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

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 entro...

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Published in:Conservation biology 2024-08, Vol.38 (4), p.e14255-n/a
Main Authors: Tan, David J. X., Freymueller, Nicholas A., Teo, Kah Ming, Symes, William S., Lum, Shawn K. Y., Rheindt, Frank E.
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description 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. Modelos de nicho ecológico para esclarecer los causantes bióticos y abióticos de las colisiones entre aves y edificios en una ciudad tropical asiática Resumen Las colisiones entre aves y edificios son causa de un gran número de muertes en todas las ciudades del mundo, y aun así se estudian muy poco fuera de América del Norte. Realizamos uno de los primeros análisis a escala fina y a escala de paisaje en una ciudad asiática y usamos el modelo de entropía máxima (como se aplica con frecuencia a los modelos de distribución de especies) de manera novedosa para analizar los causantes de estas colisiones en Singapur, una ciudad‐estado tropical. Combinamos siete años de observaciones de ciencia comunitaria con los datos públicos de teledetección y construcción. Los causantes de las colisiones entre aves y edificios variaron entre taxones. Algunos taxones migratorios tuvieron un riesgo de colisión relativamente más alto relacionado con áreas de alta densidad de edificios y niveles elevados de contaminación lumínica d
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X. ; Freymueller, Nicholas A. ; Teo, Kah Ming ; Symes, William S. ; Lum, Shawn K. Y. ; Rheindt, Frank E.</creator><creatorcontrib>Tan, David J. X. ; Freymueller, Nicholas A. ; Teo, Kah Ming ; Symes, William S. ; Lum, Shawn K. Y. ; Rheindt, Frank E.</creatorcontrib><description>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. Modelos de nicho ecológico para esclarecer los causantes bióticos y abióticos de las colisiones entre aves y edificios en una ciudad tropical asiática Resumen Las colisiones entre aves y edificios son causa de un gran número de muertes en todas las ciudades del mundo, y aun así se estudian muy poco fuera de América del Norte. Realizamos uno de los primeros análisis a escala fina y a escala de paisaje en una ciudad asiática y usamos el modelo de entropía máxima (como se aplica con frecuencia a los modelos de distribución de especies) de manera novedosa para analizar los causantes de estas colisiones en Singapur, una ciudad‐estado tropical. Combinamos siete años de observaciones de ciencia comunitaria con los datos públicos de teledetección y construcción. Los causantes de las colisiones entre aves y edificios variaron entre taxones. Algunos taxones migratorios tuvieron un riesgo de colisión relativamente más alto relacionado con áreas de alta densidad de edificios y niveles elevados de contaminación lumínica de luz azul nocturna. Los taxones no migratorios tuvieron un riesgo de colisión más elevado en las áreas cercanas a la cobertura forestal. Con la proyección de nuestros resultados sobre los planes oficiales de uso de suelo a largo plazo, pronosticamos que el incremento en el futuro de colisiones entre aves y edificios vendrá del incremento en la contaminación de luz azul y la invasión de edificios en las áreas forestales; también identificamos seis potenciales puntos calientes de colisión relacionados a futuros desarrollos inmobiliarios. Nuestros resultados sugieren que para mitigar estas colisiones se necesita considerar los diferentes causantes de dichas colisiones para las especies migratorias y residentes y también muestran que la combinación de la ciencia comunitaria y los modelos ecológicos puede ser una estrategia poderosa para analizar los datos de colisiones entre aves y edificios 利用生态位模型厘清亚洲热带城市中鸟类撞击建筑物的生物和非生物驱动因素 【摘要】在世界各地的城市中, 鸟类撞击建筑物都是造成大量鸟类死亡的重要原因, 但在北美以外的地区, 相关研究仍很稀缺。