The 'eDNAjoint' package.

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.

References

Stan Development Team (NA). RStan: the R interface to Stan. https://mc-stan.org

See also

Useful links:

• https://github.com/ropensci/eDNAjoint

• https://docs.ropensci.org/eDNAjoint/

• Report bugs at https://github.com/ropensci/eDNAjoint/issues

Author

Maintainer: Abigail G. Keller agkeller@berkeley.edu

Other contributors:

• Ryan P. Kelly rpkelly@uw.edu [contributor]

• Chitra M. Saraswati [reviewer]

• Saras M. Windecker [reviewer]