Effects of camera‐trap placement and number on detection of members of a mammalian assemblage

Abstract

A central goal in camera-trapping (CT) studies is to maximize detection probability and precision of occupancy estimates while minimizing the number of CTs to reduce equipment and labor costs. Few studies, however, have examined the effect of CT number on detection probability. Moreover, historically, most studies focused on a specific species and the design could be tailored toward maximizing detection of this target species. Increasingly, however, such studies use data for all captured, non-target, species (by-catch data) for animal community-level analyses. It remains unclear if, and how, the targeting of CTs toward one species affects the detection of non-target species. We paired CTs from a permanent cameratrapping grid (with 38 CTs) targeted at monitoring Eurasian lynx (Lynx lynx) in Innlandet County, Norway, with additional randomly placed CTs at two spatial scales (38 CTs within the same habitat patch and 38 CTs within the same 50-km 2 grid cell as the lynx-targeted CTs) for three months. We combined multi-scale occupancy models that enable the separation of large-scale occupancy, CT-scale site use, and detection probability with single-scale occupancy models. This allowed us to study the effects of targeted placement and CT number on the detection probability of the target species (lynx) and seven non-target mammal species (four carnivores, three herbivores, and one rodent). We found that all species, except moose (Alces alces), had the highest detection probability at lynx-targeted CTs. Moose had equal detection probabilities at all three placement types. Adding extra CTs generally increased detection probabilities. Consequently, for all species, combining a lynx-targeted CT with one or more randomly placed CTs, increased the accuracy and precision of occupancy estimates for 50-km 2 grid cells compared to single CT estimates. The placement of single CTs underestimated grid-cell occupancy compared to known minimum occupancy and were similar to site-use probability estimates of multi-scale models. It is, however, uncertain to which spatial extent these site-use probabilities refer. We therefore recommend the use of multiple (targeted) CTs to estimate occupancy in large grid cells and to interpret occupancy estimates from single CTs as site use of an, as of yet undefined, area surrounding the CT.

Towards a best‐practices guide for camera trapping: assessing differences among camera trap models and settings under field conditions

“…Missed detections could potentially generate misleading results in camera trapping studies, and therefore, create difficulties as regards direct comparison among studies (Jacobs & Ausband, 2018). In this respect, despite some statistical approaches accounting for the imperfect detection (Guillera-Arroita et al, 2010), recent studies have shown that biased and imprecise results can be obtained when detection probabilities are low (Hofmeester et al, 2021;Kays et al, 2021). Additionally, (1) there are a wide variety of studies that used the raw encounter rates without accounting for false-negatives (i.e.…”

The influence of fine‐scale topography on detection of a mammal assemblage at camera traps in a mountainous landscape

“…Our results have greater implications for studies of animal diversity with broad spatial extents in topographically-complex landscapes. Much effort has gone into understanding variability in animal detection at camera-traps (Moll et al 2020, Hofmeester et al 2021, Kolowski et al 2021, and our study contributes to this knowledge base in a novel way by demonstrating the nonlinear effects of terrain steepness on species-specific detection. Our results also support applying lure in camera viewsheds to increase the detection of carnivores.…”

“…Due to low levels of spatial patterning in animal detections between camera traps (Kolowski et al 2021), researchers have concluded it is problematic to assign detection of animal species at the fine spatial scale of a single camera‐trap viewshed to occurrence of that species at broad spatial scales (Evans et al 2019, Hofmeester et al 2021). However, in systems with high landscape complexity, accounting for the effects of topography on species detections (i.e.…”

Altitude, latitude, and climate zone as determinants of mountain hare (Lepus timidus) coat colour change

“…We utilized images from camera traps that were deployed by the SCANDCAM project (viltkamera.nina.no), originally designed to monitor Eurasian lynx (Lynx lynx ) (Hofmeester et al 2021). Camera traps were deployed in multiple study areas in an extensive grid with approximately one camera per 50 km 2 grid cell (Figure 1).…”