Discussion
The fish communities of our sampling sites along the Danube and near the
mouths of its main tributaries are well known both in terms of the fish
species list and the assemblage structure (Eros et al., 2017; Kottelat
& Freyhof, 2007; Sommerwerk et al., 2009); thus, these communities are
useful for testing the effectiveness of an eDNA metabarcoding strategy.
From a total of 86 taxa detected during our study, only five were
UNKTaxa in the Danube catchment (Kottelat & Freyhof, 2007; Sommerwerk
et al., 2009). For most of these taxa, the main explanation is probably
a misassignment of the detected sequences in relation to insufficient
knowledge of their regional haplotype variability. Richardsonius
balteatus , a North American species, Barbus meridionalis ,
present in rivers draining to the northwestern Mediterranean basin, andEsox cisalpinus occurring in central and northern Italy (Kottelat
& Freyhof, 2007) are species whose teleosequences are close to those ofSqualius cephalus , Barbus barbus and Esox lucius,respectively. Oncorhynchus clarkii and Oncorhynchus masou ,
two salmonid species inhabiting the northern Pacific Ocean, may also
have been confused with 0nc_Myk, but they have also been introduced
into European fish farms (Crawford & Muir, 2008), and hybridization
with other Salmonid species is conceivable (Chevassus, 1979). The
development of a more comprehensive local reference database would
reduce this risk of misassignment.
The WASTaxa category of taxa was composed mainly of food fish according
to the eDNA present in urban wastewater. Most of these taxa were
detected at only three sites: immediately downstream of the wastewater
discharge point of the city of Vienna, on the Argès River and on the
Russemski Lom River. The latter two rivers are known to receive
insufficiently treated municipal wastewater (Frincu, 2021; Kirschner et
al., 2021). eDNA released into the river from wastewater treatment
plants can lead to false-positive detection results, and a good
knowledge of the regional fauna is needed to identify them. Notably, the
detection of marine food fish is a clear sign of local pollution and can
be incorporated as a criterion for future bioassessment methods based on
eDNA samples (Pont et al., 2021). Two other taxa (0nc_Myk, Sal_spp)
are also known as food fish and farmed fish
(https://www.helgilibrary.com/indicators/fish-consumption-per-capita/austria/),
but they are also regularly present in the Upper Danube and its
tributaries, mainly due to stocking (Stankovic, Crivelli, & Snoj,
2015). Therefore, the presence of their eDNA must be interpreted with
caution when detected in a water body that does not correspond to one of
their known habitats.
A total of 60 taxa known to occur in the Danube River catchment
(KNWTaxa) were detected. In addition to the 48 taxa assigned at the
species level, the 12 taxa assigned at a higher taxonomic level
corresponded to a potential of 26 well-known Danubian species, giving a
maximum number of 74 species detected. This value was comparable to the
total of 71 species caught in the TEF survey conducted in the same
period (Bammer et al., 2021). When considering only the 18 sites sampled
with both TEF and eDNA, all the species caught by using TEF were
detected by using eDNA except four (Clupeonella cultriventris,
Eudontomyzon danfordi, Eudontomyzon mariae, Neogobius eurycephalus ),
but they were not recorded in our DNA reference database. Six of the
eight taxa (Aci_gue, Aci_rut, Aci_ste, Bar_car, Ben_sp, Rom_ura)
detected only by using eDNA were benthic species (Kottelat & Freyhof,
2007) inhabiting mainly the Danube itself or its coarse-bottomed
tributaries. Similarly, the higher taxonomic richness obtained by using
eDNA confirmed the ability of this method to be representative of all
fish fauna, especially in deep rivers where a single traditional
sampling technique does not allow sampling of the whole river section
(Eros et al., 2017). Our results highlight the effectiveness of our
integrative sampling strategy in space (the whole section of the river)
and time (approximately half an hour) as well as the performance of the
teleo primer, even if its discriminating power for some species is
limited. For the latter, the analysis of another marker in parallel,
such as MiFish, can allow more species to be discriminated (Polanco et
al., 2021).
One of the most original aspects of this study is the strong correlation
between teleo-eDNA concentrations and fish abundance estimated by using
TEF at 18 common sites. The efficiency of eDNA qPCR data to correctly
estimate taxa-specific abundance is well documented (Rourke et al.,
2021), but the estimation of the total fish abundance from the total
fish eDNA concentration (primer qPCR analysis) has been tested only in
an estuarine environment at three sites only a few kilometres apart (van
Bleijswijk et al., 2020). Here, we demonstrate the capability of eDNA
metabarcoding to estimate the total absolute abundance of fish at
distant sites, i.e., independent of their eDNA contents, and in a large
range of river sizes. The intensity of the correlation between the
teleo-eDNA concentration and fish abundance is comparable to results
obtained in species-specific qPCR studies in natural environments (Yates
et al., 2019). The difference in correlation intensity with fish
abundance observed when the eDNA concentration is expressed as density
or biomass should be viewed with caution, as no significant effect of
the fish abundance metric was found (Yates et al., 2019). The ratios of
fish species-specific read counts over the total read count of a sample
multiplied by the teleo-eDNA concentration measured with qPCR (van
Bleijswijk et al., 2020) were significantly correlated with the fish
species abundance obtained by using TEF. This correlation was higher
when all sites were pooled, which highlights the agreement between the
two methods for all the species and the importance of uncertainties
associated with the site scale with both eDNA and TEF.
