Mahon, C. L., Bayne, E. M., Sólymos, P., Matsuoka, S. M., Carlson,
M., Dzus, E., Schmiegelow, F. K. A., Cumming, S. G., & Song, S. J.
(2013): Does expected future landscape condition support proposed
population objectives for boreal birds? Forest Ecology and Management,
DOI: 10.1016/j.foreco.2013.10.025
Abstract
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 Plans. We used ALCES® to simulate future landscape condition over a 100 year 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 100 year 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.
Keywords
Bird Conservation Regions, Boreal forest, Landscape simulation model, Land use scenarios, Partners in Flight, Population 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 Plans. We used ALCES® to simulate future landscape condition over a 100 year 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 100 year 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.
Keywords
Bird Conservation Regions, Boreal forest, Landscape simulation model, Land use scenarios, Partners in Flight, Population objectives
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