Temperature and salinity
Certainly most aquatic animals specialise within a narrow range of abiotic factors that results in trade-offs at several hierarchical levels, from molecular structure to whole-organism functioning and behaviour (Pörtner
2010). In ectotherms for example, simple maintenance-metabolism reacts as a function of temperature (Tirsgaard et al.
2015).
Temperature, and concomitant microbial activity, has been demonstrated to increase DNA release from plant matter within aquatic sediments (Poté et al.
2009) and these patterns may also be reflected in animal taxa. Indeed, numerous studies suggest metabolism, growth, physiology, and immune function in fish are all influenced by water temperature (Engelsma et al.
2003; Person-Le Ruyet et al.
2004; Takahara et al.
2011), which in-turn may increase the excretion of mucus and shedding of epithelial cells of aquatic macrofauna. As a by-product of metabolic influences, evidence suggests temperature further affects the production of faeces and urine in fish (Selong et al.
2001; Gale et al.
2013), presumably the primary component of eDNA sources. Fish mobility is increased with water temperature (Petty et al.
2012) and thus genetic signals may additionally be more homogenised and/or spatially dispersed. To date, three mesocosm studies specifically examining effects of temperature on eDNA production rates have found conflicting results; no effect in two studies (common carp,
C. carpio, Takahara et al.
2012; bighead carp,
Hypophthalmichthys spp., Klymus et al. 2014), and a significant increase in production rates in Mozambique tilapia (
Oreochromis mossambicus; Robson et al.
2016). In a field study, high water temperature significantly increased the amount of Brook Charr (
Salvelinus fontinalis) eDNA within the water column, and moreover, biomass and thus population abundance predictability increased in higher temperatures (Lacoursiere-Roussel et al.
2016). Field collections have also seen higher eDNA concentrations in pools with warmer compared to cooler water, although this may have resulted from organismal attraction, and thus a resultant increase in population size, rather than an effect of temperature on eDNA sources per se (Takahara et al.
2012). Large temperature ranges among and within lakes, especially in temperate regions where seasonal, longitudinal, and latitudinal variations can impose substantial impacts on eDNA concentrations, should consequently be incorporated into predictive models in natural systems (Lacoursiere-Roussel et al.
2016).
Similar to biotic seasonal effects on eDNA production such as breeding behaviour, temperature itself can impact the excretion of genetic material into the environment when phenologies concurrently affect other organismal physiological (e.g. metabolic regulation) or behavioural responses (e.g. temporal avoidance). For example, although eDNA has yet to be specifically quantified, overwintering salmonid fry (
Oncorhynchus spp.) demonstrate very low standard metabolic rates as a direct response to low temperatures (Eliason and Farrell,
2016). More specifically, eDNA detection of Idaho giant salamanders (
D. aterrimus) and Rocky Mountain tailed frogs (
A. montanus) was observed to be lower in early spring (Goldberg et al.
2011), ostensibly due to a combination of decreased metabolism or moving into the hyporheic zone. Daily migration behaviour such as diel vertical migration (e.g. Levy
1990; Armstrong et al.
2013) further impacts eDNA detection depending on where species are in the water column (Stewart et al.
2017), DNA persistence, and time of sampling.
Exceedingly, researchers speculate that DNA location within the environment reflects preservation or decomposition rates (Moyer et al.
2014; Turner et al.
2015). However, source dynamics are also plausible contributors to DNA location, wherein sites with high eDNA concentrations may elucidate organismal behaviour and ecosystem characteristics. To passively avoid temperature limits that may induce heat-shock, some intertidal taxa employ vertical zonation for example (Somero
2002), a behavioural response that should be considered when interpreting eDNA patterns. Certainly, coarse spatio-temporal fluctuations in water temperature, and to a lesser extent fine-scale idiosyncrasies, likely have downstream effects on eDNA production and thus our inferences as to population biomass. Populations of the same species can also undoubtedly vary in habitat or phenotype (e.g. ecomorphs) where the potential for producing genetic material at vastly dissimilar rates even within different thermal habitats of the same water body may be high.
In a similar manner as temperature responses, adaptation to saline environments also requires physiological compensation and acclimation. Egg fertilization and incubation, early embryogenesis, swim bladder inflation, and larval growth in most fish species are all dependent on salinity (Boeuf and Payan
2001). In fact, studies have shown that up to 50% of fishes total energy budget may be dedicated to osmoregulation (Bushnell and Brill
1992), with food intake, food conversion, and hormones associated with growth regulation dependent on environmental salinity (Boeuf and Payan
2001). Smoltification in salmon, for instance, has demonstrated drastic physiological adjustment to saltwater, with significantly different metabolism to that of their parr freshwater counterparts (e.g. McCormick et al.
