A distribution model for Glossina brevipalpis and Glossina austeni in Southern Mozambique, Eswatini and South Africa for enhanced area-wide integrated pest management approaches.

Autor:	de Beer CJ; Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Insect Pest Control Laboratory, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna, Austria.; Epidemiology, Parasites & Vectors, Agricultural Research Council-Onderstepoort Veterinary Research (ARC-OVR), Onderstepoort, South Africa., Dicko AH; STATS4D, Dakar, Senegal., Ntshangase J; Epidemiology, Parasites & Vectors, Agricultural Research Council-Onderstepoort Veterinary Research (ARC-OVR), Onderstepoort, South Africa., Moyaba P; Epidemiology, Parasites & Vectors, Agricultural Research Council-Onderstepoort Veterinary Research (ARC-OVR), Onderstepoort, South Africa., Taioe MO; Epidemiology, Parasites & Vectors, Agricultural Research Council-Onderstepoort Veterinary Research (ARC-OVR), Onderstepoort, South Africa., Mulandane FC; Biotechnology Centre, Eduardo Mondlane University, Maputo, Mozambique., Neves L; Biotechnology Centre, Eduardo Mondlane University, Maputo, Mozambique.; Vectors and Vector Borne Diseases Research Program, Department of Veterinary Tropical Diseases, Faculty of Veterinary Science, University of Pretoria, Onderstepoort, South Africa., Mdluli S; Epidemiology Unit, Department of Veterinary Services, Manzini, Eswatini., Guerrini L; UMR ASTRE (Animal, Health, Territories, Risks and Ecosystems), CIRAD, INRA, Université de Montpellier, Montpellier, France.; RP-PCP, UMR ASTRE, Harare, Zimbabwe., Bouyer J; Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Insect Pest Control Laboratory, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna, Austria.; UMR ASTRE (Animal, Health, Territories, Risks and Ecosystems), CIRAD, INRA, Université de Montpellier, Montpellier, France.; UMR INTERTRYP, Univ Montpellier, CIRAD, IRD, Montpellier, France., Vreysen MJB; Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Insect Pest Control Laboratory, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna, Austria., Venter GJ; Epidemiology, Parasites & Vectors, Agricultural Research Council-Onderstepoort Veterinary Research (ARC-OVR), Onderstepoort, South Africa.; Vectors and Vector Borne Diseases Research Program, Department of Veterinary Tropical Diseases, Faculty of Veterinary Science, University of Pretoria, Onderstepoort, South Africa.
Jazyk:	angličtina
Zdroj:	PLoS neglected tropical diseases [PLoS Negl Trop Dis] 2021 Nov 29; Vol. 15 (11), pp. e0009989. Date of Electronic Publication: 2021 Nov 29 (Print Publication: 2021).
DOI:	10.1371/journal.pntd.0009989
Abstrakt:	Background: Glossina austeni and Glossina brevipalpis (Diptera: Glossinidae) are the sole cyclical vectors of African trypanosomes in South Africa, Eswatini and southern Mozambique. These populations represent the southernmost distribution of tsetse flies on the African continent. Accurate knowledge of infested areas is a prerequisite to develop and implement efficient and cost-effective control strategies, and distribution models may reduce large-scale, extensive entomological surveys that are time consuming and expensive. The objective was to develop a MaxEnt species distribution model and habitat suitability maps for the southern tsetse belt of South Africa, Eswatini and southern Mozambique. Methodology/principal Findings: The present study used existing entomological survey data of G. austeni and G. brevipalpis to develop a MaxEnt species distribution model and habitat suitability maps. Distribution models and a checkerboard analysis indicated an overlapping presence of the two species and the most suitable habitat for both species were protected areas and the coastal strip in KwaZulu-Natal Province, South Africa and Maputo Province, Mozambique. The predicted presence extents, to a small degree, into communal farming areas adjacent to the protected areas and coastline, especially in the Matutuíne District of Mozambique. The quality of the MaxEnt model was assessed using an independent data set and indicated good performance with high predictive power (AUC > 0.80 for both species). Conclusions/significance: The models indicated that cattle density, land surface temperature and protected areas, in relation with vegetation are the main factors contributing to the distribution of the two tsetse species in the area. Changes in the climate, agricultural practices and land-use have had a significant and rapid impact on tsetse abundance in the area. The model predicted low habitat suitability in the Gaza and Inhambane Provinces of Mozambique, i.e., the area north of the Matutuíne District. This might indicate that the southern tsetse population is isolated from the main tsetse belt in the north of Mozambique. The updated distribution models will be useful for planning tsetse and trypanosomosis interventions in the area. Competing Interests: The authors have declared that no competing interests exist.
Databáze:	MEDLINE
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