Acoustic vs. photographic monitoring of gray wolves (Canis lupus): a methodological comparison of two passive monitoring techniques

• Published in: Canadian journal of zoology Vol. 98; no. 3; pp. 219 - 228
• Main Authors: Garland, Laura, Crosby, Andrew, Hedley, Richard, Boutin, Stan, Bayne, Erin
• Format: Journal Article
• Language: English
• Published: Ottawa NRC Research Press 01.03.2020; Canadian Science Publishing NRC Research Press
• Subjects: Acoustics; Analysis; Animals; autonomous recording units; Bayesian occupancy; camera traps; Cameras; Canidae; Canis lupus; Conservation; enregistreurs autonomes; gray wolf; loup gris; Lupus; Mammals; Methods; Occupancy; occupation bayésienne; pièges photographiques; Polls & surveys; Population (statistical); Population density; Questions; Remote monitoring; Sampling; Statistical methods; Statistics; Surveillance; Traps; Wolves; Alberta; Canada
• ISSN: 0008-4301; 1480-3283; 1480-3283; 0008-4301
• DOI: 10.1139/cjz-2019-0081

Remote camera traps are often used in large-mammal research and monitoring programs because they are cost-effective, allow for repeat surveys, and can be deployed for long time periods. Statistical advancements in calculating population densities from camera-trap data have increased the popularity of camera usage in mammal studies. However, drawbacks to camera traps include their limited sampling area and tendency for animals to notice the devices. In contrast, autonomous recording units (ARUs) record the sounds of animals with a much larger sampling area but are dependent on animals producing detectable vocalizations. In this study, we compared estimates of occupancy and detectability between ARUs and remote cameras for gray wolves (Canis lupus Linnaeus, 1758) in northern Alberta, Canada. We found ARUs to be comparable with cameras in their detectability and occupancy of wolves, despite only operating for 3% of the time that cameras were active. However, combining cameras and ARUs resulted in the highest detection probabilities for wolves. These advances in survey technology and statistical methods provide innovative avenues for large-mammal monitoring that, when combined, can be applied to a broad spectrum of conservation and management questions, provided assumptions for these methods are rigorously tested and met.