The camtrapR R package: From data management to interactive ecological analysis of camera trap data

Abstract

O_LICamera trapping has become an indispensable tool in wildlife ecology, generating vast datasets that require efficient and robust analytical workflows. The R package camtrapR was originally developed for preparing and managing camera trap data for subsequent analysis in external modeling packages like unmarked. It has since become a standard tool in the field for this purpose. C_LIO_LIHere, we introduce a major update that transforms camtrapR from a data preparation tool into a comprehensive, end-to-end analytical platform. The centerpiece of this evolution is the surveyDashboard(), a novel code-free graphical user interface that guides users through the entire analysis pipeline, from data import to final predictions. This update also incorporates enhanced data import functionalities for major standards like Wildlife Insights and Camtrap DP, a complete workflow for fitting community occupancy models, and streamlined tools for environmental covariate extraction. C_LIO_LIThe interactive dashboard provides an integrated environment for the entire analytical process. Users can perform essential exploratory analyses, such as generating species accumulation curves and mapping species detections, before proceeding to model fitting. The interface supports the interactive construction of both single-species and multi-species (community) occupancy models. The dashboards covariate preparation tools generate inputs for both model fitting and for creating spatial predictions of species occupancy. C_LIO_LIFurthermore, the update introduces a comprehensive workflow for fitting Bayesian community occupancy models using JAGS or NIMBLE. This allows for hierarchical modeling of species- and community-level responses to environmental drivers, providing deeper insights into wildlife communities. The workflow includes tools for model assessment, such as convergence diagnostics and posterior predictive checks for goodness-of-fit. C_LIO_LIBy integrating a powerful, code-free interface with advanced backend modeling functions, this major update to camtrapR aims to make robust and reproducible camera trap data analysis accessible to a wider audience, including ecologists, wildlife managers, and students. This paper serves as the new definitive reference for the expanded functionality of camtrapR as a comprehensive tool for modern camera trap studies. C_LI