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dc.contributor.authorThompson, Sarah J.
dc.contributor.authorHandel, Colleen M.
dc.contributor.authorMcNew, Lance B.
dc.date.accessioned2018-04-05T13:59:30Z
dc.date.available2018-04-05T13:59:30Z
dc.date.issued2017-09
dc.identifier.citationThompson, Sarah J., Colleen M. Handel, and Lance B. Mcnew. "Autonomous acoustic recorders reveal complex patterns in avian detection probability." Journal of Wildlife Management 81, no. 7 (September 2017): 1228-1241. DOI: 10.1002/jwmg.21285.en_US
dc.identifier.issn0022-541X
dc.identifier.urihttps://scholarworks.montana.edu/xmlui/handle/1/14475
dc.description.abstractAvian point-count surveys are typically designed to occur during periods when birds are consistently active and singing, but seasonal and diurnal patterns of detection probability are often not well understood and may vary regionally or between years. We deployed autonomous acoustic recorders to assess how avian availability for detection (i.e., the probability that a bird signals its presence during a recording) varied during the breeding season with time of day, date, and weather-related variables at multiple subarctic tundra sites in Alaska, USA, 2013-2014. A single observer processed 2,692 10-minute recordings across 11 site-years. We used time-removal methods to assess availability and used generalized additive models to examine patterns of detectability (joint probability of presence, availability, and detection) for 16 common species. Despite lack of distinct dawn or dusk, most species displayed circadian vocalization patterns, with detection rates generally peaking between 0800 hours and 1200 hours but remaining high as late as 2000 hours for some species. Between 2200 hours and 0500 hours, most species\' detection rates dropped to near 0, signaling a distinctive rest period. Detectability dropped sharply for most species in early July. For all species considered, time-removal analysis indicated nearly 100% likelihood of detection during a 10-minute recording conducted in June, between 0500 hours and 2000 hours. This indicates that non-detections during appropriate survey times and dates were attributable to the species\' absence or that silent birds were unlikely to initiate singing during a 10-minute interval, whereas vocally active birds were singing very frequently. Systematic recordings revealed a gradient of species\' presence at each site, from ubiquitous to incidental. Although the total number of species detected at a site ranged from 16 to 27, we detected only 4 to 15 species on 5% of the site\'s recordings. Recordings provided an unusually detailed and consistent dataset that allowed us to identify, among other things, appropriate survey dates and times for species breeding at northern latitudes. Our results also indicated that more recordings of shorter duration (1-4min) may be most efficient for detecting passerines. Our paper describes in detail the vocalization patterns of subarctic birds based on analysis of >2,600 acoustic recordings. We found that most species were highly detectable immediately upon arrival on breeding areas and that detectability remained high for most hours of the day. Additionally, when processing audio recordings, we found that in any single 10-minute recording, the majority of species detected were noted within the first minute; thus, individuals that are present and available to be detected by song or call tend to be highly detectable during a discrete time interval and more frequent, shorter duration recordings might be a more efficient way to detect the species using a given sampling area.en_US
dc.description.sponsorshipWildlife Program of the USGS Ecosystems Mission Area;en_US
dc.titleAutonomous acoustic recorders reveal complex patterns in avian detection probabilityen_US
mus.citation.extentfirstpage1228en_US
mus.citation.extentlastpage1241en_US
mus.citation.issue7en_US
mus.citation.journaltitleJournal of Wildlife Managementen_US
mus.citation.volume81en_US
mus.identifier.categoryLife Sciences & Earth Sciencesen_US
mus.identifier.doi10.1002/jwmg.21285en_US
mus.relation.collegeCollege of Agricultureen_US
mus.relation.departmentAnimal & Range Sciences.en_US
mus.relation.universityMontana State University - Bozemanen_US
mus.data.thumbpage7en_US


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