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  1. AU="Fiona McDuie"
  2. AU="You, Kisung"
  3. AU="Sanjuan, Miguel A" AU="Sanjuan, Miguel A"
  4. AU=Weingarten-Gabbay Shira
  5. AU="Choukr-Allah, Redouane"
  6. AU="Mills, Mary Katherine"
  7. AU="Vajente, G."
  8. AU="Bhatnagar, R.C"
  9. AU="Prasad Sarkale"
  10. AU="Manfredonia, Laura"
  11. AU="Linssen, L"
  12. AU="Davide, Borroni"
  13. AU="Ingrid M. Wentzensen"
  14. AU="A.Parida, "
  15. AU="Zhu, D H"
  16. AU=Ulloa Luis
  17. AU="Böhme, Elisa"
  18. AU=Trko?lu Oya
  19. AU="Levine, Zoe"
  20. AU="Banaszkiewicz, Paul A."
  21. AU="Datrier, Laurence E. H."
  22. AU=Fala Loretta
  23. AU="McGuckin, M M"
  24. AU="Winlaw, David S"
  25. AU="Gökmen, M Refik"
  26. AU="Islam, Tousif"
  27. AU="Szczepanczyk, Marek J"
  28. AU="Boregowda, Siddaraju"
  29. AU="Lomidzew, D."

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  1. Artikel ; Online: Waterfowl recently infected with low pathogenic avian influenza exhibit reduced local movement and delayed migration

    Claire S. Teitelbaum / Michael L. Casazza / Fiona McDuie / Susan E. W. De La Cruz / Cory T. Overton / Laurie A. Hall / Elliott L. Matchett / Joshua T. Ackerman / Jeffery D. Sullivan / Andrew M. Ramey / Diann J. Prosser

    Ecosphere, Vol 14, Iss 2, Pp n/a-n/a (2023)

    2023  

    Abstract: Abstract Understanding relationships between infection and wildlife movement patterns is important for predicting pathogen spread, especially for multispecies pathogens and those that can spread to humans and domestic animals, such as avian influenza ... ...

    Abstract Abstract Understanding relationships between infection and wildlife movement patterns is important for predicting pathogen spread, especially for multispecies pathogens and those that can spread to humans and domestic animals, such as avian influenza viruses (AIVs). Although infection with low pathogenic AIVs is generally considered asymptomatic in wild birds, prior work has shown that influenza‐infected birds occasionally delay migration and/or reduce local movements relative to their uninfected counterparts. However, most observational research to date has focused on a few species in northern Europe; given that influenza viruses are widespread globally and outbreaks of highly pathogenic strains are increasingly common, it is important to explore influenza–movement relationships across more species and regions. Here, we used telemetry data to investigate relationships between influenza infection and movement behavior in 165 individuals from four species of North American waterfowl that overwinter in California, USA. We studied both large‐scale migratory and local overwintering movements and found that relationships between influenza infection and movement patterns varied among species. Northern pintails (Anas acuta) with antibodies to avian influenza, indicating prior infection, made migratory stopovers that averaged 12 days longer than those with no influenza antibodies. In contrast, greater white‐fronted geese (Anser albifrons) with antibodies to avian influenza made migratory stopovers that averaged 15 days shorter than those with no antibodies. Canvasbacks (Aythya valisineria) that were actively infected with influenza upon capture in the winter delayed spring migration by an average of 28 days relative to birds that were uninfected at the time of capture. At the local scale, northern pintails and canvasbacks that were actively infected with influenza used areas that were 7.6 and 4.9 times smaller than those of uninfected ducks, respectively, during the period of presumed active influenza infection. We ...
    Schlagwörter animal movement ; avian influenza ; infectious disease ; migration ; space use ; waterfowl ; Ecology ; QH540-549.5
    Thema/Rubrik (Code) 590
    Sprache Englisch
    Erscheinungsdatum 2023-02-01T00:00:00Z
    Verlag Wiley
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  2. Artikel ; Online: Machine learned daily life history classification using low frequency tracking data and automated modelling pipelines

    Cory Overton / Michael Casazza / Joseph Bretz / Fiona McDuie / Elliott Matchett / Desmond Mackell / Austen Lorenz / Andrea Mott / Mark Herzog / Josh Ackerman

    Movement Ecology, Vol 10, Iss 1, Pp 1-

    application to North American waterfowl

    2022  Band 13

    Abstract: Abstract Background Identifying animal behaviors, life history states, and movement patterns is a prerequisite for many animal behavior analyses and effective management of wildlife and habitats. Most approaches classify short-term movement patterns with ...

