Additional Funding Sources
This research, conducted at the Raptor Research Experiences for Undergraduates site, was supported by the National Science Foundation and Department of Defense under Grant No. DBI-1852133 and by Boise State University. We also acknowledge support from Grand Canyon National Park Service.
Presentation Date
7-2021
Abstract
Effective wildlife management and conservation rely on accurate estimates of species demographics, including their abundance and distribution. However, monitoring programs are seldom able to detect species perfectly. Cryptic or rare species are often missed, even when present. These false absences can lead to inaccurate assumptions that may misguide management. Therefore, quantifying our ability to accurately detect species is crucial in deriving accurate estimates of species demographics. Passive acoustic monitoring is an emerging technology for surveying ecological soundscapes in ways that have not been possible until recently. The use of acoustic recorders as monitoring tools have thus increased rapidly in the last decade. In the last three years (2019-2021), custom acoustic recorders were used at Grand Canyon National Park to supplement existing long-term monitoring of Mexican Spotted Owls (Strix occidentalis lucida) within their historical nesting territories. However, the factors that influence our ability to detect owls at the Grand Canyon are not yet fully understood. Using acoustic recordings from distance trials and owl surveys, we evaluated the effects of distance, habitat type, wind, and other noise sources on the detection of Mexican Spotted Owls. We found that wind was the dominant source of noise detected during owl surveys, frequently occurring in the 2 hours before sunset, the same time that the owls were most vocally active. The probability of detecting sound by the recorders was higher at further distances in canyon habitats. Detection probability dropped faster in closed forests. Recorders varied widely in their ability to detect sound. For example, in ponderosa forest, some only dropped to 0.75 probability of detection at 100m, while others dropped to < 0.25. Therefore, our confidence in assigning non-detections as true absences is low, as owls could be easily missed. Passive acoustic monitoring remains a promising method but further work is required before it can be confidently implemented at the Grand Canyon.
Factors Affecting Acoustic Detection of Mexican Spotted Owls at Grand Canyon National Park
Effective wildlife management and conservation rely on accurate estimates of species demographics, including their abundance and distribution. However, monitoring programs are seldom able to detect species perfectly. Cryptic or rare species are often missed, even when present. These false absences can lead to inaccurate assumptions that may misguide management. Therefore, quantifying our ability to accurately detect species is crucial in deriving accurate estimates of species demographics. Passive acoustic monitoring is an emerging technology for surveying ecological soundscapes in ways that have not been possible until recently. The use of acoustic recorders as monitoring tools have thus increased rapidly in the last decade. In the last three years (2019-2021), custom acoustic recorders were used at Grand Canyon National Park to supplement existing long-term monitoring of Mexican Spotted Owls (Strix occidentalis lucida) within their historical nesting territories. However, the factors that influence our ability to detect owls at the Grand Canyon are not yet fully understood. Using acoustic recordings from distance trials and owl surveys, we evaluated the effects of distance, habitat type, wind, and other noise sources on the detection of Mexican Spotted Owls. We found that wind was the dominant source of noise detected during owl surveys, frequently occurring in the 2 hours before sunset, the same time that the owls were most vocally active. The probability of detecting sound by the recorders was higher at further distances in canyon habitats. Detection probability dropped faster in closed forests. Recorders varied widely in their ability to detect sound. For example, in ponderosa forest, some only dropped to 0.75 probability of detection at 100m, while others dropped to < 0.25. Therefore, our confidence in assigning non-detections as true absences is low, as owls could be easily missed. Passive acoustic monitoring remains a promising method but further work is required before it can be confidently implemented at the Grand Canyon.