Estimating Deer Populations Using Camera Traps and Natural Marks

Abstract

Despite the ubiquity of camera traps in wildlife monitoring projects, the data gathered are rarely used to estimate wildlife population demographics, a critical step in detecting declines, managing populations, and understanding ecosystem health. In contrast to abundant white-tailed deer (Odocoileus virginianus) in the eastern United States, black-tailed deer (Odocoileus hemionus columbianus) in the western United States have declined over the past several decades. We tested whether passively operating camera traps can be used to quantify population characteristics for black-tailed deer. We used images of naturally occurring physical characteristics of deer to develop movement and activity data and inform a Bayesian spatial mark-resight model that estimates deer abundance, density, sex ratio, ratio of fawns to adult females, and home range size. We developed the model to account for the effect of attractants (bait) on encounter rate. We placed 13 cameras on all known water sources of a private ranch in California and provided bait once a month in front of each camera. Over 9,000 visits occurred between 24 May 2012 and 21 January 2013, and we identified 50 individual deer from ear notches or antler characteristics. We estimated density at 7.7 deer/km 2 in summer and 8.6 deer/km 2 in fall. In the summer, home ranges were 2.3 km 2 for females and fawns and 16.8 km 2 for males. Home ranges constricted slightly in fall. We estimated a sex ratio of 12.5 males/100 females, and a ratio of 47.0 fawns/100 adult females. Bait increased baseline encounter rates (visits/week) by 3.7 times in summer and 4.95 times in fall. We found slightly higher densities of deer in our study area compared to other recent studies in more mountainous areas of California, and lower male:female sex ratios. This approach shows that commonly deployed camera traps can be used to quantify population characteristics, monitor populations, and inform harvest or habitat management decisions.

Methodology matters when estimating deer abundance: a global systematic review and recommendations for improvements

“…This method has increasingly been used to estimate deer abundance and density in all regions except Australasia (Figure 2), reflecting a more general uptake of motion‐sensitive cameras to study wildlife (Burton et al 2015, Glover‐Kapfer et al 2019). This temporal trend likely reflects the major advances in camera technology and affordability, and also in statistical methods for estimating deer abundance from camera data (e.g., spatial capture‐recapture models; Royle et al 2013, Parsons et al 2017, Macaulay et al 2020).…”

“…Fixed‐wing aircraft were first used to directly count deer in the 1940s (Buechner et al 1951). Efforts have since focused on increasing the detection probability ( p ) of deer in field surveys by using technologies such as helicopters (Thompson and Baker 1981, Bartmann et al 1986), thermal infrared imagers (Croon et al 1968, Havens and Sharp 1998), and motion‐sensitive cameras (Macaulay et al 2020). The most recent review of deer abundance estimation methods is that of Morellet et al (2011), but this was restricted to Europe, was not systematic (Moher et al 2015), and did not consider motion‐sensitive cameras.…”

Overabundance of Black‐Tailed Deer in Urbanized Coastal California

“…We estimated an average density (18.3/km 2 ) of non‐migratory, black‐tailed deer in Marin County that was 1.7–6.1 times higher than published estimates of mule deer density from elsewhere in California (Table 3). The 2 density estimates from the nearby Coast Ranges (i.e., most geographically proximate) were both ≥40% lower than in Marin County, even though the authors considered densities from their studies be high, either because of sampling on preferred fawning grounds or because of artificial water catchments and supplemental feeding (Lounsberry et al 2015, Macaulay et al 2020).…”

Untrapped potential: Do bear hunter cameras accurately index nontarget species?

“…and identification of individuals for use in mark‐recapture methods as is performed with some species (Alonso, McClintock, Lyren, Boydston, & Crooks, 2015; Jhala, Qureshi, & Gopal, 2011; Moore, Champney, Dunlop, Valentine, & Nimmo, 2020). For example, deer identified via antler formation and ear notches, American martens identified from their ventral patches, and other species identified using tags from other studies (e.g., collared wolves) can be used in mark‐recapture analyses (Jordan, Barrett, & Purcell, 2011; Macaulay, Sollmann, & Barrett, 2020; Sirén, Pekins, Abdu, & Ducey, 2016). Collection of such metrics would expand the utility of camera data from presence, composition, and range metrics to more robust relative abundance measures.…”