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\begin{document}

\title{A qPCR assay for the rapid and specific detection of Shining ram's-horn
snail (Segmentina nitida) eDNA from Stodmarsh National Nature Reserve,
UK}



\author[1]{Helen Rees}%
\author[2]{Mags Cousins}%
\author[1]{Claire Baker}%
\author[1]{Ben Maddison}%
\affil[1]{RSK ADAS Ltd}%
\affil[2]{Natural England Peterborough}%


\vspace{-1em}



  
  \date{May 28, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Segmentina nitida M\selectlanguage{ngerman}üller 1774 is a freshwater snail which was formerly
widespread throughout England and south Wales. Since the 1840s it has
seen a rapid decline in its range which has been attributed to
deteriorating water quality due to nutrient enrichment, lowering of
water tables and over-management of the ditches in which it resides.
Segmentina nitida has therefore been identified as a UK Biodiversity
Action Plan (UKBAP) priority species which recommends further research
for its conservation. Here we have developed a Taqman based qPCR eDNA
assay for the detection of S. nitida at the Stodmarsh National Nature
Reserve and compared the results with a manual survey of the ditches at
this location. Our eDNA analysis exhibited an observed percentage
agreement of 84\% with a kappa coefficient of agreement between manual
and eDNA surveys of 0.56. Three ditches determined to be negative for
Segmentina nitida by eDNA analysis were manual survey positive, and a
further two ditches that were negative by manual survey were positive by
eDNA analysis revealing the potential for improved overall detection
rates using a combination of manual and eDNA methodologies. eDNA
analysis could therefore augment manual survey techniques for Segmentina
nitida as a relatively quick and inexpensive tool for collecting
presence and distribution data that could be used to inform manual
surveys and management of ditches.%
\end{abstract}\selectlanguage{ngerman}%



\sloppy


\textbf{A qPCR assay for the rapid and specific detection of Shining
ram's-horn snail (\emph{Segmentina nitida}) eDNA from Stodmarsh National
Nature Reserve, UK}

\textbf{Short Title: eDNA detection of Shining ram's-horn snail}

Helen C. Rees\textsuperscript{1}, Mags E. Cousins\textsuperscript{2},
Claire A. Baker\textsuperscript{1}, \& Ben C.
Maddison\textsuperscript{1}.

\textsuperscript{1}ADAS Biotechnology, Unit 27, Technology Drive,
Beeston, Nottingham, NG9 1LA.

\textsuperscript{2}Natural England, Suite D, Unex House, Bourges
Boulevard, Peterborough, PE1 1NG

Corresponding Author:

Helen C. Rees, ADAS Biotechnology, Unit 27, Technology Drive, Beeston,
Nottingham, NG9 1LA. Email: helen.rees@adas.co.uk Telephone: +44 (0)1159
229249

\textbf{Abstract}

\emph{Segmentina nitida} M\selectlanguage{ngerman}üller 1774 is a freshwater snail which was
formerly widespread throughout England and south Wales. Since the 1840s
it has seen a rapid decline in its range which has been attributed to
deteriorating water quality due to nutrient enrichment, lowering of
water tables and over-management of the ditches in which it
resides.\emph{Segmentina nitida} has therefore been identified as a UK
Biodiversity Action Plan (UKBAP) priority species which recommends
further research for its conservation. Here we have developed a Taqman
based qPCR eDNA assay for the detection of \emph{S. nitida} at the
Stodmarsh National Nature Reserve and compared the results with a manual
survey of the ditches at this location. Our eDNA analysis exhibited an
observed percentage agreement of 84\% with a kappa coefficient of
agreement between manual and eDNA surveys of 0.56. Three ditches
determined to be negative for \emph{Segmentina nitida} by eDNA analysis
were manual survey positive, and a further two ditches that were
negative by manual survey were positive by eDNA analysis revealing the
potential for improved overall detection rates using a combination of
manual and eDNA methodologies. eDNA analysis could therefore augment
manual survey techniques for \emph{Segmentina nitida} as a relatively
quick and inexpensive tool for collecting presence and distribution data
that could be used to inform manual surveys and management of ditches.

\textbf{Key Words}

Ditch, environmental DNA, qPCR, \emph{Segmentina nitida} , Shining
ram's-horn snail, water samples.

\textbf{Introduction}

Management and conservation of rare or at-risk species requires
knowledge of species distribution via the detection of populations which
could be at low densities. Traditionally, population monitoring is
carried out by visual detection, identification, and counting. However,
for the last decade environmental DNA (eDNA) has been used as a
non-invasive sampling technique as it is reliable, cost effective, less
harmful to the ecosystem and correlates well with conventional survey
results (Biggs et al., 2015; Darling 2019).

eDNA describes the DNA that is present within an environmental sample
for example water, soil, sediment, or air. The eDNA present in an
environment includes DNA that originates from sloughed cellular material
(e.g. skin cells) or that is excreted (e.g. faeces and urine) or
secreted (e.g. saliva) by organisms occupying the environment in
question (Rees et al., 2014). Similarly, the DNA of organisms that visit
the environment can also be present, for example birds or mammals
drinking from a water body. The presence of an organism's DNA within a
water body is short lived as DNA has been shown to be degraded to
undetectable levels within days to weeks and is affected by UV light, pH
and microbial activity (Shogren et al., 2017; Seymour et al., 2018;
Zulkefi et al, 2019). This suggests that the detection of an organism's
DNA is a demonstration of its presence or very recent presence and is a
suitable surrogate for the detection/capture of the organism itself
(Pilliod et al., 2013; Strickler et al., 2015;). The analysis of eDNA by
sensitive PCR-based approaches, therefore, has become an important tool
for measuring species presence/absence and has been successfully used to
detect many aquatic species including the highly
invasive\emph{Potamopyrgus antipodarum} New Zealand mud snail within
rivers (Goldberg et al, 2013; Clusa et al. 2016).

