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Ecological Indicators 155 (2023) 111014
Available online 7 October 2023
1470-160X/© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-
nc-nd/4.0/).
qPCR-based eDNA workow for humic-rich lake sediments: Combined use
of sedimentary DNA (sedDNA) and Indigenous Knowledge in reconstructing
historical sh records
Mark Louie D. Lopez
a
, Matthew Bonderud
a
, Michael J. Allison
a
, Findlay MacDermid
b
, Erin
J. Ussery
c
, Mark E. McMaster
c
, Ave Dersch
d
, Kasia J. Staniszewska
e
, Colin A. Cooke
e
,
f
,
Paul Drevnick
f
,
g
, Caren C. Helbing
a
,
*
a
Department of Biochemistry and Microbiology, University of Victoria, Victoria, British Columbia V8P 5C2, Canada
b
Cold Lake First Nations, Cold Lake, Alberta T9M 1P4, Canada
c
Environment and Climate Change Canada, Burlington, Ontario L7S 1A1, Canada
d
Chipewyan Prairie First Nation, General Delivery Chard, Alberta T0P 1G0, Canada
e
Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, Alberta T6G 2E3, Canada
f
Environment and Parks, Government of Alberta, Edmonton, Alberta, T5J 5C6, Canada
g
Department of Biological Sciences, University of Calgary, Calgary, Alberta, T2N 1N4, Canada
ARTICLE INFO
Keywords:
Fish fauna
eDNA assay
environmental DNA
PCR inhibitors
First Nations knowledge
Historical biodiversity reconstruction
ABSTRACT
Lake sediment serves as a natural archive of historical biological information. The use of sedimentary DNA
(sedDNA), a form of environmental DNA (eDNA) shed by aquatic organisms and preserved in sediment, has been
instrumental in reconstructing past faunal composition in aquatic communities. However, the low abundance of
sh sedDNA and the often humic-rich nature of lake sediments create methodological challenges for the accurate
detection of target sedDNA using quantitative polymerase chain reaction (qPCR)-based approaches. Herein, we
present a consolidated qPCR-based eDNA workow to reconstruct past and current sh fauna in Cowpar Lake
located in the Oil Sands region in Alberta (Canada), which were then validated using Indigenous Knowledge from
Chipewyan Prairie First Nation community members. The present study highlights the importance of combining
column- and precipitation-based PCR inhibitor clean-up, nucleic acid concentration, incorporating endogenous
chloroplast DNA as a sample integrity control. Robust qPCR-based eDNA assays were also useful in preventing
the false-negative detection of low copies of target sh DNA. The presence of Northern pike (1905 to 2019) and
Cisco (1919 to 1942) in Cowpar Lake was conrmed based on detected sedDNA from sediment core. The
reconstructed sh records from sedDNA-inferred data aligned with the Indigenous accounts of natural and
human-mediated changes in land use around the lake. Overall, the present study addresses common methodo-
logical concerns in processing lake sediment samples for sh eDNA detection and demonstrates the great po-
tential of combined eDNA-inferred data and Indigenous Knowledge in reconstructing historical sh records in
aquatic communities.
1. Introduction
The use of environmental DNA (eDNA) in sh biomonitoring offers
an efcient method for detecting the presence of target species in
aquatic ecosystems (Boivin-Delisle et al., 2021). In comparison to
traditional ecological survey techniques, this method allows for the
more sensitive, less intrusive, and inexpensive detection of cryptic low-
density species (Boivin-Delisle et al., 2021; Doi et al, 2015; Evans et al.,
2017). Studies have recently investigated the potential of using sedi-
mentary DNA (sedDNA) to detect certain sh species in aquatic systems,
and to infer the response of the sh faunal composition over time to
anthropogenic inuences and climate change using lake sediment core
samples (Nelson-Chorney et al., 2019; Sakata et al., 2020; Sakata et al.,
2022). Comparison between water and sediment samples shows more
abundant sh eDNA in sediments (Turner et al., 2015). Extracellular
DNA adsorbs to suspended particles and precipitates on the benthic
* Corresponding author.
E-mail address: chelbing@uvic.ca (C.C. Helbing).
Contents lists available at ScienceDirect
Ecological Indicators
journal homepage: www.elsevier.com/locate/ecolind
https://doi.org/10.1016/j.ecolind.2023.111014
Received 14 July 2023; Received in revised form 23 September 2023; Accepted 26 September 2023
Ecological Indicators 155 (2023) 111014
2
oor, preventing DNA from deteriorating and allowing for long-term
preservation (Levy-Booth et al., 2007; Pietramellara et al., 2009).
Although there has been a handful of studies that have applied sedDNA
approaches to examine past sh dynamics (Stager et al., 2015; Baldigo
et al., 2017; Buxton et al., 2018; Nelson-Chorney et al., 2019; Kuwae
et al., 2020; Olajos et al., 2018; Sakata et al., 2022), only a few of have
success in using qPCR approach (Nelson-Chorney et al., 2019; Sakata
et al., 2022).
