost‐efficient for aquatic biodiversity surveys, but few studies have systematically investigated how spatial sampling design affects eDNA‐detected fish communities across lentic systems of different sizes. We compared the spatial patterns of fish diversity determined using eDNA in three lakes of small (SL; 3 ha), medium (ML; 122 ha) and large (LL; 4,343 ha) size using a spatially explicit grid sampling method. A total of 100 water samples (including nine, 17 and 18 shoreline samples and six, 14 and 36 interior samples from SL, ML and LL, respectively) were collected, and fish communities were analysed using eDNA metabarcoding of the mitochondrial 12S region. Together, 30, 35 and 41 fish taxa were detected in samples from SL, ML, and LL, respectively. We observed that eDNA from shoreline samples effectively captured the majority of the fish diversity of entire waterbodies, and pooled samples recovered fewer species than individually processed samples. Significant spatial autocorrelations between fish communities within 250 m and 2 km of each other were detected in ML and LL, respectively. Additionally, the relative sequence abundances of many fish species exhibited spatial distribution patterns that correlated with their typical habitat occupation. Overall, our results support the validity of a shoreline sampling strategy for eDNA‐based fish community surveys in lentic systems but also suggest that a spatially comprehensive sampling design can reveal finer distribution patterns of individual species.     

Assessment of littoral algal diversity from the northern Gulf of Mexico using environmental DNA metabarcoding

Traditional methods for algal biodiversity monitoring are costly and time inefficient because they rely on high‐level taxonomic expertise to address species identity problems involving phenotypic plasticity and morphological convergence. These problems are exacerbated in regions such as the Gulf of Mexico, that has a limited history of phycological exploration, but that are economically important or threatened by numerous anthropogenic stressors. Given the high pace of disturbance to natural systems, there is a critical need for expedient and cost‐effective tools for the study of benthic algal communities. Here we document the use of environmental DNA metabarcoding, using the partial LSU rDNA and 23S rDNA plastid molecular markers, to elucidate littoral algal diversity in the Northern Gulf of Mexico. We assigned 73.7% of algal OTUs to genus and 59.6% to species ranks. Our current study detected molecular signals for 35 algal/protist species with no previous reports in the Gulf of Mexico, thus providing an important, molecular‐validated, baseline of species richness for this region. We also make several bioinformatic recommendations for the efficient use of high‐throughput sequence data to assess biological communities.