Introduction

With threats to biodiversity increasing (Barnosky et al. 2011; Pimm et al. 1995), rapid biodiversity assessment and the ability to reliably detect species that are rare or have patchy distributions is imperative for effective evidence-based conservation actions to be implemented (Ficetola et al. 2008; Magurran 2004). Data generated by citizen science are widely used for species distribution assessments and other ecological research (Bonney et al. 2009; Van Strien, Van Swaay, and Termaat 2013). Various challenges exist in working with ecological citizen science data, however, most notably error and bias due to variation among observers (Dickinson, Zuckerberg, and Bonter 2010). Accuracy of visual based species identification may be as low as 60% for non-experts (Austen et al. 2016).

Citizen science schemes for monitoring amphibians are active within the UK, for example the National Amphibian and Reptile Recording Scheme (NARRS) (Wilkinson and Arnell 2013). Such surveys, particularly those for the Great Crested Newt (Triturus cristatus), require the use of multiple survey visits and multiple methods to achieve a reasonable probability of detection (Griffiths, Raper, and Brady 1996; Langton, Beckett, and Foster 2001; Wilkinson and Arnell 2013). Methods include a combination of torchlight visual searches of ponds at night, overnight bottle trapping, sweep netting to catch individuals, and searches of vegetation for eggs. Each of these methods requires a considerable amount of time at a pond; has health and safety implications for surveyors (for example working at night); can have variable reliability of detection influenced by environmental factors; and may require extensive training and licencing to ensure that the survey is carried out with minimum risk to target and non-target organisms (Langton, Beckett, and Foster 2001). Combining all four of these methods in a single survey visit yields a probability of detecting the presence of Great Crested Newts of between 0.41–0.68. To improve confidence that a site is unoccupied to the 95% level requires between 3–6 visits using traditional methods (Sewell, Beebee, and Griffiths 2010). As a result, a regional or landscape-wide survey programme can be logistically difficult, prohibitively expensive, and require multiple visits and skilled surveyors with taxonomic training (Biggs et al. 2015; Sewell, Beebee, and Griffiths 2010). The intensity of the survey methodologies and the number of visits required to achieve high levels of confidence in the results can lead to low retention of volunteers in surveys (Pers. comm. Dr John Wilkinson).

Given the issues with traditional amphibian survey methods, simple yet reliable survey methods that can be carried out by citizen scientists are in demand. One technique is environmental DNA (eDNA) surveillance, during which DNA is isolated from a sample of environmental material and used to identify the presence of a species or community of species (Jane et al. 2015). Since 2008, eDNA has become a widespread tool for detecting invasive aquatic species (Ficetola et al. 2008; Jerde et al. 2011; Wilson et al. 2014) and species of conservation importance (Biggs et al. 2015). Laboratory analysis based on DNA circumvents variation in species identification among surveyors and should reduce inaccuracies in datasets to which many individuals contribute.

Despite wide use by the research community, eDNA has had limited uptake within citizen science studies. Its utility for citizen scientists to detect Great Crested Newts has been demonstrated by the Freshwater Habitats Trust Pond Net scheme (Biggs et al. 2015; Freshwater Habitats Trust 2017) and the “Great Crested Newt Detectives” project of Amphibian and Reptile Conservation in Scotland (Minting 2016), both within the UK. The method has much wider applicability with citizen science based studies, however, allowing assessments of species distribution at scales that would make conventional or commercial surveys prohibitive (Biggs et al. 2015; Gibson et al. 2015). Collecting environmental samples for eDNA analysis requires little training and can be done quickly. Samples can be collected in the field at any time that suits citizen science participants, with water samples returned to a central location for shipment to a laboratory for analysis. DNA can then be isolated and identified using molecular techniques such as real-time quantitative PCR (qPCR) (Thomsen et al. 2012) or metabarcoding (Valentini et al. 2016).

eDNA sample collection requires a much shorter time at a pond than traditional methods, and is often conducted using only a single sample collected during one visit, resulting in detection probabilities much greater than those for a single visit using conventional methodologies (Buxton, Groombridge, and Griffiths 2018). The reduced number of visits required and lower intensity of sample collection increases the number of sites that a single volunteer can survey for a given effort and may increase volunteer retention, facilitating an increase in scale for a study as a whole, while increasing statistical rigor (Wilkinson and Arnell 2013). Additionally, surveys targeting eDNA lessen disturbance to the studied species by reducing the number of visits required to a pond, removing the need to disturb the structure of a pond with sweep netting and removing animal welfare concerns associated with trapping. eDNA also increases the accuracy of results by removing ambiguity arising from visual species identification. As such, eDNA offers a new tool for use by citizen science project designers for generating large, accurate species distribution data sets.

