Mapping migratory flyways in Asia using dynamic Brownian bridge movement models

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• 作者：Eric C Palm (1)
  Scott H Newman (2)
  Diann J Prosser (1)
  Xiangming Xiao (3) (4)
  Luo Ze (5)
  Nyambayar Batbayar (6)
  Sivananinthaperumal Balachandran (7)
  John Y Takekawa (8) (9)
  
  1. U.S. Geological Survey ; Patuxent Wildlife Research Center ; Beltsville ; MD ; 20705 ; USA
  2. Food and Agriculture Organization of the United Nations ; Emergency Center for Transboundary Animal Disease ; Hanoi ; Vietnam
  3. Department of Botany and Microbiology ; Center for Spatial Analysis ; University of Oklahoma ; Norman ; OK ; 73019 ; USA
  4. Institute of Biodiversity Science ; Fudan University ; Shanghai ; 200433 ; China
  5. Computer Network Information Center (CNIC) ; Chinese Academy of Sciences ; Beijing ; 100080 ; China
  6. Wildlife Science and Conservation Center ; Ulaanbaatar ; 210351 ; Mongolia
  7. Bombay Natural History Society ; Hornbill House ; Mumbai ; 400 001 ; India
  8. U.S. Geological Survey ; Western Ecological Research Center ; San Francisco Bay Estuary Field Station ; Vallejo ; CA ; 94592 ; USA
  9. National Audubon Society ; Science Division ; 220 Montgomery Street ; San Francisco ; CA ; 94104 ; USA
  
• 关键词：Dynamic Brownian bridge movement model ; Flyways ; Waterfowl ; Migration ; Stopover sites ; Space use ; Habitat conservation
• 刊名：Movement Ecology
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：3
• 期：1
• 全文大小：2,335 KB
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• 刊物主题：Nature Conservation;
• 出版者：BioMed Central
• ISSN：2051-3933

文摘

Background Identifying movement routes and stopover sites is necessary for developing effective management and conservation strategies for migratory animals. In the case of migratory birds, a collection of migration routes, known as a flyway, is often hundreds to thousands of kilometers long and can extend across political boundaries. Flyways encompass the entire geographic range between the breeding and non-breeding areas of a population, species, or a group of species, and they provide spatial frameworks for management and conservation across international borders. Existing flyway maps are largely qualitative accounts based on band returns and survey data rather than observed movement routes. In this study, we use satellite and GPS telemetry data and dynamic Brownian bridge movement models to build upon existing maps and describe waterfowl space use probabilistically in the Central Asian and East Asian-Australasian Flyways. Results Our approach provided new information on migratory routes that was not easily attainable with existing methods to describe flyways. Utilization distributions from dynamic Brownian bridge movement models identified key staging and stopover sites, migration corridors and general flyway outlines in the Central Asian and East Asian-Australasian Flyways. A map of space use from ruddy shelducks depicted two separate movement corridors within the Central Asian Flyway, likely representing two distinct populations that show relatively strong connectivity between breeding and wintering areas. Bar-headed geese marked at seven locations in the Central Asian Flyway showed heaviest use at several stopover sites in the same general region of high-elevation lakes along the eastern Qinghai-Tibetan Plateau. Our analysis of data from multiple Anatidae species marked at sites throughout Asia highlighted major movement corridors across species and confirmed that the Central Asian and East Asian-Australasian Flyways were spatially distinct. Conclusions The dynamic Brownian bridge movement model improves our understanding of flyways by estimating relative use of regions in the flyway while providing detailed, quantitative information on migration timing and population connectivity including uncertainty between locations. This model effectively quantifies the relative importance of different migration corridors and stopover sites and may help prioritize specific areas in flyways for conservation of waterbird populations.