Site occupancy models in the analysis of environmental DNA presence/absence surveys: a case study of an emerging amphibian pathogen

By B. R. Schmidt, Marc Kéry, S. Ursenbacher, Oliver J. Hyman, James P. Collins. 2013

262 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Microbiology

View Paper: https://www.semanticscholar.org/paper/ec4de4056584da40549b29de3b5b42126f31b33a

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In Ecological Modeling

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In Microbiology

P. F. Thomsen

Citations in the corpus

Replication levels, false presences and the estimation of the presence/absence from eDNA metabarcoding data (2015, methodology): “Species occupancy methods have excellent performance in the estimation of detection probability, true occupancy and even false presences, and can be successfully applied to eDNA data (Schmidt et al. 2013).”
Alien Pathogens on the Horizon: Opportunities for Predicting their Threat to Wildlife (2017, background): “, molecular tools such as eDNA) technologies (Schmidt et al. 2013; Bass et al. 2015) is required to screen for putative pathogen groups and to better inform risk management.”
Critical considerations for the application of environmental DNA methods to detect aquatic species (2016, methodology): “Species detection using eDNA sampling is therefore contingent upon detection probability (MacKenzie et al. 2002; Schmidt et al. 2013; Ficetola et al. 2015; Schultz & Lance 2015).”
Environmental DNA monitoring and management of invasive fish: comparison of eDNA and fyke netting (2017, methodology): “The eDNA approach has been reported to be a more sensitive method than netting (Jerde et al. 2011) or electrofishing (Wilcox et al. 2016) for fish detection, but it remains imperfect like other traditional survey techniques (Dejean et al. 2012; Schmidt et al. 2013; Yoccoz 2012).”
Utility of Environmental DNA for Monitoring Rare and Indicator Macroinvertebrate Species (2014, background): “They can occur for reasons that reflect the limitations of eDNA as a surveillance method (Schmidt et al. 2013).”
Experimental observations on the decay of environmental DNA from bighead and silver carps (2017, background): “…role of environmental factors on eDNA detection, and probabilistic framework for interpreting eDNA data have been published (Barnes et al. 2014; Darling and Mahon 2011; Dejean et al. 2011; Farrington et al. 2015; Goldberg et al. 2011; Jerde et al. 2011; Schmidt et al. 2013; Schultz and Lance 2015).”
Dealing with false‐positive and false‐negative errors about species occurrence at multiple levels (2017, methodology): “Several eDNA-based occupancy studies have accounted for falsenegative errors (Schmidt et al. 2013; Hunter et al. 2015); in contrast, false-positive errors have received far less attention (cf. Ficetola et al. 2015; Lahoz-Monfort, Guillera-Arroita & Tingley 2016), despite early recognition that…”
Transport Distance of Invertebrate Environmental DNA in a Natural River (2014, unknown): “Environmental DNA (eDNA) is a novel molecular technique used to detect the presence of species and may have the potential to fulfill all of the above-mentioned criteria [10,11].”
Environmental DNA - An emerging tool in conservation for monitoring past and present biodiversity (2015, methodology): “Occupancy models can also be used to calculate the number of eDNA samples needed to reach a cumulative detection chance of fx 95% (Schmidt et al., 2013).”
How will the ‘molecular revolution’ contribute to biological recording? (2015, background): “…et al., 2012b; Pilliod et al., 2013) or digital droplet PCR (ddPCR, Nathan et al., 2014), counting the number of sequences per OTU in metabarcoding (Yu et al., 2012; Kelly et al., 2014), avoiding PCR (Zhou et al., 2013) and site occupancy modelling (Pilliod et al., 2013; Schmidt et al., 2013).”
Assessing the cost‐efficiency of environmental DNA sampling (2016, methodology): “Rather than choosing an arbitrary qPCR threshold, an alternative approach would be to extend the hierarchical models used here to simultaneously estimate detection rates at both the water sample level and the qPCR level (Schmidt et al. 2013).”