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Tables representing species specific mean density(males/ha) by region and landcover classes. Models for each bird conservation regions (BCRs) intersecting Canadian jurisdictional boundaries were based on covariates such as tree species biomass (local and landscape scale), forest age, topography, land use, and climate. We used a post-hoc stratification (‘post-stratification’) approach to estimate land cover based density estimates (males per ha) for each species and regions (Canada and subunits). We classified the predictive maps according to the 2005 MODIS-based North American landcover map into major land cover types (Conifer, Taiga Conifer, Deciduous, Mixedwood, Shrub, Grass, Arctic Shrub, Arctic Grass, Wetland, Cropland) and calculated the mean of the pixel level predicted densities. Uncertainty was based on the 5th and 95th percentiles of the bootstrap distribution.
Maps of density (males/ha) in relation to environmental covariates, using the Boreal Avian Modelling Project database of point-count surveys.
Species-specific spatiotemporal abundance for 18 waterfowl species across Canada based on annual species counts of 2,227 aerial-survey segments over a period of 25 years (1990–2015). Combining machine-learning and hierarchical regression modelling, we created maps and spatial data objects (TIF files) of recorded total indicated pairs (TIP), predicted TIP, Gaussian Markov random fields (GMRFs) and conditional predictive ordinates (CPO).
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.
Baseline (1996–2017) and projected (2011-2100) maps of predicted mean indicated breeding pairs (IBP) and standard deviation (SD) for the 12 waterfowl species in Eastern Canada. Projected means were summarized for the three 30-year periods under the “low” (RCP4.5) and “high” (RCP8.5) greenhouse gas concentration trajectories. From the projected abundances, we also computed maps of climate suitability indices per 12 species. PDF maps and spatial data objects (TIFF files) for the four time-lag schemes under “low” (RCP4.5) and “high” (RCP8.5) greenhouse gas concentration trajectories.
Species specific mean projections and uncertainty estimates (coefficient of variation) of80 boreal-breeding songbird species generated using boosted regression tree models for the current period (based on climate data from 1961-1990) and three future time periods (2011–2040, 2041–2070, 2071–2100).