The quantity of DNA shed from the target species, the movement of
DNA from the water column to the sediment, and DNA degradation can
all impact the detection of sh eDNA in sediment samples (Goldberg
et al., 2015; Capo et al., 2021). Mobile meiofauna, such as sh, display
signicant spatial variability and low biomass, in contrast to bacteria
and plankton, which affects the likelihood that DNA from the target
organisms would be acquired in an environmental sample (Huston et al.,
2023). To increase detection rates in lake sediments, extremely sensitive
and robust qPCR-based eDNA assays (such as digital droplet PCR) are
needed due to low abundance of sh DNA in aquatic sediments (Huston
et al., 2023). Moreover, the presence of high organic matter in lake
sediments can lead to low DNA yield and quality due to the presence of
humic substances (Thomson-Liang et al., 2022). Co-precipitation of
humic substances during DNA extraction may cause inhibition of
downstream PCR applications (Sidstedt et al., 2015). As a result, it is
essential to overcome frequent methodological difculties in the
PCR-based eDNA procedure to successfully detect sh sedDNA.
Herein, we demonstrate the potential of combined sedDNA-inferred
data and Indigenous Knowledge in reconstructing historical sh records
in Cowpar Lake located in the Oil Sands region in northeastern Alberta,
Canada (Fig. 1). Fish sedDNA is used to assess the effects of long-term
natural and human-mediated events on sh fauna in the lake. To do
this, we consolidated best practices to provide a more comprehensive
qPCR-based workow for the accurate detection of sh sedDNA. Spe-
cically, robust qPCR-based eDNA assays were designed to detect four
freshwater shes: (1) Lake whitesh [Coregonus clupeaformis, Dene
name: łú]; (2) Northern pike [Esox lucius, Dene name: uldai]; (3) Walleye
[Sander vitreus, Dene name: ¨
ech’úi]; and (4) Cisco [Coregonus artedi,
Dene name: d´
adú¨
e] from a sediment core collected at Cowpar Lake. The
sedDNA-inferred data was then validated using Indigenous Knowledge
from Chipewyan Prairie First Nation (CPFN) community members,
whose long-term relationship with Cowpar Lake continues to this day.
2. Materials and methods
2.1. Sediment core collection and dating
A sediment core (COW21-A) was collected on 27 July 2021 from the
deposition basin, location 55.90680 N, 110.45936 W, water depth 3.8
m, with a Pylonex HTH gravity corer and extruded and sectioned lake-
side with a procedure developed to prevent cross contamination of
samples. Before coring, the corer, 7 cm polycarbonate core tube, and
plastic bung and cap were cleaned with 3 % sodium hypochlorite
(NaClO) solution and rinsed thoroughly with deionized water (DI)
before use. The core recovered was 38 cm in length, with the surface
intact and consisting of organic sediment (gyttja) and kept vertical with
minimal disturbance until processing. Because extruding (pushing up
the sediment) can cause smearing of the core on the core tube, we used a
Fig. 1. Location of the sampling site. The sediment core was collected at the center of Cowpar Lake (water depth of 3.8 m; 55.90, −110.45). The circle in the right
panel indicates the location of Cowpar Lake within the sand and oil region (orange region) in Alberta, Canada. The dot in the left panel indicates the sampling site.
(For interpretation of the references to colour in this gure legend, the reader is referred to the web version of this article.)
M.L.D. Lopez et al.
Ecological Indicators 155 (2023) 111014
3
procedure to prevent cross-contamination of samples, as used by Nelson-
Chorney et al. (2019) and briey described here. First, the Pylonex
extruding device, and all implements used were cleaned with 3 % bleach
solution and rinsed thoroughly with DI water. Then, an interval of
sediment (1 cm intervals for 0–30 cm; 2 cm intervals below 30 cm) was
extruded out of the top of the core tube and a plastic scraper was pushed
under the bottom of the interval. A metal spatula was used to subsample
sediment (on the plastic scraper) that had not touched the core tube and
to place the subsample into a falcon tube designated for the analysis of
sedDNA. The rest of the sample from the interval was put into a separate
container or bag for sediment dating via radiochemical analysis. Be-
tween intervals, the plastic scraper and metal spatula were again
cleaned with 3 % bleach solution and rinsed thoroughly with DI water.
All subsamples were frozen (−20 ◦C) and later shipped to either the
University of Victoria (Uvic, British Columbia, Canada) for eDNA anal-
ysis or Institut National de la Recherche Scientique – Eau Terre Envi-
ronnement Research Centre (INRS-ETE, Quebec, Canada) for
radiochemical analysis.
For estimating ages and sedimentation rates for the core, subsamples
were freeze-dried, homogenized, and analyzed for Pb-210, Ra-226, and
Cs-137 with a high-purity germanium coaxial well detector at INRS-ETE.
Data for Pb-210 and Ra-226 were used to model age and sedimentation
rates, according to the constant rate of supply (CRS) model (Appleby and
Oldeld 1978). Data for Cs-137, an articial radionuclide introduced to
the environment with nuclear weapons testing that began in 1952 and
peaked in 1963, was used as a chronostratigraphic marker to validate
dates from the CRS model.
2.2. SedDNA extraction and viability testing
Each sediment core section was assigned to a randomized DNA
processing number (DPN). Sediment samples were centrifuged at 3,220
×g at 4 ◦C for 30 min before DNA extraction to remove excess water.
