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Affiliation(s)
- Muyang Lu
- Ecology and Evolutionary Biology Yale University New Haven CT USA
- Center for Biodiversity and Global Change Yale University New Haven CT USA
| | - Kevin Winner
- Ecology and Evolutionary Biology Yale University New Haven CT USA
- Center for Biodiversity and Global Change Yale University New Haven CT USA
| | - Walter Jetz
- Ecology and Evolutionary Biology Yale University New Haven CT USA
- Center for Biodiversity and Global Change Yale University New Haven CT USA
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2
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Abstract
Monitoring avian migration within subarctic regions of the globe poses logistical challenges. Populations in these regions often encounter the most rapid effects of changing climates, and these seasonally productive areas are especially important in supporting bird populations-emphasizing the need for monitoring tools and strategies. To this end, we leverage the untapped potential of weather surveillance radar data to quantify active migration through the airspaces of Alaska. We use over 400 000 NEXRAD radar scans from seven stations across the state between 1995 and 2018 (86% of samples derived from 2013 to 2018) to measure spring and autumn migration intensity, phenology and directionality. A large bow-shaped terrestrial migratory system spanning the southern two-thirds of the state was identified, with birds generally moving along a northwest-southeast diagonal axis east of the 150th meridian, and along a northeast-southwest axis west of this meridian. Spring peak migration ranged from 3 May to 30 May and between, 18 August and 12 September during the autumn, with timing across stations predicted by longitude, rather than latitude. Across all stations, the intensity of migration was greatest during the autumn as compared to spring, highlighting the opportunity to measure seasonal indices of net breeding productivity for this important system as additional years of radar measurements are amassed.
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Affiliation(s)
| | - Daniel Sheldon
- College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, USA
| | - Kevin Winner
- College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, USA.,Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA.,Center for Biodiversity and Global Change, Yale University, New Haven, CT, USA
| | - Carolyn S Burt
- Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO, USA
| | - Kyle G Horton
- Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO, USA
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3
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Newcombe PB, Nilsson C, Lin TY, Winner K, Bernstein G, Maji S, Sheldon D, Farnsworth A, Horton KG. Migratory flight on the Pacific Flyway: strategies and tendencies of wind drift compensation. Biol Lett 2019; 15:20190383. [PMID: 31530114 DOI: 10.1098/rsbl.2019.0383] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Applications of remote sensing data to monitor bird migration usher a new understanding of magnitude and extent of movements across entire flyways. Millions of birds move through the western USA, yet this region is understudied as a migratory corridor. Characterizing movements in the Pacific Flyway offers a unique opportunity to study complementary patterns to those recently highlighted in the Atlantic and Central Flyways. We use weather surveillance radar data from spring and autumn (1995-2018) to examine migrants' behaviours in relation to winds in the Pacific Flyway. Overall, spring migrants tended to drift on winds, but less so at northern latitudes and farther inland from the Pacific coastline. Relationships between winds and autumn flight behaviours were less striking, with no latitudinal or coastal dependencies. Differences in the preferred direction of movement (PDM) and wind direction predicted drift patterns during spring and autumn, with increased drift when wind direction and PDM differences were high. We also observed greater total flight activity through the Pacific Flyway during the spring when compared with the autumn. Such complex relationships among birds' flight strategies, winds and seasonality highlight the variation within a migration system. Characterizations at these scales complement our understanding of strategies to clarify aerial animal movements.