我们在亚洲首次进行了全市范围内鸟撞的精细尺度和景观尺度分析, 并以一种新的方式利用最大熵模型(通常应用于物种分布模型)来评估热带城市国家新加坡鸟撞的驱动因素。本研究整合了7年的社区科学观测结果与公开的建筑和遥感数据。我们发现鸟撞的驱动因素因类群而异, 一些候鸟的相对撞击风险较高, 这与建筑密度高和夜间蓝光污染严重的地区有关;而留鸟则在森林附近的撞击风险较高。结合我们的结果与官方的长期土地利用规划, 我们预测未来鸟撞风险的增加源于蓝光污染的增加和建筑对森林地区的侵占, 并确定了与未来发展相关的六个潜在鸟撞热点地区。我们的研究结果表明, 减缓鸟撞的措施需要考虑留鸟和候鸟发生撞击的不同驱动因素。我们的研究还展示了将社区科学和生态建模相结合是分析鸟撞数据的有效方法。【翻译:胡怡思;审校:聂永刚】</description><identifier>ISSN: 0888-8892</identifier><identifier>ISSN: 1523-1739</identifier><identifier>EISSN: 1523-1739</identifier><identifier>DOI: 10.1111/cobi.14255</identifier><identifier>PMID: 38488338</identifier><language>eng</language><publisher>United States: Blackwell Publishing Ltd</publisher><subject>bird strikes ; Birds ; Buildings ; ciencia comunitaria ; Cities ; colisiones con ventanas ; Collisions ; community science ; Ecological distribution ; Ecological models ; Ecological niches ; ecología urbana ; Encroachment ; Forests ; Geographical distribution ; golpes de aves ; Land use ; Light pollution ; Light sources ; Maxent ; Maxent软件 ; Maximum entropy ; Migratory species ; Mitigation ; Modelling ; Niches ; Remote sensing ; Taxa ; urban ecology ; urbanización ; urbanization ; window collisions ; 城市化 ; 城市生态学 ; 窗户碰撞 ; 群落科学 ; 鸟类撞击</subject><ispartof>Conservation biology, 2024-08, Vol.38 (4), p.e14255-n/a</ispartof><rights>2024 Society for Conservation Biology.</rights><rights>2024, Society for Conservation Biology.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c3165-4c9dfeac40eb941a5b273d6cfdc0482408624483670e58f2c53c69bf37ace11e3</cites><orcidid>0000-0001-7019-7871 ; 0000-0001-8946-7085</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38488338$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Tan, David J. X.</creatorcontrib><creatorcontrib>Freymueller, Nicholas A.</creatorcontrib><creatorcontrib>Teo, Kah Ming</creatorcontrib><creatorcontrib>Symes, William S.</creatorcontrib><creatorcontrib>Lum, Shawn K. Y.</creatorcontrib><creatorcontrib>Rheindt, Frank E.</creatorcontrib><title>Disentangling the biotic and abiotic drivers of bird–building collisions in a tropical Asian city with ecological niche modeling</title><title>Conservation biology</title><addtitle>Conserv Biol</addtitle><description>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. Modelos de nicho ecológico para esclarecer los causantes bióticos y abióticos de las colisiones entre aves y edificios en una ciudad tropical asiática Resumen Las colisiones entre aves y edificios son causa de un gran número de muertes en todas las ciudades del mundo, y aun así se estudian muy poco fuera de América del Norte. Realizamos uno de los primeros análisis a escala fina y a escala de paisaje en una ciudad asiática y usamos el modelo de entropía máxima (como se aplica con frecuencia a los modelos de distribución de especies) de manera novedosa para analizar los causantes de estas colisiones en Singapur, una ciudad‐estado tropical. Combinamos siete años de observaciones de ciencia comunitaria con los datos públicos de teledetección y construcción. Los causantes de las colisiones entre aves y edificios variaron entre taxones. Algunos taxones migratorios tuvieron un riesgo de colisión relativamente más alto relacionado con áreas de alta densidad de edificios y niveles elevados de contaminación lumínica de luz azul nocturna. Los taxones no migratorios tuvieron un riesgo de colisión más elevado en las áreas cercanas a la cobertura