Autonomous Recording Units
The Idea –
Public land management agencies, conservation organizations, and private corporations have begun to realize how useful landbirds are as indicators of land management effects. Unfortunately, the use of human observers poses a number of concerns for those who wish to understand patterns of bird abundance. One concern involves the cost associated with having to hire and train a large number of seasonal field technicians every year. Another involves sampling biases associated with the use of human observers. An alternative that may circumvent or alleviate some of these concerns involves the use of Autonomous Recording Units (ARUs) to detect birds through the use of recordings that can then be analyzed later in the laboratory. The purpose of this study was to test the efficacy of ARUs in detecting birds at points where observers simultaneously conducted traditional point counts in the field.
Methods –
Ten ARUs were deployed at a total of 63 points in forests near Missoula, Montana, from 30 May-4 July 2007. You can examine the distribution of points using our geospatial web interface here. Between 0600 and 1000 on one of two days when the ARU was recording for a 5-hr period, an observer conducted a 10-min count using a basic point-count protocol. We then compared bird lists from the two methods and accounted for differences in results.
Results –
Two human observers and the ARUs generated a total of 858 bird species detections that were distributed across 86 different bird species. On average, 9.7% of the 858 bird species detections were recorded by the ARU only, 40.9% by the human only, and 49.4% by both the ARU and human (see Table).
Method |
Observer |
Totals |
|
RLH |
RJS |
||
Human only |
185 (35.6%) |
166 (49.1%) |
351 (40.9%) |
Human and ARU |
272 (52.3%) |
152 (45.0%) |
424 (49.4%) |
ARU only |
63 (12.1%) |
20 (5.9%) |
83 (9.7%) |
Totals |
520 (100.0%) |
338 (100.0%) |
858 (100.0%) |
In general, about half of the detections missed by the ARU were too distant. Even though the use of more sensitive recording equipment might eliminate those misses, a large number of detections were also missed by the ARUs because they resulted from visual cues alone, or were too hard to identify or overlooked in the lab. About two-thirds of the detections missed by the human observers were simply overlooked in the field; most of the rest were the result of misidentifications in the lab. The failure of ARUs to record a large proportion of the detections recorded by human observers, combined with errors in detecting or identifying sounds in the lab and the extra time and cost associated with use of ARUs, suggest that they would not provide a cost effective means of gathering data for traditional point-count surveys.
Annual Reports or Publications from this Project –
click here for copy of MS submitted to Journal of Field Ornithology.
Funders –
USFS San Dimas Technology & Development Center’s Inventory and Monitoring Program, and University of Montana (Undergraduate Research Award). Equipment and software were provided by the Cornell Lab of Ornithology.
Contact –
Richard Hutto (hutto@mso.umt.edu)