Estimation of fish biomass using environmental DNA

Environmental DNA (eDNA) from aquatic vertebrates has recently been used to estimate the presence of a species. We hypothesized that fish release DNA into the water at a rate commensurate with their biomass. Thus, the concentration of eDNA of a target species may be used to estimate the species biomass. We developed an eDNA method to estimate the biomass of common carp (Cyprinus carpio L.) using laboratory and field experiments. In the aquarium, the concentration of eDNA changed initially, but reached an equilibrium after 6 days. Temperature had no effect on eDNA concentrations in aquaria. The concentration of eDNA was positively correlated with carp biomass in both aquaria and experimental ponds. We used this method to estimate the biomass and distribution of carp in a natural freshwater lagoon. We demonstrated that the distribution of carp eDNA concentration was explained by water temperature. Our results suggest that biomass data estimated from eDNA concentration reflects the potential distribution of common carp in the natural environment. Measuring eDNA concentration offers a non-invasive, simple, and rapid method for estimating biomass. This method could inform management plans for the conservation of ecosystems.     

Development and application of environmental DNA surveillance for the threatened crucian carp (Carassius carassius)

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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.     

Occupancy in dynamic systems: accounting for multiple scales and false positives using environmental DNA to inform monitoring

Occupancy is an important metric to understand current and future trends in populations that have declined globally. In addition, occupancy can be an efficient tool for conducting landscape-scale and long-term monitoring. A challenge for occupancy monitoring programs is to determine the appropriate spatial scale of analysis and to obtain precise occupancy estimates for elusive species. We used a multi-scale occupancy model to assess occupancy of Columbia spotted frogs in the Great Basin, USA, based on environmental DNA (eDNA) detections. We collected three replicate eDNA samples at 220 sites across the Great Basin. We estimated and modeled ecological factors that described watershed and site occupancy at multiple spatial scales simultaneously while accounting for imperfect detection. Additionally, we conducted visual and dipnet surveys at all sites and used our paired detections to estimate the probability of a false positive detection for our eDNA sampling. We applied the estimated false positive rate to our multi-scale occupancy dataset and assessed changes in model selection. We had higher naïve occupancy estimates for eDNA (0.37) than for traditional survey methods (0.20). We estimated our false positive detection rate per qPCR replicate at 0.023 (95% CI: 0.016–0.033). When the false positive rate was applied to the multi-scale dataset, we did not observe substantial changes in model selection or parameter estimates. Conservation and resource managers have an increasing need to understand species occupancy in highly variable landscapes where the spatial distribution of habitat changes significantly over time due to climate change and human impact. A multi-scale occupancy approach can be used to obtain regional occupancy estimates that can account for spatially dynamic differences in availability over time, especially when assessing potential declines. Additionally, this study demonstrates how eDNA can be used as an effective tool for improved occupancy estimates across broad geographic scales for long-term monitoring.     

Modeling the Sensitivity of Field Surveys for Detection of Environmental DNA (eDNA)

The environmental DNA (eDNA) method is the practice of collecting environmental samples and analyzing them for the presence of a genetic marker specific to a target species. Little is known about the sensitivity of the eDNA method. Sensitivity is the probability that the target marker will be detected if it is present in the water body. Methods and tools are needed to assess the sensitivity of sampling protocols, design eDNA surveys, and interpret survey results. In this study, the sensitivity of the eDNA method is modeled as a function of ambient target marker concentration. The model accounts for five steps of sample collection and analysis, including: 1) collection of a filtered water sample from the source; 2) extraction of DNA from the filter and isolation in a purified elution; 3) removal of aliquots from the elution for use in the polymerase chain reaction (PCR) assay; 4) PCR; and 5) genetic sequencing. The model is applicable to any target species. For demonstration purposes, the model is parameterized for bighead carp (Hypophthalmichthys nobilis) and silver carp (H. molitrix) assuming sampling protocols used in the Chicago Area Waterway System (CAWS). Simulation results show that eDNA surveys have a high false negative rate at low concentrations of the genetic marker. This is attributed to processing of water samples and division of the extraction elution in preparation for the PCR assay. Increases in field survey sensitivity can be achieved by increasing sample volume, sample number, and PCR replicates. Increasing sample volume yields the greatest increase in sensitivity. It is recommended that investigators estimate and communicate the sensitivity of eDNA surveys to help facilitate interpretation of eDNA survey results. In the absence of such information, it is difficult to evaluate the results of surveys in which no water samples test positive for the target marker. It is also recommended that invasive species managers articulate concentration-based sensitivity objectives for eDNA surveys. In the absence of such information, it is difficult to design appropriate sampling protocols. The model provides insights into how sampling protocols can be designed or modified to achieve these sensitivity objectives.     