Using the soil DNA Isolation Maxi Kit (Cat. 62000; Norgen Biotek,
Ontario, Canada), sedDNA was extracted from 2 g of wet weight sedi-
ment. A nal elution volume of 3 mL was collected. The eluted sedDNA
was then concentrated and puried using the modied ethanol precip-
itation protocol. The DNA pellets were resuspended in 300 µL of TE
buffer (10 mM Tris, 1 mM EDTA, pH 8.0). The IntegritE-DNA
TM
assay
targeting endogenous chloroplast DNA was used to assess the presence
of any residual PCR inhibitory compounds and ascertain the viability of
the extracted sedDNA samples (Veldhoen et al., 2016). Successful
amplication of endogenous plant chloroplast DNA contained within
the sedDNA samples conrms that the recovered DNA is viable and
sufcient inhibitory compounds have been removed. Two µL of sedDNA
samples in four technical replicates were analyzed, with eight technical
replicates receiving ultrapure distilled water acting as non-template
controls, and two technical replicates receiving synthetic plant DNA
(250 copies/µL; gBlocks
TM
, Integrated DNA Technologies [IDT], Iowa,
USA) to act as the positive control. The TaqMan thermocycler prole
was as follows: initial denaturation of 9 min at 95 ◦C followed by 50
cycles of 15 s at 95 ◦C, 30 s at 64 ◦C, and 30 s at 72 ◦C. The samples were
considered to pass the IntegritE-DNA
TM
assay if the recorded C
t
value is
signicantly lower (~30 cycles) than the negative control (~33 cycles).
The OneStep PCR Inhibitor Removal Kit (D6030; Zymo Research, Cali-
fornia, USA) was used for another round of PCR inhibitor removal for
samples that failed DNA viability testing. The cleaned-up DNA was
stored at −20 ◦C until needed for qPCR analysis.
2.3. eDNA assay design and validation
A total of ve sh eDNA qPCR-based assays were used in the present
study: eFISH1 (general sh DNA, Klymus et al., 2019), eESLU1
(E. lucius), eSAVI2 (S. vitreus), eCOCL1 (C. clupeaformis), and eCOAR7
(C. artedi). All assays were designed and validated according to the
suggested workow by Langlois et al. (2021). The mitochondrial
genome for target species as well as any closely related and co-occurring
sh species were obtained from Genbank. The mitogenomes were then
aligned with MAFFT (v7.490, Katoh et al., 2002) and the aligned se-
quences were used for constructing a phylogenetic tree using RAXml
(Stamatakis, 2014). Mitogenomes of target species were run through the
Unikseq pipeline (Allison et al., 2023) to identify regions of the mito-
genome unique to the target species exclusively. The identied unique
region was then used for primer and probe design with Beacon
Designer
TM
8.21 (PREMIER Biosoft, California, USA). Primer and probe
sequences for each eDNA assay used in the present study are listed in
Table 1. For in vitro specicity validation, SYBR green qPCR (QIAcuity
EG PCR Kit [250111, Qiagen, Hilden, Germany]) validation was run
using several primer pairs together with target and sympatric species’
genomic DNA (gDNA) as a template. The used thermocycler prole is as
follows: initial denaturation of 2 min at 95 ◦C followed by 50 cycles of
15 s at 95 ◦C, 30 s at 64 ◦C, and 45 s at 72 ◦C, followed by a melt curve in
0.5 ◦C increments from 65 to 95 ◦C. The resulting amplicon was then run
using gel electrophoresis for amplicon size validation. Afterward, high-
end specicity validation with primer and probe was done through
TaqMan qPCR (QIAcuity Probe PCR Kit [250101, Qiagen, Hilden, Ger-
many]) using species of interest gDNA as a template having 25 technical
replicates per sample. To characterize assay sensitivity, serial dilutions
of synthetic DNA amplicon (gBlocks®, IDT) were prepared to construct a
standard curve.
Based on the constructed standard curve, eLowQuant was used to
calculate the limit of detection (LOD) and limit of quantication (LOQ)
based on a modied Binomial-Poisson distribution model (Lesperance
et al., 2021). These measurements generally describe the smallest con-
centration of DNA that can be reliably measured by eDNA assays with
reasonable statistical certainty. The LOD from continuous data (LOD-
continuous
) was also determined as the lowest copy number where there is
a ≥95 % detection (Klymus et al., 2019). This LOD
continuous
indicates the
breakpoint for continuous and discontinuous data dening the compu-
tational approaches for determining sample copy number. Lastly, the
PCR assay efciency, measuring the ability of the designed primers and
probe to amplify the target DNA region for every PCR cycle, was
computed for each designed eDNA assay using the equation shown in
Supplemental Table S1.
2.4. SedDNA analyses
Following the IntegritE-DNA
TM
assay, the eDNA samples were run
through the general sh detection assay (eFISH1) to establish a back-
ground sh presence for each sediment core section. Following the
conrmation of the presence of sh eDNA in the sediment layers, several
species were identied based on CPFN Indigenous Knowledge for
further eDNA analysis. Two species of interest, Cisco (eCOAR7) and Lake
whitesh (eCOCL1) were tested as targets, while Northern pike
(eESLU1) and Walleye (eSAVI2) were selected as eld positive and
negative controls, respectively. Each sediment layer sample was
analyzed using 16 technical replicates per assay to improve the detec-
tion probability of target eDNA (Matthias et al., 2021). Eight replicates
received UltraPure-dH
2
O (Invitrogen, Massachusetts, USA) acting as a
non-template control (NTC), and two replicates received 20 copies/re-
action of synthetic target DNA fragment of the appropriate DNA
sequence (gBlocks
TM
, IDT Supplemental Table S1) to act as a positive
control for each assay on every 96-well qPCR plate. Each qPCR reaction
consisted of two µL of puried sediment eDNA, 700 nM forward and
reverse primers, 100 nM TaqMan probe, and 1X of QIAcuity Probe
Master Mix (QIAcuity Probe PCR Kit, QIAGEN) for a nal reaction vol-
ume of 15 µL. The following TaqMan thermocycler prole was used for
all assays: initial denaturation of 9 min at 95 ◦C followed by 50 cycles of
15 s at 95 ◦C, 30 s at 64 ◦C, and 30 s at 72 ◦C. The eDNA concentration
(copies/g) of amplied samples was extrapolated from C
t
values using
the previously generated standard curves. Any calculated eDNA con-
centrations higher than the LOD and LOQ values of the respective eDNA
M.L.D. Lopez et al.