    Abstract Abstract Background Identifying animal behaviors, life history states, and movement patterns is a prerequisite for many animal behavior analyses and effective management of wildlife and habitats. Most approaches classify short-term movement patterns with high frequency location or accelerometry data. However, patterns reflecting life history across longer time scales can have greater relevance to species biology or management needs, especially when available in near real-time. Given limitations in collecting and using such data to accurately classify complex behaviors in the long-term, we used hourly GPS data from 5 waterfowl species to produce daily activity classifications with machine-learned models using “automated modelling pipelines”. Methods Automated pipelines are computer-generated code that complete many tasks including feature engineering, multi-framework model development, training, validation, and hyperparameter tuning to produce daily classifications from eight activity patterns reflecting waterfowl life history or movement states. We developed several input features for modeling grouped into three broad categories, hereafter “feature sets”: GPS locations, habitat information, and movement history. Each feature set used different data sources or data collected across different time intervals to develop the “features” (independent variables) used in models. Results Automated modelling pipelines rapidly developed easily reproducible data preprocessing and analysis steps, identification and optimization of the best performing model and provided outputs for interpreting feature importance. Unequal expression of life history states caused unbalanced classes, so we evaluated feature set importance using a weighted F1-score to balance model recall and precision among individual classes. Although the best model using the least restrictive feature set (only 24 hourly relocations in a day) produced effective classifications (weighted F1 = 0.887), models using all feature sets performed substantially better ...
    Schlagwörter Animal behavior ; Daily activity ; Life history state ; Global positioning system ; Supervised machine learning ; Classification ; Biology (General) ; QH301-705.5
    Thema/Rubrik (Code) 006
    Sprache Englisch
    Erscheinungsdatum 2022-05-01T00:00:00Z
    Verlag BMC
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  3. Artikel ; Online: Migration stopover ecology of Cinnamon Teal in western North America

    Desmond A. Mackell / Michael L. Casazza / Cory T. Overton / J. Patrick Donnelly / David Olson / Fiona McDuie / Joshua T. Ackerman / John M. Eadie

    Ecology and Evolution, Vol 11, Iss 20, Pp 14056-

    2021  Band 14069

    Abstract: Abstract Identifying migration routes and fall stopover sites of Cinnamon Teal (Spatula cyanoptera septentrionalium) can provide a spatial guide to management and conservation efforts, and address vulnerabilities in wetland networks that support ... ...

    Abstract Abstract Identifying migration routes and fall stopover sites of Cinnamon Teal (Spatula cyanoptera septentrionalium) can provide a spatial guide to management and conservation efforts, and address vulnerabilities in wetland networks that support migratory waterbirds. Using high spatiotemporal resolution GPS‐GSM transmitters, we analyzed 61 fall migration tracks across western North America during our three‐year study (2017–2019). We marked Cinnamon Teal primarily during spring/summer in important breeding and molting regions across seven states (California, Oregon, Washington, Idaho, Utah, Colorado, and Nevada). We assessed fall migration routes and timing, detected 186 fall stopover sites, and identified specific North American ecoregions where sites were located. We classified underlying land cover for each stopover site and measured habitat selection for 12 land cover types within each ecoregion. Cinnamon Teal selected a variety of flooded habitats including natural, riparian, tidal, and managed wetlands; wet agriculture (including irrigation ditches, flooded fields, and stock ponds); wastewater sites; and golf and urban ponds. Wet agriculture was the most used habitat type (29.8% of stopover locations), and over 72% of stopover locations were on private land. Relatively scarce habitats such as wastewater ponds, tidal marsh, and golf and urban ponds were highly selected in specific ecoregions. In contrast, dry non‐habitat across all ecoregions, and dry agriculture in the Cold Deserts and Mediterranean California ecoregions, was consistently avoided. Resources used by Cinnamon Teal often reflected wetland availability across the west and emphasize their adaptability to dynamic resource conditions in arid landscapes. Our results provide much needed information on spatial and temporal resource use by Cinnamon Teal during migration and indicate important wetland habitats for migrating waterfowl in the western United States.
    Schlagwörter avian migration ; GPS telemetry ; habitat selection ; spectral mixture analysis ; waterfowl ; wetland conservation ; Ecology ; QH540-549.5
    Thema/Rubrik (Code) 333
    Sprache Englisch
    Erscheinungsdatum 2021-10-01T00:00:00Z
    Verlag Wiley
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  4. Artikel ; Online: GPS tracking data reveals daily spatio-temporal movement patterns of waterfowl

    Fiona McDuie / Michael L. Casazza / Cory T. Overton / Mark P. Herzog / C. Alexander Hartman / Sarah H. Peterson / Cliff L. Feldheim / Joshua T. Ackerman

    Movement Ecology, Vol 7, Iss 1, Pp 1-

    2019  Band 17

    Abstract: Abstract Background Spatio-temporal patterns of movement can characterize relationships between organisms and their surroundings, and address gaps in our understanding of species ecology, activity budgets, bioenergetics, and habitat resource management. ... ...

