Estimating the size of bird populations is central to effective conservation planning and prudent management. I updated estimated regional bird populations for the East Gulf Coastal Plain of Mississippi using data from 275 North American Breeding Bird Surveys from 2009 to 2013. However, regional bird populations estimated from count surveys of breeding birds may be biased due to lack of empirical knowledge of the distance at which a species is effectively detected and the probability of detecting a species if it is present. I used data recorded within two distance classes (0–50 m and >50–400 m) and three 1-min time intervals on 130 Breeding Bird Surveys to estimate detection probability and effective detection distance for 77 species. Incorporating these empirical estimates of detection probability and detection distance resulted in estimated regional populations for these species that were markedly greater than regional populations estimated without species-specific estimates of detection parameters. Using the same Breeding Bird Survey data, I also estimated probability of site occupancy for 66 species and extrapolated this to the proportion of area occupied in the East Gulf Coastal Plain of Mississippi. I combined the area occupied with the reported range of breeding territory size for 54 species to obtain independent estimates of regional bird populations. Although the true population of these species is unknown, estimated populations that incorporated empirical estimates of detection probability and detection distance were more likely to be within the range of independently estimated, occupancy-based, regional population estimates than were population estimates that lacked empirical detection and distance information.
|Title||Estimating regional landbird populations from enhanced North American Breeding Bird Surveys|
|Authors||Daniel J. Twedt|
|Publication Subtype||Journal Article|
|Series Title||Journal of Field Ornithology|
|Record Source||USGS Publications Warehouse|
|USGS Organization||Patuxent Wildlife Research Center|
Daniel Twedt, Ph.D.
Daniel Twedt, Ph.D.