Ecological Indicators 155 (2023) 111014
4
assay (Klymus et al., 2019; Lesperance et al., 2021) were selected for
Sanger sequencing to verify amplicon sequence was that of the desired
target species.
2.5. Gathering Indigenous Knowledge from CPFN
Gathering of Indigenous Knowledge from elders and knowledge
holders was independently conducted by Dr. Ave Dersch as CPFN’s
principal archaeologist. Historical accounts of sh species present in
Cowpar Lake along with observations of environmental events affecting
the lake were collected through personal communications and small
group discussions. The list of noted sh species from the past was
consolidated with the generational ecosystem changes noted by CPFN
community. All discussions and information were gathered before the
genetic analysis of sediment core samples. All Indigenous narratives and
sedDNA-inferred diversity data were consolidated to reconstruct past
and current sh fauna in Cowpar Lake.
2.6. Sediment chemistry
To aid in interpretation of factors affecting sh presence/absence,
subsamples of sediment were subject to geochemical analyses. One
subsample from each interval was digested and analyzed for elements at
Institut national de la recherche scientique (INRS, Quebec, Canada).
Samples were subject to a total digestion of ultra-trace metal grade ni-
tric, perchloric, and hydrouoric acids (Optima™, Fisher Chemical™,
Washington, USA). Major and minor elements were analyzed by ICP-
OES with a Varian Agilent Dual View (Agilent Scientic Instruments,
USA), per US EPA Method 200.7 (US EPA 1994a). Minor and trace el-
ements were analyzed by ICP-MS with a Thermo iCAP (Thermo Scien-
tic, USA), per US EPA Method 200.8 (US EPA 1994b). Certied
reference materials were also analyzed for major, minor, and trace el-
ements, in triplicate, with percent recovery averaging 94 % and 99 % for
LKSD-2 (NRCAN) and Buffalo River sediment 8704 (NIST), respectively,
among elements. Another subsample from each interval was analyzed
for total Hg and organic matter (OM) content using loss on ignition (LOI)
at the University of Alberta. Both total Hg and LOI were analyzed with a
Milestone DMA-80 (Milestone Srl, Italy) per US EPA Method 7473 and
Chen et al. (2015), respectively. MESS-4 (NRCAN) was analyzed in
triplicate, with all results within the certied range for total Hg. LOI is a
direct measure of organic matter and an indirect measure of inorganic
matter, with the equation: inorganic matter (%) =100 % – LOI (%).
3. Results
3.1. Assay sensitivity
Details on the sensitivity characterization of all eDNA assays
designed in the present study are presented in Table 2. The R
2
values of
the standard curve calibration for all assays were >0.98. The calculated
PCR assay efciency values for all assays are above 85 % (86 – 99 %). For
limit of detection (LOD) and limit of quantitation (LOQ; n =16, Sup-
plemental Table S1), the calculated values for all assays range from 0.3
to 3.0 and 0.7 – 3.0 DNA copies/reaction, respectively. The LOD and
LOQ measurements describe the smallest concentration of DNA that can
be reliably detected and measured, respectively, by each eDNA assay
with reasonable statistical certainty, thus increasing the condence in
the reported results from downstream eDNA analyses. Moreover, the
designed assays have highly comparable sensitivity with other published
sh eDNA assays with reported LOD and LOQ based on discontinuous
data (Fig. 2).
3.2. DNA viability testing and sh sedDNA detection
To address the requirement for a false negative control in the eDNA
workow, we tested the presence of ampliable internal chloroplast
DNA in all extracted sedDNA samples using the IntegritE-DNA
TM
assay.
Earlier detection of the target gene (C
t
<30) was noted in all samples
other than the no template control containing UltraPure water (C
t
>33).
Moreover, the calculated values for DNA copies per sample for all rep-
licates are above the set C
t
threshold for IntegritE-DNA
TM
assay (Fig. 3;
LOD and LOQ not shown). These observations indicate that the recov-
ered total DNA is of sufcient quality to evaluate further in the eDNA
workow and can then be run in species-specic qPCR reactions.
Table 1
Summary of primer and probe sequences for qPCR-based environmental DNA assay developed in this study.
