CamtrapReport: An R Package for Automating Camera-Trap Data Reporting for Wildlife Monitoring

Camera traps are vital for wildlife monitoring and biodiversity research, enabling continuous data collection across diverse ecosystems. However, processing, standardizing, and analyzing these datasets can be challenging, as existing methods for data validation, interpretation, and visualization are often too complex for many end users. Beyond simplifying workflows, there is a critical need to establish reproducible computational pipelines that ensure transparency, comparability, and reliability in ecological research, ultimately strengthening biodiversity conservation efforts. To address these challenges, we developed camtrapReport, an object-oriented, extensible, and mutable R package that delivers reproducible camera-trap data processing workflows and automates the generation of informative ecological reports. The package accepts datasets formatted in the widely used Camtrap DP standard and is organized into three main components: (i) Data Status Check, which performs automated diagnostics of data quality; (ii) Report Generation, which produces standardized outputs with a comprehensive suite of ecological analyses and visualizations, including sampling effort, species richness, species co-occurrence, abundance distributions, community composition, habitat use, activity patterns, population density, and spatial mapping; and (iii) a Graphical User Interface, a Shiny-based environment for interactive filtering and exploration of results. By transforming raw camera-trap data into structured ecological insights, camtrapReport standardizes data collection and analysis, thereby enhancing comparability, scalability, and reproducibility across sites and time. Its automated workflow reduces technical barriers, supports users across programming skill levels, and accelerates biodiversity trend detection and wildlife status assessment. In doing so, the package enables transparent, efficient, and timely ecological reporting, providing a powerful tool for evidence-based conservation decision-making.