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      Pathogen transmission risk by opportunistic gulls moving across human landscapes

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          Abstract

          Wildlife that exploit human-made habitats hosts and spreads bacterial pathogens. This shapes the epidemiology of infectious diseases and facilitates pathogen spill-over between wildlife and humans. This is a global problem, yet little is known about the dissemination potential of pathogen-infected animals. By combining molecular pathogen diagnosis with GPS tracking of pathogen-infected gulls, we show how this knowledge gap could be filled at regional scales. Specifically, we generated pathogen risk maps of Salmonella, Campylobacter and Chlamydia based on the spatial movements of pathogen-infected yellow-legged gulls ( Larus michahellis) equipped with GPS recorders. Also, crossing this spatial information with habitat information, we identified critical habitats for the potential transmission of these bacteria in southern Europe. The use of human-made habitats by infected-gulls could potentially increase the potential risk of direct and indirect bidirectional transmission of pathogens between humans and wildlife. Our findings show that pathogen-infected wildlife equipped with GPS recorders can provide accurate information on the spatial spread risk for zoonotic bacteria. Integration of GPS-tracking with classical epidemiological approaches may help to improve zoonosis surveillance and control programs.

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          Urbanization and the ecology of wildlife diseases

          Urbanization is intensifying worldwide, with two-thirds of the human population expected to reside in cities within 30 years. The role of cities in human infectious disease is well established, but less is known about how urban landscapes influence wildlife–pathogen interactions. Here, we draw on recent advances in wildlife epidemiology to consider how environmental changes linked with urbanization can alter the biology of hosts, pathogens and vectors. Although urbanization reduces the abundance of many wildlife parasites, transmission can, in some cases, increase among urban-adapted hosts, with effects on rarer wildlife or those living beyond city limits. Continued rapid urbanization, together with risks posed by multi-host pathogens for humans and vulnerable wildlife populations, emphasize the need for future research on wildlife diseases in urban landscapes.
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            Spatial epidemiology: an emerging (or re-emerging) discipline.

            Spatial epidemiology is the study of spatial variation in disease risk or incidence. Several ecological processes can result in strong spatial patterns of such risk or incidence: for example, pathogen dispersal might be highly localized, vectors or reservoirs for pathogens might be spatially restricted, or susceptible hosts might be clumped. Here, we briefly describe approaches to spatial epidemiology that are spatially implicit, such as metapopulation models of disease transmission, and then focus on research in spatial epidemiology that is spatially explicit, such as the creation of risk maps for particular geographical areas. Although the spatial dynamics of infectious diseases are the subject of intensive study, the impacts of landscape structure on epidemiological processes have so far been neglected. The few studies that demonstrate how landscape composition (types of elements) and configuration (spatial positions of those elements) influence disease risk or incidence suggest that a true integration of landscape ecology with epidemiology will be fruitful.
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              A flexible GPS tracking system for studying bird behaviour at multiple scales

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                Author and article information

                Contributors
                joan@icm.csic.es
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                23 July 2019
                23 July 2019
                2019
                : 9
                : 10659
                Affiliations
                [1 ]ISNI 0000 0004 1793 765X, GRID grid.418218.6, Institut de Ciències del Mar - CSIC, ; Barcelona, Spain
                [2 ]GRID grid.440910.8, Centre d’Ecologie Fonctionnelle et Evolutive, UMR 5175, CNRS - Université de Montpellier, , Université Paul-Valéry Montpellier - EPHE, ; Montpellier, France
                [3 ]ISNI 0000 0004 1937 1151, GRID grid.7836.a, FitzPatrick Institute, , University of Cape Town, ; Rondebosch, South Africa
                [4 ]ISNI 0000 0001 1091 6248, GRID grid.418875.7, Estación Biológica de Doñana - CSIC, ; Sevilla, Spain
                [5 ]ISNI 0000000084992262, GRID grid.7177.6, Computational Geo-Ecology, Institute for Biodiversity and Ecosystem Dynamics (IBED), , University of Amsterdam, ; Amsterdam, The Netherlands
                [6 ]ISNI 0000 0000 9314 1427, GRID grid.413448.e, CIBER Epidemiología y Salud Pública (CIBER-ESP), ; Sevilla, Spain
                Author information
                http://orcid.org/0000-0002-5756-9543
                http://orcid.org/0000-0002-7711-9398
                http://orcid.org/0000-0003-3874-0461
                http://orcid.org/0000-0002-5250-8872
                http://orcid.org/0000-0002-4664-9011
                Article
                46326
                10.1038/s41598-019-46326-1
                6650491
                31337777
                0a4a2bd0-352c-48a3-8456-ea67ecba4d3b
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 9 October 2018
                : 21 June 2019
                Funding
                Funded by: ESFRI-LifeWatch - Science and Technology Infrastructure for Biodiversity Data and Observatories. Grant Reference Number: SP34163 Andalucia Talent Hub Program (Andalusian Knowledge Agency and European Union's Seventh Framework Program). Grant Reference Number: 291780 Spanish National Program Ramón y Cajal. Grant Reference Number: RYC-2015-17809
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                ecology,pathogens,behavioural ecology
                Uncategorized
                ecology, pathogens, behavioural ecology

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