    Abstract Abstract Background Spatio-temporal patterns of movement can characterize relationships between organisms and their surroundings, and address gaps in our understanding of species ecology, activity budgets, bioenergetics, and habitat resource management. Highly mobile waterfowl, which can exploit resources over large spatial extents, are excellent models to understand relationships between movements and resource usage, landscape interactions and specific habitat needs. Methods We tracked 3 species of dabbling ducks with GPS-GSM transmitters in 2015–17 to examine fine-scale movement patterns over 24 h periods (30 min interval), dividing movement pathways into temporally continuous segments and spatially contiguous patches. We quantified distances moved, area used and time allocated across the day, using linear and generalized linear mixed models. We investigated behavior through relationships between these variables. Results Movements and space-use were small, and varied by species, sex and season. Gadwall (Mareca strepera) generally moved least (FFDs: 0.5–0.7 km), but their larger foraging patches resulted from longer within-area movements. Pintails (Anas acuta) moved most, were more likely to conduct flights > 300 m, had FFDs of 0.8–1.1 km, used more segments and patches per day that they revisited more frequently, resulting in the longest daily total movements. Females and males differed only during the post-hunt season when females moved more. 23.6% of track segments were short duration (1–2 locations), approximately 1/3 more than would be expected if they occurred randomly, and were more dispersed in the landscape than longer segments. Distance moved in 30 min shortened as segment duration increased, likely reflecting phases of non-movement captured within segments. Conclusions Pacific Flyway ducks spend the majority of time using smaller foraging and resting areas than expected or previously reported, implying that foraging areas may be highly localized, and nutrients obtainable from smaller areas. Additionally, movement reductions over time demonstrates behavioral adjustments that represent divergent energetic demands, the detection of which is a key advantage of higher frequency data. Ducks likely use less energy for movement than currently predicted and management, including distribution and configuration of essential habitat, may require reconsideration. Our study illustrates how fine-scale movement data from tracking help understand and inform various other fields of research.
    Schlagwörter Activity budgets ; Animal movement ; Contagion index ; Energetics ; Fine-scale movement ; High frequency GPS ; Biology (General) ; QH301-705.5
    Thema/Rubrik (Code) 333 ; 590
    Sprache Englisch
    Erscheinungsdatum 2019-02-01T00:00:00Z
    Verlag BMC
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  5. Artikel ; Online: Global assessment of marine plastic exposure risk for oceanic birds

