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Future land-use change predictions using Dyna-Clue to support mosquito-borne disease risk assessment
Mosquitoes are known vectors for viral diseases in Canada, and their distribution is driven by climate and land use. Despite that, future land-use changes have not yet been used as a driver in mosquito distribution models in North America. In this paper, we developed land-use change projections desi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246872/ https://www.ncbi.nlm.nih.gov/pubmed/37286856 http://dx.doi.org/10.1007/s10661-023-11394-4 |
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author | Rakotoarinia, Miarisoa Rindra Seidou, Ousmane Lapen, David R. Leighton, Patrick A. Ogden, Nicholas H. Ludwig, Antoinette |
author_facet | Rakotoarinia, Miarisoa Rindra Seidou, Ousmane Lapen, David R. Leighton, Patrick A. Ogden, Nicholas H. Ludwig, Antoinette |
author_sort | Rakotoarinia, Miarisoa Rindra |
collection | PubMed |
description | Mosquitoes are known vectors for viral diseases in Canada, and their distribution is driven by climate and land use. Despite that, future land-use changes have not yet been used as a driver in mosquito distribution models in North America. In this paper, we developed land-use change projections designed to address mosquito-borne disease (MBD) prediction in a 38 761 km(2) area of Eastern Ontario. The landscape in the study area is marked by urbanization and intensive agriculture and hosts a diverse mosquito community. The Dyna-CLUE model was used to project land-use for three time horizons (2030, 2050, and 2070) based on historical trends (from 2014 to 2020) for water, forest, agriculture, and urban land uses. Five scenarios were generated to reflect urbanization, agricultural expansion, and natural areas. An ensemble of thirty simulations per scenario was run to account for land-use conversion uncertainty. The simulation closest to the average map generated was selected to represent the scenario. A concordance matrix generated using map pair analysis showed a good agreement between the simulated 2020 maps and 2020 observed map. By 2050, the most significant changes are predicted to occur mainly in the southeastern region’s rural and forested areas. By 2070, high deforestation is expected in the central west. These results will be integrated into risk models predicting mosquito distribution to study the possibility of humans’ increased exposure risk to MBDs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10661-023-11394-4. |
format | Online Article Text |
id | pubmed-10246872 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-102468722023-06-08 Future land-use change predictions using Dyna-Clue to support mosquito-borne disease risk assessment Rakotoarinia, Miarisoa Rindra Seidou, Ousmane Lapen, David R. Leighton, Patrick A. Ogden, Nicholas H. Ludwig, Antoinette Environ Monit Assess Research Mosquitoes are known vectors for viral diseases in Canada, and their distribution is driven by climate and land use. Despite that, future land-use changes have not yet been used as a driver in mosquito distribution models in North America. In this paper, we developed land-use change projections designed to address mosquito-borne disease (MBD) prediction in a 38 761 km(2) area of Eastern Ontario. The landscape in the study area is marked by urbanization and intensive agriculture and hosts a diverse mosquito community. The Dyna-CLUE model was used to project land-use for three time horizons (2030, 2050, and 2070) based on historical trends (from 2014 to 2020) for water, forest, agriculture, and urban land uses. Five scenarios were generated to reflect urbanization, agricultural expansion, and natural areas. An ensemble of thirty simulations per scenario was run to account for land-use conversion uncertainty. The simulation closest to the average map generated was selected to represent the scenario. A concordance matrix generated using map pair analysis showed a good agreement between the simulated 2020 maps and 2020 observed map. By 2050, the most significant changes are predicted to occur mainly in the southeastern region’s rural and forested areas. By 2070, high deforestation is expected in the central west. These results will be integrated into risk models predicting mosquito distribution to study the possibility of humans’ increased exposure risk to MBDs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10661-023-11394-4. Springer International Publishing 2023-06-07 2023 /pmc/articles/PMC10246872/ /pubmed/37286856 http://dx.doi.org/10.1007/s10661-023-11394-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Rakotoarinia, Miarisoa Rindra Seidou, Ousmane Lapen, David R. Leighton, Patrick A. Ogden, Nicholas H. Ludwig, Antoinette Future land-use change predictions using Dyna-Clue to support mosquito-borne disease risk assessment |
title | Future land-use change predictions using Dyna-Clue to support mosquito-borne disease risk assessment |
title_full | Future land-use change predictions using Dyna-Clue to support mosquito-borne disease risk assessment |
title_fullStr | Future land-use change predictions using Dyna-Clue to support mosquito-borne disease risk assessment |
title_full_unstemmed | Future land-use change predictions using Dyna-Clue to support mosquito-borne disease risk assessment |
title_short | Future land-use change predictions using Dyna-Clue to support mosquito-borne disease risk assessment |
title_sort | future land-use change predictions using dyna-clue to support mosquito-borne disease risk assessment |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246872/ https://www.ncbi.nlm.nih.gov/pubmed/37286856 http://dx.doi.org/10.1007/s10661-023-11394-4 |
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