The Shining ram's-horn snail \emph{Segmentina nitida} (Muller, 1774) is
a small (4-6 mm diameter) rare European freshwater snail (Figure 1)
which is highly sensitive to changes in management of ditches and is
found only in good quality, well vegetated ditches (Rowson et al, 2021).
Although once common in UK, and widespread across lowland England and
south Wales, the range of this species has substantially declined since
the 1840s (Kerney, 1999). Its presence has been verified at only a few
locations in southeast England where it is mainly confined to marshes
and shallow drainage ditches with dense emergent vegetation (Watson and
Ormerod, 2003). \emph{S. nitida} is listed as a rare and declining
Section 41 species and also a Ramsar criteria feature of Stodmarsh
National Nature Reserve (NNR). In order to provide sensitive management
of ditches at this site, there is a requirement to know where
the\emph{S. nitida} occurs. Here, we describe a qPCR assay for the
detection of \emph{S. nitida} and demonstrate the detection of this
species within ditch water samples from Stodmarsh NNR with known
presence/absence status.

\textbf{Materials and methods}

\emph{Sample collection}

22 ditch water samples were collected from ditch surface water by
Natural England staff at Stodmarsh NNR between the
16\textsuperscript{th} and 27\textsuperscript{th} November 2020 (Figure
2). 10 ditch water samples outside the known range of S. nitida were
collected by ADAS staff between the 10\textsuperscript{th} January and
the 4\textsuperscript{th} February (sample information can be found in
supplemental file 1, table S1 and S2). 20x 30 mL water samples were
collected along the length of each of the ditch and pooled into sterile
sampling bag. Up to 500 mLs of this water was filtered through a 0.22 \selectlanguage{greek}µ\selectlanguage{english}M
PES sterivex filter (Millipore) using a 50 mL luer-lock syringe (Table
1). After filtration of water, 95\% ethanol was added as a preservative.

Snail specimens were collected during an invertebrate survey carried out
at the same 22 ditches at Stodmarsh NNR by Dan Bennett of The Ecology
Co-op, contracted by Natural England between December and January
2020/2021 (specimen information and detailed sampling methodology can be
found in supplemental file 1, table S3). Manual surveys of the 22
ditches were performed using an adapted invertebrate sampling protocol
from Drake (2007). The emphasis was on the free-style netting of
suitable looking micro-habitats (e.g. emergent vegetation stands) that
are likely to be most productive for this assemblage. Effort was
deliberately not divided in proportion to the extent of features nor
length of ditch, since species are not distributed in this fashion.
Snail specimens from \emph{S.nitida} and nine other similar ram's-horn
shaped species, from the 16 species of snail ) found during invertebrate
survey were identified and preserved in 95\% ethanol prior to shipment
to the laboratory: \emph{Anisus vortex, Bathyomphalus contortus,
Gyraulus crista, Gyraulus albus, Hippeutis complanatus, Planorbarius
corneus, Planorbis carinatus, Planorbis planorbis, Segmentina nitida,
Valvata cristata.}

\emph{DNA Extraction}

Upon return to the laboratory, the preservative solution was removed
from the sterivex filters and any DNA containing material captured on
the filter membrane was recovered by addition of 720 \selectlanguage{greek}µ\selectlanguage{english}L of ATL lysis
buffer and 40 \selectlanguage{greek}µ\selectlanguage{english}l proteinase K to the filter, followed by incubation at
56\selectlanguage{ngerman}°C in a water bath with regular mixing by vortexing. The supernatant
was then extracted using the DNeasy blood and tissue kit (Qiagen)
following the manufacturer's instructions with final resuspension in
200\selectlanguage{greek}µ\selectlanguage{english}l of elution buffer. All DNA samples were quantified using a Qubit
3.0 Fluorometer (Invitrogen) following the manufacturer's instructions
then stored at -20 0\selectlanguage{english}C before use.

Each snail specimen was individually transferred to a clean, sterile
mortar and ground into a fine paste using a pestle and liquid nitrogen.
For some snail species, the individual specimens were pooled prior to
grinding (see Table 1). After use mortar and pestles were immediately
immersed in 10 \% bleach for a minimum of 10 minutes and then cleaned in
between samples with 10 \% Distel (Tristel), rinsed with
dH\textsubscript{2}O and then autoclaved at 121 0\selectlanguage{english}C for 15-20 minutes.
DNA was extracted by the DNeasy blood and tissue kit (Qiagen) -with a
final elution volume of 50 or 200\selectlanguage{greek}µ\selectlanguage{english}l - in a separate laboratory remote
from water sample extraction and qPCR set up, using dedicated tissue
extraction equipment. Disposable laboratory coats were worn, and benches
and equipment were wiped down with a 10\% bleach solution before and
after use. Extracted DNA was quantified using a Qubit 3.0 Fluorometer
(Invitrogen) following the manufacturer's instructions then stored at
-20 \selectlanguage{ngerman}°C before use.

