eDNAjoint - Joint Modeling of Traditional and Environmental DNA Survey Data
in a Bayesian Framework
Models integrate environmental DNA (eDNA) detection data
and traditional survey data to jointly estimate species catch
rate (see package vignette: <https://ednajoint.netlify.app/>).
Models can be used with count data via traditional survey
methods (i.e., trapping, electrofishing, visual) and replicated
eDNA detection/nondetection data via polymerase chain reaction
(i.e., PCR or qPCR) from multiple survey locations. Estimated
parameters include probability of a false positive eDNA
detection, a site-level covariates that scale the sensitivity
of eDNA surveys relative to traditional surveys, and
catchability coefficients for traditional gear types. Models
are implemented with a Bayesian framework (Markov chain Monte
Carlo) using the 'Stan' probabilistic programming language.
