Abstract
AbstractBird-building collisions are responsible for a large number of bird deaths in cities around the world, yet they remain poorly studied outside of North America. This study presents one of the first city-wide fine-scale and landscape-scale analyses of bird-building collisions from Asia and represents a novel application of maximum entropy modeling (as commonly applied to species distribution modeling) to assess the drivers of bird-building collisions in the tropical city-state of Singapore. Our results show that the drivers of bird-building collisions often vary among taxa, with several migratory taxa having a higher relative collision risk linked to areas with high building densities and high levels of nocturnal blue light pollution. In contrast, non-migratory taxa had a higher collision risk in areas proximate to woodland cover. Projecting these models onto high-fidelity long-term government land-use plans, we demonstrate that our approach can be applied to predict future changes in bird-building collision risk stemming from future increases in blue light pollution and encroachment of buildings into forested areas. Our results suggest that bird-building collision mitigation measures need to account for the differential drivers of collision across both resident and migratory species, and show that combining community science and ecological modeling can be a powerful approach for analyzing bird-building collision data.Article impact statementInferring the drivers and distribution patterns of bird-building collision hotspots in Singapore using community science and maximum entropy modeling
Publisher
Cold Spring Harbor Laboratory
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