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

Abstract

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.

Identifying unknown Indian wolves by their distinctive howls: its potential as a non-invasive survey method

“…This study increases the feasibility of wolf pack census using a howling survey 35 , 60 . Since wolves may actively avoid camera traps 54 and photo-identification of wolf requires arduous effort 3 , 67 , identifying wolves from their howls is a big step towards population estimation using CMR.…”

“…Although CMR associated with camera trapping provides population estimation without bias for an identifiable animal like a tiger 68 , camera trapping has several limitations for non-identifiable and long-ranging species like the wolf 3 . Other non-invasive methods like DNA-based CMR resulted in biased population estimation due to the animals’ non-uniform scent-marking patterns 59 , 69 .…”

“…Other non-invasive methods like DNA-based CMR resulted in biased population estimation due to the animals’ non-uniform scent-marking patterns 59 , 69 . However, acoustics based surveys allow vast area sampling with limited resources as compared to camera trapping and other non-invasive methods 3 . Furthermore, our field observations of wolves have shown that the whole pack typically howls during choruses and that all individuals are acoustically active.…”

“…Therefore, it is of the foremost importance to have a statistically robust population estimation technique. However, widely used population estimation methods such as camera trapping and sighting-based distance sampling fall short in analysing population trends of certain elusive species or species living in extensive home ranges 3 , 4 . Many of these species are vocally active, which inspired scientists to study the effectiveness of an acoustics-based population abundance model for these species 5 – 8 .…”

Testing a New Passive Acoustic Recording Unit to Monitor Wolves

“…Some chorus howls were detected by AudioMoths as far away as 3.2 km (2.0 mi), so AudioMoths could be used any time of the year to monitor multiple packs simultaneously in a wider sampling array (Papin et al 2018). Similar to other ARUs, AudioMoths would be effective in occupancy studies, especially if used in concert with other noninvasive tools such as camera‐trapping (Harrington and Mech 1982, Garland et al 2020). Our detectability findings are directly relevant to occupancy studies in distinguishing between nondetection and absence of wild wolves (i.e., probability of detection).…”