1989). The pervasive links between salinity and fish growth has been shown for both marine and freshwater species, with general patterns suggesting marine species growth rates are increased in slightly lower saline environments, whereas freshwater species development show the opposite relationship (Boeuf and Payan
2001). Granted, assessing marine species richness and approximate abundance is a relatively new foray for eDNA (e.g.Günther et al.
2018; Knudsen et al.
2019) and has proven successful for accurate detection, read abundance has failed to find correlations with DNA proportions (Günther et al.
2018) or traditional visual biomass measures such as trawling (Knudsen et al.
2019). Undoubtedly marine and freshwater systems are likely to experience difference abiotic parameters affecting eDNA dynamics, but whether production rates in marine systems vary in vastly dissimilar ways compared to freshwater habitats, is a yet unknown facet of this methodology.
Other influences
Abiotic parameters for aquatic macrofauna can ultimately act directly through receptors to increase/decrease growth (e.g. temperature, salinity) or can be a limiting threshold within a tolerance range (e.g. pH, CO
2, O
2). Often acting synergistically (e.g. with temperature), pH, UV radiation, CO
2, and O
2 have complex interactions, and decoupling how these components influence eDNA sources may be difficult. Increasing temperature for example, decreases saturation concentrations of O
2 due to the decreased capacity of water to carry oxygen, and aerobic performance is often limited by high temperatures (Bozinovic and Pörtner
2015) as seen in crustaceans (e.g. Storch et al.
2009) and zooplankton (Seidl et al.
2005). In aquatic ecosystems with fluctuating O
2 levels (e.g. lakes or streams), dissolved O
2 depletion could increase the frequency of hypoxia status. Reduced spawning, sperm motility, fertilization success, hatching rate, and larval survival have been described as hypoxia effects on wild fish populations (Wu et al.
2003), which although only speculative, likely have large impacts on eDNA sources at a population scale.
Confluences in various abiotic parameters further exist, for instance, intertidal fish increase O
2 consumption and demonstrate a disruption to body growth when exposed to high UV radiation, revealing the power of UV on respiration and energy expenditure in fish (García-Huidobro et al.
2017). Increasing temperatures and concomitant summer droughts favour acidic environmental conditions in surface waters due to higher CO
2 production (Wright
2008). Rates of survival, reproduction, hatching success, swimming behaviour, and body chemistry of both fish and aquatic invertebrate species (Jordahl and Benson
1987; Havas and Rosseland
1995) have all been shown to be affected by pH, with early developmental stages being more sensitive to pH variations. In amphibians specifically, embryonic development and growth curves are stunted in acidic environments, and evidence also demonstrates reduced tadpole swimming performance (Arena-Rodríguez et al.
2016). What’s more, changes in aquatic pH may also affect the biotic community and translate into alterations in population structure or reduced species diversity.
Of the limited eDNA research that has been done on these abiotic influences to date, Seymour et al. (
2018) demonstrate eDNA quantification to be 1–2 orders of magnitude greater in basic compared to acidic sites. However, whether this solely results from differential degradation rates (e.g. Strickler et al.
2015) rather than DNA production has yet to be determined. On the other hand, Buxton et al. (
2017) found pH to be of little influence on detection rates in mesocosms. Certainly, systematic research quantifying how these abiotic parameters influence the production of DNA being released from focal organisms (paralleling analysis of abiotic influences on eDNA degradation rates; Barnes et al.
2014) will expand the utility of aquatic eDNA tools for conservation purposes, especially in light of rapidly changing environments (e.g. climate change and species range shifts).
Finally, it’s important to note that input of genetic material may further become redistributed within aquatic systems via abiotic processes such as flow/discharge (e.g. Deiner and Altermatt
2014; Jane et al.
2015) or from previous particle settlement (e.g. sedimentation; Turner et al.
2015). While these signals are often described as sinks of eDNA for their propensity to remove DNA from their place of origin (Fig.
1), they could also be argued
sources of eDNA, despite not currently being
produced by focal organisms at a given location. Still, these abiotic processes have been shown to render longer-lasting and abundant genetic signals (Turner et al.
2015) from locations far from their origin (Deiner and Altermatt
2014), thus I advocate practitioners using eDNA for conservation should be aware of their influence on eDNA detection/quantification.