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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doaj-27670230ca5d4f00b118520e4680672c2021-03-01T00:02:58ZengMDPI AGPlants2223-77472021-02-011046046010.3390/plants10030460Assessing the Impact of Climate Change on the Distribution of Lime (16srii-B) and Alfalfa (16srii-D) Phytoplasma Disease Using MaxEntAmna M. Al Ruheili0Alaba Boluwade1Ali M. Al Subhi2Department of Plant Science, College of Agriculture and Marine Science, Sultan Qaboos University, Muscat 123, OmanDepartment of Soil, Water and Agricultural Engineering, College of Agriculture and Marine Science, Sultan Qaboos University, Muscat 123, OmanDepartment of Plant Science, College of Agriculture and Marine Science, Sultan Qaboos University, Muscat 123, OmanWitches’ 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<sup>2</sup> (7.1%), while for 16SrII-B, an area of 8835 km<sup>2</sup> (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.https://www.mdpi.com/2223-7747/10/3/460future projectiondistribution modelbioclimatic variableswitches’ broom disease |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Amna M. Al Ruheili Alaba Boluwade Ali M. Al Subhi |
spellingShingle |
Amna M. Al Ruheili Alaba Boluwade Ali M. Al Subhi Assessing the Impact of Climate Change on the Distribution of Lime (16srii-B) and Alfalfa (16srii-D) Phytoplasma Disease Using MaxEnt Plants future projection distribution model bioclimatic variables witches’ broom disease |
author_facet |
Amna M. Al Ruheili Alaba Boluwade Ali M. Al Subhi |
author_sort |
Amna M. Al Ruheili |
title |
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_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_sort |
assessing the impact of climate change on the distribution of lime (16srii-b) and alfalfa (16srii-d) phytoplasma disease using maxent |
publisher |
MDPI AG |
series |
Plants |
issn |
2223-7747 |
publishDate |
2021-02-01 |
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<sup>2</sup> (7.1%), while for 16SrII-B, an area of 8835 km<sup>2</sup> (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. |
topic |
future projection distribution model bioclimatic variables witches’ broom disease |
url |
https://www.mdpi.com/2223-7747/10/3/460 |
work_keys_str_mv |
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