Spatial multi-criteria decision analysis for modelling suitable habitats of Ornithodoros soft ticks in the Western Palearctic region
Autor: | Anton Gerilovych, A.A. Pérez de León, D.S. McVey, Denis Kolbasov, Els Ducheyne, E. De Clercq, I. Sindryakova, Sergey Morgunov, Laurence Vial, Serhii Filatov |
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Přispěvatelé: | Animal, Santé, Territoires, Risques et Ecosystèmes (UMR ASTRE), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA), Avia-GIS, National Scientific Center, USDA-ARS : Agricultural Research Service, National Research Institute of Veterinary Virology and Microbiology, Université Catholique de Louvain = Catholic University of Louvain (UCL), Fonds national de la recherche scientifique, This work was supported by the European Centre for Disease Control and Prevention [VBORNET project - ECDC/09/019], the 7th Framework Program of the European Union [ASFORCE project - KBBE.2012.1.3-02], the U.S. Defense Threat Reduction Agency Project [CBEP Agreement IAA# U.S.C. 3318(b) - 15217, European Project: 311931,EC:FP7:KBBE,FP7-KBBE-2012-6-singlestage,ASFORCE(2012) |
Jazyk: | angličtina |
Rok vydání: | 2018 |
Předmět: |
0301 basic medicine
relapsing fever Rain [SDV]Life Sciences [q-bio] 030231 tropical medicine Species distribution Wildlife Tick L73 - Maladies des animaux Models Biological Mediterranean Basin 03 medical and health sciences tick-borne relapsing fever western palearctic region 0302 clinical medicine medicine Animals Ornithodoros soft ticks Ornithodoros Ecosystem General Veterinary biology Ecology U10 - Informatique mathématiques et statistiques Temperature modeling General Medicine Vegetation 15. Life on land medicine.disease biology.organism_classification 030104 developmental biology Habitat 13. Climate action S50 - Santé humaine Parasitology species distribution Seasons multi-Criteria decision analysis African swine fever Animal Distribution |
Zdroj: | Veterinary Parasitology Veterinary Parasitology, Elsevier, 2018, 249, pp.2-16. ⟨10.1016/j.vetpar.2017.10.022⟩ Veterinary Parasitology, 2018, 249, pp.2-16. ⟨10.1016/j.vetpar.2017.10.022⟩ |
ISSN: | 0304-4017 |
DOI: | 10.1016/j.vetpar.2017.10.022⟩ |
Popis: | International audience; Ticks are economically and medically important ectoparasites due to the injuries inflicted through their bite, and their ability to transmit pathogens to humans, livestock, and wildlife. Whereas hard ticks have been intensively studied, little is known about soft ticks, even though they can also transmit pathogens, including African Swine Fever Virus (ASFV) affecting domestic and wild suids or Borrelia bacteria causing tick-borne relapsing fever (TBRF) in humans. We thus developed a regional model to identify suitable spatial areas for a community of nine Ornithodoros tick species (O. erraticus, O. sonrai, O. alactagalis, O. nereensis, O. tholozani, O. papillipes, O. tartakovskyi, O. asperus, O. verrucosus), which may be of medical and veterinary importance in the Western Palearctic region. Multi-Criteria Decision Analysis was used due to the relative scarcity of high-quality occurrence data. After an in-depth literature review on the ecological requirements of the selected tick community, five climate related factors appeared critical for feeding activity and tick development: (i) a spring temperature exceeding 10 degrees C to induce the end of winter soft tick quiescent period, (ii) a three-months summer temperature above 20 degrees C to allow tick physiological activities, (iii) annual precipitation ranging from 60 mm to 750 mm and, in very arid areas, (iv) dry seasons interrupted by small rain showers to maintain minimum moisture inside their habitat along the year or (v) residual water provided by perennial rivers near habitats. We deliberately chose not to include biological factors such as host availability or vegetation patterns. A sensitivity analysis was done by performing multiple runs of the model altering the environmental variables, their suitability function, and their attributed weights. To validate the models, we used 355 occurrence data points, complemented by random points within sampled ecoregions. All models indicated suitable areas in the Mediterranean Basin and semi desert areas in South-West and Central Asia. Most variability between models was observed along northern and southern edges of highly suitable areas. The predictions featured a relatively good accuracy with an average Area Under Curve (AUC) of 0.779. These first models provide a useful tool for estimating the global distribution of Ornithodoros ticks and targeting their surveillance in the Western Palearctic region. |
Databáze: | OpenAIRE |
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