A variety of methods have been used for collecting aquatic environmental samples for DNA analysis, and when using eDNA, it is vital to choose sampling methodologies that are appropriate for the goals of the research. Most studies to date have focused on how best to detect a target species from samples rather than the reliability of the sample collection protocol itself (Deiner et al. 2015; Goldberg et al. 2016). The most popular protocols use one of two approaches. Firstly is precipitation in ethanol, where a sample of water is preserved within a large volume of absolute ethanol and a small volume of a salt (Biggs et al. 2015; Deiner et al. 2015; Eichmiller, Miller, and Sorensen 2016; Ficetola et al. 2008; Spens et al. 2016). Alternatively, a sample of water can be passed across a micropore membrane to concentrate and preserve DNA, however, the volume of water, membrane substrate, and membrane pore sizes used vary considerably between studies (Goldberg et al. 2016). A summary of methods used by different studies has been collated by Rees et al. (2014b). The different sample collection and extraction methodologies have advantages and disadvantages, but few studies have assessed how they perform against each other, or within different environments, i.e., in ponds, lakes, rivers, and the marine environment. Some studies have found that filtration recovers more DNA than ethanol precipitation (Deiner et al. 2015; Eichmiller, Miller, and Sorensen 2016; Spens et al. 2016), however, these studies focus on stream and lake environments and do not take into account environmental conditions unique to ponds.

Likewise, not all sampling protocols are suitable for citizen science initiatives (Biggs et al. 2015). For example, many filtration protocols require the transport of large volumes of unpreserved sample water, on ice, to a central location for filtration (Pilliod et al. 2013), while others use expensive electronic pumping equipment in the field (Pilliod et al. 2013). Neither approach is easily adopted by—nor practical for—citizen science studies, where volunteers may be expected to collect a small number of samples in a time frame fitted around other commitments. Due to the very low environmental concentrations of target DNA, it is imperative that eDNA sample collection and extraction methods recover the highest amount of DNA possible in a sample.

Here we assess two eDNA collection methods that would be applicable to a citizen science study for which a large number of surveyors each collect a small number of samples. We evaluated these methods for their suitability for citizen science because they do not require bulky, expensive, or electronic pumping equipment or the transport of large volumes of water, and the data-collection tools can be supplied as individual sealed kits for each sample. We tested the precipitation in ethanol method (Biggs et al. 2015) and the syringe filtration (Deiner et al. 2015) with glass microfiber syringe filtration method, aiming to identify whether eDNA extract concentrations varied between the two methods as they would be used in the field. We did this in both laboratory tanks and ponds, using water volumes applicable to the different methods. We targeted the Great Crested Newt, a semi-aquatic amphibian that has been widely used as a study species within eDNA research and citizen science (Biggs et al. 2014, 2015; Buxton et al. 2017; Buxton, Groombridge, and Griffiths 2017; Minting 2016; Rees et al. 2014a, 2017; Thomsen et al. 2012), and one for which commercial eDNA analysis has been pioneered (Natural England 2014).

Methods

Results

Samples from naturally colonised ponds

All positive field samples were found to be above the limit of quantification for this study, the minimum concentration that can be reliably quantified by the qPCR assay (Buxton et al. 2017). There was no difference in extract concentration from filters and ethanol precipitation paired samples collected from ponds (Wilcoxon-Pratt signed-rank test z = –1.03; p = 0.30; Figure 1).

Figure 1 

Paired eDNA samples collected from natural ponds. The black line indicates the point at which the two extract concentrations have equal DNA concentration. Sample pairs with greater extract concentration from the glass-microfiber filter collection method appear above the line and sample pairs with greater extract concentration from the precipitation method appear below the line. Due to logarithmic scale where one or both of a pair have a concentration of zero, no result is shown.

