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Towards a best‐practices guide for camera trapping: assessing differences among camera trap models and settings under field conditions
Author(s) -
Palencia P.,
Vicente J.,
Soriguer R. C.,
Acevedo P.
Publication year - 2022
Publication title -
journal of zoology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.915
H-Index - 96
eISSN - 1469-7998
pISSN - 0952-8369
DOI - 10.1111/jzo.12945
Subject(s) - camera trap , trap (plumbing) , usable , computer vision , computer science , artificial intelligence , sensitivity (control systems) , trapping , field (mathematics) , field of view , flash (photography) , biology , wildlife , ecology , optics , mathematics , physics , multimedia , engineering , electronic engineering , meteorology , pure mathematics
Abstract Camera trapping is a widely used tool in wildlife research and conservation, and a plethora of makes and models of camera traps have emerged. However, insufficient attention has been paid to testing their performance, particularly under field conditions. In this study, we have comparatively tested five of the most frequently used makes of camera trap (Bushnell, KeepGuard, Ltl Acorn, Reconyx and Scoutguard) to identify the key factors behind their probability of detection (i.e. the probability that the camera successfully capturing a usable photograph of an animal passing through the field of view) and trigger speed (i.e. the time delay between the instant at which a motion is detected, and the time at which the picture is taken). We used 45 cameras (nine devices of each make) with infrared flash in a field experiment in which a continuous remote video was used in parallel (as a gold‐standard) to discover the animals that entered the camera trap detection zone. The period (day/night), distance between animals and cameras, model, species, deployment height and activation sensitivity were significantly related to the probability of detection. This probability was lower during the night than during the day. There was a greater probability of detecting a given species when the cameras were set at its shoulder height. The interaction between species and the distance between the animals and the cameras significantly affected the trigger speed, meaning that the closer the animals that entered the detection zone, the higher the trigger speed, with substantial differences among species. This was probably related by movement speed. In conclusion, this study shows differences in the performance of camera trap models and settings, signifying that caution is required when making direct comparisons among results obtained in different experiments, or when designing new ones. These results provide empirical guidelines for best practices in camera trapping and highlight the relevance of field experiments for testing the performance of the camera traps.