1 Camera trapping for animal monitoring and management: a review of applications

Camera traps are being used throughout the world to address a wide range of issues in wildlife management and to address both research and management questions that cannot be easily answered with other methods. In addition to detecting rare species and providing answers to practical management questions, camera traps have a potentially large role in assessing global changes in biodiversity of mammals. The quality of camera traps is continuing to improve, and field and analytical techniques are also moving rapidly forward. This paper reviews the current state of camera trapping in wildlife ecology with a focus on new and emerging applications in management and monitoring. Recent papers, including many in this volume, indicate that camera traps have the potential to be a powerful new tool in areas of animal ecology where they have not previously been widely used, such as estimation abundance, sampling of small animals, and establishing conservation priorities based on regional monitoring. In addition, the use of camera traps by citizen scientists and environmental educators continues to grow and become more integrated with more traditional scientific studies. Introduction Cameras that record images of wild animals when humans are not present have a long history in ecology, but their use dramatically increased with the introduction of commercial infrared-triggered cameras in the early 1990s. Today, the term ‘camera trap’ typically refers to cameras units that are triggered by the movement of an animal within a detection area, although the term also can describe cameras set to take photos at set time intervals. Nearly all camera traps used in current wildlife applications are small (the size of a shoebox or smaller), consist of only one piece, shoot digital still or video images, and are passively triggered using an infrared light source. Nevertheless, a dazzling array of commercial camera traps and optional features are available (Rovero et al. 2013; Swann et al. 2004, 2011; <http://www.trailcampro.com>), and these can be further modified by researchers. Camera traps have been applied to nearly every aspect of vertebrate ecology, including to study nest ecology, research activity patterns and behaviour, document rare species or events, and estimate state variables such as species richness, occupancy, abundance (Cutler and Swann 1999; Kucera and Barrett 2011). Data recorded by camera traps 061402 Camera Trapping 1pp.indd 3 23/06/2014 3:13 pm PArt 1 – cAMErA trAPPIng for AnIMAL MonItorIng: cAsE studIEs 4 typically consist of an image (e.g. Plate 1.1), series of images, or video of an individual or group of animals within the area of detection covered by the camera trap, as well as other information such as the date, time, and location of the photograph. Because most individuals in the image can be identified to species, the trap thus records the presence of that species at that place and time. Other information, such as behavioural data (e.g. Meek et al. 2012) or events such as predation or feeding (e.g. Zimmerman et al. 2011) can also be recorded. In some cases individual animals can be identified either through tags previously affixed by researchers or by unique natural marks. Some data gathered by physical trapping techniques, such as reproductive condition and genetic data, cannot usually be obtained by camera traps, but camera trap data are often combined with other techniques such as radio-telemetry (e.g. Larrucea et al. 2007) and genetics (e.g. Janečka et al. 2011). Despite the limits of the data that can be gathered by camera traps, experience during the past two decades indicates why they are powerful tools for addressing conservation of populations of native species, especially mammals. First, camera traps provide basic knowledge of the distribution of mammals (their presence in a certain place), which is essential for conservation on both the local and regional scale, but often previously lacking for the many species that are nocturnal, avoid humans, and seek cover. Second, they are relatively inexpensive, which means they can be deployed very efficiently to increase sample sizes over wide areas (De Bondi et al. 2010). And third, camera traps are relatively non-invasive and safe for both humans and animals. From a practical point of view, it is obviously much easier to sample populations of very large mammals with camera traps than with live traps. As a result, camera trapping has been truly significant for wildlife management and conservation throughout the world. Camera traps have documented species that are new to science, or occur in areas where they were thought to be locally extinct or not previously known to exist (e.g. Sangay et al., Chapter 10). Kucera and Barrett (2011) list several recent examples, including a new species of striped rabbit (Nesolagus timminsi) in South-east Asia (Surridge et al. 1999), a range extension for the Sulawesi palm civet (Macrogalidia musschenbroekii) (Lee et al. 2003) and the documentation of the wolverine (Gulo gulo) in California for the first time since 1922 (Moriarty et al. 2009). Camera traps also have been used to reliably estimate, for the first time, the abundance of the tiger (Panthera tigris; Karanth and Nichols 1998) and other species where individuals can be readily recognised based on their spot pattern. After many years of debate and poor information on the number of species of mammals present in natural areas, camera traps are now producing reliable estimates of species richness and other community measures (Tobler et al. 2008; O’Brien et al. 2011) that are not based on poor-quality observational data or generalised range maps (e.g. Newmark 1995; Parks and Harcourt 2002). As demonstrated at the First International Camera Trapping Colloquium in Wildlife Management and Research, new developments in camera trapping are arriving at a staggering pace. Camera traps themselves are rapidly evolving, becoming faster, cheaper, more resilient, and more versatile (Meek 2011). Researchers are developing new techniques for deploying them, including using vertical mounts (Swann et al. 2004; Welbourne, Chapter 20). More researchers are aware that detectability is always < 1 in camera studies (Kéry 2011) and are becoming more adept and sophisticated at analysing camera trap data using occupancy and other methods (O’Connell and Bailey 2011). They are rapidly improving methods for managing data, including extracting data directly from photos, eliminating the need for data entry, and even developing methods for using pattern recognition to identify animals automatically (Falzon et al., Chapter 28). And of course, they are improving methods for sharing data through the internet and cell phone applications. What is truly exciting about camera trapping in the modern era is that the explosive adoption of this technology, in synergy with improvements in 061402 Camera Trapping 1pp.indd 4 23/06/2014 3:13 pm 5 1 – cAMErA trAPPIng for AnIMAL MonItorIng And MAnAgEMEnt camera trap quality, wildlife data analysis, and information management, is resulting in novel applications in wildlife conservation around the world. It is a testament to the rapid advances in camera trapping that several important developments in camera trapping have occurred since the very recent publication of a major book on the subject, Camera Traps in Animal Ecology (O’Connell and Bailey 2011). The goal of this paper is to provide a short summary of some of these applications and explore their potential for creating ground-breaking developments in the coming years. Estimating animal abundance and density Camera traps are often used to provide an index of abundance (also called relative abundance), such as the number of photos of a species per trap night. However, indices typically provide biased estimates of abundance (Anderson 2001), which in camera trapping is primarily due to spatial variability and detectability (O’Brien 2011). Many users of camera traps assume that the number of photographs per unit time is an accurate reflection of the number of individual animals present. However, this assumption may not be valid because many factors may influence the number of photographs, including attraction to the camera trap, trap shyness, use of or type of attractant, weather, ability of the camera trap to detect an animal when present, and others. Several recent studies (see Karanth et al. 2011) have followed Karanth (1995), who used camera traps and individual natural markings to estimate tiger abundance and density using capture–recapture models. However, this approach does not work for species without features that allow them to be individually recognised. The recent work by Marcus Rowcliffe and colleaques (Rowcliffe et al. 2008, 2011) is thus truly important for camera trap researchers, as it presents an opportunity to estimate density by modelling the underlying process of the encounter between the camera trap and the animal. Their random encounter model (REM) relies on characteristics of the camera trap (the distance and angle with which it detects animals) and the characteristics of animals that can be determined from videos taken at the camera sites, including its size and speed. One of the complications of using the REM has to do with the difficulty of accurately estimating the area of the detection zone. Although this problem has been addressed using distance sampling techniques by Rowcliffe et al. (2011), papers presented in this volume (e.g. Welbourne, Chapter 20) suggest that another approach may be to mount cameras vertically (facing down at the ground), so as to more precisely control the area of detection. This approach may not be appropriate for larger animals in tropical areas where a large amount of vegetation is present, but might work in less vegetated areas and for smaller mammals in most habitats. Studying small animals Another interesting new direction for camera trapping is in studies of