2019
DOI: 10.1002/edn3.59
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Detection of spatiotemporal variation in ranavirus distribution using eDNA

Abstract: Amphibian population declines have been associated with emerging diseases including ranaviruses, which can cause mass die‐offs across entire amphibian communities. Understanding and mitigating disease spread requires knowledge of spatial and temporal patterns of pathogen distribution, but also how environmental factors influence pathogen occurrence. We applied environmental DNA (eDNA) detection tools to survey spatial and temporal distributions of ranaviruses by sampling 103 waterbodies in southeastern Ontario… Show more

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Cited by 22 publications
(28 citation statements)
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“…Furthermore, intensive agricultural land use (i.e., cattle accessing wetlands) can also lead to increased Ranavirus prevalence [ 70 ] and, hence, co-infections involving Ranavirus . Seasonality may also influence the probability of co-infection by affecting the prevalence of both Bd and Ranavirus : the prevalence of Bd is usually the highest during cool and moderately warm months [ 159 , 165 ]; in contrast, Ranavirus peaks were present in the warmest period(s) of the year [ 171 , 172 ]. Talbott and colleagues [ 160 ] found that Bd and Ranavirus co-infection probability was significantly higher during spring than summer or fall.…”
Section: Co-infection By Heterologous Parasitesmentioning
confidence: 99%
“…Furthermore, intensive agricultural land use (i.e., cattle accessing wetlands) can also lead to increased Ranavirus prevalence [ 70 ] and, hence, co-infections involving Ranavirus . Seasonality may also influence the probability of co-infection by affecting the prevalence of both Bd and Ranavirus : the prevalence of Bd is usually the highest during cool and moderately warm months [ 159 , 165 ]; in contrast, Ranavirus peaks were present in the warmest period(s) of the year [ 171 , 172 ]. Talbott and colleagues [ 160 ] found that Bd and Ranavirus co-infection probability was significantly higher during spring than summer or fall.…”
Section: Co-infection By Heterologous Parasitesmentioning
confidence: 99%
“…Although, eDNA approaches have largely been used to detect the presence/absence of free-living species and biodiversity assessments (Taberlet et al 2012;Bohmann et al 2014;Thomsen and Willerslev 2015), they show promising potential in early detection of parasites, spread of invasive parasites, identifying reservoir host populations and quantifying disease risk at ecosystem scales. Until now, eDNA techniques have been successfully employed to detect amphibian pathogens from aquatic ecosystems, such as ranavirus (Miaud et al 2019;Vilaça et al 2019), the trematode Ribeiroia ondatrae (Huver et al 2015) and the fungus B. dendrobatidis (Kamoroff and Goldberg 2017). Moreover, eDNA metabarcoding has also been used in early detection of disease vectors such as dipteran insects (Schneider et al 2016) and phlebotamine sand flies (Kocher et al 2017), which are known to transmit numerous diseases affecting human and wildlife populations.…”
Section: Parasite Detection and Parasite Genetic Diversitymentioning
confidence: 99%
“…Environmental DNA detection methods have been used successfully to identify Ranavirus eDNA in both commercial facilities and natural environments (Hall et al, 2016, 2018; Julian et al, 2019; Kolby et al, 2015; Miaud et al, 2019; Vilaça et al, 2020). Ranavirus has also been identified in amphibian breeding pools in association with observed die‐offs of wood frog larvae ( Lithobates sylvaticus , Hall et al, 2016, 2018).…”
Section: Introductionmentioning
confidence: 99%
“…Ranavirus has also been identified in amphibian breeding pools in association with observed die‐offs of wood frog larvae ( Lithobates sylvaticus , Hall et al, 2016, 2018). Previous Ranavirus eDNA studies have focused on surveillance of amphibian breeding pools during the expected season of ranavirus‐associated disease outbreaks and die‐offs (Hall et al, 2016, 2018; Julian et al, 2019; Miaud et al, 2019; Vilaça et al, 2020). However, Ranavirus eDNA has also been detected in natural settings outside of observed disease or die‐offs (Hall et al, 2018; Miaud et al, 2019; Vilaça et al, 2020).…”
Section: Introductionmentioning
confidence: 99%