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Assessing the Impact of Climate Change on the Distribution of Lime (16srii-B) and Alfalfa (16srii-D) Phytoplasma Disease Using MaxEnt

Witches’ broom disease has led to major losses in lime and alfalfa production in Oman. This paper identifies bioclimatic variables that contribute to the prediction of distribution of witches’ broom disease in current and future climatic scenarios. It also explores the expansion, reduction, or shift...

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Autores principales: Al Ruheili, Amna M., Boluwade, Alaba, Al Subhi, Ali M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7997136/
https://www.ncbi.nlm.nih.gov/pubmed/33670998
http://dx.doi.org/10.3390/plants10030460
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author Al Ruheili, Amna M.
Boluwade, Alaba
Al Subhi, Ali M.
author_facet Al Ruheili, Amna M.
Boluwade, Alaba
Al Subhi, Ali M.
author_sort Al Ruheili, Amna M.
collection PubMed
description Witches’ broom disease has led to major losses in lime and alfalfa production in Oman. This paper identifies bioclimatic variables that contribute to the prediction of distribution of witches’ broom disease in current and future climatic scenarios. It also explores the expansion, reduction, or shift in the climatic niche of the distribution of the disease across the different geographical areas of the entire country (309,501 km²). The maximum entropy model (MaxEnt) and geographical information system were used to investigate the potential suitability of habitats for the phytoplasma disease. This study used current (1970–2000) and future projected climatic scenarios (2021–2040, 2041–2060, 2061–2080, and 2081–2100) to model the distribution of phytoplasma for lime trees and alfalfa in Oman. Bioclimatic variables were downloaded from WorldClim with ± 60 occurrence points for lime trees and alfalfa. The area under the curve (AUC) was used to evaluate the model’s performance. Quantitatively, the results showed that the mean of the AUC values for lime (16SrII-B) and alfalfa (16SrII-D) future distribution for the periods of 2021–2040, 2041–2060, 2061–2080, and 2081–2100 were rated as “excellent”, with the values for the specified time periods being 0.859, 0.900, 0.931, and 0.913 for 16SrII-B; and 0.826, 0.837, 08.58, and 0.894 for 16SrII-D respectively. In addition, this study identified the hotspots and proportions of the areas that are vulnerable under the projected climate-change scenarios. The area of current (2021–2040) highly suitable distribution within the entire country for 16SrII-D was 19474.2 km(2) (7.1%), while for 16SrII-B, an area of 8835 km(2) (3.2%) was also highly suitable for the disease distribution. The proportions of these suitable areas are very significant from the available arable land standpoint. Therefore, the results from this study will be of immense benefit and will also bring significant contributions in mapping the areas of witches’ broom diseases in Oman. The results will equally aid the development of new strategies and the formulation of agricultural policies and practices in controlling the spread of the disease across Oman.
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spelling pubmed-79971362021-03-27 Assessing the Impact of Climate Change on the Distribution of Lime (16srii-B) and Alfalfa (16srii-D) Phytoplasma Disease Using MaxEnt Al Ruheili, Amna M. Boluwade, Alaba Al Subhi, Ali M. Plants (Basel) Article Witches’ broom disease has led to major losses in lime and alfalfa production in Oman. This paper identifies bioclimatic variables that contribute to the prediction of distribution of witches’ broom disease in current and future climatic scenarios. It also explores the expansion, reduction, or shift in the climatic niche of the distribution of the disease across the different geographical areas of the entire country (309,501 km²). The maximum entropy model (MaxEnt) and geographical information system were used to investigate the potential suitability of habitats for the phytoplasma disease. This study used current (1970–2000) and future projected climatic scenarios (2021–2040, 2041–2060, 2061–2080, and 2081–2100) to model the distribution of phytoplasma for lime trees and alfalfa in Oman. Bioclimatic variables were downloaded from WorldClim with ± 60 occurrence points for lime trees and alfalfa. The area under the curve (AUC) was used to evaluate the model’s performance. Quantitatively, the results showed that the mean of the AUC values for lime (16SrII-B) and alfalfa (16SrII-D) future distribution for the periods of 2021–2040, 2041–2060, 2061–2080, and 2081–2100 were rated as “excellent”, with the values for the specified time periods being 0.859, 0.900, 0.931, and 0.913 for 16SrII-B; and 0.826, 0.837, 08.58, and 0.894 for 16SrII-D respectively. In addition, this study identified the hotspots and proportions of the areas that are vulnerable under the projected climate-change scenarios. The area of current (2021–2040) highly suitable distribution within the entire country for 16SrII-D was 19474.2 km(2) (7.1%), while for 16SrII-B, an area of 8835 km(2) (3.2%) was also highly suitable for the disease distribution. The proportions of these suitable areas are very significant from the available arable land standpoint. Therefore, the results from this study will be of immense benefit and will also bring significant contributions in mapping the areas of witches’ broom diseases in Oman. The results will equally aid the development of new strategies and the formulation of agricultural policies and practices in controlling the spread of the disease across Oman. MDPI 2021-02-28 /pmc/articles/PMC7997136/ /pubmed/33670998 http://dx.doi.org/10.3390/plants10030460 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Al Ruheili, Amna M.
Boluwade, Alaba
Al Subhi, Ali M.
Assessing the Impact of Climate Change on the Distribution of Lime (16srii-B) and Alfalfa (16srii-D) Phytoplasma Disease Using MaxEnt
title Assessing the Impact of Climate Change on the Distribution of Lime (16srii-B) and Alfalfa (16srii-D) Phytoplasma Disease Using MaxEnt
title_full Assessing the Impact of Climate Change on the Distribution of Lime (16srii-B) and Alfalfa (16srii-D) Phytoplasma Disease Using MaxEnt
title_fullStr Assessing the Impact of Climate Change on the Distribution of Lime (16srii-B) and Alfalfa (16srii-D) Phytoplasma Disease Using MaxEnt
title_full_unstemmed Assessing the Impact of Climate Change on the Distribution of Lime (16srii-B) and Alfalfa (16srii-D) Phytoplasma Disease Using MaxEnt
title_short Assessing the Impact of Climate Change on the Distribution of Lime (16srii-B) and Alfalfa (16srii-D) Phytoplasma Disease Using MaxEnt
title_sort assessing the impact of climate change on the distribution of lime (16srii-b) and alfalfa (16srii-d) phytoplasma disease using maxent
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7997136/
https://www.ncbi.nlm.nih.gov/pubmed/33670998
http://dx.doi.org/10.3390/plants10030460
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