Identifying landscape drivers of genetic variation of a pond-breeding amphibian on multiple spatial scales

peer reviewe

Scale-dependent effects of terrestrial habitat on genetic variation in the great crested newt (Triturus cristatus)

peer reviewedContext Terrestrial landscapes surrounding aquatic habitat influence the persistence of amphibian spatially structured populations (SSPs) via their crucial role in providing estivation and overwintering sites, facilitating or hampering dispersal and colonisation, and consequently the maintenance or loss of genetic diversity. Objectives To highlight the landscape drivers of genetic variation, we investigated the relationship between the level of genetic variation measured within ponds of the great crested newt (Triturus cristatus), and the composition of the surrounding landscape at various spatial scales. Methods Based on the sampling of 40 ponds in 13 SSPs, the influence of landscape features on several estimators of genetic variation was investigated via linear mixed models, with effects within and between SSPs incorporated. Results The best models depended on the spatial scale, with more significant associations within radii of 50 and 100 m of core ponds, particularly for allelic richness. Responses within and between SSPs were mostly similar. The availability of aquatic habitat in the landscape had a positive effect, while woodland, arable land and pasture had different effects depending on scale and response variable. Total length of roads within a 250 m radius influenced effective population size negatively Conclusions Our results stress the need to investigate the influence of environmental predictors at multiple spatial scales for an adequate understanding of ongoing processes. Generally, the landscape affected genetic variation similarly within and between SSPs. This allowed us to provide general guidelines for the persistence of great crested newt populations, with an emphasis on the importance of the aquatic habitat

Effects of preservation strategies on environmental DNA detection and quantification using ddPCR

Molecular-based monitoring relying on environmental DNA (eDNA) detection became routinely used around the world in the last few years, especially in aquatic environments. The large potential and increasing applications of this technique calls for technical improvements to optimize the reliability of these surveys. An important technical aspect in the eDNA workflow is the appropriate preservation of samples taken in the field, as it can significantly affect eDNA recovery and ultimately false negative rates. In this study, we explored the efficiency of five different preservation strategies by using a controlled mesocosm experiment in which we included three fish communities of different composition. Specifically, we compared eDNA recovery in DNA extractions (a) performed immediately following collection, or after eight months storage from (b) frozen filters, (c) unfiltered water samples stored at −20°C, and filters preserved at room temperature with (d) Longmire and (e) Sarkosyl buffer. Effects of different preservation strategies were quantified using ddPCR measurements of three fish species (Neogobius melanostomus, Rutilus rutilus, and Lota lota) and total fish DNA content using group-specific primers for Teleostei. Samples extracted immediately following collection without any further preservation yielded significantly less DNA compared to the other approaches. Overall, Longmire's buffer facilitated the best eDNA recovery across all fish species although approaches such as filter freezing or the use of Sarkosyl buffer yielded similar recovery results. Relative measurement variability, an important indicator for reliable eDNA quantification, was lowest when using Longmire's and Sarkosyl buffers and generally decreased when increasing eDNA quantity. Overall, our results clearly highlight the significant impact of sample preservation and how this can substantially affect the performance and reliability of eDNA-based approaches

The use of multiple markers and internal positive controls significantly improves species eDNA detection rates and data reliability

In recent years, environmental DNA analyses became increasingly integrated to detect and monitor the presence and abundance of rare organisms, especially in inaccessible aquatic habitats. Although it is generally proven that detection probabilities of eDNA surveys exceed those obtained via conventional techniques, these molecular approaches are, however, also subjected to detection limitations and levels of uncertainty. Besides improvements that can be made in terms of sampling design, volumes of filtered water, and the effective quantity of DNA that is finally analysed, the sensitivity of eDNA surveys is inherently determined by the number of target eDNA copies suspended in the water column. Here we show that multiplexing different primer/probe assays for the same species, but targeting amplicons situated at different loci, is a surprisingly overlooked aspect that can substantially contribute to reduce these limitations and increase the sensitivity of single-species detections. By empirically testing a large number of natural eDNA samples via ddPCR, we reveal that the use of multiple markers can significantly lower the LOD and LOQ of rare and elusive species, such as the invasive American bullfrog and the endangered European weather loach in a variety of different water bodies, such as ponds, lakes, streams, canals, etc. Especially at very low eDNA concentrations of both target species, our results showed that analysing mulitple loci significantly increased detection probabilities and lowered stochasticity effects, and thus ultimately reduces PCR costs when analysed in multiplex. The validation and use of more than one assay taregtting a single species, may further increase the confidence of positive detections. Finally, we illustrate that the implementation of internal positive controls (IPC's), is an absolute must for accurate validation of eDNA workflows and reliable interpretation of the generated data. IPC’s not only help to track down degraded and inhibited samples, to avoid false-negative detections, it also offers insights into extraction efficiency, indispensable for accurate quantification of population densities. Overall, our findings provide strong support that the multiplexing of multiple markers on different loci in combination with the use of internal positive controls ensures increased detection rates at very low eDNA concentrations and generates more robust and reliable data

eDNA-based detection and quantification to improve the management of the invasive American bullfrog in Belgium

