Concentrations of environmental DNA (eDNA) reflect spawning salmon abundance at fine spatial and temporal scales
Introduction
All organisms shed bits of DNA into their surrounding environments, leaving behind a genetic footprint comprised of skin, scales, waste, and other tissues, collectively referred to as environmental DNA or eDNA. In aquatic environments, eDNA remains suspended in the water, where it can be collected, extracted, and sequenced/amplified, to reveal the habitat's species composition (Díaz-Ferguson and Moyer, 2014; Rees et al., 2014; Thomsen and Willerslev, 2015). Over the past decade, the use of eDNA technologies in the conservation and management of animal populations has evolved from a novelty to a valuable tool for scientists and resource managers (Jones, 2013; Kelly et al., 2014b). In comparison with traditional means of sampling taxa, eDNA technologies may be more efficient with regard to both time and money, and can overcome the practical and regulatory challenges associated with capturing rare or endangered species (Evans et al., 2017; Shaw et al., 2016). Indeed, in some cases, eDNA can generate substantially more information on species in less time than traditional survey methods (Ji et al., 2013; Valentini et al., 2015), such as alpha and beta diversity (e.g. Kelly et al., 2016). Furthermore, the rapid reduction in costs associated with genetic research over the past decades makes genetic approaches increasingly cost-effective.
At present, eDNA sampling is being applied extensively for the detection of invasive (Fujiwara et al., 2016; Jerde et al., 2011; Takahara et al., 2013) and endangered (Laramie et al., 2015a; Thomsen et al., 2012; Wilcox et al., 2013) species, and for the estimation of biodiversity across terrestrial, aquatic, and marine environments (Kelly et al., 2014a; Lodge et al., 2012; Port et al., 2016). These applications of eDNA all rely on its ability to detect the presence or absence of one or more species in a given environment. As such, the usefulness of eDNA methods remain limited because effective conservation of threatened species and management of exploited populations often requires estimates of abundance in addition to knowledge of presence and distribution. Consequently, development of eDNA sampling and analysis protocols that allow for estimation of relative or absolute abundance will greatly expand the applicability of the technology for conservation and management, and remains an important frontier in eDNA research (Kelly, 2016).
Recent examples of quantitative eDNA applications highlight both the promise and challenge of abundance estimation using these technologies. Kelly et al. (2014a) and Evans et al. (2016) both found positive correlations between eDNA concentration and biomass of multiple species in mesocosm settings using a multispecies metabarcoding approach. However, in both cases, despite known abundance and biomass, the relationships were generally weak and varied markedly between taxa. Targeted analyses using species-specific probes and qPCR avoid some of the potential biases of multi-species methods, and recent field studies have reported significant relationships between abundance or biomass and eDNA quantity using this approach. For example, Lacoursière-Roussel et al. (2016) found a weak, but positive relationship between catch per unit effort of lake trout (Salvelinus namaycush) and concentrations of the species' eDNA as detected using qPCR in several large lakes in Canada. Doi et al. (2017) detected a significant, positive relationship between snorkel-survey counts of the stream-dwelling fish Plecoglossus altivelis and eDNA concentrations in the Saba River, Japan. The direction of the relationship remained constant across seasons, but the slope increased markedly in the fall, highlighting the potential for temporal variability in the processes of eDNA production, transport or degradation. Buxton et al. (2017) also found a positive relationship between great crested newt (Triturus cristatus) abundance and eDNA concentrations in a series of ponds. However, they detected seasonal dynamics in eDNA concentration independent of abundance (likely a result of breeding activity). The results of these and other recent studies (e.g., Baldigo et al., 2017; Pilliod et al., 2013; Takahara et al., 2012) suggest that estimating abundance of aquatic organisms with eDNA approaches may indeed be possible.
Quantitative applications of eDNA would be particularly valuable in conservation of salmon and other anadromous fishes. Productive populations of these species are often exploited at high rates and managed using data-intensive approaches. Other populations are severely depleted and of significant conservation concern with many listed as endangered or threatened (Quinn, 2005). In both cases, estimates of abundance at various stages of the life cycle provide valuable data on survival, movement, habitat quality, and population productivity that directly inform management and conservation efforts. Traditional methods of salmon enumeration include weirs, counting towers, mark-recapture studies, float/walking/aerial surveys and hydroacoustics (Enzenhofer et al., 1998; Holt and Cox, 2008). These and other counting methods can be expensive and are often labor-intensive, limiting the spatial and temporal extent of monitoring by management agencies with finite budgets. The extent or resolution of monitoring efforts would be greatly increased if robust abundance estimates could be derived from eDNA samples, benefiting fish populations and the ecosystems, individuals, and communities that rely upon them. However, despite recent progress in quantitative applications of eDNA sampling, many uncertainties remain regarding the generation, transport and degradation of DNA in the environment (Andruszkiewicz et al., 2017; Barnes and Turner, 2015; Civade et al., 2016; Deiner and Altermatt, 2014; Jerde et al., 2016; Sassoubre et al., 2016; Shogren et al., 2016), and thus the spatial and temporal resolution of eDNA-based abundance estimates. For example, shedding rates may vary seasonally (Buxton et al., 2017) or with age (Maruyama et al., 2014) and degradation rates may be correlated with environmental factors such as temperature and microbial activity (Lance et al., 2017). Many of these issues are particularly acute for spawning salmonids occupying dynamic stream environments and undergoing rapid physiological, behavioral and morphological changes.