\emph{Snail specimen identification}

All PCR set up was performed in a clean `PCR room' within a UV
sterilisable cabinet and in a separate laboratory to DNA extraction
using dedicated equipment and PPE. To ensure the unidirectional workflow
DNA extracts are collected from the DNA extraction laboratory and
transferred to the PCR set-up laboratory. Laboratory personnel do not
return to the DNA extraction laboratory during that same day thus
maintaining the unidirectional workflow.

PCR was performed to confirm the identity of the provided snail
specimens using the mICOIintF/jgHCO2198 primer combination (Leray et al.
2013). These primers amplify a fragment of the Cytochrome c Oxidase
subunit I gene (COI) and have been shown to perform well in invertebrate
metabarcoding studies (Leray et al. 2013; Geller et al. 2013). PCRs were
set up in a total volume of 25 \selectlanguage{greek}µ\selectlanguage{english}L consisting of: 2 \selectlanguage{greek}µ\selectlanguage{english}L of extracted
template DNA, 2.5 \selectlanguage{greek}µ\selectlanguage{english}L of each primer (0.4 \selectlanguage{greek}µ\selectlanguage{english}mol/L), 12.5 \selectlanguage{greek}µ\selectlanguage{english}L of Itaq
(BioRad) Sybr Green mastermix, and 5.5 \selectlanguage{greek}µ\selectlanguage{english}L ddH2O. Each sample was run in
duplicate on a Bio-Rad CFX Connect real-time PCR machine as follows: an
initial incubation for 1 minute at 950\selectlanguage{english}C; followed by 35 cycles with a
melting temperature of 95\selectlanguage{ngerman}°C for 1 minute; an annealing temperature of
40\selectlanguage{english}0C and a final extension step at 720\selectlanguage{english}C for 90 seconds before holding at
40\selectlanguage{english}C until collection of PCR products for analysis. After PCR and
amplicon clean-up, PCR products were Sanger sequenced using mICOIintF
and returned sequences identified using BLAST.

\emph{Species-specific assay development}

In order to design primers specific to the \emph{S. nitida} the DNA
sequences for the cytochrome oxidase 1 (COI) gene for \emph{S.
nitida}and the nine other co-occurring similar ram's-horn shaped species
commonly found at the Stodmarsh NNR were downloaded from Genbank and
their sequences aligned using BioEdit version 7.2.5. Primers and probes
were designed using PrimerBLAST with default settings except for
targeting a 70-300 bp fragment and including only base pairs between 70
and 600 in the \emph{S. nitida} consensus sequence as this corresponded
to the most variable region on the multi-species alignment. Ten
potential primer/probe combinations were generated and reduced to four
using PrimerBLAST and looking for cross-species amplification
(Supplemental file 2).

The four potential primer/probe combinations were tested firstly on DNA
extracted from \emph{S. nitida} followed by the other nine co-occurring
snail species to test for cross-species reactivity. PCRs were set up in
a total volume of 25 \selectlanguage{greek}µ\selectlanguage{english}L consisting of: 3 \selectlanguage{greek}µ\selectlanguage{english}L of extracted template DNA, 1
\selectlanguage{greek}µ\selectlanguage{english}L of each primer/probe (0.2 \selectlanguage{greek}µ\selectlanguage{english}mol/L forward primer; 0.4 \selectlanguage{greek}µ\selectlanguage{english}mol/L reverse
primer; 0.1 \selectlanguage{greek}µ\selectlanguage{english}mol/L probe), 12.5 \selectlanguage{greek}µ\selectlanguage{english}L of TaqMan\selectlanguage{ngerman}® Environmental Master Mix
2.0 (containing AmpliTaq GOLD DNA polymerase), and 6.5 \selectlanguage{greek}µ\selectlanguage{english}L ddH2O. Each
sample was run as 12 replicates on a Bio-Rad CFX Connect real-time PCR
machine as follows: an initial incubation for 5 minutes at 56.30\selectlanguage{english}C then
10 minutes at 95\selectlanguage{ngerman}°C; followed by 55 cycles with a melting temperature of
95°C for 30 seconds and an annealing temperature of 59.6\selectlanguage{english}0C for 1 minute.

Once specificity of primer/probe combinations was confirmed, the primer
concentrations of two primer/probe combinations (primer/probe
combinations 2 and 9) were optimised by independently varying final
primer concentrations (the probe was held at a final concentration of
0.1 \selectlanguage{greek}µ\selectlanguage{english}mol/L) (Wilcox \emph{et al} , 2015). The sensitivity of the assay
was tested by creating a six-level standard curve dilution series
(3x10\textsuperscript{-1} to 3x10\textsuperscript{-7} \selectlanguage{greek}µ\selectlanguage{english}g/\selectlanguage{greek}µ\selectlanguage{english}l). The
standard curve was created by quantifying the DNA extracted from\emph{S.
nitida} sample 7a on a Qubit Fluorometer (Thermo Fisher Scientific) and
diluting the DNA to the desired concentrations using the elution buffer
provided in the DNeasy Blood and Tissue kit (Qiagen). 12 replicates of
each dilution were run using the optimised primer/probe concentrations
to determine the standard curve slope, the limit of detection (LOD) and
limit of quantification (LOQ).