Assay Target species Common name/
Indigenous name
Sequence
type
Sequence 5
′
→ 3
′
Target
gene
Amplicon
size
Source
IntegritE-
DNA
TM
Plant DNA General plant Forward TCTAGGGATAACAGGCTGAT cl-23S 130 Veldhoen et al.,
2016
Reverse TGAACCCAGCTCACGTAC
Probe FAM-TTTGGCACCTCGATGTCGG-ZEN/IB
eFISH1 Fish DNA General sh Forward CACCTAGAGGAGCCTGTTCTA mt-rnr1 153 Klymus et. al.,
2019
Reverse CTACACCTCGACCTGACGTT
Probe FAM-TATATACCRCCGTCGTCAGCTTACCC-ZEN/
IB
eCOCL1 Coregonus
clupeaformis
Lake whitesh/łú Forward CATCATTCCTCTCATAGCA mt-nd2 162 The present
study
Reverse ATTGGGTGGGTTAATTGT
Probe FAM-CCATTCTCCAACCAGTCAAGCATTAGT-
ZEN/IB
eESLU1 Esox Lucius Northern pike/uldai Forward TCTCCACAGCCTTCTCATC mt-cytb 325 The present
study
Reverse CCGCCTCAGATTCATTGG
Probe FAM-CTCCTCCTAACAATAATAACCGCCTTCGT-
ZEN/IB
eSAVI2 Sander vitreus Walleye/¨
ech’úi Forward CTCGGGATCTTGTTTCTA mt-nd1 331 The present
study
Reverse CTGATACTAATTCGGATTCG
Probe FAM-CCTATCAAGCCTAGCAGTCTACTCTATTCT-
ZEN/IB
eCOAR7 Coregonus artedi Cisco/d´
adú¨
e Forward CACCACAAATAGCGTTAG mt-nd5 78 The present
study
Reverse GTAGCCCTAATATACTCTTCA
Probe FAM-CACACACCACCAACAGTCCC-ZEN/IB
M.L.D. Lopez et al.
Ecological Indicators 155 (2023) 111014
5
3.3. Detection of sh sedDNA from sediment core
The results of all sh eDNA analyses performed on the sedDNA
extracted from Cowpar Lake sediment core are summarized in Fig. 3.
The DNA copy estimates presented in the results are all based on
dewatered wet weight (weight after centrifuging) sediment sample. Fish
sedDNA was detected in 16 sections of the sediment core that were dated
from 1905 ±8.1 to 2019 ±1.0, where detection frequency varies for
each section (n =16). The DNA concentrations from sediment layers
with detected non-specic sh, ranging from 6.67 to 29.73 copies/g of
wet weight sediment sample, are all within eFISH1 LOD (±95 % CI)
range. For the eld positive control, Northern pike, positive detections
were noted in 10 sections of the sediment core spanning from oldest to
most recent samples. The estimated DNA concentrations for the wet
weight sediment sample range from 4.98 to 28.95 copies/g and do not
signicantly differ from the eESLU1 LOD (±95 % CI) value. Walleye
which serves as the negative eld control was not detected in any section
of the sediment core with eSAVI2 assay. In terms of the Whitesh spe-
cies, only Cisco was detected in six sections of the sediment dated from
1919 to 1943. The DNA concentrations range from 4.12 to 967.60
copies/g of sediment sample, where one section (from 1919 sediment
section) had value lower than the eCOAR7 LOD and LOQ (±95 % CI).
Positive controls containing 20 copies gBlocks®/reaction appropriate
for each eDNA assay showed expected amplication of the target
amplicon, whereas NTCs resulted in no amplication on every plate.
Table 2
Summary of sensitivity parameters of the sh eDNA assays used in the present study. The values presented for the limits of detection (LOD) and quantication (LOQ)
were computed based on n =16 technical replicates.
Assay Target
species
Binomial data Continuous data Source
LOD
(c/
rxn)
LOD
95 %
CI
Lower
LOD
95 %
CI
Upper
LOQ
(c/
rxn)
LOQ
95 %
CI
Lower
LOQ
95 %
CI
Upper
LOQ
continuous
(c/rxn)
Slope %
Efciency
Y-
Intercept
R
2
value
eFISH1 General sh 3.0 1.8 6.1 4.7 3 9.5 20 −3.52 92 37.39 0.98 Klymus
et al.,
2019
eCOCL1 Coregonus
clupeaformis
0.8 0.6 1.3 3.0 2.2 4.8 20 −3.35 98 35.99 0.99 The
present
study
eCOAR7 Coregonus
artedi
0.6 0.5 1.1 2.4 1.7 4.0 20 −3.45 95 36.24 0.99 The
present
study
eESLU1 Esox lucius 0.4 0.2 0.7 1.3 0.9 2.6 20 −3.35 99 −3.35 0.99 The
present
study
eSAVI2 Sander
vitreus
0.3 0.2 0.5 1.0 0.7 1.8 4 −3.70 86 38.53 0.99 The
present
study
c/rxn, copies/reaction; CI, Condence interval; LOD, Limit of detection; LOQ, Limit of quantication.
Fig. 2. Calculated limit of detection (LOD) and limit of quantication (LOQ) for the developed assays in the present study (Coregonus artedi, eCOAR7; Sander
vitreus, eSAVI2; C. clupeaformis, eCOCL1; Esox lucius, eESLU1) based on a modied Binomial-Poisson model (Lesperance et al., 2021) for n =16 technical replicates.
Published sh eDNA assays: Klymus et al., 2019 (general freshwater sh, eFISH1; Oncorhynchus kisutch, eONKI4); Brys et al., 2021 (Misgurnus fossilis, eMIFO);
Sakata et al., 2022 (Plecoglossus altivelis, ePLAL, and Gymnogobius isaza, eGYIS); Salter et al., 2019 (Gadus morhua, eGAMO); and Fu’adil Amin et al., 2021
(Oncorhynchus keta, eONKE; Oncorhynchus masou, eONMA; Oncorhynchus mykiss, eONMY). Note: Values for eGAMO, eONKE, eONMA, and eONMY were based on
the continuous linear model.
M.L.D. Lopez et al.