We analysed the eDNA score (proportion of positive qPCR replicates) for the two collection methods for all 61 paired eDNA samples. Again we found no significant difference between the sample collection methods (Wilcoxon-Pratt signed-rank test z = –1.0; p = 0.319).

Experimental Serial Dilution

All samples from the experimental serial dilution fell above the qPCR minimum concentration for reliable quantification (limit of quantification) (Buxton et al. 2017). Regression analysis of the level of dilution on the final extract concentration was highly significant for both the ethanol precipitation (t = 5.0; df = 46; p < 0.0001) and filter (t = 6.3; df = 46; p < 0.0001) collection methods. A significant interaction (ANCOVA: F = 33.3; df = 1, 93; p < 0.0001) was found between the collection method and the sample dilution level. In addition to the significant difference in slope between the two eDNA collection methods, the intercept was also found to be different (precipitation = 2.541 × 10^–5 ngul^–1; glass-microfiber filter = 0.003892 ngul^–1). This indicates that the effect of initial sample concentration on the final extract concentration depends on the collection method used (Figure 2).

Figure 2 

Relationship between DNA extract concentration and the level of dilution. Each point represents the median qPCR concentration value for an eDNA sample for two collection methods at the different dilution levels. Open circles represent samples collected via filtration, closed circles represent samples collected via ethanol precipitation.

For each of the paired samples at all dilution levels, the filtered samples yielded a greater extract concentration than the corresponding sample collected using the ethanol precipitation method (Figure 3). This result was highly significant (Wilcoxon-Pratt signed-rank test: z = 6.03, p < 0.0001).

Figure 3 

Paired eDNA samples collected from serial dilution of tank water. The black line indicates the point at which the two extract concentrations would have equal DNA concentration. Sample pairs with greater extract concentration from the glass-microfiber filter collection method appear above the line and sample pairs with greater extract concentration from the precipitation collection method appear below the line. Note the logarithmic scale for clarity.

Discussion

In experimental tanks where water contained no organic or particulate matter, filtration of 0.91 L of sample water using 0.7 µm glass-microfiber syringe filters recovered larger amounts of eDNA than ethanol precipitation with a sample volume of 0.09 L across the range of sample water concentrations tested. However, when assessed in the field with real pond water, no significant difference between the collection methods was observed.

We compared two methodologies considered to be suitable for use within widespread citizen science projects, where provision of equipment such as peristaltic pumps would not be logistically or financially viable (Biggs et al. 2015). However, we recognise that other filtration methodologies are available that require the use of pumping equipment, which may allow for increased eDNA capture rates (Minamoto et al. 2016; Spens et al. 2016).

The concentrations of target DNA in the extracts from the laboratory tanks were within or above the range of that observed in the natural ponds. Our results from the laboratory tanks support previous work on lake water, which showed that filtration recovers greater amounts of total and target eDNA than the ethanol precipitation method (Spens et al. 2016). However, Spens et al. (2016) used different filters and sampling volumes from the present study. Increased sample volumes used in the filtration method are likely to have been responsible for the greater concentrations of eDNA recovered, when compared with the ethanol precipitation method, in the tank experiment.

The difference in extract concentrations between the two sampling methods observed in the laboratory tanks was not repeated in the field samples. This result may reflect the composition of pond water compared with tap water. When processing natural pond water, filters may become blocked by suspended solids and algae that were not in the samples from laboratory tanks. We found that that 0.91 L of water from laboratory tanks could easily be passed through two filters. In contrast, in some field samples it was not possible to pass 500 mL of pond water through two glass-microfiber filters disks. The lower water volume is likely to reduce the amount of eDNA captured and therefore the quantity available for extraction. In contrast, during the initial precipitation and centrifugation step with the ethanol precipitation samples, suspended solids and algae precipitated out of solution with the eDNA collecting as a pellet on the side of the tube. This additional material may have assisted in securing the eDNA in the pellet, preventing it being discarded with the supernatant and increasing the amount of DNA within the extract.

