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- Publisher Website: 10.1016/j.ecolmodel.2017.06.004
- Scopus: eid_2-s2.0-85023626779
- WOS: WOS:000411771800007
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Article: Dynamic response of East Asian Greater White-fronted Geese to changes of environment during migration: Use of multi-temporal species distribution model
Title | Dynamic response of East Asian Greater White-fronted Geese to changes of environment during migration: Use of multi-temporal species distribution model |
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Authors | |
Keywords | Multi-temporal Dynamic water mask Satellite tracking Habitat selection Remote sensing Species distribution model (SDM) Spring migration |
Issue Date | 2017 |
Citation | Ecological Modelling, 2017, v. 360, p. 70-79 How to Cite? |
Abstract | © 2017 Elsevier B.V. Understanding how migratory species select habitats is essential for applied ecology and biological conservation. Although migratory species move across a wide range of environments during migration, their dynamic response to environments has rarely been considered. Taking advantage of the fine spatial-temporal resolution of satellite tracking data, we studied habitat selection of East Asian greater white-fronted geese (Anser albifrons) along their spring migration route from Yangtze River Basin to Lena Delta and Yana Bay. We developed a novel methodology to improve dynamic species distribution models (SDMs) by incorporating environmental variables derived from remotely sensed data precisely corresponding to migration time. Our results demonstrate that distance to the nearest water body, elevation, human population density and temperature contribute greatly to the models. Water-related and topographic factors (e.g., elevation, slope and distance to the nearest water body) were consistently associated with habitat selection of the geese from wintering area to breeding area, while the varied influences of temperature and human population density in different migration periods are closely related to their adaptation to local environments. In addition, response curves of vegetation index indicate that the geese are more strongly associated with food quality than quantity in wintering area and stopover sites. By building SDMs in different periods, we provide a unique dynamic perspective on how a long-distance migrant responds to different environments. The methodology proposed here could be integrated to future conservation management plans for predicting species relationship with fast changing environmental conditions. |
Persistent Identifier | http://hdl.handle.net/10722/296823 |
ISSN | 2023 Impact Factor: 2.6 2023 SCImago Journal Rankings: 0.824 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Li, Xueyan | - |
dc.contributor.author | Si, Yali | - |
dc.contributor.author | Ji, Luyan | - |
dc.contributor.author | Gong, Peng | - |
dc.date.accessioned | 2021-02-25T15:16:45Z | - |
dc.date.available | 2021-02-25T15:16:45Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Ecological Modelling, 2017, v. 360, p. 70-79 | - |
dc.identifier.issn | 0304-3800 | - |
dc.identifier.uri | http://hdl.handle.net/10722/296823 | - |
dc.description.abstract | © 2017 Elsevier B.V. Understanding how migratory species select habitats is essential for applied ecology and biological conservation. Although migratory species move across a wide range of environments during migration, their dynamic response to environments has rarely been considered. Taking advantage of the fine spatial-temporal resolution of satellite tracking data, we studied habitat selection of East Asian greater white-fronted geese (Anser albifrons) along their spring migration route from Yangtze River Basin to Lena Delta and Yana Bay. We developed a novel methodology to improve dynamic species distribution models (SDMs) by incorporating environmental variables derived from remotely sensed data precisely corresponding to migration time. Our results demonstrate that distance to the nearest water body, elevation, human population density and temperature contribute greatly to the models. Water-related and topographic factors (e.g., elevation, slope and distance to the nearest water body) were consistently associated with habitat selection of the geese from wintering area to breeding area, while the varied influences of temperature and human population density in different migration periods are closely related to their adaptation to local environments. In addition, response curves of vegetation index indicate that the geese are more strongly associated with food quality than quantity in wintering area and stopover sites. By building SDMs in different periods, we provide a unique dynamic perspective on how a long-distance migrant responds to different environments. The methodology proposed here could be integrated to future conservation management plans for predicting species relationship with fast changing environmental conditions. | - |
dc.language | eng | - |
dc.relation.ispartof | Ecological Modelling | - |
dc.subject | Multi-temporal | - |
dc.subject | Dynamic water mask | - |
dc.subject | Satellite tracking | - |
dc.subject | Habitat selection | - |
dc.subject | Remote sensing | - |
dc.subject | Species distribution model (SDM) | - |
dc.subject | Spring migration | - |
dc.title | Dynamic response of East Asian Greater White-fronted Geese to changes of environment during migration: Use of multi-temporal species distribution model | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.ecolmodel.2017.06.004 | - |
dc.identifier.scopus | eid_2-s2.0-85023626779 | - |
dc.identifier.volume | 360 | - |
dc.identifier.spage | 70 | - |
dc.identifier.epage | 79 | - |
dc.identifier.isi | WOS:000411771800007 | - |
dc.identifier.issnl | 0304-3800 | - |