A generalized modeling framework for spatially extensive species abundance prediction and population estimation

Abstract Spatially explicit estimates of species abundance and distribution are increasingly needed to support conservation planning and management across multiple spatial scales. We present a generalized modeling framework that bridges the gap between local studies and regional to national planning by compiling and harmonizing diverse datasets to predict avian abundance at fine resolution and broad extent. We applied detectability offsets to integrate point‐count data from over 250,000 locations across subarctic Canada. Data were subsampled by two time periods and 16 geographic regions, and we used boosted regression trees to model the density of 143 boreal landbird species as a function of climate, vegetation composition (local [250 m] and landscape [~1.5 km]), land cover, and topography. Bootstrapped regional predictions were combined to generate density maps, region‐ and habitat‐specific estimates, and Canada‐wide population totals. We estimated ~3.56 billion breeding males (7.13 billion individuals), with most occurring in boreal and hemi‐boreal regions. Forest generalists accounted for nearly half the total (1.57 billion males), followed by boreal specialists (1.05 billion), habitat generalists (350 million), and species associated with eastern forests (274 million), grasslands (124 million), western forests (74.7 million), wetlands (63.5 million), and Arctic tundra (17.7 million). Introduced species totaled 48.9 million breeding males. Across species, landscape‐level vegetation composition explained most variation in abundance, indicating that climate effects are primarily indirect, operating through vegetation. Landscape‐scale variables were critical to capturing this variation. Model classification accuracy was highest for forest‐ and grassland‐associated species (lowest for mountain and urban species), and for the families Regulidae and Phasianidae (lowest for Bombycillidae and Paridae). This work provides a standardized, updatable, and reproducible workflow for generating spatially explicit bird abundance estimates. These products can be revised as new data become available and used to support ongoing conservation and land‐use decisions.