Ecological Indicators 155 (2023) 111014
6
3.4. Chronology of Cowpar lake sediment core
The observed stratigraphic proles of Pb-210 and Ra-226 met the
assumptions of the CRS model, yielding reliable estimates for dates and
sedimentation rates that are validated by Indigenous Knowledge and Cs-
137 data (Supplementary Fig. S7). Total Pb-210 declines with depth,
although not simply exponential, indicating there are changes in sedi-
mentation rate in the historical record. Activities of total Pb-210 and Ra-
226 are equivalent below 24 cm depth, and the CRS model assigned the
dating horizon (24 cm) a date of 1905.6 CE (Fig. 4). Linear sedimenta-
tion rates and mass accumulation rates are relatively constant for
approximately three decades until a large sedimentation event occurred
in the early 1940 s, recorded in the core at depths 17–19 cm. Following
this event, sedimentation stabilized to previous (baseline) rates. Post
c.1990 CE, linear sedimentation rates and mass accumulation rates are
again above baseline and increasing, though not as a short-term event
but more as a multi-decadal change to a different (steady or unsteady)
state. For further validation of the model estimates, the Cs-137 prole
shows a marked increase in activity at 13 – 14 cm depth, dated to 1964.9
CE. Diffusion of Cs-137 (i.e., upward and downward movement) in the
sediment column is apparent, however, that is common in lake sedi-
ments (e.g., Wang et al. 2017).
Fig. 3. eDNA concentration (copies/g [wet weight]) and detection frequency (n =16) for each gram of sediment sample. Dashed lines show the limits of detection
(LOD: gray line) and quantication (LOQ: red line) for each assay. Shading around the respective dashed and dotted lines indicate the 95 % CI. Not shown in the
gure due to axis scale: eFish1 LOQ: 176.25 (95 % CI Lower limit 112.5, Upper limit 356.25); and eCOCL1 LOQ: 112.50 (95 % CI Lower limit 82.5, Upper limit
180.0). (For interpretation of the references to colour in this gure legend, the reader is referred to the web version of this article.)
M.L.D. Lopez et al.
Ecological Indicators 155 (2023) 111014
7
Fig. 4. Detect/no detect data for detected sh DNA across sections of Lake Cowpar sediment core and documented historical land use in Athabasca Oil Sands region.
Fig. 5. Sediment chemistry. (a) LOI peak records organic matter pulse from landslide; sulfur (S) peak records metabolism of organic matter pulse. (b) Increasing
sediment concentrations (and uxes) of organic matter and the alkaline earth metals Ca, Sr, Ba suggest recent increase in algal production, as documented by
Indigenous Knowledge. (c) Dilution of inorganic matter and lithogenic elements (Al and Ti shown) are a result of increases in within-lake production.
M.L.D. Lopez et al.
Ecological Indicators 155 (2023) 111014
8
3.5. Braiding sedDNA-inferred data and Indigenous Knowledge in
reconstructing historical sh faunal composition
Personal communications with CPFN elders and Indigenous Knowl-
edge holders described a hill completely collapsing into the east side of
the lake in the 1940 s after which time whitesh disappeared. This ac-
count of the landslide, which would have resulted in a ux of soil and
parent material into Cowpar Lake, corresponds with a spike in the
sedimentation rate observed c. 1941 (Fig. 4). This event is also recorded
in the sediment prole via peaks in organic matter (as LOI) and sulfur, a
redox sensitive element (Fig. 5a). Microbial respiration of organic
matter – and thus the consumption of oxygen – may have made Cowpar
Lake an unfavorable habitat for whitesh, a species intolerant of dis-
solved oxygen concentrations less than 6.5 mg/L (Taylor and Barton
1992).
After the landslide/sedimentation event, climate warming may
contribute to conditions that continue to be unfavorable for whitesh.
Moreover, CPFN elders and Indigenous Knowledge holders reported
Cowpar Lake as having more algae in recent years than in the past,
including nuisance blooms. Sediment chemistry has fundamentally
shifted, with increases in organic matter (as LOI) and the alkaline earth
metals Ca, Sr, Ba (Fig. 5b). Warmer temperatures are increasing primary
production in lakes regionally (Summers et al. 2016), and photosyn-
thesis can increase sediment uxes of organic matter, and Ca, Sr, and Ba
through association with organic matter (uptake or adsorption) and/or
pH-dependent mineral precipitation (McGrath et al. 1989, Stabel 1989).
In Cowpar Lake, summer water temperatures can exceed both the
chronic (20 ◦C) and acute (23 ◦C) thermal criteria for whitesh (Taylor
and Barton 1992), and during winter ice cover dissolved oxygen con-
centrations approach 6.5 mg/L. These conditions may preclude re-
establishment of a whitesh population in the lake if it were possible
through migration.
Land use changes, including forestry and in situ oil sands develop-
ment beginning in the 1990s and 2000s, respectively, do not have a
clear, direct impact on Cowpar Lake geochemistry. The recent increases
in linear sedimentation rates and mass accumulation rates appear (see
above) to be driven by greater primary production within the lake, and
the increased organic ux to sediments is diluting inputs of inorganic
matter and lithogenic elements from the watershed (Fig. 5c). The lake’s
shoreline is undeveloped, possibly buffering impacts from disturbance
occurring more distant (~30 km away) from the lake. Metals subject to
regional and global atmospheric transport and deposition, e.g., Pb and
Hg, show recent increases in sediment as expected (Cooke et al. 2017),
but concentrations of these metals in sh are not at levels that would
cause overt toxicity (and affect presence/absence).
