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      Ranging patterns, spatial overlap, and association with dolphin morbillivirus exposure in common bottlenose dolphins (Tursiops truncatus) along the Georgia, USA coast

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          During 2013–2015, an outbreak of dolphin morbillivirus (DMV) occurred in the western North Atlantic, which resulted in the stranding of over 1,600 common bottlenose dolphins (Tursiops truncatus). There are currently five coastal and 10 bay, sound, and estuary dolphin stocks along the U.S. Atlantic coast, yet there is very limited understanding of which stocks were exposed to DMV during the recent outbreak, or how DMV was transmitted across stocks. In order to address these questions, information is needed on spatial overlap and stock interactions. The goals of this project were to determine ranging patterns, prevalence of DMV, and spatial overlap of the South Carolina‐Georgia (SC‐GA) Coastal Stock, and adjacent Southern Georgia Estuarine System (SGES) Stock. During September 2015, a health assessment and telemetry study was conducted in which 19 dolphins were captured, tested for antibodies to DMV, and satellite tagged. Dolphins were classified into one of three ranging patterns (Coastal, Sound, or Estuary) based upon telemetry data. Coastal dolphins (likely members of the SC‐GA Coastal Stock) had a significantly higher prevalence of positive DMV antibody titers (0.67; N = 2/3), than Sound and Estuary dolphins (likely members of the SGES Stock) (0.13; N = 2/16). These results suggest that the SC‐GA Coastal Stock may have experienced greater exposure to DMV as compared to the SGES Stock. However, due to the small size of the SGES Stock and its exposure to high levels of persistent contaminants, this stock may be particularly vulnerable to DMV infection in the future.

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          Most cited references 61

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            The home-range concept: are traditional estimators still relevant with modern telemetry technology?

            Recent advances in animal tracking and telemetry technology have allowed the collection of location data at an ever-increasing rate and accuracy, and these advances have been accompanied by the development of new methods of data analysis for portraying space use, home ranges and utilization distributions. New statistical approaches include data-intensive techniques such as kriging and nonlinear generalized regression models for habitat use. In addition, mechanistic home-range models, derived from models of animal movement behaviour, promise to offer new insights into how home ranges emerge as the result of specific patterns of movements by individuals in response to their environment. Traditional methods such as kernel density estimators are likely to remain popular because of their ease of use. Large datasets make it possible to apply these methods over relatively short periods of time such as weeks or months, and these estimates may be analysed using mixed effects models, offering another approach to studying temporal variation in space-use patterns. Although new technologies open new avenues in ecological research, our knowledge of why animals use space in the ways we observe will only advance by researchers using these new technologies and asking new and innovative questions about the empirical patterns they observe.
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              Social Barriers to Pathogen Transmission in Wild Animal Populations

               Craig Loehle (1995)

                Author and article information

                Ecol Evol
                Ecol Evol
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                26 November 2018
                December 2018
                : 8
                : 24 ( doiID: 10.1002/ece3.2018.8.issue-24 )
                : 12890-12904
                [ 1 ] Jardon and Howard Technologies (JHT) Incorporated Orlando Florida
                [ 2 ] National Oceanic and Atmospheric Administration, National Ocean Service National Centers for Coastal Ocean Science Charleston South Carolina
                [ 3 ] National Marine Mammal Foundation San Diego California
                [ 4 ] National Oceanic and Atmospheric Administration, National Marine Fisheries Service Office of Protected Resources Silver Spring Maryland
                [ 5 ] Bayside Hospital for Animals Fort Walton Beach Florida
                [ 6 ] Georgia Department of Natural Resources Nongame Wildlife Conservation Brunswick Georgia
                [ 7 ] Karen C. Drayer Wildlife Health Center, One Health Institute, School of Veterinary Medicine University of California Davis California
                [ 8 ] National Oceanic and Atmospheric Administration, National Marine Fisheries Service Southeast Fisheries Science Center Lafayette Louisiana
                [ 9 ] Athens Veterinary Diagnostic Laboratory University of Georgia Athens Georgia
                Author notes
                [* ] Correspondence

                Brian Balmer, National Marine Mammal Foundation, San Diego, CA.

                Email: Brian.Balmer@

                © 2018 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                Page count
                Figures: 6, Tables: 2, Pages: 15, Words: 23016
                Original Research
                Original Research
                Custom metadata
                December 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:version=5.5.4 mode:remove_FC converted:28.12.2018

                Evolutionary Biology

                spatial overlap, bottlenose dolphin, movement patterns, morbillivirus, telemetry


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