The optimised assay using primer/probe combination 9 (Snit9F: 5'-
CCACTTTTAATTGGGGCTCCG-3'; Snit9R: 5'- CCATGTGCAATAGGACCGCT-3'; Snit9P:
5'- TGAAGGAGGTGTTGGTACTGGGTG-3', FAM/BHQ-1) was used to determine the
presence/absence of \emph{S. nitida} within the 22 ditch samples from
Stodmarsh NNR and the 10 ditch samples from outside of the known range
of \emph{S. nitida} .

\emph{Inhibition testing}

All DNA extracts were tested for inhibition by adding 3\selectlanguage{greek}µ\selectlanguage{english}L of extract
into a qPCR for the amplification of an internal positive control (DNA
derived from the plasmid pSD3). PCRs were set up in a total volume of 25
\selectlanguage{greek}µ\selectlanguage{english}L consisting of: 3 \selectlanguage{greek}µ\selectlanguage{english}L of extracted template DNA, 3 \selectlanguage{greek}µ\selectlanguage{english}L of internal
positive control DNA (0.08 ng/\selectlanguage{greek}µ\selectlanguage{english}l),1 \selectlanguage{greek}µ\selectlanguage{english}L of each primer/probe (0.2 \selectlanguage{greek}µ\selectlanguage{english}mol/L
forward primer; 0.4 \selectlanguage{greek}µ\selectlanguage{english}mol/L reverse primer; 0.1 \selectlanguage{greek}µ\selectlanguage{english}mol/L probe;
Supplemental file 2), 12.5 \selectlanguage{greek}µ\selectlanguage{english}L of TaqMan\selectlanguage{ngerman}® Environmental Master Mix 2.0
(containing AmpliTaq GOLD DNA polymerase), and 3.5 \selectlanguage{greek}µ\selectlanguage{english}L ddH2O. PCR cycling
was as above.

\emph{Statistical analysis}

To measure the agreement between the two survey methods, that is, manual
survey and eDNA analysis, Cohen's kappa coefficient (Cohen 1960) was
calculated as follows:

\begin{equation}
k=\frac{\Pr\left(a\right)-Pr(e)}{1-Pr(e)}\nonumber \\
 \end{equation}

where Pr(a) is the relative agreement among rates, and Pr(e) is the
hypothetical probability of chance agreement, using the observed data to
calculate the probabilities of each method randomly giving a positive
detection. If the methods are in complete agreement, then j = 1. If
there is no agreement other than what would be expected by chance, j =
0.

Once PCR analyses had been performed, the program PRESENCE version 13.12
{[}available from http://www.mbr-pwrc.usgs.gov/software/presence.html
(Mackenzie et al. 2002){]} was used for occupancy modelling of the data.
A single-season model was used which assumes that species are never
falsely detected at a site when absent, but that may or may not be
detected when present; the detection of a species at an individual site
is independent of the detection of the species at all other sites; and
the probability of detecting the species across all sites is constant.

\textbf{Results}

\emph{Detection}

The limit of detection (LOD) and limit of quantification (LOQ) of
primer/probe combination 9 were found to be
3x10\textsuperscript{-4}ng/\selectlanguage{greek}µ\selectlanguage{english}L and 3x10\textsuperscript{-5} ng/\selectlanguage{greek}µ\selectlanguage{english}L
respectively. The LOD and LOQ have various definitions in the eDNA
literature, here LOD is defined as the lowest standard concentration at
which 95\% of technical replicates amplify and LOQ is the lowest
standard concentration for which the coefficient of variation (CV; equal
to the standard deviation quantity divided by the mean quantity of a
group of replicates) value is \textless{}35\% (Klymus \emph{et al} .
2019). The LOD corresponded to a Ct value of 37.47 which encompassed
100\% of the Ct values in this study i.e. all positive amplifications
were above the limit of detection. Detection in a water sample was
indicated by at least 1 of 12 positive qPCR replicates (Biggs et al.
2015).

All Stodmarsh NNR ditch water samples and ditch samples from outside the
known range of \emph{S. nitida} were subjected to inhibition testing,
all samples except two from Stodmarsh NNR (136 and 146) did not cause
inhibition of qPCR. Samples 136 and 146 caused complete inhibition of
the qPCR inhibition assay.

All Stodmarsh NNR ditch water samples and ditch samples from outside the
known range of \emph{S. nitida} were then subjected to the optimised
assay for \emph{S. nitida} detection, with seven ditches from Stodmarsh
NNR being positive for \emph{S. nitida} DNA (Table 1). One ditch (ditch
34) with very low positivity (1/12), was re-tested to confirm positivity
(3/12 on repeat). All remaining ditches were negative for \emph{S.
nitida} DNA, therefore other than those ditches where \emph{S.
nitida}was found by manual survey - ditches 62, 70 and 108 (Table 1) -
\emph{S. nitida} is likely to be absent.

\emph{Occupancy Analysis}

Using the observed percentage agreement of the two methods of 0.84 (1 =
100\%) and the probability of random agreement of 0.64, Cohen's kappa
coefficient was calculated as 0.56 for manual survey-positive ponds
versus their qPCR analysis results i.e. moderate agreement.

Site occupancy modelling was used to calculate the occupancy estimate
and the probability of detection of \emph{S. nitida.} Using the combined
manual survey and qPCR assay results the occupancy estimate was
calculated to be 0.35 (95\% CRI 0.19, 0.56) with a probability of
detection of 0.67 (Table 2).

