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Predicting the potential geographical distribution of onion thrips, Thrips tabaci in India based on climate change projections using MaxEnt

Onion thrips, Thrips tabaci Lindeman, an economically important onion pest in India, poses a severe threat to the domestic and export supply of onions. Therefore, it is important to study the distribution of this pest in order to assess the possible crop loss, which it may inflict if not managed in...

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Autores principales: Karuppaiah, V., Maruthadurai, R., Das, Bappa, Soumia, P. S., Gadge, Ankush S., Thangasamy, A., Ramesh, S. V., Shirsat, Dhananjay V., Mahajan, Vijay, Krishna, Hare, Singh, Major
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10188569/
https://www.ncbi.nlm.nih.gov/pubmed/37193780
http://dx.doi.org/10.1038/s41598-023-35012-y
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author Karuppaiah, V.
Maruthadurai, R.
Das, Bappa
Soumia, P. S.
Gadge, Ankush S.
Thangasamy, A.
Ramesh, S. V.
Shirsat, Dhananjay V.
Mahajan, Vijay
Krishna, Hare
Singh, Major
author_facet Karuppaiah, V.
Maruthadurai, R.
Das, Bappa
Soumia, P. S.
Gadge, Ankush S.
Thangasamy, A.
Ramesh, S. V.
Shirsat, Dhananjay V.
Mahajan, Vijay
Krishna, Hare
Singh, Major
author_sort Karuppaiah, V.
collection PubMed
description Onion thrips, Thrips tabaci Lindeman, an economically important onion pest in India, poses a severe threat to the domestic and export supply of onions. Therefore, it is important to study the distribution of this pest in order to assess the possible crop loss, which it may inflict if not managed in time. In this study, MaxEnt was used to analyze the potential distribution of T. tabaci in India and predict the changes in the suitable areas for onion thrips under two scenarios, SSP126 and SSP585. The area under the receiver operating characteristic curve values of 0.993 and 0.989 for training and testing demonstrated excellent model accuracy. The true skill statistic value of 0.944 and 0.921, and the continuous Boyce index of 0.964 and 0.889 for training and testing, also showed higher model accuracy. Annual Mean Temperature (bio1), Annual Precipitation (bio12) and Precipitation Seasonality (bio15) are the main variables that determined the potential distribution of T. tabaci, with the suitable range of 22–28 °C; 300–1000 mm and 70–160, respectively. T. tabaci is distributed mainly in India's central and southern states, with 1.17 × 10(6) km(2), covering 36.4% of land area under the current scenario. Multimodal ensembles show that under a low emission scenario (SSP126), low, moderate and optimum suitable areas of T. tabaci is likely to increase, while highly suitable areas would decrease by 17.4% in 2050 20.9% in 2070. Whereas, under the high emission scenario (SSP585), the high suitability is likely to contract by 24.2% and 51.7% for 2050 and 2070, respectively. According to the prediction of the BCC-CSM2-MR, CanESM5, CNRM-CM6-1 and MIROC6 model, the highly suitable area for T. tabaci would likely contract under both SSP126 and SSP585. This study detailed the potential future habitable area for T. tabaci in India, which could help monitor and devise efficient management strategies for this destructive pest.
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spelling pubmed-101885692023-05-18 Predicting the potential geographical distribution of onion thrips, Thrips tabaci in India based on climate change projections using MaxEnt Karuppaiah, V. Maruthadurai, R. Das, Bappa Soumia, P. S. Gadge, Ankush S. Thangasamy, A. Ramesh, S. V. Shirsat, Dhananjay V. Mahajan, Vijay Krishna, Hare Singh, Major Sci Rep Article Onion thrips, Thrips tabaci Lindeman, an economically important onion pest in India, poses a severe threat to the domestic and export supply of onions. Therefore, it is important to study the distribution of this pest in order to assess the possible crop loss, which it may inflict if not managed in time. In this study, MaxEnt was used to analyze the potential distribution of T. tabaci in India and predict the changes in the suitable areas for onion thrips under two scenarios, SSP126 and SSP585. The area under the receiver operating characteristic curve values of 0.993 and 0.989 for training and testing demonstrated excellent model accuracy. The true skill statistic value of 0.944 and 0.921, and the continuous Boyce index of 0.964 and 0.889 for training and testing, also showed higher model accuracy. Annual Mean Temperature (bio1), Annual Precipitation (bio12) and Precipitation Seasonality (bio15) are the main variables that determined the potential distribution of T. tabaci, with the suitable range of 22–28 °C; 300–1000 mm and 70–160, respectively. T. tabaci is distributed mainly in India's central and southern states, with 1.17 × 10(6) km(2), covering 36.4% of land area under the current scenario. Multimodal ensembles show that under a low emission scenario (SSP126), low, moderate and optimum suitable areas of T. tabaci is likely to increase, while highly suitable areas would decrease by 17.4% in 2050 20.9% in 2070. Whereas, under the high emission scenario (SSP585), the high suitability is likely to contract by 24.2% and 51.7% for 2050 and 2070, respectively. According to the prediction of the BCC-CSM2-MR, CanESM5, CNRM-CM6-1 and MIROC6 model, the highly suitable area for T. tabaci would likely contract under both SSP126 and SSP585. This study detailed the potential future habitable area for T. tabaci in India, which could help monitor and devise efficient management strategies for this destructive pest. Nature Publishing Group UK 2023-05-16 /pmc/articles/PMC10188569/ /pubmed/37193780 http://dx.doi.org/10.1038/s41598-023-35012-y 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 Article
Karuppaiah, V.
Maruthadurai, R.
Das, Bappa
Soumia, P. S.
Gadge, Ankush S.
Thangasamy, A.
Ramesh, S. V.
Shirsat, Dhananjay V.
Mahajan, Vijay
Krishna, Hare
Singh, Major
Predicting the potential geographical distribution of onion thrips, Thrips tabaci in India based on climate change projections using MaxEnt
title Predicting the potential geographical distribution of onion thrips, Thrips tabaci in India based on climate change projections using MaxEnt
title_full Predicting the potential geographical distribution of onion thrips, Thrips tabaci in India based on climate change projections using MaxEnt
title_fullStr Predicting the potential geographical distribution of onion thrips, Thrips tabaci in India based on climate change projections using MaxEnt
title_full_unstemmed Predicting the potential geographical distribution of onion thrips, Thrips tabaci in India based on climate change projections using MaxEnt
title_short Predicting the potential geographical distribution of onion thrips, Thrips tabaci in India based on climate change projections using MaxEnt
title_sort predicting the potential geographical distribution of onion thrips, thrips tabaci in india based on climate change projections using maxent
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10188569/
https://www.ncbi.nlm.nih.gov/pubmed/37193780
http://dx.doi.org/10.1038/s41598-023-35012-y
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