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Modelling the impact of climate change on the distribution and abundance of tsetse in Northern Zimbabwe
BACKGROUND: Climate change is predicted to impact the transmission dynamics of vector-borne diseases. Tsetse flies (Glossina) transmit species of Trypanosoma that cause human and animal African trypanosomiasis. A previous modelling study showed that temperature increases between 1990 and 2017 can ex...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7574501/ https://www.ncbi.nlm.nih.gov/pubmed/33076987 http://dx.doi.org/10.1186/s13071-020-04398-3 |
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author | Longbottom, Joshua Caminade, Cyril Gibson, Harry S. Weiss, Daniel J. Torr, Steve Lord, Jennifer S. |
author_facet | Longbottom, Joshua Caminade, Cyril Gibson, Harry S. Weiss, Daniel J. Torr, Steve Lord, Jennifer S. |
author_sort | Longbottom, Joshua |
collection | PubMed |
description | BACKGROUND: Climate change is predicted to impact the transmission dynamics of vector-borne diseases. Tsetse flies (Glossina) transmit species of Trypanosoma that cause human and animal African trypanosomiasis. A previous modelling study showed that temperature increases between 1990 and 2017 can explain the observed decline in abundance of tsetse at a single site in the Mana Pools National Park of Zimbabwe. Here, we apply a mechanistic model of tsetse population dynamics to predict how increases in temperature may have changed the distribution and relative abundance of Glossina pallidipes across northern Zimbabwe. METHODS: Local weather station temperature measurements were previously used to fit the mechanistic model to longitudinal G. pallidipes catch data. To extend the use of the model, we converted MODIS land surface temperature to air temperature, compared the converted temperatures with available weather station data to confirm they aligned, and then re-fitted the mechanistic model using G. pallidipes catch data and air temperature estimates. We projected this fitted model across northern Zimbabwe, using simulations at a 1 km × 1 km spatial resolution, between 2000 to 2016. RESULTS: We produced estimates of relative changes in G. pallidipes mortality, larviposition, emergence rates and abundance, for northern Zimbabwe. Our model predicts decreasing tsetse populations within low elevation areas in response to increasing temperature trends during 2000–2016. Conversely, we show that high elevation areas (> 1000 m above sea level), previously considered too cold to sustain tsetse, may now be climatically suitable. CONCLUSIONS: To our knowledge, the results of this research represent the first regional-scale assessment of temperature related tsetse population dynamics, and the first high spatial-resolution estimates of this metric for northern Zimbabwe. Our results suggest that tsetse abundance may have declined across much of the Zambezi Valley in response to changing climatic conditions during the study period. Future research including empirical studies is planned to improve model accuracy and validate predictions for other field sites in Zimbabwe. [Image: see text] |
format | Online Article Text |
id | pubmed-7574501 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-75745012020-10-21 Modelling the impact of climate change on the distribution and abundance of tsetse in Northern Zimbabwe Longbottom, Joshua Caminade, Cyril Gibson, Harry S. Weiss, Daniel J. Torr, Steve Lord, Jennifer S. Parasit Vectors Research BACKGROUND: Climate change is predicted to impact the transmission dynamics of vector-borne diseases. Tsetse flies (Glossina) transmit species of Trypanosoma that cause human and animal African trypanosomiasis. A previous modelling study showed that temperature increases between 1990 and 2017 can explain the observed decline in abundance of tsetse at a single site in the Mana Pools National Park of Zimbabwe. Here, we apply a mechanistic model of tsetse population dynamics to predict how increases in temperature may have changed the distribution and relative abundance of Glossina pallidipes across northern Zimbabwe. METHODS: Local weather station temperature measurements were previously used to fit the mechanistic model to longitudinal G. pallidipes catch data. To extend the use of the model, we converted MODIS land surface temperature to air temperature, compared the converted temperatures with available weather station data to confirm they aligned, and then re-fitted the mechanistic model using G. pallidipes catch data and air temperature estimates. We projected this fitted model across northern Zimbabwe, using simulations at a 1 km × 1 km spatial resolution, between 2000 to 2016. RESULTS: We produced estimates of relative changes in G. pallidipes mortality, larviposition, emergence rates and abundance, for northern Zimbabwe. Our model predicts decreasing tsetse populations within low elevation areas in response to increasing temperature trends during 2000–2016. Conversely, we show that high elevation areas (> 1000 m above sea level), previously considered too cold to sustain tsetse, may now be climatically suitable. CONCLUSIONS: To our knowledge, the results of this research represent the first regional-scale assessment of temperature related tsetse population dynamics, and the first high spatial-resolution estimates of this metric for northern Zimbabwe. Our results suggest that tsetse abundance may have declined across much of the Zambezi Valley in response to changing climatic conditions during the study period. Future research including empirical studies is planned to improve model accuracy and validate predictions for other field sites in Zimbabwe. [Image: see text] BioMed Central 2020-10-19 /pmc/articles/PMC7574501/ /pubmed/33076987 http://dx.doi.org/10.1186/s13071-020-04398-3 Text en © The Author(s) 2020 Open AccessThis 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/. 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 in a credit line to the data. |
spellingShingle | Research Longbottom, Joshua Caminade, Cyril Gibson, Harry S. Weiss, Daniel J. Torr, Steve Lord, Jennifer S. Modelling the impact of climate change on the distribution and abundance of tsetse in Northern Zimbabwe |
title | Modelling the impact of climate change on the distribution and abundance of tsetse in Northern Zimbabwe |
title_full | Modelling the impact of climate change on the distribution and abundance of tsetse in Northern Zimbabwe |
title_fullStr | Modelling the impact of climate change on the distribution and abundance of tsetse in Northern Zimbabwe |
title_full_unstemmed | Modelling the impact of climate change on the distribution and abundance of tsetse in Northern Zimbabwe |
title_short | Modelling the impact of climate change on the distribution and abundance of tsetse in Northern Zimbabwe |
title_sort | modelling the impact of climate change on the distribution and abundance of tsetse in northern zimbabwe |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7574501/ https://www.ncbi.nlm.nih.gov/pubmed/33076987 http://dx.doi.org/10.1186/s13071-020-04398-3 |
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