forestal. Con la proyección de nuestros resultados sobre los planes oficiales de uso de suelo a largo plazo, pronosticamos que el incremento en el futuro de colisiones entre aves y edificios vendrá del incremento en la contaminación de luz azul y la invasión de edificios en las áreas forestales; también identificamos seis potenciales puntos calientes de colisión relacionados a futuros desarrollos inmobiliarios. Nuestros resultados sugieren que para mitigar estas colisiones se necesita considerar los diferentes causantes de dichas colisiones para las especies migratorias y residentes y también muestran que la combinación de la ciencia comunitaria y los modelos ecológicos puede ser una estrategia poderosa para analizar los datos de colisiones entre aves y edificios 利用生态位模型厘清亚洲热带城市中鸟类撞击建筑物的生物和非生物驱动因素 【摘要】在世界各地的城市中, 鸟类撞击建筑物都是造成大量鸟类死亡的重要原因, 但在北美以外的地区, 相关研究仍很稀缺。我们在亚洲首次进行了全市范围内鸟撞的精细尺度和景观尺度分析, 并以一种新的方式利用最大熵模型(通常应用于物种分布模型)来评估热带城市国家新加坡鸟撞的驱动因素。本研究整合了7年的社区科学观测结果与公开的建筑和遥感数据。我们发现鸟撞的驱动因素因类群而异, 一些候鸟的相对撞击风险较高, 这与建筑密度高和夜间蓝光污染严重的地区有关;而留鸟则在森林附近的撞击风险较高。结合我们的结果与官方的长期土地利用规划, 我们预测未来鸟撞风险的增加源于蓝光污染的增加和建筑对森林地区的侵占, 并确定了与未来发展相关的六个潜在鸟撞热点地区。我们的研究结果表明, 减缓鸟撞的措施需要考虑留鸟和候鸟发生撞击的不同驱动因素。我们的研究还展示了将社区科学和生态建模相结合是分析鸟撞数据的有效方法。【翻译:胡怡思;审校:聂永刚】</description><subject>bird strikes</subject><subject>Birds</subject><subject>Buildings</subject><subject>ciencia comunitaria</subject><subject>Cities</subject><subject>colisiones con ventanas</subject><subject>Collisions</subject><subject>community science</subject><subject>Ecological distribution</subject><subject>Ecological models</subject><subject>Ecological niches</subject><subject>ecología urbana</subject><subject>Encroachment</subject><subject>Forests</subject><subject>Geographical distribution</subject><subject>golpes de aves</subject><subject>Land use</subject><subject>Light pollution</subject><subject>Light sources</subject><subject>Maxent</subject><subject>Maxent软件</subject><subject>Maximum entropy</subject><subject>Migratory species</subject><subject>Mitigation</subject><subject>Modelling</subject><subject>Niches</subject><subject>Remote sensing</subject><subject>Taxa</subject><subject>urban ecology</subject><subject>urbanización</subject><subject>urbanization</subject><subject>window collisions</subject><subject>城市化</subject><subject>城市生态学</subject><subject>窗户碰撞</subject><subject>群落科学</subject><subject>鸟类撞击</subject><issn>0888-8892</issn><issn>1523-1739</issn><issn>1523-1739</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kU1uFDEQhS0EIkNgwwGQJTYIqYN_e-xlGP4iRcoG1pbbdk8q8tiD3U00O8QVcsOcBE9mYMGC2lRJ9dV7JT2EXlJyRlu9c3mAMyqYlI_QgkrGO7rk-jFaEKVUp5RmJ-hZrTeEEC2peIpOuBJKca4W6NcHqCFNNq0jpDWergMeIE_gsE0e2-PsC_wIpeI8tm3x9z_vhhmi31-4HCNUyKliSNjiqeQtOBvxeQWbsINph29husahkXn9sErgms8m-7A3fY6ejDbW8OLYT9G3Tx-_rr50l1efL1bnl53jtJedcNqPwTpBwqAFtXJgS-57N3pHhGKCqJ4JoXi_JEGqkTnJXa-HkS-tC5QGforeHHS3JX-fQ53MBqoLMdoU8lwN01Ix3XMtGvr6H_QmzyW17wwnzUIIqUmj3h4oV3KtJYxmW2Bjy85QYvbJmH0y5iGZBr86Ss7DJvi_6J8oGkAPwC3EsPuPlFldvb84iP4GHoebCA</recordid><startdate>202408</startdate><enddate>202408</enddate><creator>Tan, David J. 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X.</au><au>Freymueller, Nicholas A.</au><au>Teo, Kah Ming</au><au>Symes, William S.</au><au>Lum, Shawn K. Y.