While the ultimate goal of quantitative eDNA methodologies is to estimate animal abundance from DNA concentration, the studies described above demonstrate such correlations to be both variable and uncertain. Reversing this model, and instead examining biological and environmental factors that influence the amount of DNA detectable in the environment is a key step in improving the predictive power of eDNA-based quantification. In this study, we sought to address some of these key uncertainties by exploring the quantitative relationship between eDNA and the abundance of sockeye salmon (Oncorhynchus nerka) in Hansen Creek, a small tributary of Lake Aleknagik near Bristol Bay, Alaska, USA. Counts of live and dead fish in the creek have been conducted daily during the spawning season – typically mid-July through August – for over 20 years. As such, the timing and spatial extent of the spawning run is well understood, and there is an established methodology for assessing the salmon population. Moreover, sockeye salmon are semelparous, so all adults die at the end of the spawning season rather than remaining in the stream, as would be the case for most fishes. These features, combined with physical characteristics making it amenable to visual surveys of salmon, make Hansen Creek attractive for exploring the relationship between eDNA and fish abundance in a natural setting. In order to examine the relationship between sockeye salmon abundance and the amount of sockeye salmon eDNA in the water we tested three hypotheses:
- 1.
eDNA does not substantially degrade or settle, or become entrained in sediment along the length of Hansen Creek, and therefore the furthest-downstream sampling site will consistently record the highest concentrations of eDNA.
- 2.
eDNA from tributaries will be additive, so that eDNA sampled on separate tributaries upstream of a confluence should approximately equal eDNA sampled just downstream of the confluence.
- 3.
eDNA concentration is linearly related to the total number of fish in Hansen Creek and inversely related to temperature.
Section snippets
Field methods
Hansen Creek is a small stream located in the Wood River watershed of southwest Alaska. It is well suited for exploring eDNA dynamics for several reasons. The spring-fed creek is both small (~2 km long and averaging 4 m wide and 10 cm deep) and simple, with only one significant tributary entering from a spring-fed pond (hereafter “side pond”) ~0.5 km downstream of the headwater pool created by an old beaver dam (Fig. 1; Quinn and Buck, 2001). Adult sockeye salmon occupy the stream only during
Season summary
We began eDNA sampling on 10 July 2016 to measure background DNA levels, a date well before the long-term average arrival of the first adult sockeye to Hansen Creek (Carlson and Quinn, 2007). Based on historical observations and a lack of any signs of live or dead adult sockeye salmon in the creek, we are very confident in our zero-count of adults on this date. Nevertheless, sockeye DNA was detected in all sites and in all replicates, though at levels (0.99–5.62 copies · 103/s) at least an
Discussion
Using high-resolution sampling (in both space and time) in a well-characterized field setting, we addressed important unknowns surrounding the quantitative relationship between species abundance and eDNA concentration, and the spatial and temporal resolution of the technique. Supporting the idea that eDNA sampling may be suitable for enumeration of salmon in streams, we found a strong correlation between eDNA and abundance in Hansen Creek. More generally, we found that (1) eDNA concentrations
Conclusion
As eDNA sampling has become a more common way of surveying aquatic and marine ecosystems, analytical and bioinformatic techniques have improved in step (e.g., Caporaso et al., 2010; Ficetola et al., 2015; Lahoz-Monfort et al., 2016; O'Donnell et al., 2016). Yet, field-based studies have only begun to test the boundaries of genetic sampling as a useful tool for ecology and for applied environmental science (Spear et al., 2015; Yamamoto et al., 2016). Quantitative applications of eDNA sampling
Acknowledgements
We thank Blakely Adkins, Catherine Austin, Jackie Carter, Jason Ching, Susan Harris, Anne Hilborn, Matt Hilborn, Katie McElroy, Joe Smith and others for the often tedious field work required for this study, and Carl Ostberg for genetics assistance. We also appreciate the valuable input from Mathew Laramie and three anonymous reviewers on previous versions of this manuscript. We acknowledge funding from the IGERT Program on Ocean Change, USGS Ecosystems Mission Area and the University of
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