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Although point counts are frequently used in ornithological studies, basic assumptions about detection probabilities often are untested. We apply a double-observer approach developed to estimate detection probabilities for aerial surveys (Cook and Jacobson 1979) to avian point counts. At each point count, a designated “primary” observer indicates to another (“secondary”) observer all birds detected. The secondary observer records all detections of the primary observer as well as any birds not detected by the primary observer. Observers alternate primary and secondary roles during the course of the survey. The approach permits estimation of observer-specific detection probabilities and bird abundance. We developed a set of models that incorporate different assumptions about sources of variation (e.g. observer, bird species) in detection probability. Seventeen field trials were conducted, and models were fit to the resulting data using program SURVIV. Single-observer point counts generally miss varying proportions of the birds actually present, and observer and bird species were found to be relevant sources of variation in detection probabilities. Overall detection probabilities (probability of being detected by at least one of the two observers) estimated using the double-observer approach were very high (>0.95), yielding precise estimates of avian abundance. We consider problems with the approach and recommend possible solutions, including restriction of the approach to fixed-radius counts to reduce the effect of variation in the effective radius of detection among various observers and to provide a basis for using spatial sampling to estimate bird abundance on large areas of interest. We believe that most questions meriting the effort required to carry out point counts also merit serious attempts to estimate detection probabilities associated with the counts. The double-observer approach is a method that can be used for this purpose.

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Conservation planning requires information at a variety of geographic scales, and it is often unclear whether surveys designed for other purposes will provide appropriate information for management at various scales. We evaluated the use of the North American Breeding Bird Survey (BBS) to meet information needs for conservation planning in Bird Conservation Regions (BCRs). The BBS originally was developed to provide regional estimates for states, provinces, physiographic regions, and larger areas. Many analyses have used physiographic regions within states/provinces as strata. We evaluated potential consequences of using BCRs instead of the BBS physiographic regions, testing for spatial differences in sample intensity within states and provinces. We reclassified the BBS survey routes to BCRs and conducted route regression trend (interval-specific population change) analyses for a variety of regions and time intervals. Our results were similar to those based on traditional BBS regions and suggest minimal consequences of the reclassification for the BBS sample. We summarized population change within BCRs and assessed the efficiency of the BBS in estimating population change for 421species surveyed. As would be expected from an omnibus survey, many species appeared to be poorly monitored by the BBS, with 42%of species encountered at <1bird/route from the survey, and 28%of trend estimates too imprecise to detect a 3%/year change over 35 years. Our results indicated that the quality of the survey for estimation of population change varied among BCRs. Population trends of species were heterogeneous over space and time, varying among BCRs for 76%of species and over time for 39%of species. Regional heterogeneity also existed in trends of species groups from the BBS. While 49%of all species in the survey had increasing populations, grassland breeding birds showed consistent declines, with only 18%of species having positive trend estimates. Bird conservation regions appear to provide reasonable strata for summary of BBS data. JOURNAL OF WILDLIFE MANAGEMENT 67(2):372-389

Land managers must balance the needs of a variety of species when manipulating habitats. Structured decision making provides a systematic means of defining choices and choosing among alternative management options; implementation of a structured decision requires quantitative approaches to predicting consequences of management on the relevant species. Multi‐species occupancy models provide a convenient framework for making structured decisions when the management objective is focused on a collection of species. These models use replicate survey data that are often collected on managed lands. Occupancy can be modeled for each species as a function of habitat and other environmental features, and Bayesian methods allow for estimation and prediction of collective responses of groups of species to alternative scenarios of habitat management. We provide an example of this approach using data from breeding bird surveys conducted in 2008 at the Patuxent Research Refuge in Laurel, Maryland, evaluating the effects of eliminating meadow and wetland habitats on scrub‐successional and woodland‐breeding bird species using summed total occupancy of species as an objective function. Removal of meadows and wetlands decreased value of an objective function based on scrub‐successional species by 23.3% (95% CI: 20.3–26.5), but caused only a 2% (0.5, 3.5) increase in value of an objective function based on woodland species, documenting differential effects of elimination of meadows and wetlands on these groups of breeding birds. This approach provides a useful quantitative tool for managers interested in structured decision making. © 2012 The Wildlife Society.