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Affiliation(s)
| | - Cecilia Nilsson
- Cornell Lab of Ornithology, Cornell University, Ithaca, NY, USA
| | - Tsung-Yu Lin
- College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, USA
| | - Kevin Winner
- College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, USA
| | - Garrett Bernstein
- College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, USA
| | - Subhransu Maji
- College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, USA
| | - Daniel Sheldon
- College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, USA.,Department of Computer Science, Mount Holyoke College, South Hadley, MA, USA
| | | | - Kyle G Horton
- Cornell Lab of Ornithology, Cornell University, Ithaca, NY, USA.,Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO, USA
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Lin T, Winner K, Bernstein G, Mittal A, Dokter AM, Horton KG, Nilsson C, Van Doren BM, Farnsworth A, La Sorte FA, Maji S, Sheldon D. M
ist
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: Measuring historical bird migration in the US using archived weather radar data and convolutional neural networks. Methods Ecol Evol 2019. [DOI: 10.1111/2041-210x.13280] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Tsung‐Yu Lin
- College of Information and Computer Sciences University of Massachusetts Amherst Amherst MA USA
| | - Kevin Winner
- College of Information and Computer Sciences University of Massachusetts Amherst Amherst MA USA
| | - Garrett Bernstein
- College of Information and Computer Sciences University of Massachusetts Amherst Amherst MA USA
| | - Abhay Mittal
- College of Information and Computer Sciences University of Massachusetts Amherst Amherst MA USA
| | | | - Kyle G. Horton
- Cornell Lab of Ornithology Cornell University Ithaca NY USA
- Department o f Fish Wildlife, and Conservation Biology Colorado State University Fort Collins CO USA
| | | | | | | | | | - Subhransu Maji
- College of Information and Computer Sciences University of Massachusetts Amherst Amherst MA USA
| | - Daniel Sheldon
- College of Information and Computer Sciences University of Massachusetts Amherst Amherst MA USA
- Department of Computer Science Mount Holyoke College South Hadley MA USA
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5
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Affiliation(s)
- Kevin Winner
- College of Information and Computer Sciences University of Massachusetts Amherst Amherst Massachusetts
| | - Michael J. Noonan
- Smithsonian Conservation Biology Institute National Zoological Park Front Royal Virginia
- Department of Biology University of Maryland College Park Maryland
| | - Christen H. Fleming
- Smithsonian Conservation Biology Institute National Zoological Park Front Royal Virginia
- Department of Biology University of Maryland College Park Maryland
| | - Kirk A. Olson
- Wildlife Conservation Society Mongolia Program Ulaanbaatar Mongolia
| | - Thomas Mueller
- Smithsonian Conservation Biology Institute National Zoological Park Front Royal Virginia
- Senckenberg Biodiversity and Climate Research Centre Senckenberg Gesellschaft für Naturforschung Frankfurt (Main) Germany
- Department of Biological Sciences Goethe University Frankfurt (Main) Germany
| | - Daniel Sheldon
- College of Information and Computer Sciences University of Massachusetts Amherst Amherst Massachusetts
- Department of Computer Science Mount Holyoke College South Hadley Massachusetts
| | - Justin M. Calabrese
- Smithsonian Conservation Biology Institute National Zoological Park Front Royal Virginia
- Department of Biology University of Maryland College Park Maryland
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6
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Farnsworth A, Van DOREN BM, Hochachka WM, Sheldon D, Winner K, Irvine J, Geevarghese J, Kelling S. A characterization of autumn nocturnal migration detected by weather surveillance radars in the northeastern USA. Ecol Appl 2016; 26:752-770. [PMID: 27411248 DOI: 10.1890/15-0023] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Billions of birds migrate at night over North America each year. However, few studies have described the phenology of these movements, such as magnitudes, directions, and speeds, for more than one migration season and at regional scales. In this study, we characterize density, direction, and speed of nocturnally migrating birds using data from 13 weather surveillance radars in the autumns of 2010 and 2011 in the northeastern USA. After screening radar data to remove precipitation, we applied a recently developed algorithm for characterizing velocity profiles with previously developed methods to document bird migration. Many hourly radar scans contained windborne "contamination," and these scans also exhibited generally low overall reflectivities. Hourly scans dominated by birds showed nightly and seasonal patterns that differed markedly from those of low reflectivity scans. Bird migration occurred during many nights, but a smaller number of nights with large movements of birds defined regional nocturnal migration. Densities varied by date, time, and location but peaked in the second and third deciles of night during the autumn period when the most birds were migrating. Migration track (the direction to which birds moved) shifted within nights from south-southwesterly to southwesterly during the seasonal migration peaks; this shift was not consistent with a similar shift in wind direction. Migration speeds varied within nights, although not closely with wind speed. Airspeeds increased during the night; groundspeeds were highest between the second and third deciles of night, when the greatest density of birds was migrating. Airspeeds and groundspeeds increased during the fall season, although groundspeeds fluctuated considerably with prevailing winds. Significant positive correlations characterized relationships among bird densities at southern coastal radar stations and northern inland radar stations. The quantitative descriptions of broadscale nocturnal migration patterns presented here will be essential for biological and conservation applications. These descriptions help to define migration phenology in time and space, fill knowledge gaps in avian annual cycles, and are useful for monitoring long-term population trends of migrants. Furthermore, these descriptions will aid in assessing potential risks to migrants, particularly from structures with which birds collide and artificial lighting that disorients migrants.