Performance of eDNA assays to detect and quantify an elusive benthic fish in upland streams

The sensitivity and specificity of eDNA-based monitoring, coupled with its potential utility to estimate population density or biomass, makes it a useful tool in invasive species management. In this study, we investigated the potential of the eDNA method to improve the detection of the elusive invasive fish, oriental weatherloach (Misgurnus anguillicaudatus), in a river system where a density gradient of the species occurs. We compared detection rates between eDNA and conventional monitoring methods and examined the relationship between eDNA and abundance in a flowing environment. The eDNA method had a higher site detection rate than conventional methods (63 vs. 38%). Weatherloach eDNA was detected at all sites where the fish has been previously caught and none of the sites where the species has not been caught for the past 7 years. There was an increasing density trend going downstream based on long-term conventional monitoring, but the eDNA concentration in water samples reflected this trend only in a continuous section of the river where impoundments were absent. We did not find a positive relationship between eDNA concentration and contemporary abundance estimates in our study area. A high eDNA concentration was recorded at a site (DVC) which was designated a low density site based on long-term catch data. This discrepancy was a likely result of physical habitat characteristics which influenced the efficiency of the conventional methods used. This study highlighted the challenges of inferring density from eDNA data in flowing water because habitat features may confound results, necessitating careful consideration for results to be useful to management.     

The Relationship between the Distribution of Common Carp and Their Environmental DNA in a Small Lake

Although environmental DNA (eDNA) has been used to infer the presence of rare aquatic species, many facets of this technique remain unresolved. In particular, the relationship between eDNA and fish distribution is not known. We examined the relationship between the distribution of fish and their eDNA (detection rate and concentration) in a lake. A quantitative PCR (qPCR) assay for a region within the cytochrome b gene of the common carp (Cyprinus carpio or ‘carp’), an ubiquitous invasive fish, was developed and used to measure eDNA in Lake Staring (MN, USA), in which both the density of carp and their distribution have been closely monitored for several years. Surface water, sub-surface water, and sediment were sampled from 22 locations in the lake, including areas frequently used by carp. In water, areas of high carp use had a higher rate of detection and concentration of eDNA, but there was no effect of fish use on sediment eDNA. The detection rate and concentration of eDNA in surface and sub-surface water were not significantly different (p≥0.5), indicating that eDNA did not accumulate in surface water. The detection rate followed the trend: high-use water > low-use water > sediment. The concentration of eDNA in sediment samples that were above the limit of detection were several orders of magnitude greater than water on a per mass basis, but a poor limit of detection led to low detection rates. The patchy distribution of eDNA in the water of our study lake suggests that the mechanisms that remove eDNA from the water column, such as decay and sedimentation, are rapid. Taken together, these results indicate that effective eDNA sampling methods should be informed by fish distribution, as eDNA concentration was shown to vary dramatically between samples taken less than 100 m apart.     

Assessing vertebrate biodiversity in a kelp forest ecosystem using environmental DNA