Rapidly responding to incipient invasions is the most effective strategy to counter alien invasive species (AIS). Reliable monitoring programs defined by a high detection resolution and applicable on vast geographical and temporal scales are therefore a prerequisite for the development of successful extermination actions. Moreover, local abundance estimates can facilitate the design of effective region-scale management strategies by allowing resources to be allocated proportionally to the severity of the invasion. However, detecting aquatic biological invasions in an early stage and gauging the intensity of established invasions using conventional surveillance methods can be challenging, costly and destructive. In this study, we highlight the potential of environmental DNA (eDNA)-based species monitoring as the fundament of modern-day aquatic AIS management using the American bullfrog as a case study. This large frog species exerts a severe pressure on indigenous communities and is therefore ranked among the most destructive invaders worldwide. In Belgium, its distribution range covers 500 km² and in spite of almost a decade of intensive management efforts, successful eradication of this highly fertile and mobile species remains challenging. We first show how eDNA-based detection methods revealed the hitherto unnoticed expansion of a bullfrog population towards a new province. By quantifying eDNA concentrations before and after a national eradication campaign with droplet digital PCR (ddPCR), we then demonstrate that quantitative eDNA analyses can (i) accurately predict the number of bullfrogs that can be captured, (ii) locate breeding ponds that serve as dispersal hubs, (iii) evaluate the efficacy of eradication programs, and thus that this technique can be a valuable addition to the nature resource manager’s toolbox. As such, we present a novel approach in which quantitative eDNA analyses can significantly contribute to the control of biological invasions

Reliable eDNA detection and quantification of the European weather loach (Misgurnus fossilis)

The European weather loach (Misgurnus fossilis) is a cryptic and poorly known fish species of high conservation concern. The species is experiencing dramatic population collapses across its native range to the point of regional extinction. Although environmental DNA (eDNA)‐based approaches offer clear advantages over conventional field methods for monitoring rare and endangered species, accurate detection and quantification remain difficult and quality assessment is often poorly incorporated. In this study, we developed and validated a novel digital droplet PCR (ddPCR) eDNA‐based method for reliable detection and quantification, which allows accurate monitoring of M. fossilis across a number of habitat types. A dilution experiment under laboratory conditions allowed the definition of the limit of detection (LOD) and the limit of quantification (LOQ), which were set at concentrations of 0.07 and 0.14 copies μl–1, respectively. A series of aquarium experiments revealed a significant and positive relationship between the number of individuals and the eDNA concentration measured. During a 3 year survey (2017–2019), we assessed 96 locations for the presence of M. fossilis in Flanders (Belgium). eDNA analyses on these samples highlighted 45% positive detections of the species. On the basis of the eDNA concentration per litre of water, only 12 sites appeared to harbour relatively dense populations. The other 31 sites gave a relatively weak positive signal that was typically situated below the LOQ. Combining sample‐specific estimates of effective DNA quantity (Qe) and conventional field sampling, we concluded that each of these weak positive sites still likely harboured the species and therefore they do not represent false positives. Further, only seven of the classified negative samples warrant additional sampling as our analyses identified a substantial risk of false‐negative detections (i.e., type II errors) at these locations. Finally, we illustrated that ddPCR outcompetes conventional qPCR analyses, especially when target DNA concentrations are critically low, which could be attributed to a reduced sensitivity of ddPCR to inhibition effects, higher sample concentrations being accommodated and higher sensitivity obtained.N/

Data from: Using environmental DNA metabarcoding to monitor fish communities in small rivers and large brooks: Insights on the spatial scale of information

Monitoring fish communities is central to the evaluation of ecological health of rivers. Not only presence/absence of species is important to assess, but also the species composition of local fish assemblages is a crucial parameter. Lotic fish communities are traditionally monitored via electrofishing, characterized by a known limited efficiency and high survey costs. The use of environmental DNA-based analyses could serve as a non-destructive alternative, but this approach requires further insights in practical sampling schemes incorporating transport and dilution of the eDNA fragments; as well as optimization of molecular detection in terms of predictive power and quality assurance. By introducing fifteen species known to occur in Belgian waters via a controlled cage experiment, we aim to extend the knowledge on streamreach of eDNA in small rivers and large brooks, as laid out in the European Water Framework Directive’s water typology. Introducing fish communities in two transects of a species poor river characterized by contrasting river discharge rates, we found strong and significant correlations between the eDNA relative abundances and the relative biomass per species in the cage community. Despite a decreasing correlation over distance, the underlying community composition remained stable over a distance of 300 m up to 1 km downstream of the cages, depending on the river discharge rate. Such decrease in similarity between relative source biomass and the corresponding eDNA-based community profile with increasing distance downstream from the source, can partly be attributed to variation in species-specific eDNA persistence. Our findings offer novel insights on eDNA behaviour and characterization of riverine fish communities. We conclude that water sampled from a relatively small river offers an adequate snapshot of the total fish community composition occurring within an upstream perimeter ranging between 300 and 1000 meters. The potential application for other river systems is discussed in this study.A controlled cage experiment was performed. Fifteen fish species were held in keepnets (~cages) in a small river in Belgium. At varying distances downstream from the nets, water samples were taken. Environmental DNA was extracted and samples were analysed via both droplet digital PCR (see Van Driessche et al., 2022) as well as via eDNA metabarcoding. This dataset includes the data of the eDNA metabarcoding. The entire set-up was repeated in two river transects with contrasting river discharge rates. Two levels of source fish biomass were used. Raw data was deposited on the NCBI’s Sequence Read Archive (SRA) under BioProject number PRJNA904931. The bioinformatical pipeline as used on these raw read counts is available on Zenodo (https://zenodo.org/record/3731310#.Y8pdbXbMI2w). The OBITools software was used for further processing of the generated sequence data. The resulting count table as available here was used for further quality screening and cleaning, as well as for statistical analyses.Data can best be accessed using Microsoft Excel and R