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La Sorte FA, Hochachka WM, Farnsworth A, Sheldon D, Fink D, Geevarghese J, Winner K, Van Doren BM, Kelling S. Migration timing and its determinants for nocturnal migratory birds during autumn migration. J Anim Ecol 2015; 84:1202-12. [PMID: 25850460 DOI: 10.1111/1365-2656.12376] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2014] [Accepted: 03/29/2015] [Indexed: 10/23/2022]
Abstract
1. Migration is a common strategy used by birds that breed in seasonal environments, and multiple environmental and biological factors determine the timing of migration. How these factors operate in combination during autumn migration, which is considered to be under weaker time constraints relative to spring migration, is not clear. 2. Here, we examine the patterns and determinants of migration timing for nocturnal migrants during autumn migration in the north-eastern USA using nocturnal reflectivity data from 12 weather surveillance radar stations and modelled diurnal probability of occurrence for 142 species of nocturnal migrants. We first model the capacity of seasonal atmospheric conditions (wind and precipitation) and ecological productivity (vegetation greenness) to predict autumn migration intensity. We then test predictions, formulated under optimal migration theory, on how migration timing should be related to assemblage-level estimates of body size and total migration distance within the context of dietary guild (insectivore and omnivore) and level of dietary plasticity during autumn migration. 3. Our results indicate seasonal declines in ecological productivity delineate the beginning and end of peak migration, whose intensity is best predicted by the velocity of winds at migration altitudes. Insectivorous migrants departed earlier in the season and, consistent with our predictions, large-bodied and long-distance insectivorous migrants departed the earliest. Contrary to our predictions, large-bodied and some long-distance omnivorous migrants departed later in the season, patterns that were replicated in part by insectivorous migrants that displayed dietary plasticity during autumn migration. 4. Our findings indicate migration timing in the region is dictated by optimality strategies, modified based on the breadth and flexibility of migrant's foraging diets, with declining ecological productivity defining possible resource thresholds during which migration occurs when winds at migration altitudes are mild. These observations provide the basis to assess how avian migration strategies may be affected by adjustments in seasonal patterns of atmospheric circulation and ecological productivity that may occur under global climate change.
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Affiliation(s)
- Frank A La Sorte
- Cornell Laboratory of Ornithology, Cornell University, Ithaca, New York, 14850, USA
| | - Wesley M Hochachka
- Cornell Laboratory of Ornithology, Cornell University, Ithaca, New York, 14850, USA
| | - Andrew Farnsworth
- Cornell Laboratory of Ornithology, Cornell University, Ithaca, New York, 14850, USA
| | - Daniel Sheldon
- School of Computer Science, University of Massachusetts, Amherst, MA, 01003, USA.,Department of Computer Science, Mount Holyoke College, South Hadley, MA, 01075, USA
| | - Daniel Fink
- Cornell Laboratory of Ornithology, Cornell University, Ithaca, New York, 14850, USA
| | - Jeffrey Geevarghese
- School of Computer Science, University of Massachusetts, Amherst, MA, 01003, USA
| | - Kevin Winner
- School of Computer Science, University of Massachusetts, Amherst, MA, 01003, USA
| | - Benjamin M Van Doren
- Cornell Laboratory of Ornithology, Cornell University, Ithaca, New York, 14850, USA
| | - Steve Kelling
- Cornell Laboratory of Ornithology, Cornell University, Ithaca, New York, 14850, USA
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8
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Köck R, Winner K, Schaumburg F, Jurke A, Rossen J, Friedrich A. Admission prevalence and acquisition of nasal carriage of meticillin-resistant Staphylococcus aureus (MRSA) in German rehabilitation centres. J Hosp Infect 2014; 87:115-8. [DOI: 10.1016/j.jhin.2014.02.007] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2013] [Accepted: 02/23/2014] [Indexed: 11/25/2022]
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