Preserving biodiversity is a global challenge requiring data on species’ distribution and abundance over large geographic and temporal scales. However, traditional methods to survey mobile species’ distribution and abundance in marine environments are often inefficient, environmentally destructive, or resource‐intensive. Metabarcoding of environmental DNA (eDNA) offers a new means to assess biodiversity and on much larger scales, but adoption of this approach for surveying whole animal communities in large, dynamic aquatic systems has been slowed by significant unknowns surrounding error rates of detection and relevant spatial resolution of eDNA surveys. Here, we report the results of a 2.5 km eDNA transect surveying the vertebrate fauna present along a gradation of diverse marine habitats associated with a kelp forest ecosystem. Using PCR primers that target the mitochondrial 12S rRNA gene of marine fishes and mammals, we generated eDNA sequence data and compared it to simultaneous visual dive surveys. We find spatial concordance between individual species’ eDNA and visual survey trends, and that eDNA is able to distinguish vertebrate community assemblages from habitats separated by as little as ~60 m. eDNA reliably detected vertebrates with low false‐negative error rates (1/12 taxa) when compared to the surveys, and revealed cryptic species known to occupy the habitats but overlooked by visual methods. This study also presents an explicit accounting of false negatives and positives in metabarcoding data, which illustrate the influence of gene marker selection, replication, contamination, biases impacting eDNA count data and ecology of target species on eDNA detection rates in an open ecosystem.     

Improved Methods for Capture,Extraction, and Quantitative Assay of Environmental DNA from Asian Bigheaded Carp (Hypophthalmichthys spp.)

Indirect, non-invasive detection of rare aquatic macrofauna using aqueous environmental DNA (eDNA) is a relatively new approach to population and biodiversity monitoring. As such, the sensitivity of monitoring results to different methods of eDNA capture, extraction, and detection is being investigated in many ecosystems and species. One of the first and largest conservation programs with eDNA-based monitoring as a central instrument focuses on Asian bigheaded carp (Hypophthalmichthys spp.), an invasive fish spreading toward the Laurentian Great Lakes. However, the standard eDNA methods of this program have not advanced since their development in 2010. We developed new, quantitative, and more cost-effective methods and tested them against the standard protocols. In laboratory testing, our new quantitative PCR (qPCR) assay for bigheaded carp eDNA was one to two orders of magnitude more sensitive than the existing endpoint PCR assays. When applied to eDNA samples from an experimental pond containing bigheaded carp, the qPCR assay produced a detection probability of 94.8% compared to 4.2% for the endpoint PCR assays. Also, the eDNA capture and extraction method we adapted from aquatic microbiology yielded five times more bigheaded carp eDNA from the experimental pond than the standard method, at a per sample cost over forty times lower. Our new, more sensitive assay provides a quantitative tool for eDNA-based monitoring of bigheaded carp, and the higher-yielding eDNA capture and extraction method we describe can be used for eDNA-based monitoring of any aquatic species.     

The effect of filtration method on the efficiency of environmental DNA capture and quantification via metabarcoding

Environmental DNA (eDNA) is a promising tool for rapid and noninvasive biodiversity monitoring. eDNA density is low in environmental samples, and a capture method, such as filtration, is often required to concentrate eDNA for downstream analyses. In this study, six treatments, with differing filter types and pore sizes for eDNA capture, were compared for their efficiency and accuracy to assess fish community structure with known fish abundance and biomass via eDNA metabarcoding. Our results showed that different filters (with the exception of 20‐μm large‐pore filters) were broadly consistent in their DNA capture ability. The 0.45‐μm filters performed the best in terms of total DNA yield, probability of species detection, repeatability within pond and consistency between ponds. However performance of 0.45‐μm filters was only marginally better than for 0.8‐μm filters, while filtration time was significantly longer. Given this trade‐off, the 0.8‐μm filter is the optimal pore size of membrane filter for turbid, eutrophic and high fish density ponds analysed here. The 0.45‐μm Sterivex enclosed filters performed reasonably well and are suitable in situations where on‐site filtration is required. Finally, prefilters are applied only if absolutely essential for reducing the filtration time or increasing the throughput volume of the capture filters. In summary, we found encouraging similarity in the results obtained from different filtration methods, but the optimal pore size of filter or filter type might strongly depend on the water type under study.     

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.