Pond water can differ from water found in rivers, lakes, or the marine environment. Pond water is more stagnant, allowing the build-up of algae and suspended solids to a greater extent than lotic water or large lakes where stratification and wind action allow for water movement. The results from our field experiment do not fully support the conclusions of Spens et al. (2016) or Deiner et al. (2015), both of whom conclude that filtration outperforms precipitation. In our experiment we observed no difference between the sampling methods when they are applied to pond water. However, these two studies utilised lake and river water respectively and so may not have faced the same limitations found with ponds.

Deiner et al. (2015) show that different combinations of sampling and extraction protocols are appropriate when targeting different taxa, and conclude that it is imperative to pick the combination best suited to the specific study, advice also advocated by Minamoto et al. (2016). Our results suggest that this approach should be extended to environment type as well as to taxon, given that the difference in recovery between the sample types, which we observed in tank experiments, disappears with pond water.

Within the laboratory tank experiment there was a significant relationship between the level of dilution and eDNA extract concentration, with more diluted samples showing a reduced extract concentration. However, some samples exhibited greater extract concentration than more heavily diluted samples collected from the same tank. Although this may result from sampling error, it was apparent with both collection methods, but was more prominent in ethanol precipitation samples. This finding suggests that even though concentration of eDNA extracts are related to the amount of DNA within the water sampled, extraction efficiency between samples may not be consistent, or the amount of eDNA within a sample may be heavily influenced by the form that the eDNA takes (extracellular, single cells, or aggregations of cells). Assuming that the majority of eDNA collected is intracellular (Deiner et al. 2015; Rees et al. 2014b), concentration may be influenced by aggregations of cells within samples, with larger water volumes used with the filtration samples helping to mitigate for this.

To detect statistically meaningful changes in pond occupancy by amphibians on a regional or national scale using traditional visual based survey methods, the number of sites needed to be visited and the survey effort required may be prohibitive (Biggs et al. 2014; Wilkinson and Arnell 2013). This would be the same for citizen scientists or professional surveyors. New survey methods, such as the targeting of eDNA, require fewer visits to a pond, less time on site, and more sociable working hours. This may allow surveys to be undertaken on a larger scale, thereby improving estimates of occupancy and population change, which have been goals of citizen science led national monitoring projects such as the Amphibian and Reptile Conservations Trust (ARC) NARRS project (Wilkinson and Arnell 2013). However, there is a financial cost associated with processing eDNA samples, and the laboratory analysis would need to be budgeted from the outset. The use of the eDNA technique by citizen scientists within national or regional distribution assessment projects has been demonstrated within the ARC Great Crested Newt Detectives project in Scotland (Minting 2016) and the Freshwater Habitats Trust PondNet project (Biggs et al. 2015). These projects are managed centrally by nature conservation charities partnering with a commercial laboratory. The nature conservation charities draw on their network of volunteers and advise on identification of locations to collect samples, obtaining access permissions as well as running training on the use of eDNA kits. The laboratory partner provides eDNA sampling kits to the volunteer surveyors and undertakes the genetic analysis, returning the results to the charity to compile the data. It is imperative that the volunteer surveyor’s receive prompt feedback on the samples they collect, to maintain the link between surveyors and results, maintaining participant engagement that could be lost through the lack of interaction with the target species itself. The availability of eDNA survey methods for projects utilizing samples collected by citizen scientists has the potential to be utilised for a wide range of taxa of conservation concern.

Citizen scientists clearly have options for eDNA sample collection. However, the collection of filtered samples from natural ponds with filtration was challenging, as filters can easily become blocked, and this may not lend itself to participant engagement and retention. Citizen scientists are likely to vary in the level of perseverance when trying to pass water across a filter. This may cause differences in the amount of water collected between individuals under the same conditions, impacting the consistency of the results and reducing the efficiency of the filtration method. Although filtration outperformed ethanol precipitation under experimental conditions, citizen scientists would be sampling natural ponds. Given that no difference in performance was observed between the methodologies in the field, either methodology would seem to be equally applicable under the conditions encountered here. However, different methods may recover different amounts of eDNA in different situations. We recommend that pilot studies be undertaken to identify the most appropriate method for individual studies, with decisions on the most appropriate method taking into account practical considerations relating to the two methods, and the specific study needs.