\textbf{Discussion}

This study was carried out to design and evaluate the use of an eDNA
assay for the detection of \emph{S. nitida} in ditches at Stodmarsh NNR
and to compare to manual survey data taken shortly after water samples
were collected. \emph{S. nitida} DNA was detected at 62.5\% (5 of 8) of
the ditches where \emph{S. nitida} presence was detected by manual
survey and in two additional ditches where \emph{S. nitida} was not
detected by manual survey (7 ditches in total). A further 22 ditches
sampled within Stodmarsh NNR and outside the known distribution
of\emph{S. nitida} were negative for \emph{S. nitida.} This resulted in
an observed percentage agreement of 84\% and a kappa coefficient of 0.56
which shows a moderate agreement between the results. When taken
together, manual survey in combination with eDNA analysis has led to
improved \emph{S. nitida} detection rates, that is, 10 of 32 ditches
rather than the 8 reported by field survey. However, it still should be
noted that where eDNA was detected but no \emph{S. nitida} found by
manual survey (ditches 98 and 115) it is unknown whether the animals
were present but not detected by manual survey (present in very low
numbers), or whether they are absent and the eDNA drifted into the ditch
e.g. through hydrological connections. Ditches 98 and 115 are not
directly adjacent to occupied ditches and the direction of flow would
not `normally' facilitate drift between the ditches concerned in normal
flow conditions, but ultimately they are connected nevertheless. Site
occupancy models can be used to account for imperfect detection and were
used by Schmidt et al. (Schmidt et al. 2013) to demonstrate their
applicability to eDNA surveys. When applied to the data within this
study, site occupancy estimates were greater than the actual observed
proportion though not significantly when combining field survey with
eDNA assay. This matches the observed increase in positive detections
from 8/32 to 10/32 ditches when both techniques were combined.

Where rare or threatened species are concerned, it is likely that their
detection by either manual survey or eDNA will be imperfect leading to
an underestimation of its distribution.

During particular time periods or developmental stages, some species can
be difficult to detect potentially biasing survey outcomes (Gotelli and
Colwell 2001; Mackenzie

et al. 2006). This may have been the case here for the two ditches
where\emph{S. nitida} was found by manual survey but not via qPCR of
eDNA. A study in Poland showed that \emph{S. nitida} breed during
April-May (Ksi\selectlanguage{polish}ąż\selectlanguage{english}kiewicz and Goldyn, 2008) and although conditions may be
slightly different in the UK as these ditch water samples were taken
outside the likely breeding season their detection will be more
difficult as there is likely to be less \emph{S. nitida} DNA in the
water. The sampling strategy of taking 20x 30 mL samples along the
length of each ditch should have overcome the fact that eDNA can be
highly localised in space and time (Li et al, 2019). To achieve a higher
level of coverage (especially for longer ditches), more samples may need
to be taken. This could allow for targeting more locations within the
ditches where\emph{S. nitida} would most likely be present, that is,
where the ditch is thickly vegetated, thus improving the probability of
detection.

A further cause of false negative results can be PCR inhibition (Jane et
al. 2015, McKee et al. 2015). Upon testing of the DNA extracts only two
samples, from ditches 136 and 146, were found to cause complete
inhibition of the qPCR inhibition assay. These were not from ditches
that were positive for \emph{S. nitida} on manual survey so are unlikely
to be false negatives. Therefore, it is unlikely that inhibition is the
reason for the qPCR of the samples from ditches 62, 70 and 108 being
negative for \emph{S. nitida} .

It is also likely that the volume of water filtered will play an
important role in the detection of \emph{S. nitida} . The volume of
water filtered was between 200 mL and 500 mL for all samples - the
volume determined by how soon the filter clogged. A larger pore sized
filter eg. 0.45\selectlanguage{greek}µ\selectlanguage{english}M or 0.8\selectlanguage{greek}µ\selectlanguage{english}M may have allowed a larger volume of water to
be filtered which could enable more \emph{S. nitida} eDNA to be
recovered at sites where it was found by manual survey. It is common for
volumes of water between 500 mL and 5L to be filtered although there is
little consensus on the minimum volume (Bruce et al., 2021). Small
volumes (0.25 L) have been shown to contain detectable eDNA from
macroinvertebrate species when a range of volumes up to 2 L were sampled
and analysed (Machler et al., 2016) and increasing the volume of
filtered water has been shown to have a positive effect on eDNA capture
and PCR amplification efficiency (Muha et al., 2019).

Finally, the density of snails in the ditch system will play an
important role in its detectability. The relative abundance of \emph{S.
nitida} was recorded during the manual survey (Supplemental file 1), and
at sites where the eDNA assay was negative for \emph{S. nitida} but it
was found during manual survey, the abundance was recorded as occasional
or rare. Studies on the New Zealand mud snail have shown that this
snail's eDNA can be detected when snails are present at low densities
(Goldberg et al, 2013), this species is similar in size to \emph{S.
nitida} , however, far larger volumes of water (4 L) were filtered
(using multiple filters if necessary) prior to analysis which could
account for its detectability at low density although eDNA transport
would need to be considered as these samples were taken from a river
system.

Since this study was carried out a study (Hobbs et al., 2021)
investigating the population structure of \emph{S. nitida} individuals
from Poland, Germany, Sweden and the UK to identify differences both
within and between populations has been published. The study found that
there are two distinct genetic lineages (also distinct in shape), one in
western Europe (UK, Germany -- Lineage 1) and one in eastern Europe
(Poland, Sweden -- Lineage 2). Although only a UK population was tested
during the present study it likely that the assay designed herein would
also detect \emph{S. nitida} populations in eastern Europe as during the
primer design phase the three \emph{S. nitida} sequences retrieved from
Genbank were from specimens collected in Poland, Denmark and Germany.
Future work could involve testing our primer/probe combination on
individuals from these other populations.

