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Invasive Trends of Spartina alterniflora in the Southeastern Coast of China and Potential Distributional Impacts on Mangrove Forests

Mangrove forests are one of the most productive and seriously threatened ecosystems in the world. The widespread invasion of Spartina alterniflora has seriously imperiled the security of mangroves as well as coastal mudflat ecosystems. Based on a model evaluation index, we selected RF, GBM, and GLM...

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Autores principales: Zheng, Jiaying, Wei, Haiyan, Chen, Ruidun, Liu, Jiamin, Wang, Lukun, Gu, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10222674/
https://www.ncbi.nlm.nih.gov/pubmed/37653840
http://dx.doi.org/10.3390/plants12101923
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author Zheng, Jiaying
Wei, Haiyan
Chen, Ruidun
Liu, Jiamin
Wang, Lukun
Gu, Wei
author_facet Zheng, Jiaying
Wei, Haiyan
Chen, Ruidun
Liu, Jiamin
Wang, Lukun
Gu, Wei
author_sort Zheng, Jiaying
collection PubMed
description Mangrove forests are one of the most productive and seriously threatened ecosystems in the world. The widespread invasion of Spartina alterniflora has seriously imperiled the security of mangroves as well as coastal mudflat ecosystems. Based on a model evaluation index, we selected RF, GBM, and GLM as a predictive model for building a high-precision ensemble model. We used the species occurrence records combined with bioclimate, sea–land topography, and marine environmental factors to predict the potentially suitable habitats of mangrove forests and the potentially suitable invasive habitats of S. alterniflora in the southeastern coast of China. We then applied the invasion risk index (IRI) to assess the risk that S. alterniflora would invade mangrove forests. The results show that the suitable habitats for mangrove forests are mainly distributed along the coastal provinces of Guangdong, Hainan, and the eastern coast of Guangxi. The suitable invasive habitats for S. alterniflora are mainly distributed along the coast of Zhejiang, Fujian, and relatively less in the southern provinces. The high-risk areas for S. alterniflora invasion of mangrove forests are concentrated in Zhejiang and Fujian. Bioclimate variables are the most important variables affecting the survival and distribution of mangrove forests and S. alterniflora. Among them, temperature is the most important environmental variable determining the large-scale distribution of mangrove forests. Meanwhile, S. alterniflora is more sensitive to precipitation than temperature. Our results can provide scientific insights and references for mangrove forest conservation and control of S. alterniflora.
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spelling pubmed-102226742023-05-28 Invasive Trends of Spartina alterniflora in the Southeastern Coast of China and Potential Distributional Impacts on Mangrove Forests Zheng, Jiaying Wei, Haiyan Chen, Ruidun Liu, Jiamin Wang, Lukun Gu, Wei Plants (Basel) Article Mangrove forests are one of the most productive and seriously threatened ecosystems in the world. The widespread invasion of Spartina alterniflora has seriously imperiled the security of mangroves as well as coastal mudflat ecosystems. Based on a model evaluation index, we selected RF, GBM, and GLM as a predictive model for building a high-precision ensemble model. We used the species occurrence records combined with bioclimate, sea–land topography, and marine environmental factors to predict the potentially suitable habitats of mangrove forests and the potentially suitable invasive habitats of S. alterniflora in the southeastern coast of China. We then applied the invasion risk index (IRI) to assess the risk that S. alterniflora would invade mangrove forests. The results show that the suitable habitats for mangrove forests are mainly distributed along the coastal provinces of Guangdong, Hainan, and the eastern coast of Guangxi. The suitable invasive habitats for S. alterniflora are mainly distributed along the coast of Zhejiang, Fujian, and relatively less in the southern provinces. The high-risk areas for S. alterniflora invasion of mangrove forests are concentrated in Zhejiang and Fujian. Bioclimate variables are the most important variables affecting the survival and distribution of mangrove forests and S. alterniflora. Among them, temperature is the most important environmental variable determining the large-scale distribution of mangrove forests. Meanwhile, S. alterniflora is more sensitive to precipitation than temperature. Our results can provide scientific insights and references for mangrove forest conservation and control of S. alterniflora. MDPI 2023-05-09 /pmc/articles/PMC10222674/ /pubmed/37653840 http://dx.doi.org/10.3390/plants12101923 Text en © 2023 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
Zheng, Jiaying
Wei, Haiyan
Chen, Ruidun
Liu, Jiamin
Wang, Lukun
Gu, Wei
Invasive Trends of Spartina alterniflora in the Southeastern Coast of China and Potential Distributional Impacts on Mangrove Forests
title Invasive Trends of Spartina alterniflora in the Southeastern Coast of China and Potential Distributional Impacts on Mangrove Forests
title_full Invasive Trends of Spartina alterniflora in the Southeastern Coast of China and Potential Distributional Impacts on Mangrove Forests
title_fullStr Invasive Trends of Spartina alterniflora in the Southeastern Coast of China and Potential Distributional Impacts on Mangrove Forests
title_full_unstemmed Invasive Trends of Spartina alterniflora in the Southeastern Coast of China and Potential Distributional Impacts on Mangrove Forests
title_short Invasive Trends of Spartina alterniflora in the Southeastern Coast of China and Potential Distributional Impacts on Mangrove Forests
title_sort invasive trends of spartina alterniflora in the southeastern coast of china and potential distributional impacts on mangrove forests
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10222674/
https://www.ncbi.nlm.nih.gov/pubmed/37653840
http://dx.doi.org/10.3390/plants12101923
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