At the end of the road: Lessons learned from comparing model- and design-based approaches to estimate population sizes of boreal birds in Alberta, Canada
Estimating population abundance is a challenging task complicated by the amount, type, and quality of available data. Conservationists have relied on design-based estimates from Partners in Flight (PIF), which primarily uses roadside data from the North American Breeding Bird Survey (BBS) to estimate populations sizes. However, the BBS was not designed to estimate population sizes. We developed models incorporating land cover and climate variables based on roadside and off-road point-count surveys. We calculated spatially explicit, model-based population estimates for 81 landbird species in Bird Conservation Region 6 in Alberta, Canada, and compared these to PIF estimates. We also 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 two estimators. We showed that the key assumptions of the PIF population size estimator were commonly violated in this region, and the two approaches provided very different population size estimates for most species. The average differences between estimators were explained by differences in the detection distance and time-of-day components, but these adjustments left much unexplained variation among species. Differences in the roadside count and habitat representation components explained most of the among-species variation. The variation caused by these factors was large enough to change the population size ranking of the species. The roadside count bias needs serious attention when roadside surveys are used to extrapolate over off-road areas. Habitat representation bias is likely prevalent in regions sparsely and non-representatively sampled by roadside surveys, such as the boreal region of North America, and thus population size estimates for these regions need to be treated with caution for certain species. Model-based integration of available data sources and additional sampling can contribute towards more accurate population size estimates for conservation in remote areas of North America.