     

Use of Droplet Digital PCR for Estimation of Fish Abundance and Biomass in Environmental DNA Surveys

An environmental DNA (eDNA) analysis method has been recently developed to estimate the distribution of aquatic animals by quantifying the number of target DNA copies with quantitative real-time PCR (qPCR). A new quantitative PCR technology, droplet digital PCR (ddPCR), partitions PCR reactions into thousands of droplets and detects the amplification in each droplet, thereby allowing direct quantification of target DNA. We evaluated the quantification accuracy of qPCR and ddPCR to estimate species abundance and biomass by using eDNA in mesocosm experiments involving different numbers of common carp. We found that ddPCR quantified the concentration of carp eDNA along with carp abundance and biomass more accurately than qPCR, especially at low eDNA concentrations. In addition, errors in the analysis were smaller in ddPCR than in qPCR. Thus, ddPCR is better suited to measure eDNA concentration in water, and it provides more accurate results for the abundance and biomass of the target species than qPCR. We also found that the relationship between carp abundance and eDNA concentration was stronger than that between biomass and eDNA by using both ddPCR and qPCR; this suggests that abundance can be better estimated by the analysis of eDNA for species with fewer variations in body mass.     

Detection limits of quantitative and digital PCR assays and their influence in presence–absence surveys of environmental DNA

A set of universal guidelines is needed to determine the limit of detection (LOD) in PCR‐based analyses of low‐concentration DNA. In particular, environmental DNA (eDNA) studies require sensitive and reliable methods to detect rare and cryptic species through shed genetic material in environmental samples. Current strategies for assessing detection limits of eDNA are either too stringent or subjective, possibly resulting in biased estimates of species’ presence. Here, a conservative LOD analysis grounded in analytical chemistry is proposed to correct for overestimated DNA concentrations predominantly caused by the concentration plateau, a nonlinear relationship between expected and measured DNA concentrations. We have used statistical criteria to establish formal mathematical models for both quantitative and droplet digital PCR. To assess the method, a new Grass Carp (Ctenopharyngodon idella) TaqMan assay was developed and tested on both PCR platforms using eDNA in water samples. The LOD adjustment reduced Grass Carp occupancy and detection estimates while increasing uncertainty—indicating that caution needs to be applied to eDNA data without LOD correction. Compared to quantitative PCR, digital PCR had higher occurrence estimates due to increased sensitivity and dilution of inhibitors at low concentrations. Without accurate LOD correction, species occurrence and detection probabilities based on eDNA estimates are prone to a source of bias that cannot be reduced by an increase in sample size or PCR replicates. Other applications also could benefit from a standardized LOD such as GMO food analysis and forensic and clinical diagnostics.     

A probabilistic model for designing and assessing the performance of eDNA sampling protocols

Environmental DNA (eDNA) sampling, the detection of species‐specific genetic material in water samples, is an emerging tool for monitoring aquatic invasive species. Optimizing eDNA sampling protocols can be challenging because there is imperfect understanding of how each step of the protocol influences its sensitivity. This paper develops a probabilistic model that characterizes each step of an eDNA sampling protocol to evaluate the protocol's overall detection sensitivity for one sample. The model is then applied to analyse how changes over time made to the eDNA sampling protocol to detect bighead (BH) and silver carp (SC) eDNA have influenced its sensitivity, and hence interpretation of the results. The model shows that changes to the protocol have caused the sensitivity of the protocol to fluctuate. A more efficient extraction method in 2013, new species‐specific markers with a qPCR assay in 2014, and a more efficient capture method in 2015 have improved the sensitivity, while switching to a larger elution volume in 2013 and a smaller sample volume in 2015 have reduced the sensitivity. Overall, the sensitivity of the current protocol is higher for BH eDNA detection and SC eDNA detection compared to the original protocol used from 2009 to 2012. The paper shows how this model of eDNA sampling can be used to evaluate the effect of proposed changes in an eDNA sampling and analysis protocol on the sensitivity of that protocol to help researchers optimize their design.     