To confirm the results of the eDNA assay designed herein further manual
survey is required to corroborate the two additional eDNA assay positive
ditches found. For those manual survey samples where \emph{S.
nitida}specimens were found but the eDNA assay did not detect \emph{S.
nitida}DNA a larger pore sized filter/filtration of more water may be
required to enable eDNA assay corroboration. This study has shown that
eDNA assays can be used for the detection of \emph{S. nitida} and if
used in the future could have time and cost savings and could inform
manual survey and therefore management of the ditches.

\textbf{List of Abbreviations}

Cytochrome oxidase I (COI), Environmental DNA (eDNA), quantitative
polymerase chain reaction (qPCR), National Nature Reserve (NNR).

\textbf{Ethics approval and consent to participate}

Water samples and snail specimens were collected from several ditches at
Stodmarsh NNR and no institutional animal care and use committee (IACUC)
or animal welfare protocol was required for their collection as
generally invertebrates do not require approval for use (except
cephalopods). No endangered or protected species were collected during
field survey and all land was accessed with the permission of the
landowners facilitated by the Stodmarsh National Nature Reserve Manager.

\textbf{Competing interests}

None

\textbf{Funding}

This project was funded by Natural England

\textbf{Data Accessibility Statement}

All data can be found within the main manuscript or supporting files.

\textbf{Authors contributions}

HR and MC conceived and designed the experiments; CB performed the
experiments; HR and BM analysed the data and prepared the figures; MC
facilitated provision of the samples from the surveyor; HR wrote the
manuscript; all authors reviewed the manuscript.

\textbf{Acknowledgements}

We would like to thank Natural England staff, in particular Ken Obbard
(Area Team Lead Advisor) for collecting the water samples and Stephen
Etherington (Reserve Manager Stodmarsh NNR) for facilitating access; Dan
Bennett of Ecology Co-op for carrying out the invertebrate survey; and
Nick Button (Natural England Field Unit), Dr Martin Willing
(conchologist), Martin Winter and Harry Ferguson (Environment Agency)
for confirming or identifying some of the invertebrate samples.

\textbf{References}

Biggs, J., Ewald, N., Valentini, A., Gaboriaud, C., Dejean, T.,
Griffiths, R. A., Foster, J., Wilkinson, J. W., Arnell, A., Brotherton,
P., Williams, P. \& Dunn, F. (2015). Using eDNA to develop a national
citizen science-based monitoring programme for the great crested newt
(\emph{Triturus cristatus} ). \emph{Biological Conservation,}
183\textbf{,} 19-28.

Bruce, K., Blackman, R.C., Bourlat., Hellstrom, M., Bakker, J.,
\ldots{}..Deiner, K. (2021). A Practical guide to DNA-based methods for
biodiversity assessment. Pensoft, Sofia, Bulgaria.

Clusa, L., Ardura, A., Gower, F., Miralles, L., Tsartsianidou, V.,
Zaiko, A., et al. 2016. An Easy Phylogenetically Informative Method to
Trace the Globally Invasive Potamopyrgus Mud Snail from River's eDNA.
PLoS ONE 11(10): e0162899. doi:10.1371/journal.pone.0162899.

Darling, J.A. (2019). How to learn to stop worrying and love
environmental DNA monitoring. \emph{Aquatic Ecosystem Health \&
Management} 22: 440--451, https://doi.org/10.1080/14634988.2019.1682912

Drake, C.M., Lott, D.A., Alexander, K.N.A., Webb, J. 2007. Surveying
terrestrial and freshwater invertebrates for conservation evaluation,
Natural England Research Report NERR005.

Geller, J., Meyer, C., Parker, M., Hawk, H. (2013). Redesign of PCR
primers for mitochondrial cytochrome c oxidase subunit I for marine
invertebrates and application in all-taxa biotic surveys.\emph{Molecular
Ecology Resources} , 13, 851-861. DOI: 10.1111/1755-0998.12138

Goldberg, C.S., Sepulveda, A., Ray, A., Baumgardt, J., Waits, L.P.
(2013). Environmental DNA as a new method for early detection of New
Zealand mudsnails (\emph{Potamopyrgus antipodarum} ). \emph{Freshwater
Science,} 32: 792-800. DOI: 10.1899/13-046.1

Hobbs, C.S., Vega, R., Rahman, F., Horsburgh, G.J., Dawson, D.A.,
Harvey, C.D. (2021). Population genetics and geometric morphometrics of
the freshwater snail~\emph{Segmentina nitida} ~reveal cryptic sympatric
species of conservation value in Europe. \emph{Conservation Genetics}
,~22,~855--871 (2021). DOI: 10.1007/s10592-021-01369-8

Jane, S.F., Wilcox, T.M., McKelvey, K.S., Young, M.K., Schwartz, M.K.,
Lowe, W.H., Letcher, B.H., Whiteley, A.R. (2015). Distance, flow and PCR
inhibition: eDNA dynamics in two headwater streams. \emph{Molecular
Ecology Resources} 15: 216--227. DOI: 10.1111/1755-0998.12285

Kerney, M. (1999). Atlas of the land and freshwater molluscs of Britain
and Ireland. Harley Books, Clochester, UK. 246 pp.

