Maps representing near-national waterfowl density and abundance of 13 individual species and 4 species groups (goldeneyes, mergansers, scoters, and scaup). Predictive models were built using Boosted Regression Tree analysis, data from the Waterfowl Breeding Population and Habitat Survey, and several environmental datasets. Methods used to create 17 species-level models are described in Barker et al. 2014 (ACE 9(2): 7). Guild-Level Maps (cavity nesters, ground nesters, and overwater Nesters) were produced by summing species-level observations and then built models at the guild level. The prediction of total waterfowl abundance was produced by summing the predictions from guild-level models (cavity nesters, ground nesters, and overwater nesters). Species specific model uncertainty are also provided.

We calculated population estimates for 81 landbird species in Bird Conservation Region 6 in Alberta, Canada, using spatially explicit models on roadside and off-road point-count surveys that incorporate land cover and climate as predictors. We compared our results with population estimates from Partners in Flight (PIF) and developed a framework to evaluate how the differences between the detection distance, time-of-day, roadside count, and habitat representation adjustments explain discrepancies between the 2 estimators.