Does expected future landscape condition support proposed population objectives for boreal birds?

•Analysis of future habitat supply and population size for priority landbirds.•ALCES® landscape simulation model and statistical bird habitat models in BCR 6.•Three land use scenarios: business as usual, protected areas, climate change.•Boreal landbirds in mature and old forests exhibited greatest population declines.•New approach to step down BCR population objectives to habitat objectives. Assessing the feasibility of proposed Bird Conservation Region (BCR) population objectives requires comparing expected future population size estimates to proposed population objectives. Linking statistical bird habitat models with landscape simulation models can provide a direct method for assessing the ecological and economic implications of alternative land and resource scenarios within a BCR or BCR sub-region. We demonstrate our approach for analyses of future habitat supply and population size for a suite of priority landbird species using the ALCES® landscape simulation model and empirical bird habitat models within a multi-use landscape located in northeast Alberta, Canada and BCR 6-Boreal Taiga Plains. We used ALCES® to simulate future landscape condition over a 100year time period under three scenarios: business as usual, protected areas, and climate change. Shortfalls between simulated population size estimates at year 30 and proposed population objectives existed for each of the four priority bird species examined suggesting that expected future landscape condition will not support proposed population objectives for these species. Boreal species strongly associated with mature and old forest habitats exhibited population declines over the 100year simulation period. One habitat generalist, a species associated with both early and late seral stages, appeared to benefit from the range of land use scenarios examined. Our approach improves upon current static approaches used to step down BCR scale population objectives to sub-regional scale habitat objectives by utilizing statistical bird population response models to estimate density and a dynamic landscape simulation model to estimate expected future habitat condition.