4. Discussion
SedDNA has proven useful in reconstructing native sh records and
detecting non-native sh invasion in aquatic systems (Nelson-Chorney
et al., 2019). Recently, sedDNA was also found to reect uctuations in
sh abundance caused by changes in ecological conditions (Kuwae et al.,
2020; Sakata et al., 2022). However, detection of sh sedDNA using
qPCR-based methods remains highly variable due to ecological and
methodological uncertainties. Herein, we aimed to reconstruct historical
sh records of Cowpar Lake, located within the Alberta Oil Sands region,
using a comprehensive qPCR-based eDNA workow for the analysis of
humic-rich lake sediments.
The proper preservation of sh DNA in the sediment is crucial for the
successful detection of sh sedDNA. Fish eDNA is transported from the
water column to sediments inside carcasses or by binding to particulate
organic matter (Turner et al., 2015). Fish eDNA preservation following
deposition into sediments is signicantly inuenced by the physical and
geochemical composition of aquatic sediments as well as DNA form
(intra- or extracellular) (Huston et al., 2023). Most sh biomass is made
up of unprotected cells, making it more susceptible to degradation than
other taxa with resistant structural components (such as resting stages
(e.g., seeds or ephippia) or lignin for terrestrial plants). Accordingly,
sedDNA is impacted by the mineralogic composition, pore-water pH,
and the valence and concentrations of cations in the sediments (Torti
et al., 2015; Kanbar et al., 2020). SedDNA preservation is further
inuenced by the adsorption and desorption of DNA to mineral particles.
The relative ratio of sh DNA to all other macrobial taxa is largely un-
known and is expected to differ between ecosystems. What is known is
that the majority of the sedDNA pool in both surface and deep sediment
layers is comprised of bacterial and archaeal DNA. This is because of
their relatively high densities in the water column and sediments (Capo
et al., 2022). To successfully detect sh sedDNA, a thorough work-
ow using highly sensitive detection tools is required.
Based on our experience in processing Cowpar Lake sediment sam-
ples, we constructed an optimized qPCR-based workow summarized in
Fig. 6 for detecting sh sedDNA in humic-rich sediment samples. First,
randomized processing numbers should be designated to each sediment
core section to eliminate inherent biases in the succeeding downstream
analyses. In the present study, we used 2 g of dewatered wet weight
sediment samples (weight after centrifugation) for DNA extraction (due
to limited availability) that was eluted with 3 mL buffer. Depending on
sample availability, this can be adjusted up to 10 g of input material as
recommended by most commercial soil DNA extraction kits (Thomson-
Liang et al., 2022). The extracted sedDNA can then be further concen-
trated and puried through ethanol precipitation to increase the total
amount of sedDNA in the sample volume that will be used for each qPCR
reaction. For complete removal of co-precipitated humic substances,
two independent column-based clean-up steps are included in this
workow: (1) built-in Norgen soil DNA extraction kit humic acid
removal columns treated with organic substance removal (OSR) solu-
tion; and (2) Zymo Research OneStep PCR inhibitor removal spin col-
umn. The complete removal of organic contents helps avoid reporting
false negative detection due to failed amplication of the target gene
caused by co-precipitated PCR inhibitors (Thomson-Liang et al., 2022).
A step for DNA viability testing using IntegritE-DNA
TM
assay is also
added to detect PCR ampliable endogenous plant chloroplast DNA in
the sedDNA samples. This assay detects the chloroplast 23S ribosomal
RNA that is ubiquitously present in almost all types of environmental
samples (Veldhoen et al., 2016). DNA viability testing allows the iden-
tication of non-viable DNA that excludes the potential inclusion of false
negative observations in an eDNA eld survey. For sh sedDNA detec-
tion, eFISH1 assay that targets a conserved region in sh mitochondrial
12S ribosomal RNA (Table 1, mt-rnr1) can be used in screening the
presence of non-species-specic sh DNA. Samples containing general
sh DNA can then be processed for species-targeted assays to identify
sh species present. Compared to more abundant taxa (microbes and
plankton), captured sh DNA from sediment samples is expected to be in
trace amounts (Capo et al., 2021). With this, an increased number of
technical replicates (n =16) for each qPCR analysis per sample is rec-
ommended to improve the detection of the target species (Veldhoen
et al., 2016; Matthias et al., 2021; Lesperance et al., 2021). In reporting
the presence of sh species DNA, only those sediment sections with DNA
concentration (copies/g sediment) values within and above the eDNA
assays’ LOD and LOQ ((±95 % CI) range will be reported for positive
detection (Lesperance et al., 2021). The use of standardized LOD and
LOQ allows enhanced reproducibility of eDNA qPCR assay results
(Klymus et al., 2019). This echoes the need for a well-established
workow to develop robust qPCR-based eDNA assays (Langlois et al.,
2021). Last, the resulting amplicon from qPCR runs were sent for Sanger
sequencing, if possible, to validate the amplication of the target gene
region. Overall, this comprehensive workow addresses common
methodological uncertainties regarding the accurate detection of sh
sedDNA from humic-rich sediment samples in aquatic systems, thus
increasing the condence in reported eDNA results.
Moreover, the present study highlights the potential use of sedDNA
and Indigenous Knowledge in reconstructing sh records in aquatic
M.L.D. Lopez et al.
