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camtrapR : an R package for efficient camera trap data management
Author(s) -
Niedballa Jürgen,
Sollmann Rahel,
Courtiol Alexandre,
Wilting Andreas
Publication year - 2016
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12600
Subject(s) - computer science , camera trap , software , workflow , toolbox , identification (biology) , data management , automation , data mining , visualization , database , ecology , mechanical engineering , wildlife , engineering , biology , programming language
Summary Camera trapping is a widely applied method to study mammalian biodiversity and is still gaining popularity. It can quickly generate large amounts of data which need to be managed in an efficient and transparent way that links data acquisition with analytical tools. We describe the free and open‐source R package camtrapR , a new toolbox for flexible and efficient management of data generated in camera trap‐based wildlife studies. The package implements a complete workflow for processing camera trapping data. It assists in image organization, species and individual identification, data extraction from images, tabulation and visualization of results and export of data for subsequent analyses. There is no limitation to the number of images stored in this data management system; the system is portable and compatible across operating systems. The functions provide extensive automation to minimize data entry mistakes and, apart from species and individual identification, require minimal manual user input. Species and individual identification are performed outside the R environment, either via tags assigned in dedicated image management software or by moving images into species directories. Input for occupancy and (spatial) capture–recapture analyses for density and abundance estimation, for example in the R packages unmarked or secr , is computed in a flexible and reproducible manner. In addition, survey summary reports can be generated, spatial distributions of records can be plotted and exported to gis software, and single‐ and two‐species activity patterns can be visualized. camtrapR allows for streamlined and flexible camera trap data management and should be most useful to researchers and practitioners who regularly handle large amounts of camera trapping data.

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