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Predicting Climate Change Effects on the Potential Distribution of Two Invasive Cryptic Species of the Bemisia tabaci Species Complex in China
SIMPLE SUMMARY: Biological invasions have become an ecological issue worldwide, and climate change may further influence the spread of invasive species. In this study, the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) data were used to predict the suitable habitats of two invasive cry...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9783486/ https://www.ncbi.nlm.nih.gov/pubmed/36554991 http://dx.doi.org/10.3390/insects13121081 |
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author | Xue, Yantao Lin, Congtian Wang, Yaozhuo Liu, Wanxue Wan, Fanghao Zhang, Yibo Ji, Liqiang |
author_facet | Xue, Yantao Lin, Congtian Wang, Yaozhuo Liu, Wanxue Wan, Fanghao Zhang, Yibo Ji, Liqiang |
author_sort | Xue, Yantao |
collection | PubMed |
description | SIMPLE SUMMARY: Biological invasions have become an ecological issue worldwide, and climate change may further influence the spread of invasive species. In this study, the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) data were used to predict the suitable habitats of two invasive cryptic species, namely Middle East-Asia Minor 1 (MEAM1) and Mediterranean (MED), of the Bemisia tabaci species complex in China based on a species distribution modeling technique in current and future climate change scenarios from the present to the end of the 21st century. The results demonstrated differences in the future changes and dispersal in their suitable habitats in China under different future climatic scenarios, which suggests that climate change would have greater but divergent impacts on the potential distribution of these two invasive cryptic species. It has direct implications for developing regional management strategies in China for certain periods in the future and also provides a practical approach that can be applied to other invasive species. ABSTRACT: Middle East-Asia Minor 1 (MEAM1) and Mediterranean (MED) are two invasive cryptic species of the Bemisia tabaci species complex (Hemiptera: Aleyrodidae) that cause serious damage to agricultural and horticultural crops worldwide. To explore the possible impact of climate change on their distribution, the maximum entropy (MaxEnt) model was used to predict the potential distribution ranges of MEAM1 and MED in China under current and four future climate scenarios, using shared socioeconomic pathways (SSPs), namely SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, over four time periods (2021–2040, 2041–2060, 2061–2080, and 2081–2100). The distribution ranges of MEAM1 and MED were extensive and similar in China under current climatic conditions, while their moderately and highly suitable habitat ranges differed. Under future climate scenarios, the areas of suitable habitat of different levels for MEAM1 and MED were predicted to increase to different degrees. However, the predicted expansion of suitable habitats varied between them, suggesting that these invasive cryptic species respond differently to climate change. Our results illustrate the difference in the effects of climate change on the geographical distribution of different cryptic species of B. tabaci and provide insightful information for further forecasting and managing the two invasive cryptic species in China. |
format | Online Article Text |
id | pubmed-9783486 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97834862022-12-24 Predicting Climate Change Effects on the Potential Distribution of Two Invasive Cryptic Species of the Bemisia tabaci Species Complex in China Xue, Yantao Lin, Congtian Wang, Yaozhuo Liu, Wanxue Wan, Fanghao Zhang, Yibo Ji, Liqiang Insects Article SIMPLE SUMMARY: Biological invasions have become an ecological issue worldwide, and climate change may further influence the spread of invasive species. In this study, the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) data were used to predict the suitable habitats of two invasive cryptic species, namely Middle East-Asia Minor 1 (MEAM1) and Mediterranean (MED), of the Bemisia tabaci species complex in China based on a species distribution modeling technique in current and future climate change scenarios from the present to the end of the 21st century. The results demonstrated differences in the future changes and dispersal in their suitable habitats in China under different future climatic scenarios, which suggests that climate change would have greater but divergent impacts on the potential distribution of these two invasive cryptic species. It has direct implications for developing regional management strategies in China for certain periods in the future and also provides a practical approach that can be applied to other invasive species. ABSTRACT: Middle East-Asia Minor 1 (MEAM1) and Mediterranean (MED) are two invasive cryptic species of the Bemisia tabaci species complex (Hemiptera: Aleyrodidae) that cause serious damage to agricultural and horticultural crops worldwide. To explore the possible impact of climate change on their distribution, the maximum entropy (MaxEnt) model was used to predict the potential distribution ranges of MEAM1 and MED in China under current and four future climate scenarios, using shared socioeconomic pathways (SSPs), namely SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, over four time periods (2021–2040, 2041–2060, 2061–2080, and 2081–2100). The distribution ranges of MEAM1 and MED were extensive and similar in China under current climatic conditions, while their moderately and highly suitable habitat ranges differed. Under future climate scenarios, the areas of suitable habitat of different levels for MEAM1 and MED were predicted to increase to different degrees. However, the predicted expansion of suitable habitats varied between them, suggesting that these invasive cryptic species respond differently to climate change. Our results illustrate the difference in the effects of climate change on the geographical distribution of different cryptic species of B. tabaci and provide insightful information for further forecasting and managing the two invasive cryptic species in China. MDPI 2022-11-23 /pmc/articles/PMC9783486/ /pubmed/36554991 http://dx.doi.org/10.3390/insects13121081 Text en © 2022 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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Xue, Yantao Lin, Congtian Wang, Yaozhuo Liu, Wanxue Wan, Fanghao Zhang, Yibo Ji, Liqiang Predicting Climate Change Effects on the Potential Distribution of Two Invasive Cryptic Species of the Bemisia tabaci Species Complex in China |
title | Predicting Climate Change Effects on the Potential Distribution of Two Invasive Cryptic Species of the Bemisia tabaci Species Complex in China |
title_full | Predicting Climate Change Effects on the Potential Distribution of Two Invasive Cryptic Species of the Bemisia tabaci Species Complex in China |
title_fullStr | Predicting Climate Change Effects on the Potential Distribution of Two Invasive Cryptic Species of the Bemisia tabaci Species Complex in China |
title_full_unstemmed | Predicting Climate Change Effects on the Potential Distribution of Two Invasive Cryptic Species of the Bemisia tabaci Species Complex in China |
title_short | Predicting Climate Change Effects on the Potential Distribution of Two Invasive Cryptic Species of the Bemisia tabaci Species Complex in China |
title_sort | predicting climate change effects on the potential distribution of two invasive cryptic species of the bemisia tabaci species complex in china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9783486/ https://www.ncbi.nlm.nih.gov/pubmed/36554991 http://dx.doi.org/10.3390/insects13121081 |
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