Ksi\selectlanguage{polish}ąż\selectlanguage{english}kiewicz, Z. and Go\selectlanguage{polish}ł\selectlanguage{english}dyn, B. (2008). Life cycle of Segmentina nitida
(Gastropoda: Pulmonata:Planorbidae) in a small, impermanent kettle hole
pond. \emph{The Functioning and} \emph{Protection of Water Ecosytems} ,
pp. 51--57.

Leray, M., Yang, J.Y., Meyer, C.P., Mills, S.C., Agudelo, N., Ranwez,
V., Boehm, J.T., Machida, R.J. (2013). A new versatile primer set
targeting a short fragment of the mitochondrial COI region for
metabarcoding metazoan diversity: application for characterizing coral
reef fish gut contents. \emph{Frontiers in Zoology} , 10, 34 DOI:
10.1186/1742-9994-10-34

M\selectlanguage{ngerman}ächler, E., Deiner, K., Spahn, F., Altermatt, F. (2016) Fishing in the
Water: Effect of Sampled Water Volume on Environmental DNA-Based
Detection of Macroinvertebrates. \emph{Environmental Science \&
Technology} 50: 305--312. DOI: 10.1021/acs.est.5b04188

McKee, A.M., Spear, S.F., Pierson, T.W. (2015). The effect of dilution
and the use of a post-extraction nucleic acid purification column on the
accuracy, precision, and inhibition of environmental DNA
samples.\emph{Biological Conservation} 183: 70--76. DOI:
10.1016/j.biocon.2014.11.031

Muha, T.P., Robinson, C.V., de Leaniz, C.G., Consuegra, S. (2019). An
optimised eDNA protocol for detecting fish in lentic and lotic
freshwaters using a small water volume. \emph{PloS One} 14: e0219218.
DOI: 10.1371/journal.pone.0219218

Pilliod, D.S., Goldberg, C.S., Arkle, R.S., Waits, L.P. (2013).
Estimating occupancy and abundance of stream amphibians using
environmental DNA from filtered water samples. \emph{CanadianJournal of
Fisheries and Aquatic Sciences} 70: 11231130,
https://doi.org/10.1139/cjfas-2013-0047

Rees, H. C., Maddison, B. C., Middleditch, D. J., Patmore, J. R. M. \&
Gough, K.C. (2014). The detection of aquatic animal species using
environmental DNA -- a review of eDNA as a survey tool in
ecology.\emph{Journal of Applied Ecology, 51} :1450-1459 DOI:
10.1111/1365-2664.12306

Rowson, B., Powell, H., Willing, M., Dobson., M., Shaw, H., 2021.
Freshwater Snails of Britain and Ireland. Telford: FSC Publications.

Seymour, M., Durance, I., Cosby, B.J., Ransom-Jones, E., Deiner, K.,
Ormerod, S.J., Colbourne, J.K., Wilgar, G., Carvalho, G.R., de Bruyn,
M., Edwards, F., Emmett, B.A., Bik, H.M., Creer, S. (2018). Acidity
promotes degradation of multi-species environmental DNA in lotic
mesocosms. \emph{Communications Biology} 1: 4.
https://doi.org/10.1038/s42003-017-0005-3

Shogren, A.J., Tank, J.L., Andruszkiewicz, E., Olds, B., Mahon, A.R.,
Jerde, C.L., Bolster, D. (2017). Controls on eDNA movement in streams:
Transport, Retention, and Resuspension. \emph{Scientific}
\emph{Reports}7: 5065, https://doi.org/10.1038/s41598-017-05223-1

Schmidt, B.R., Kery, M., Ursenbacher, S., Hyman, O.J., Collins, J.P.
(2013). Site occupancy models in the analysis of environmental DNA
presence/absence surveys: a case study of an emerging amphibian
pathogen. \emph{Methods in Ecology and Evolution} , 4: 646-653. DOI:
10.1111/2041-210X.12052

Strickler, K.M., Fremier, A.K., Goldberg, C.S. (2015). Quantifying
effects of UV-B, temperature, and pH on eDNA degradation in aquatic
microcosms. \emph{Biological Conservation} 183: 85--92.
https://doi.org/10.1016/j. biocon.2014.11.038

Watson, A.M., \& Ormerod, S.J. (2003). The distribution of three
uncommon freshwater gastropods in the drainage ditches of British
grazing marshes. \emph{Biological Conservation} , 118: 455-466 DOI:
10.1016/j.biocon.2003.09.021

Wilcox, T.M., Carim, K.J., McKelvy, K.S., Young, M.K., Schwartz, M.K.
(2015). The dual challenges of generality and specificity with
developing environmental DNA markers for species and subspecies of
Oncorhynchus. PLoS ONE. DOI :10.1371/journal.pone.0142008

Zulkefli, N.S., Kim, K-H., Hwang, S-J. (2019). Effects of Microbial
Activity and Environmental Parameters on the Degradation of
Extracellular Environmental DNA from a Eutrophic
Lake.\emph{International journal of Environmental Research and Public
Health}16. https://doi.org/10.3390/ijerph16183339