Ecological Indicators 155 (2023) 111014
9
ecosystems. The noted changes in land use around the region according
to CPFN Indigenous Knowledge holder are aligned with the modeled
shifts in sedimentation rates (Fig. 4). Lake sedimentation processes are
often linked to natural and/or human-mediated events that increase
sediment input from terrestrial zones around the lake (Jenny et al.,
2019). The highest sediment inux was noted in a sediment section
dating back to 1941 ±4.3 years, the same time (~1940 s) that CPFN
Indigenous Knowledge holders described a hill collapsing into the east
side of the lake. With the use of sedDNA from lake sediment cores, we
demonstrated that previous sh fauna can be reconstructed and aligned
to historical and/or human-mediated shifts in land use. Detection of one
Coregonus species, Cisco (d´
adú¨
e), followed by their disappearance
around the 1940 s based on sedDNA data aligned with CPFN Indigenous
knowledge of Whitesh in Cowpar lake. According to McKenna et al.
(2020), both species have overlapping habitat niches and could inhabit
the same lake. If there was a period when both Cisco and Lake whitesh
were present in the lake, mitochondrial recombination could happen
due to hybridization of this closely related species (Tsaousis et al.,
Fig. 6. Overall eDNA workow for processing sediment samples from Cowpar Lake for the detection of sh sedDNA.
M.L.D. Lopez et al.
Ecological Indicators 155 (2023) 111014
10
2005). This could have resulted in the cisco DNA detected in our core
having a lake whitesh phenotype. Thus, examination of additional
cores is needed to conrm the actual identity of the Whitesh species
observed in the lake.
The present study showcases the benet of integrating Indigenous
Knowledge with western scientic approaches to improve system-
understanding that can guide sheries resource governance (Reid
et al., 2020). Enhanced knowledge of changes to lake sh fauna im-
proves understanding of how these sh populations respond to their
dynamic natural habitat as well as human anthropogenic impacts. This
provides critical information for lake managers in developing conser-
vation policies that could directly benet wildlife and the Indigenous
Peoples governing the area.
5. Conclusion
The use of sedDNA can help determine past sh records, and aid in
the understanding of how these sh populations respond to natural and
human-mediated land use changes. Indigenous Knowledge is an
invaluable historical record of natural events and anthropogenic activ-
ities around aquatic systems. Combined sedDNA data and Indigenous
Knowledge can be a powerful tool in reconstructing historical sh re-
cords in aquatic communities. The current study presents a compre-
hensive qPCR-based eDNA workow, which utilizes column- and
precipitation-based PCR inhibitor clean-up, nucleic acid concentration,
sample integrity control, and robust qPCR-based eDNA assays to address
methodological and ecological uncertainties. This workow increases
condence in reported sh eDNA detection from humic-rich aquatic
sediment samples. As further advancements in sampling design,
extraction and purication, detection method, and reporting of results
emerge, the repeatability and condence of sh sedDNA-inferred bio-
logical data will be strengthened to support historical biodiversity
reconstructions.
CRediT authorship contribution statement
Mark Louie D. Lopez: Data curation, Formal analysis, Investigation,
Methodology, Validation, Visualization, Writing – original draft,
Writing – review & editing. Matthew Bonderud: Methodology, Writing
– original draft. Michael J. Allison: Methodology, Writing – review &
editing. Findlay MacDermid: Conceptualization, Investigation, Meth-
odology, Writing – review & editing. Erin J. Ussery: Conceptualization,
Investigation, Methodology, Writing – review & editing. Mark E.
McMaster: Conceptualization, Formal analysis, Funding acquisition,
Investigation, Methodology, Project administration, Supervision, Vali-
dation, Writing – review & editing. Ave Dersch: Conceptualization,
Formal analysis, Funding acquisition, Investigation, Methodology,
Project administration, Supervision, Validation, Writing – review &
editing. Kasia J. Staniszewska: Investigation, Visualization, Writing –
review & editing. Colin A. Cooke: Investigation, Formal analysis,
Visualization, Writing – review & editing. Paul Drevnick: Conceptual-
ization, Formal analysis, Funding acquisition, Investigation, Methodol-
ogy, Project administration, Supervision, Validation, Writing – original
draft, Writing – review & editing. Caren C. Helbing: Conceptualization,
Formal analysis, Funding acquisition, Investigation, Methodology,
Project administration, Supervision, Validation, Writing – original draft,
Writing – review & editing.
Declaration of Competing Interest
The authors declare the following nancial interests/personal re-
lationships which may be considered as potential competing interests:
[Caren Helbing reports nancial support was provided by Oil Sands
Monitoring program. Mark Louie D. Lopez reports nancial support was
provided by Liber Ero. Caren Helbing reports nancial support was
provided by Genome Canada. Caren Helbing reports nancial support
was provided by Genome British Columbia. Caren Helbing reports
nancial support was provided by G´
enome Qu´
ebec.
Data availability
Data will be made available on request.
Acknowledgments
This work was funded under the Oil Sands Monitoring program
workplan (W-LTM-S-5-2122: Indigenous Community-based Monitoring
Projects Integrated with Core Aquatic Ecosystem Health Monitoring) but
does not necessarily reect the position of the Program or its partici-
pants. MLDL is supported by a Liber Ero postdoctoral fellowship and
Genome Canada, Genome British Columbia, and Genome Qu´
ebec large-
scale applied research project #312ITD awarded to CCH. The funders
had no role in study design; in the collection, analysis, and interpreta-
tion of data; in the writing of the report; and in the decision to submit the
article for publication.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.ecolind.2023.111014.
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