</au><au>Rheindt, Frank E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Disentangling the biotic and abiotic drivers of bird–building collisions in a tropical Asian city with ecological niche modeling</atitle><jtitle>Conservation biology</jtitle><addtitle>Conserv Biol</addtitle><date>2024-08</date><risdate>2024</risdate><volume>38</volume><issue>4</issue><spage>e14255</spage><epage>n/a</epage><pages>e14255-n/a</pages><issn>0888-8892</issn><issn>1523-1739</issn><eissn>1523-1739</eissn><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. Modelos de nicho ecológico para esclarecer los causantes bióticos y abióticos de las colisiones entre aves y edificios en una ciudad tropical asiática Resumen Las colisiones entre aves y edificios son causa de un gran número de muertes en todas las ciudades del mundo, y aun así se estudian muy poco fuera de América del Norte. Realizamos uno de los primeros análisis a escala fina y a escala de paisaje en una ciudad asiática y usamos el modelo de entropía máxima (como se aplica con frecuencia a los modelos de distribución de especies) de manera novedosa para analizar los causantes de estas colisiones en Singapur, una ciudad‐estado tropical. Combinamos siete años de observaciones de ciencia comunitaria con los datos públicos de teledetección y construcción. Los causantes de las colisiones entre aves y edificios variaron entre taxones. Algunos taxones migratorios tuvieron un riesgo de colisión relativamente más alto relacionado con áreas de alta densidad de edificios y niveles elevados de contaminación lumínica de luz azul nocturna. Los taxones no migratorios tuvieron un riesgo de colisión más elevado en las áreas cercanas a la cobertura forestal. Con la proyección de nuestros resultados sobre los planes oficiales de uso de suelo a largo plazo, pronosticamos que el incremento en el futuro de colisiones entre aves y edificios vendrá del incremento en la contaminación de luz azul y la invasión de edificios en las áreas forestales; también identificamos seis potenciales puntos calientes de colisión relacionados a futuros desarrollos inmobiliarios. Nuestros resultados sugieren que para mitigar estas colisiones se necesita considerar los diferentes causantes de dichas colisiones para las especies migratorias y residentes y también muestran que la combinación de la ciencia comunitaria y los modelos ecológicos puede ser una estrategia poderosa para analizar los datos de colisiones entre aves y edificios 利用生态位模型厘清亚洲热带城市中鸟类撞击建筑物的生物和非生物驱动因素 【摘要】在世界各地的城市中, 鸟类撞击建筑物都是造成大量鸟类死亡的重要原因, 但在北美以外的地区, 相关研究仍很稀缺。我们在亚洲首次进行了全市范围内鸟撞的精细尺度和景观尺度分析, 并以一种新的方式利用最大熵模型(通常应用于物种分布模型)来评估热带城市国家新加坡鸟撞的驱动因素。本研究整合了7年的社区科学观测结果与公开的建筑和遥感数据。我们发现鸟撞的驱动因素因类群而异, 一些候鸟的相对撞击风险较高, 这与建筑密度高和夜间蓝光污染严重的地区有关;而留鸟则在森林附近的撞击风险较高。结合我们的结果与官方的长期土地利用规划, 我们预测未来鸟撞风险的增加源于蓝光污染的增加和建筑对森林地区的侵占, 并确定了与未来发展相关的六个潜在鸟撞热点地区。我们的研究结果表明, 减缓鸟撞的措施需要考虑留鸟和候鸟发生撞击的不同驱动因素。我们的研究还展示了将社区科学和生态建模相结合是分析鸟撞数据的有效方法。【翻译:胡怡思;审校:聂永刚】</abstract><cop>United States</cop><pub>Blackwell Publishing Ltd</pub><pmid>38488338</pmid><doi>10.1111/cobi.14255</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0001-7019-7871</orcidid><orcidid>https://orcid.org/0000-0001-8946-7085</orcidid></addata></record>
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identifier ISSN: 0888-8892
ispartof Conservation biology, 2024-08, Vol.38 (4), p.e14255-n/a
issn 0888-8892
1523-1739
1523-1739
language eng
recordid cdi_proquest_miscellaneous_2958296394
source Wiley
subjects bird strikes
Birds
Buildings
ciencia comunitaria
Cities
colisiones con ventanas
Collisions
community science
Ecological distribution
Ecological models
Ecological niches
ecología urbana
Encroachment
Forests
Geographical distribution
golpes de aves
Land use
Light pollution
Light sources
Maxent
Maxent软件
Maximum entropy
Migratory species
Mitigation
Modelling
Niches
Remote sensing
Taxa
urban ecology
urbanización
urbanization
window collisions
城市化
城市生态学
窗户碰撞
群落科学
鸟类撞击
title Disentangling the biotic and abiotic drivers of bird–building collisions in a tropical Asian city with ecological niche modeling
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