    Bethany L. Clark / Ana P. B. Carneiro / Elizabeth J. Pearmain / Marie-Morgane Rouyer / Thomas A. Clay / Win Cowger / Richard A. Phillips / Andrea Manica / Carolina Hazin / Marcus Eriksen / Jacob González-Solís / Josh Adams / Yuri V. Albores-Barajas / Joanna Alfaro-Shigueto / Maria Saldanha Alho / Deusa Teixeira Araujo / José Manuel Arcos / John P. Y. Arnould / Nadito J. P. Barbosa /
    Christophe Barbraud / Annalea M. Beard / Jessie Beck / Elizabeth A. Bell / Della G. Bennet / Maud Berlincourt / Manuel Biscoito / Oskar K. Bjørnstad / Mark Bolton / Katherine A. Booth Jones / John J. Borg / Karen Bourgeois / Vincent Bretagnolle / Joël Bried / James V. Briskie / M. de L. Brooke / Katherine C. Brownlie / Leandro Bugoni / Licia Calabrese / Letizia Campioni / Mark J. Carey / Ryan D. Carle / Nicholas Carlile / Ana R. Carreiro / Paulo Catry / Teresa Catry / Jacopo G. Cecere / Filipe R. Ceia / Yves Cherel / Chang-Yong Choi / Marco Cianchetti-Benedetti / Rohan H. Clarke / Jaimie B. Cleeland / Valentina Colodro / Bradley C. Congdon / Jóhannis Danielsen / Federico De Pascalis / Zoe Deakin / Nina Dehnhard / Giacomo Dell’Omo / Karine Delord / Sébastien Descamps / Ben J. Dilley / Herculano A. Dinis / Jerome Dubos / Brendon J. Dunphy / Louise M. Emmerson / Ana Isabel Fagundes / Annette L. Fayet / Jonathan J. Felis / Johannes H. Fischer / Amanda N. D. Freeman / Aymeric Fromant / Giorgia Gaibani / David García / Carina Gjerdrum / Ivandra Soeli Gonçalves Correia Gomes / Manuela G. Forero / José P. Granadeiro / W. James Grecian / David Grémillet / Tim Guilford / Gunnar Thor Hallgrimsson / Luke R. Halpin / Erpur Snær Hansen / April Hedd / Morten Helberg / Halfdan H. Helgason / Leeann M. Henry / Hannah F. R. Hereward / Marcos Hernandez-Montero / Mark A. Hindell / Peter J. Hodum / Simona Imperio / Audrey Jaeger / Mark Jessopp / Patrick G. R. Jodice / Carl G. Jones / Christopher W. Jones / Jón Einar Jónsson / Adam Kane / Sven Kapelj / Yuna Kim / Holly Kirk / Yann Kolbeinsson / Philipp L. Kraemer / Lucas Krüger / Paulo Lago / Todd J. Landers / Jennifer L. Lavers / Matthieu Le Corre / Andreia Leal / Maite Louzao / Jeremy Madeiros / Maria Magalhães / Mark L. Mallory / Juan F. Masello / Bruno Massa / Sakiko Matsumoto / Fiona McDuie / Laura McFarlane Tranquilla / Fernando Medrano / Benjamin J. Metzger / Teresa Militão / William A. Montevecchi / Rosalinda C. Montone / Leia Navarro-Herrero / Verónica C. Neves / David G. Nicholls / Malcolm A. C. Nicoll / Ken Norris / Steffen Oppel / Daniel Oro / Ellie Owen / Oliver Padget / Vítor H. Paiva / David Pala / Jorge M. Pereira / Clara Péron / Maria V. Petry / Admilton de Pina / Ariete T. Moreira Pina / Patrick Pinet / Pierre A. Pistorius / Ingrid L. Pollet / Benjamin J. Porter / Timothée A. Poupart / Christopher D. L. Powell / Carolina B. Proaño / Júlia Pujol-Casado / Petra Quillfeldt / John L. Quinn / Andre F. Raine / Helen Raine / Iván Ramírez / Jaime A. Ramos / Raül Ramos / Andreas Ravache / Matt J. Rayner / Timothy A. Reid / Gregory J. Robertson / Gerard J. Rocamora / Dominic P. Rollinson / Robert A. Ronconi / Andreu Rotger / Diego Rubolini / Kevin Ruhomaun / Asunción Ruiz / James C. Russell / Peter G. Ryan / Sarah Saldanha / Ana Sanz-Aguilar / Mariona Sardà-Serra / Yvan G. Satgé / Katsufumi Sato / Wiebke C. Schäfer / Stefan Schoombie / Scott A. Shaffer / Nirmal Shah / Akiko Shoji / Dave Shutler / Ingvar A. Sigurðsson / Mónica C. Silva / Alison E. Small / Cecilia Soldatini / Hallvard Strøm / Christopher A. Surman / Akinori Takahashi / Vikash R. V. Tatayah / Graeme A. Taylor / Robert J. Thomas / David R. Thompson / Paul M. Thompson / Thorkell L. Thórarinsson / Diego Vicente-Sastre / Eric Vidal / Ewan D. Wakefield / Susan M. Waugh / Henri Weimerskirch / Heiko U. Wittmer / Takashi Yamamoto / Ken Yoda / Carlos B. Zavalaga / Francis J. Zino / Maria P. Dias

    Nature Communications, Vol 14, Iss 1, Pp 1-

    2023  Band 14

    Abstract: Abstract Plastic pollution is distributed patchily around the world’s oceans. Likewise, marine organisms that are vulnerable to plastic ingestion or entanglement have uneven distributions. Understanding where wildlife encounters plastic is crucial for ... ...

    Abstract Abstract Plastic pollution is distributed patchily around the world’s oceans. Likewise, marine organisms that are vulnerable to plastic ingestion or entanglement have uneven distributions. Understanding where wildlife encounters plastic is crucial for targeting research and mitigation. Oceanic seabirds, particularly petrels, frequently ingest plastic, are highly threatened, and cover vast distances during foraging and migration. However, the spatial overlap between petrels and plastics is poorly understood. Here we combine marine plastic density estimates with individual movement data for 7137 birds of 77 petrel species to estimate relative exposure risk. We identify high exposure risk areas in the Mediterranean and Black seas, and the northeast Pacific, northwest Pacific, South Atlantic and southwest Indian oceans. Plastic exposure risk varies greatly among species and populations, and between breeding and non-breeding seasons. Exposure risk is disproportionately high for Threatened species. Outside the Mediterranean and Black seas, exposure risk is highest in the high seas and Exclusive Economic Zones (EEZs) of the USA, Japan, and the UK. Birds generally had higher plastic exposure risk outside the EEZ of the country where they breed. We identify conservation and research priorities, and highlight that international collaboration is key to addressing the impacts of marine plastic on wide-ranging species.
    Schlagwörter Science ; Q
    Thema/Rubrik (Code) 333
    Sprache Englisch
    Erscheinungsdatum 2023-07-01T00:00:00Z
    Verlag Nature Portfolio
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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