Camera-based occupancy monitoring at large scales: Power to detect trends in grizzly bears across the Canadian Rockies. (September 2016)

• Record Type: Journal Article
• Authors: Steenweg, Robin; Whittington, Jesse; Hebblewhite, Mark; Forshner, Anne; Johnston, Barb; Petersen, Derek; Shepherd, Brenda; Lukacs, Paul M.
• Is Part Of: Biological conservation. Volume 201(2016)
• Page Start: 192
• Page End: 200
• Publication Date: 2016-09
• Subjects: Carnivore monitoring -- Occupancy modeling -- Power analysis -- Non-invasive monitoring -- Remote camera -- Camera trapping -- Ursus arctos; Conservation of natural resources -- Periodicals; Nature conservation -- Periodicals; Ecology -- Periodicals; Environment -- Periodicals; Environmental Pollution -- Periodicals; Electronic journals; 333.9516
• DOI: 10.1016/j.biocon.2016.06.020
• Languages: English
• ISSNs: 0006-3207

Abstract

Abstract: Monitoring carnivores is critical for conservation, yet challenging because they are rare and elusive. Few methods exist for monitoring wide-ranging species over large spatial and sufficiently long temporal scales to detect trends. Remote cameras are an emerging technology for monitoring large carnivores around the world because of their low cost, non-invasive methodology, and their ability to capture pictures of species of concern that are difficult to monitor. For species without uniquely identifiable spots, stripes, or other markings, cameras collect detection/non-detection data that are well suited for monitoring trends in occupancy as its own independent useful metric of species distribution, as well as an index for abundance. As with any new monitoring method, prospective power analysis is essential to ensure meaningful trends can be detected. Here we test camera-based occupancy models as a method to monitor changes in occupancy of a threatened species, grizzly bears ( Ursus arctos ), at large landscape scales, across 5 Canadian national parks (~ 21, 000 km 2 ). With n = 183 cameras, the top occupancy model estimated regional occupancy to be 0.79 across all 5 parks. We evaluate the statistical power to detect simulated 5–40% declines in occupancy between two sampling years and test applied questions of how power is affected by the spatial scale of interest (park level vs. regional level), the number of cameras deployed, and duration of camera deployment. We also explore several ecological mechanisms (i.e., spatial patterns) of decline in occupancy, and examine how power changes when focusing only on grizzly bears family groups. As hypothesized, statistical power increased with the number of cameras and with the number of days deployed. Power was unaffected, however, by the ecological mechanisms of decline, indicating that our systematic sampling design can detect a decline regardless of whether occupancy declined due to range edge attrition, ecological trap or other mechanisms. Despite their lower occupancy, power was similarly high for grizzly bear family groups compared to grizzly bears in general. We highlight which study design attributes contributed to high power and we provide advice for establishing cost-effective camera-based programs for monitoring large carnivore occupancy at large spatial scales. Graphical abstract: Highlights: Emerging remote camera technology may effectively track occupancy of unmarked species. We evaluate this promise to track grizzly bear occupancy over large spatial scales. We show high power to track trends at regional and local scales when n ≥ 60 cameras. Results appear robust to various ecological mechanisms of occupancy decline. We provide advice for cost-effective camera-based programs to monitor occupancy.