Point counts are one of the most widely used and efficient approaches to survey land‐bird populations. A new approach to point‐count surveys involves the use of 2 observers, which allows the calculation of a detection probability for each bird species. Detection probabilities derived from 2 observers permit investigators to calculate a corrected abundance estimate that accounts for birds present but not detected. We evaluated 2 double‐observer point count approaches: the dependent‐observer approach and the independent‐observer approach. The dependent‐observer approach involves 2 observers recording data together on a single data sheet with one observer designated the primary observer and the other designated as the secondary observer. The primary observer verbally dictates the number of each species detected while the secondary observer records this information; the secondary observer also records birds that the primary observer did not detect. The independent‐observer approach involves 2 observers recording data independently on separate data sheets without verbal communication between observers. This study compares the detection probabilities and associated levels of precision generated by both double‐observer approaches to ascertain which technique generates data that are more accurate and more feasible to apply in the field. We conducted point counts at 137 point locations in northern West Virginia during the spring of 2000 and 2001 using both double‐observer approaches. We generated detection probabilities and abundances from data collected using both double‐observer approaches using program DOBSERV. The dependent‐observer approach resulted in higher observer‐specific and joint detection probabilities, as well as lower standard errors of detection probability across most cover types. Species‐specific detection probabilities were higher across all cover types under the dependent‐observer approach. Given the higher detection probabilities and associated precision combined with fewer logistical constraints, we suggest that the dependent‐observer approach be used when investigators are interested in surveying birds using point counts.

Aim  We examined the influences of regional climate and land‐use variables on mallard (Anas platyrhynchos), blue‐winged teal (Anas discors), ruddy duck (Oxyura jamaicensis) and pied‐billed grebe (Podilymbus podiceps) abundances to inform conservation planning in the Prairie Pothole Region of the United States. Location  The US portion of Bird Conservation Region 11 (US‐BCR11, the Prairie Potholes), which encompasses six states within the United States: Montana, North Dakota, South Dakota, Nebraska, Minnesota and Iowa. Methods  We used data from the North American Breeding Bird Survey (NABBS), the National Land Cover Data Set, and the National Climatic Data Center to model the effects of environmental variables on waterbird abundance. We evaluated land‐use covariates at three logarithmically related spatial scales (1000, 10,000 and 100,000 ha), and constructed hierarchical spatial count models a priori using information from published habitat associations. Model fitting was performed using a hierarchical modelling approach within a Bayesian framework. Results  Models with the same variables expressed at different scales were often in the best model subset, indicating that the influence of spatial scale was small. Both land‐use and climate variables contributed strongly to predicting waterbird abundance in US‐BCR11. The strongest positive influences on waterbird abundance were the percentage of wetland area across all three spatial scales, herbaceous vegetation and precipitation variables. Other variables that we included in our models did not appear to influence waterbirds in this study. Main conclusions  Understanding the relationships of waterbird abundance to climate and land use may allow us to make predictions of future distribution and abundance as environmental factors change. Additionally, results from this study can suggest locations where conservation and management efforts should be focused.

Bird populations are influenced by a variety of factors at both small and large scales that range from the presence of suitable nesting habitat, predators, and food supplies to climate conditions and land-use patterns. We evaluated the influences of regional climate and land-use variables on wetland breeding birds in the Canada section of Bird Conservation Region 11 (CA-BCR11), the Prairie Potholes. We used bird abundance data from the North American Breeding Bird Survey, land-use data from the Prairie Farm Rehabilitation Administration, and weather data from the National Climatic Data and Information Archive to model effects of regional environmental variables on bird abundance. Models were constructed a priori using information from published habitat associations in the literature, and fitting was performed with WinBUGS using Markov chain Monte Carlo techniques. Both land-use and climate variables contributed to predicting bird abundance in CA-BCR11, although climate predictors contributed the most to improving model fit. Examination of regional effects of climate and land use on wetland birds in CA-BCR11 revealed relationships with environmental covariates that are often overlooked by small-scale habitat studies. Results from these studies can be used to improve conservation and management planning for regional populations of avifauna.