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利用生态位模型解开热带亚洲城市鸟类筑巢碰撞的生物和非生物驱动因素。

Disentangling the biotic and abiotic drivers of bird-building collisions in a tropical Asian city with ecological niche modeling.

机构信息

Department of Biology and Museum of Southwestern Biology, University of New Mexico, Albuquerque, New Mexico, USA.

National Parks Board, Singapore, Singapore.

出版信息

Conserv Biol. 2024 Aug;38(4):e14255. doi: 10.1111/cobi.14255. Epub 2024 Mar 15.

DOI:10.1111/cobi.14255
PMID:38488338
Abstract

Bird collisions with buildings are responsible for a large number of bird deaths in cities around the world, yet they remain poorly studied outside North America. We conducted one of the first citywide fine-scale and landscape-scale analyses of bird-building collisions in Asia and used maximum entropy modeling (as commonly applied to species distribution modeling) in a novel way to assess the drivers of bird-building collisions in the tropical city-state of Singapore. We combined 7 years of community science observations with publicly available building and remote sensing data. Drivers of bird-building collisions varied among taxa. Some migratory taxa had a higher relative collision risk that was linked to areas with high building densities and high levels of nocturnal blue light pollution. Nonmigratory taxa had a higher collision risk in areas near forest cover. Projecting our results onto official long-term land-use plans, we predicted that future increases in bird-building collision risk stemmed from increases in blue light pollution and encroachment of buildings into forested areas and identified 6 potential collision hotspots linked to future developments. Our results suggest that bird-building collision mitigation measures need to account for the different drivers of collision for resident and migratory species and show that combining community science and ecological modeling can be a powerful approach for analyzing bird-building collision data.

摘要

鸟类与建筑物的碰撞导致了世界各地城市中大量鸟类死亡,但在北美以外,这些碰撞仍未得到充分研究。我们对亚洲进行了首次全市范围内的精细尺度和景观尺度的鸟类与建筑物碰撞分析,并以新颖的方式利用最大熵建模(通常应用于物种分布建模)来评估新加坡热带城邦鸟类与建筑物碰撞的驱动因素。我们将 7 年的社区科学观测与公开的建筑物和遥感数据相结合。鸟类与建筑物碰撞的驱动因素因分类群而异。一些迁徙分类群的相对碰撞风险较高,这与建筑密度高和夜间蓝光污染水平高的地区有关。非迁徙分类群在靠近森林覆盖的地区碰撞风险较高。我们将研究结果预测到官方的长期土地利用规划中,预计未来鸟类与建筑物碰撞风险的增加源于蓝光污染的增加以及建筑物侵入森林地区,并确定了与未来发展相关的 6 个潜在碰撞热点。我们的研究结果表明,鸟类与建筑物碰撞的缓解措施需要考虑到留鸟和候鸟的不同碰撞驱动因素,并表明结合社区科学和生态建模可以成为分析鸟类与建筑物碰撞数据的有力方法。

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