title: The importance of including imperfect detection models in eDNA experimental design.
abstract: Environmental DNA (eDNA) is DNA that has been isolated from field samples, and it is increasingly used to infer the presence or absence of particular species in an ecosystem. However, the combination of sampling procedures and subsequent molecular amplification of eDNA can lead to spurious results. As such, it is imperative that eDNA studies include a statistical framework for interpreting eDNA presence/absence data. We reviewed published literature for studies that utilized eDNA where the species density was known and compared the probability of detecting the focal species to the sampling and analysis protocols. Although biomass of the target species and the volume per sample did not impact detectability, the number of field replicates and number of samples from each replicate were positively related to detection. Additionally, increased number of PCR replicates and increased primer specificity significantly increased detectability. Accordingly, we advocate for increased use of occupancy modelling as a method to incorporate effects of sampling effort and PCR sensitivity in eDNA study design. Based on simulation results and the hierarchical nature of occupancy models, we suggest that field replicates, as opposed to molecular replicates, result in better detection probabilities of target species.
authors.affiliation: Department of Forestry and Natural Resources, Purdue University, 715 W. State St., West Lafayette, IN, 47907, USA.|Department of Biological Sciences, Purdue University, 915 W. State St., West Lafayette, IN, 47907, USA.
authors.forename: Janna R
authors.initials: JR
authors.lastname: Willoughby
authors.affiliation: Department of Biological Sciences, Purdue University, 915 W. State St., West Lafayette, IN, 47907, USA.
authors.forename: Bhagya K
authors.initials: BK
authors.lastname: Wijayawardena
authors.affiliation: Department of Forestry and Natural Resources, Purdue University, 715 W. State St., West Lafayette, IN, 47907, USA.
authors.forename: Mekala
authors.initials: M
authors.lastname: Sundaram
authors.affiliation: Department of Forestry and Natural Resources, Purdue University, 715 W. State St., West Lafayette, IN, 47907, USA.
authors.forename: Robert K
authors.initials: RK
authors.lastname: Swihart
authors.affiliation: Department of Forestry and Natural Resources, Purdue University, 715 W. State St., West Lafayette, IN, 47907, USA.|Department of Biological Sciences, Purdue University, 915 W. State St., West Lafayette, IN, 47907, USA.
authors.forename: J Andrew
authors.initials: JA
authors.lastname: DeWoody
mesh_terms: D056808:Biostatistics / Q000379:methods*; D058448:Biota; D004777:Environment; D054892:Metagenome; D056186:Metagenomics / Q000379:methods*; D012107:Research Design
keywords: environmental DNA; occupancy model; probability of detection; sampling effort