multimark: an R package for analysis of capture-recapture data consisting of multiple "noninvasive" marks

I describe an open-source R package, multimark, for estimation of survival and abundance from capture-mark-recapture data consisting of multiple "noninvasive" marks. Noninvasive marks include natural pelt or skin patterns, scars, and genetic markers that enable individual identification in lieu of physical capture. multimark provides a means for combining and jointly analyzing encounter histories from multiple noninvasive sources that otherwise cannot be reliably matched (e.g., left- and right-sided photographs of bilaterally asymmetrical individuals). The package is currently capable of fitting open population Cormack-Jolly-Seber (CJS) and closed population abundance models with up to two mark types using Bayesian Markov chain Monte Carlo (MCMC) methods. multimark can also be used for Bayesian analyses of conventional capture-recapture data consisting of a single-mark type. Some package features include (1) general model specification using formulas already familiar to most R users, (2) ability to include temporal, behavioral, age, cohort, and individual heterogeneity effects in detection and survival probabilities, (3) improved MCMC algorithm that is computationally faster and more efficient than previously proposed methods, (4) Bayesian multimodel inference using reversible jump MCMC, and (5) data simulation capabilities for power analyses and assessing model performance. I demonstrate use of multimark using left- and right-sided encounter histories for bobcats (Lynx rufus) collected from remote single-camera stations in southern California. In this example, there is evidence of a behavioral effect (i.e., trap "happy" response) that is otherwise indiscernible using conventional single-sided analyses. The package will be most useful to ecologists seeking stronger inferences by combining different sources of mark-recapture data that are difficult (or impossible) to reliably reconcile, particularly with the sparse datasets typical of rare or elusive species for which noninvasive sampling techniques are most commonly employed. Addressing deficiencies in currently available software, multimark also provides a user-friendly interface for performing Bayesian multimodel inference using capture-recapture data consisting of a single conventional mark or multiple noninvasive marks.