DOI: 10.5061/dryad.m0cfxpp3m
title: A motion-detection based camera trap for small nocturnal mammals with low latency and high signal-to-noise ratio

description: 1. Camera traps are useful for monitoring wildlife populations, but traps
 may not always trigger when targeting small, nocturnal species. Motion
 detection techniques have advantages over time-lapse and heat-triggered
 traps, but need to be deployed to maximize signal-to-noise ratio. 2. As
 part of a study of flying squirrels (Glaucomys) in urban environments we
 developed motion detecting camera traps using a raspberry pi microcomputer
 and camera and a 940 nm IR illuminator on a tree-mounted wooden platform.
 The system was built from commercially available parts and was comparable
 in cost to a consumer camera trap, although this cost did not include a
 waterproof housing. We compared the performance of our system to
 commercial trailcams. 3. Four pi cameras successfully documented visits by
 Glaucomys and other animals to bait placed on the platform over three
 nights at four wooded sites: suburban and rural backyards, a private
 outdoors club, and a small urban nature reserve (16 camera X site
 combinations, 48 trap nights). The traps showed low latency, with an
 average of &lt; 1 night until detection of Glaucomys at each site.
 Data collected had a high signal-to-noise ratio; of 2182 capture events
 55% documented Glaucomys, 40% documented non-target mammals, 1% were
 caused by large insects, and the remaining 4% were unknown. Commercial
 camera traps placed at the sites failed to capture many of these events.
 4. The low cost and high signal-to-noise ratio of this system may make it
 easy to adapt for other small animal applications. The main modifications
 required to deploy this system in new situations will be in locating or
 providing a fixed or static background against which animals can be
 observed and in using masking techniques within motion detection software.
description: This dataset describes trailcam images generated from four
 Raspberry Pi-based trailcam prototypes and associated commercial trailcams
 as described in the associated MS (Klemens, Tripepi, and McFoy 2021). The
 data was generated by reviewing all motion detection events generated by
 the cameras and attributing them to either flying squirrels
 (<em>Glaucomys sp.</em>), other mammals, insects, or
 'other', which includes capture events that cannot be attributed
 to an organism. The data records the total number of capture events
 recorded between placement of bait at the camera trap and sunrise, and
 then attributes each events to one of the four categories.
 For some but not all site by camera combinations commercial
 camera traps were used to observe the Pi cams. The insect category is
 excluded as trail cams did not create events due to insect
 movement. The number of capture events in each of the other categories is
 presented. Percentages presented for the trailcam data represent the
 percent of capture events recorded by the Pi camera that were also
 captured by the trailcam.     Location data was
 collected using a Garmin GPSMAP64ST and the default WGS 84 map datum and
 WGS 84 map spheroid.
description: Data.csv contains the records for each camera trap for each night
 of the experiment.  Locations.csv contains the lat/long
 data for each camera trap X site combination