Environmental DNA metabarcoding of lake fish communities reflects long‐term data from established survey methods

Organisms continuously release DNA into their environments via shed cells, excreta, gametes and decaying material. Analysis of this ‘environmental DNA’ (eDNA) is revolutionizing biodiversity monitoring. eDNA outperforms many established survey methods for targeted detection of single species, but few studies have investigated how well eDNA reflects whole communities of organisms in natural environments. We investigated whether eDNA can recover accurate qualitative and quantitative information about fish communities in large lakes, by comparison to the most comprehensive long‐term gill‐net data set available in the UK. Seventy‐eight 2L water samples were collected along depth profile transects, gill‐net sites and from the shoreline in three large, deep lakes (Windermere, Bassenthwaite Lake and Derwent Water) in the English Lake District. Water samples were assayed by eDNA metabarcoding of the mitochondrial 12S and cytochrome b regions. Fourteen of the 16 species historically recorded in Windermere were detected using eDNA, compared to four species in the most recent gill‐net survey, demonstrating eDNA is extremely sensitive for detecting species. A key question for biodiversity monitoring is whether eDNA can accurately estimate abundance. To test this, we used the number of sequence reads per species and the proportion of sampling sites in which a species was detected with eDNA (i.e. site occupancy) as proxies for abundance. eDNA abundance data consistently correlated with rank abundance estimates from established surveys. These results demonstrate that eDNA metabarcoding can describe fish communities in large lakes, both qualitatively and quantitatively, and has great potential as a complementary tool to established monitoring methods.     

The application of CRISPR‐Cas for single species identification from environmental DNA

We report the first application of CRISPR‐Cas technology to single species detection from environmental DNA (eDNA). Organisms shed and excrete DNA into their environment such as in skin cells and faeces, referred to as environmental DNA (eDNA). Utilising eDNA allows noninvasive monitoring with increased specificity and sensitivity. Current methods primarily employ PCR‐based techniques to detect a given species from eDNA samples, posing a logistical challenge for on‐site monitoring and potential adaptation to biosensor devices. We have developed an alternative method; coupling isothermal amplification to a CRISPR‐Cas12a detection system. This utilises the collateral cleavage activity of Cas12a, a ribonuclease guided by a highly specific single CRISPR RNA. We used the target species Salmo salar as a proof‐of‐concept test of the specificity of the assay among closely related species and to show the assay is successful at a single temperature of 37°C with signal detection at 535 nM. The specific assay, detects at attomolar sensitivity with rapid detection rates (<2.5 hr). This approach simplifies the challenge of building a biosensor device for rapid target species detection in the field and can be easily adapted to detect any species from eDNA samples from a variety of sources enhancing the capabilities of eDNA as a tool for monitoring biodiversity.     

Model‐based integration of observed and expert‐based information for assessing the geographic and environmental distribution of freshwater species

Freshwater ecosystems harbor specialized and vulnerable biodiversity, and the prediction of potential impacts of freshwater biodiversity to environmental change requires knowledge of the geographic and environmental distribution of taxa. To date, however, such quantitative information about freshwater species distributions remains limited. Major impediments include heterogeneity in available species occurrence data, varying detectability of species in their aquatic environment, scarcity of contiguous freshwater‐specific predictors, and methods that support addressing these issues in a single framework. Here we demonstrate the use of a hierarchical Bayesian modeling (HBM) framework that combines disparate species occurrence information with newly‐developed 1 km freshwater‐specific predictors, to account for imperfect species detection and make fine‐grain (1 km) estimates of distributions in freshwater organisms. The approach integrates a Bernoulli suitability and a Binomial observability process into a hierarchical zero‐inflated Binomial model. The suitability process includes point presence observations, records of site visits, 1 km environmental predictors and expert‐derived species range maps integrated with a distance‐decay function along the within‐stream distance as covariates. The observability process uses repeated observations to estimate a probability of observation given that the species was present. The HBM accounts for the spatial autocorrelation in species habitat suitability projections using an intrinsic Gaussian conditional autoregressive model. We used this framework for three fish species native to different regions and habitats in North America. Model comparison shows that HBMs significantly outperformed non‐spatial GLMs in terms of AUC and TSS scores, and that expert information when appropriately included in the model can provide an important refinement. Such ancillary species information and an integrative, hierarchical Bayesian modeling framework can therefore be used to advance fine‐grain habitat suitability predictions and range size estimates in the freshwater realm. Our approach is extendable in terms of data availability and generality and can be used on other freshwater organisms and regions.     