The very high values of the co-inertia criteria also demonstrate that
the descriptions of fish community structures obtained with the TEF
(abundance per ha) and eDNA methods (taxa-specific DNA copy numbers per
litre) were quite similar. The distribution of species along the entire
Danube River obtained by using eDNA was consistent with previous
knowledge (Eros et al., 2017) but with a lower between-site variability.
For example, Aci_rut, a resident sturgeon species, was regularly
detected downstream of the first 1000 km of the river by using eDNA,
whereas no or few individuals were captured by using traditional methods
(Bammer et al., 2021; Eros et al., 2017). The anadromous taxa Alo_spp
(Alosa immaculata / A. tanaica ) was detected by using eDNA
in almost all the sites located downstream of the Iron Gate dams that
are known to limit their upstream migration (Sommerwerk et al., 2009).
In addition, the detection of Alo_spp 12 km upstream of Iron Gate I dam
(KM 1908) is consistent with previous captures of Alosa tanaicaindividuals upstream of Iron Gate II (M. Lenhardt, pers. comm.).
Nevertheless, eDNA is only an indirect estimator of organism abundance
and is influenced by many physiological processes and environmental
conditions, and the uncertainties associated with all factors affecting
eDNA concentration in the environment are high (Rourke et al., 2021).
eDNA cannot be expected to provide a highly accurate quantification of
the fish populations as needed for precise fish stock estimations in
fisheries (Boivin-Delisle et al., 2021; Rourke et al., 2021; Yates,
Cristescu, et al., 2021). For such a purpose, recent technical options
could provide a good alternative (Hoshino et al., 2021; Sato et al.,
2021; Taylor M. Wilcox et al., 2020; Ushio et al., 2018). However, it
must also be considered that most conventional fish sampling methods are
associated with many biases and high uncertainties, especially in large
water bodies where the spatial representativeness of samples is limited
and multiple methods must be used (Eros et al., 2017; Zajiceke &
Wolter, 2018). For most biomonitoring purposes, a rough estimation of
absolute fish abundance is sufficient, as the main objective is to
compare fish assemblages on a large scale or to detect long-term
variability in relation to changes in anthropogenic disturbances.
An additional benefit of quantifying total fish eDNA by qPCR is to
optimize sampling effort. Our NLME models showed that the species
richness was underestimated when the amount of teleo-eDNA extracted from
a sample was below a threshold of 0.65.106 eDNA
copies. Although several authors have recognized the importance of this
parameter (Shu, Ludwig, & Peng, 2020; Wang et al., 2021), to our
knowledge, no studies have quantified its influence. In addition, our
results demonstrated the significant influence of river size on the
concentration of teleo-eDNA per litre, with values 10 to 100 times lower
in larger rivers. This can be due to different processes, e.g., dilution
of eDNA with increasing river depth, as most fish species are confined
to the river bottom or shoreline, or the decreased abundance of fish in
large rivers compared to small rivers. Further research is needed to
better understand the processes that explain such a pattern. As the
quantity of teleo-eDNA extracted depends on both its concentration per
litre and the water volume sampled, the water volume needed to extract
an amount of eDNA over the threshold of 0.65x106 eDNA
copies is approximately 40 litres for large rivers but only a few litres
for smaller rivers. The volume of water to be sampled is the main issue
in many studies, with values ranging from less than a litre to 68 L
(Cantera et al., 2019; Civade et al., 2016; Doi et al., 2017), but no
general guidelines have been established (Shu et al., 2020; Wang et al.,
2021). This study highlights that river size is one of the main factors
that influences the minimum water volume to be sampled. Nevertheless,
this result is only valid in the context of our spatial and temporal
integrative sampling strategy: the total volume collected must be
sufficient to allow the collection of eDNA from the entire river
section.
In conclusion, our results show that the combination of qPCR analysis to
estimate the total concentration eDNA amplified by the “teleo” primer,
an eDNA metabarcoding workflow with a high number of technical
replicates, and an integrative sampling strategy allows a correct
estimation of species diversity and delivers a good proxy of absolute
species abundance (based on taxa-specific DNA copy numbers per litre).
Our approach is not appropriate if accurate abundance estimation is
required, such as in intensively managed fisheries. However, we consider
it sufficient for most biomonitoring and bioassessment purposes,
especially given the limited effectiveness of conventional fish sampling
methods in most aquatic ecosystems. The efficiency of our procedure
needs to be tested in ponds and lakes, estuaries, and marine
environments. Our results should inspire a more quantitative approach to
aquatic community analysis using eDNA methods.