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Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population

BACKGROUND: Changes in land use and land cover (LULC) as well as climate are likely to affect the geographic distribution of malaria vectors and parasites in the coming decades. At present, malaria transmission is concentrated mainly in the Amazon basin where extensive agriculture, mining, and loggi...

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Autores principales: Alimi, Temitope O., Fuller, Douglas O., Qualls, Whitney A., Herrera, Socrates V., Arevalo-Herrera, Myriam, Quinones, Martha L., Lacerda, Marcus V. G., Beier, John C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4546039/
https://www.ncbi.nlm.nih.gov/pubmed/26289677
http://dx.doi.org/10.1186/s13071-015-1033-9
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author Alimi, Temitope O.
Fuller, Douglas O.
Qualls, Whitney A.
Herrera, Socrates V.
Arevalo-Herrera, Myriam
Quinones, Martha L.
Lacerda, Marcus V. G.
Beier, John C.
author_facet Alimi, Temitope O.
Fuller, Douglas O.
Qualls, Whitney A.
Herrera, Socrates V.
Arevalo-Herrera, Myriam
Quinones, Martha L.
Lacerda, Marcus V. G.
Beier, John C.
author_sort Alimi, Temitope O.
collection PubMed
description BACKGROUND: Changes in land use and land cover (LULC) as well as climate are likely to affect the geographic distribution of malaria vectors and parasites in the coming decades. At present, malaria transmission is concentrated mainly in the Amazon basin where extensive agriculture, mining, and logging activities have resulted in changes to local and regional hydrology, massive loss of forest cover, and increased contact between malaria vectors and hosts. METHODS: Employing presence-only records, bioclimatic, topographic, hydrologic, LULC and human population data, we modeled the distribution of malaria and two of its dominant vectors, Anopheles darlingi, and Anopheles nuneztovari s.l. in northern South America using the species distribution modeling platform Maxent. RESULTS: Results from our land change modeling indicate that about 70,000 km(2) of forest land would be lost by 2050 and 78,000 km(2) by 2070 compared to 2010. The Maxent model predicted zones of relatively high habitat suitability for malaria and the vectors mainly within the Amazon and along coastlines. While areas with malaria are expected to decrease in line with current downward trends, both vectors are predicted to experience range expansions in the future. Elevation, annual precipitation and temperature were influential in all models both current and future. Human population mostly affected An. darlingi distribution while LULC changes influenced An. nuneztovari s.l. distribution. CONCLUSION: As the region tackles the challenge of malaria elimination, investigations such as this could be useful for planning and management purposes and aid in predicting and addressing potential impediments to elimination. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13071-015-1033-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-45460392015-08-23 Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population Alimi, Temitope O. Fuller, Douglas O. Qualls, Whitney A. Herrera, Socrates V. Arevalo-Herrera, Myriam Quinones, Martha L. Lacerda, Marcus V. G. Beier, John C. Parasit Vectors Research BACKGROUND: Changes in land use and land cover (LULC) as well as climate are likely to affect the geographic distribution of malaria vectors and parasites in the coming decades. At present, malaria transmission is concentrated mainly in the Amazon basin where extensive agriculture, mining, and logging activities have resulted in changes to local and regional hydrology, massive loss of forest cover, and increased contact between malaria vectors and hosts. METHODS: Employing presence-only records, bioclimatic, topographic, hydrologic, LULC and human population data, we modeled the distribution of malaria and two of its dominant vectors, Anopheles darlingi, and Anopheles nuneztovari s.l. in northern South America using the species distribution modeling platform Maxent. RESULTS: Results from our land change modeling indicate that about 70,000 km(2) of forest land would be lost by 2050 and 78,000 km(2) by 2070 compared to 2010. The Maxent model predicted zones of relatively high habitat suitability for malaria and the vectors mainly within the Amazon and along coastlines. While areas with malaria are expected to decrease in line with current downward trends, both vectors are predicted to experience range expansions in the future. Elevation, annual precipitation and temperature were influential in all models both current and future. Human population mostly affected An. darlingi distribution while LULC changes influenced An. nuneztovari s.l. distribution. CONCLUSION: As the region tackles the challenge of malaria elimination, investigations such as this could be useful for planning and management purposes and aid in predicting and addressing potential impediments to elimination. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13071-015-1033-9) contains supplementary material, which is available to authorized users. BioMed Central 2015-08-20 /pmc/articles/PMC4546039/ /pubmed/26289677 http://dx.doi.org/10.1186/s13071-015-1033-9 Text en © Alimi et al. 2015 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Alimi, Temitope O.
Fuller, Douglas O.
Qualls, Whitney A.
Herrera, Socrates V.
Arevalo-Herrera, Myriam
Quinones, Martha L.
Lacerda, Marcus V. G.
Beier, John C.
Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population
title Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population
title_full Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population
title_fullStr Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population
title_full_unstemmed Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population
title_short Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population
title_sort predicting potential ranges of primary malaria vectors and malaria in northern south america based on projected changes in climate, land cover and human population
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4546039/
https://www.ncbi.nlm.nih.gov/pubmed/26289677
http://dx.doi.org/10.1186/s13071-015-1033-9
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