Technical and biological variance structure in mRNA-Seq data: life in the real world

ABSTRACT: BACKGROUND: mRNA expression data from next generation sequencing platforms is obtained in the form of counts per gene or exon. Counts have classically been assumed to follow a Poisson distribution in which the variance is equal to the mean. The Negative Binomial distribution which allows for over-dispersion, i.e., for the variance to be greater than the mean, is commonly used to model count data as well. RESULTS: In mRNA-Seq data from 25 subjects, we found technical variation to generally follow a Poisson distribution as has been reported previously and biological variability was over-dispersed relative to the Poisson model. The mean-variance relationship across all genes was quadratic, in keeping with a Negative Binomial (NB) distribution. Over-dispersed Poisson and NB distributional assumptions demonstrated marked improvements in goodness-of-fit (GOF) over the standard Poisson model assumptions, but with evidence of over-fitting in some genes. Modeling of experimental effects improved GOF for high variance genes but increased the over-fitting problem. CONCLUSIONS: These conclusions will guide development of analytical strategies for accurate modeling of variance structure in these data and sample size determination which in turn will aid in the identification of true biological signals that inform our understanding of biological systems.     

Individual haplotyping of whale sharks from seawater environmental DNA

Population genetic data can provide valuable information on the demography of a species. For rare and elusive marine megafauna, samples for generating the data are traditionally obtained from tissue biopsies, which can be logistically difficult and expensive to collect and require invasive sampling techniques. Analysis of environmental DNA (eDNA) offers an alternative, minimally invasive approach to provide important genetic information. Although eDNA approaches have been studied extensively for species detection and biodiversity monitoring in metabarcoding studies, the potential for the technique to address population-level questions remains largely unexplored. Here, we applied “eDNA haplotyping” to obtain estimates of the intraspecific genetic diversity of a whale shark (Rhincodon typus) aggregation at Ningaloo reef, Australia. Over 2 weeks, we collected seawater samples directly behind individual sharks prior to taking a tissue biopsy sample from the same animal. Our data showed a 100% match between mtDNA sequences recovered in the eDNA and tissue sample for all 28 individuals sampled. In the seawater samples, >97% of all reads were assigned to six dominant haplotypes, and a clear dominant signal (~99% of sample reads) was recovered in each sample. Our study demonstrates accurate individual-level haplotyping from seawater eDNA. When DNA from one individual clearly dominates each eDNA sample, it provides many of the same opportunities for population genetic analyses as a tissue sample, potentially removing the need for tissue sampling. Our results show that eDNA approaches for population-level analyses have the potential to supply critical demographic data for the conservation and management of marine megafauna.     

Assessing Environmental DNA Detection in Controlled Lentic Systems

Little consideration has been given to environmental DNA (eDNA) sampling strategies for rare species. The certainty of species detection relies on understanding false positive and false negative error rates. We used artificial ponds together with logistic regression models to assess the detection of African jewelfish eDNA at varying fish densities (0, 0.32, 1.75, and 5.25 fish/m³). Our objectives were to determine the most effective water stratum for eDNA detection, estimate true and false positive eDNA detection rates, and assess the number of water samples necessary to minimize the risk of false negatives. There were 28 eDNA detections in 324, 1-L, water samples collected from four experimental ponds. The best-approximating model indicated that the per-L-sample probability of eDNA detection was 4.86 times more likely for every 2.53 fish/m³ (1 SD) increase in fish density and 1.67 times less likely for every 1.02 C (1 SD) increase in water temperature. The best section of the water column to detect eDNA was the surface and to a lesser extent the bottom. Although no false positives were detected, the estimated likely number of false positives in samples from ponds that contained fish averaged 3.62. At high densities of African jewelfish, 3–5 L of water provided a >95% probability for the presence/absence of its eDNA. Conversely, at moderate and low densities, the number of water samples necessary to achieve a >95% probability of eDNA detection approximated 42–73 and >100 L, respectively. Potential biases associated with incomplete detection of eDNA could be alleviated via formal estimation of eDNA detection probabilities under an occupancy modeling framework; alternatively, the filtration of hundreds of liters of water may be required to achieve a high (e.g., 95%) level of certainty that African jewelfish eDNA will be detected at low densities (i.e., <0.32 fish/m³ or 1.75 g/m³).