R/caribouMetrics-package.R
caribouMetrics-package.RdcaribouMetrics provides implementations of several different different models of Boreal woodland caribou demography and habitat selection. A national two-stage demographic model with density dependence and interannual variability follows [Johnson et. al. (2020)](doi:10.1111/1365-2664.13637) with modifications described in [Dyson et al. (2022)](https://doi.org/10.1101/2022.06.01.494350). Demographic rates vary with disturbance as estimated by [Johnson et. al. (2020)](doi:10.1111/1365-2664.13637). The package also includes a Bayesian population model designed to integrate prior information from Johnson et al's national analysis of demographic-disturbance relationships with available local demographic data to reduce uncertainty in population viability projections. The Bayesian population model is an extension of work by [Eacker et al. (2019)](https://doi.org/10.1002/wsb.950). The national model can be used to simulate example population trajectories, and combined with a simple observation model and the Bayesian population model to show how monitoring requirements depend on landscape condition. Finally, caribouMetrics contains an implementation of [Hornseth and Rempel's (2016)](https://doi.org/10.1139/cjz-2015-0101) Ontario boreal caribou resource selection model described in [Dyson et al. (2022)](https://doi.org/10.1101/2022.06.01.494350). Model implementation is intended to be modular and flexible, allowing reuse of components in a variety of contexts including projections of the cumulative effects of disturbance and climate change [(e.g. Stewart et al. 2023)](https://doi.org/10.1002/eap.2816) and a [Shiny app](https://landscitech.github.io/BayesianCaribouDemographicProjection/) designed to allow allow exploration of user-specified monitoring and disturbance scenarios.