Table 1. Summary of \emph{S. nitida} survey and PCR status of the 32
ponds studies\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Sample ID & DNA (ng/\selectlanguage{greek}µ\selectlanguage{english}L) & \emph{S. nitida} species-specific qPCR result
& \emph{S. nitida} manual survey\tabularnewline
\midrule
\endhead
1 & \textless{}1 ng/\selectlanguage{greek}µ\selectlanguage{english}L & 0/12; negative & N/A\tabularnewline
2 & \textless{}1 ng/\selectlanguage{greek}µ\selectlanguage{english}L & 0/12; negative & N/A\tabularnewline
3 & \textless{}1 ng/\selectlanguage{greek}µ\selectlanguage{english}L & 0/12; negative & N/A\tabularnewline
4 & \textless{}1 ng/\selectlanguage{greek}µ\selectlanguage{english}L & 0/12; negative & N/A\tabularnewline
5 & \textless{}1 ng/\selectlanguage{greek}µ\selectlanguage{english}L & 0/12; negative & N/A\tabularnewline
D1 & \textless{}1 ng/\selectlanguage{greek}µ\selectlanguage{english}L & 0/12; negative & N/A\tabularnewline
D2 & \textless{}1 ng/\selectlanguage{greek}µ\selectlanguage{english}L & 0/12; negative & N/A\tabularnewline
Top & 1.7 & 0/12; negative & N/A\tabularnewline
LHS & 1.34 & 0/12; negative & N/A\tabularnewline
RHS & \textless{}1 ng/\selectlanguage{greek}µ\selectlanguage{english}L & 0/12; negative & N/A\tabularnewline
34 & 2.14 & 1\textsuperscript{*}/12; positive & positive\tabularnewline
42 & 2.95 & 0/12; negative & negative\tabularnewline
44 & 1.71 & 0/12; negative & negative\tabularnewline
56 & 6.56 & 12/12; positive & positive\tabularnewline
58 & 11.1 & 0/12; negative & negative\tabularnewline
60 & 3.96 & 0/12; negative & negative\tabularnewline
62 & 2.11 & 0/12; negative & positive\tabularnewline
65 & 3.78 & 9/12; positive & positive\tabularnewline
70 & 0.84 & 0/12; negative & positive\tabularnewline
87 & 18.1 & 12/12; positive & positive\tabularnewline
92 & 4.88 & 6/12; positive & positive\tabularnewline
98 & 4.36 & 3/12; positive & negative\tabularnewline
106 & 1.66 & 0/12; negative & negative\tabularnewline
108 & 2.32 & 0/12; negative & positive\tabularnewline
115 & 2.06 & 4/12; positive & negative\tabularnewline
131 & 1.08 & 0/12; negative & negative\tabularnewline
135 & 1.46 & 0/12; negative & negative\tabularnewline
136 & \textless{}1 ng/\selectlanguage{greek}µ\selectlanguage{english}L & 0/12; negative & negative\tabularnewline
146 & \textless{}1 ng/\selectlanguage{greek}µ\selectlanguage{english}L & 0/12; negative & negative\tabularnewline
153 & 1.89 & 0/12; negative & negative\tabularnewline
155 & \textless{}1 ng/\selectlanguage{greek}µ\selectlanguage{english}L & 0/12; negative & negative\tabularnewline
161 & 1.35 & 0/12; negative & negative\tabularnewline
Positive control & 5 ng/\selectlanguage{greek}µ\selectlanguage{english}l & N/A & N/A\tabularnewline
Negative control & n/a & N/A & N/A\tabularnewline
\bottomrule
\end{longtable}

\selectlanguage{greek}\emph{Samples marked as `\textless{}1 ng/µL were samples where the DNA
concentration was too low to measure using the Qubit broad range kit.
Green highlighted samples were found to be positive for S. nitida by
both qPCR and manual survey; orange highlighted surveys were found to be
positive for S. nitida by qPCR but not manual survey; red highlighted
samples were found to be positive for S. nitida by manual survey but not
by qPCR.}\selectlanguage{english}

\emph{*qPCR was repeated for this sample to confirm positivity and 3/12
replicates were found to be positive for S. nitida.}

Table 2. Parameter estimates for a combination of manual survey and qPCR
methods using a single-season model \selectlanguage{greek}Ψ\selectlanguage{english}(-), p(-),that is, assuming
constant occupancy and detection.\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
Model & N & -2 log likelihood & \selectlanguage{greek}Ψ \selectlanguage{english}(95\% CRI) & Est. P (95\% CRI) & SE
(P)\tabularnewline
\midrule
\endhead
Manual survey plus qPCR & 2 & 60.54 & 0.35 (0.19, 0.56) & 0.67 (0.37,
0.87) & 0.14\tabularnewline
\bottomrule
\end{longtable}

Where N = number of parameters, \selectlanguage{greek}Ψ \selectlanguage{english}= occupancy estimate, P = estimated
detection rate. Sample size = 32 sites

\textbf{Hosted file}

\verb`Figure 1.docx`  available at \url{https://authorea.com/users/489525/articles/573215-a-qpcr-assay-for-the-rapid-and-specific-detection-of-shining-ram-s-horn-snail-segmentina-nitida-edna-from-stodmarsh-national-nature-reserve-uk}

\textbf{Hosted file}

\verb`Figure 2.docx`  available at \url{https://authorea.com/users/489525/articles/573215-a-qpcr-assay-for-the-rapid-and-specific-detection-of-shining-ram-s-horn-snail-segmentina-nitida-edna-from-stodmarsh-national-nature-reserve-uk}

\selectlanguage{english}
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