Publikasjoner
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Davey, Marie Louise; Kamenova, Stefaniya; Fossøy, Frode; Solberg, Erling Johan; Davidson, Rebecca K. & Mysterud, Atle
[Vis alle 7 forfattere av denne artikkelen]
(2023).
Faecal metabarcoding provides improved detection and taxonomic resolution for non-invasive monitoring of gastrointestinal nematode parasites in wild moose populations.
Parasites & Vectors.
ISSN 1756-3305.
16(1).
doi:
10.1186/s13071-022-05644-6.
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Background Although wild ungulate populations are heavily monitored throughout Europe, we understand little
of how parasites afect population dynamics, and there is no systematic, long-term monitoring of parasite diversity
and parasite loads. Such monitoring is in part hampered by a lack of time- and cost-efective assay methodologies
with high sensitivity and good taxonomic resolution. DNA metabarcoding has been successfully used to characterize the parasitic nemabiome with high taxonomic resolution in a variety of wild and domestic hosts. However, in
order to implement this technique in large-scale, potentially non-invasive monitoring of gastrointestinal parasitic
nematodes (GIN), protocol optimization is required to maximize biodiversity detection, whilst maintaining time- and
cost-efectiveness.
Methods Faecal samples were collected from a wild moose population and GIN communities were characterized
and quantifed using both parasitological techniques (egg and larva counting) and DNA metabarcoding of the ITS2
region of rDNA. Three diferent isolation methods were compared that difered in the volume of starting material and
cell lysis method.
Results Similar nematode faunas were recovered from all samples using both parasitological and metabarcoding
methods, and the approaches were largely congruent. However, metabarcoding assays showed better taxonomic
resolution and slightly higher sensitivity than egg and larvae counts. The metabarcoding was not strictly quantitative,
but the proportion of target nematode sequences recovered was correlated with the parasitologically determined
parasite load. Species detection rates in the metabarcoding assays were maximized using a DNA isolation method
that included mechanical cell disruption and maximized the starting material volume.
Conclusions DNA metabarcoding is a promising technique for the non-invasive, large-scale monitoring of parasitic
GINs in wild ungulate populations, owing to its high taxonomic resolution, increased assay sensitivity, and time- and
cost-efectiveness. Although metabarcoding is not a strictly quantitative method, it may nonetheless be possible
to create a management- and conservation-relevant index for the host parasite load from this data. To optimize the
detection rates and time- and cost-efectiveness of metabarcoding assays, we recommend choosing a DNA isolation
method that involves mechanical cell disruption and maximizes the starting material volume.
Nemabiome, Metabarcoding, ITS2, DNA extraction method, NC1–NC2 primers, Alces alces, Helminth,
Ungulates
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Soininen, Eeva M; Barrio, Isabel C.; Bjørkås, Ragnhild; Björnsdóttir, Katrin; Ehrich, Dorothee & Hopping, Kelly A.
[Vis alle 44 forfattere av denne artikkelen]
(2021).
Location of studies and evidence of effects of herbivory on Arctic vegetation: a systematic map.
Environmental Evidence.
ISSN 2047-2382.
10(25).
doi:
10.1186/s13750-021-00240-0.
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Herbivores modify the structure and function of tundra ecosystems. Understanding their impacts is necessary to assess the responses of these ecosystems to ongoing environmental changes. However, the effects of herbivores on plants and ecosystem structure and function vary across the Arctic. Strong spatial variation in herbivore effects implies that the results of individual studies on herbivory depend on local conditions, i.e., their ecological context. An important first step in assessing whether generalizable conclusions can be produced is to identify the existing studies and assess how well they cover the underlying environmental conditions across the Arctic. This systematic map aims to identify the ecological contexts in which herbivore impacts on vegetation have been studied in the Arctic. Specifically, the primary question of the systematic map was: “What evidence exists on the effects of herbivores on Arctic vegetation?”.
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Neby, Magne; Kamenova, Stefaniya; Devineau, Olivier; Ims, Rolf Anker & Soininen, Eeva M
(2021).
Issues of under-representation in quantitative DNA metabarcoding weaken the inference about diet of the tundra vole Microtus oeconomus
.
PeerJ.
ISSN 2167-8359.
9.
doi:
10.7717/peerj.11936.
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Kamenova, Stefaniya; Bretagnolle, Vincent; Plantegenest, Manuel & Canard, Elsa
(2018).
DNA metabarcoding diet analysis reveals dynamic feeding behaviour and biological control potential of carabid farmland communities.
bioRxiv.
ISSN 2692-8205.
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Kamenova, Stefaniya; Mayer, Rebecca; Rubbmark, Oskar R.; Coissac, Eric; Plantegenest, Manuel & Traugott, Michael
(2018).
Comparing three types of dietary samples for prey DNA decay in an insect generalist predator.
Molecular Ecology Resources.
ISSN 1755-098X.
doi:
10.1111/1755-0998.12775.
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Johaadien, Rukaya Sarah; Frøslev, Tobias Guldberg; Du Plessis, Morne; Torma, Michal; Kamenova, Stefaniya & Braathen, Catherine
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(2023).
Course on DNA barcode data in BOLD and GBIF - Cape Town, South Africa.
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Accelerating biodiversity research through DNA barcodes, collection, and observation data. Regional Training Course for M.Sc. and Ph.D. students with expert trainers and trainers-in-training - Cape Town, South Africa.
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Soininen, Eeva M; Barrio, Isabel C.; Bjørkås, Ragnhild; Björnsdóttir, Katrín; Ehrich, Dorothee & Hopping, Kelly
[Vis alle 44 forfattere av denne artikkelen]
(2022).
Correction to: Location of studies and evidence of effects of herbivory on Arctic vegetation: a systematic map (Environmental Evidence, (2021), 10, 1, (25), 10.1186/s13750-021-00240-0).
Environmental Evidence.
ISSN 2047-2382.
11(1).
doi:
10.1186/s13750-022-00265-z.
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Kamenova, Stefaniya; de Boer, Hugo; Endresen, Dag; Russell, Laura Anne; Schigel, Dmitry & Wirta, Helena K
(2021).
Accelerating biodiversity research through DNA barcodes, collection and observation data (online for Georgia and Armenia June 2021).
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This course will teach how to use DNA barcodes, collection and observation data to resolve research questions in biodiversity. The four-day intensive programme will use a combination of lectures, tutorials, and hands-on exercises. You will learn to handle biodiversity data including DNA barcoding. You will gain practical experience in using open and digitally documented biodiversity data through GBIF and BOLD to answer biodiversity research questions. You will understand and practice capturing observation, collection, and genetic data from analogue and digital sources. Finally, the course provides basic skills in data publishing through GBIF.
This course is a collaboration between the Diku-funded University of Oslo project BioDATA, the BMBF-funded project Caucasus Barcode of Life (CaBOL), and GBIF - Global Biodiversity Information Facility.
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Kamenova, Stefaniya
(2018).
REININ project: Reindeer interactions from plants and birds to humans: balancing the odds of climate change.
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Kamenova, Stefaniya
(2017).
REININ project: Reindeer interactions from plants and birds to humans: Balancing the odds of climate change.
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Publisert
23. mars 2022 10:57
- Sist endret
23. mars 2022 10:57