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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 gear scaling coefficients for traditional gear types. Models are implemented with a Bayesian framework (Markov chain Monte Carlo) using the 'Stan' probabilistic programming language.
Getting started
Browse package contents
Package details |
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| Author | Abigail G. Keller [aut, cre], Ryan P. Kelly [ctb], Chitra M. Saraswati [rev], Saras M. Windecker [rev] |
| Maintainer | Abigail G. Keller <agkeller@berkeley.edu> |
| License | GPL-3 |
| Version | 0.3.3 |
| URL | https://github.com/ropensci/eDNAjoint https://docs.ropensci.org/eDNAjoint/ |
| Package repository | View on CRAN |
| Installation |
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