Ecological niche shifts affect the potential invasive risk of Phytolacca americana (Phytolaccaceae) in China
Background Predicting the potential habitat of Phytolacca americana, a high-risk invasive species, can help provide a scientific basis for its quarantine and control strategies. Using the optimized MaxEnt model, we applied the latest climate data, CMIP6, to predict the distribution of potential risk...
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Published in | Ecological processes Vol. 12; no. 1; p. 1 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.12.2023
Springer Nature B.V SpringerOpen |
Subjects | |
Online Access | Get full text |
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Abstract | Background
Predicting the potential habitat of
Phytolacca americana,
a high-risk invasive species, can help provide a scientific basis for its quarantine and control strategies. Using the optimized MaxEnt model, we applied the latest climate data, CMIP6, to predict the distribution of potential risk zones and their change patterns for
P
.
americana
under current and future (SSP126, SSP245, SSP585) climate conditions, followed by invasion potential analysis.
Results
The predictions of MaxEnt model based on R language optimization were highly accurate. A significantly high area of 0.8703 was observed for working characteristic curve (AUC value) of subject and the kappa value was 0.8074. Under the current climate conditions, the risk zones for
P. americana
were mainly distributed in Sichuan, Chongqing, Guizhou, Hunan, and Guangxi provinces. The contribution rate of each climatic factor of
P
.
americana
was calculated using the jackknife test. The four factors with the highest contribution rate included minimum temperature of coldest month (bio6, 51.4%), the monthly mean diurnal temperature difference (bio2, 27.9%), precipitation of the driest quarter (bio17, 4.9%), and the warmest seasonal precipitation (bio12, 4.3%).
Conclusion
Under future climatic conditions, the change in the habitat pattern of
P
.
americana
generally showed a migration toward the Yangtze River Delta region and the southeastern coastal region of China. This migration exhibited an expansion trend, highlighting the strong future invasiveness of the species. Based on the predictions, targeted prevention and control strategies for areas with significant changes in
P
.
americana
were developed. Therefore, this study emphasizes the need of an integrated approach to effectively prevent the further spread of invasive plants. |
---|---|
AbstractList | Abstract Background Predicting the potential habitat of Phytolacca americana, a high-risk invasive species, can help provide a scientific basis for its quarantine and control strategies. Using the optimized MaxEnt model, we applied the latest climate data, CMIP6, to predict the distribution of potential risk zones and their change patterns for P. americana under current and future (SSP126, SSP245, SSP585) climate conditions, followed by invasion potential analysis. Results The predictions of MaxEnt model based on R language optimization were highly accurate. A significantly high area of 0.8703 was observed for working characteristic curve (AUC value) of subject and the kappa value was 0.8074. Under the current climate conditions, the risk zones for P. americana were mainly distributed in Sichuan, Chongqing, Guizhou, Hunan, and Guangxi provinces. The contribution rate of each climatic factor of P. americana was calculated using the jackknife test. The four factors with the highest contribution rate included minimum temperature of coldest month (bio6, 51.4%), the monthly mean diurnal temperature difference (bio2, 27.9%), precipitation of the driest quarter (bio17, 4.9%), and the warmest seasonal precipitation (bio12, 4.3%). Conclusion Under future climatic conditions, the change in the habitat pattern of P. americana generally showed a migration toward the Yangtze River Delta region and the southeastern coastal region of China. This migration exhibited an expansion trend, highlighting the strong future invasiveness of the species. Based on the predictions, targeted prevention and control strategies for areas with significant changes in P. americana were developed. Therefore, this study emphasizes the need of an integrated approach to effectively prevent the further spread of invasive plants. Background Predicting the potential habitat of Phytolacca americana, a high-risk invasive species, can help provide a scientific basis for its quarantine and control strategies. Using the optimized MaxEnt model, we applied the latest climate data, CMIP6, to predict the distribution of potential risk zones and their change patterns for P . americana under current and future (SSP126, SSP245, SSP585) climate conditions, followed by invasion potential analysis. Results The predictions of MaxEnt model based on R language optimization were highly accurate. A significantly high area of 0.8703 was observed for working characteristic curve (AUC value) of subject and the kappa value was 0.8074. Under the current climate conditions, the risk zones for P. americana were mainly distributed in Sichuan, Chongqing, Guizhou, Hunan, and Guangxi provinces. The contribution rate of each climatic factor of P . americana was calculated using the jackknife test. The four factors with the highest contribution rate included minimum temperature of coldest month (bio6, 51.4%), the monthly mean diurnal temperature difference (bio2, 27.9%), precipitation of the driest quarter (bio17, 4.9%), and the warmest seasonal precipitation (bio12, 4.3%). Conclusion Under future climatic conditions, the change in the habitat pattern of P . americana generally showed a migration toward the Yangtze River Delta region and the southeastern coastal region of China. This migration exhibited an expansion trend, highlighting the strong future invasiveness of the species. Based on the predictions, targeted prevention and control strategies for areas with significant changes in P . americana were developed. Therefore, this study emphasizes the need of an integrated approach to effectively prevent the further spread of invasive plants. BACKGROUND: Predicting the potential habitat of Phytolacca americana, a high-risk invasive species, can help provide a scientific basis for its quarantine and control strategies. Using the optimized MaxEnt model, we applied the latest climate data, CMIP6, to predict the distribution of potential risk zones and their change patterns for P. americana under current and future (SSP126, SSP245, SSP585) climate conditions, followed by invasion potential analysis. RESULTS: The predictions of MaxEnt model based on R language optimization were highly accurate. A significantly high area of 0.8703 was observed for working characteristic curve (AUC value) of subject and the kappa value was 0.8074. Under the current climate conditions, the risk zones for P. americana were mainly distributed in Sichuan, Chongqing, Guizhou, Hunan, and Guangxi provinces. The contribution rate of each climatic factor of P. americana was calculated using the jackknife test. The four factors with the highest contribution rate included minimum temperature of coldest month (bio6, 51.4%), the monthly mean diurnal temperature difference (bio2, 27.9%), precipitation of the driest quarter (bio17, 4.9%), and the warmest seasonal precipitation (bio12, 4.3%). CONCLUSION: Under future climatic conditions, the change in the habitat pattern of P. americana generally showed a migration toward the Yangtze River Delta region and the southeastern coastal region of China. This migration exhibited an expansion trend, highlighting the strong future invasiveness of the species. Based on the predictions, targeted prevention and control strategies for areas with significant changes in P. americana were developed. Therefore, this study emphasizes the need of an integrated approach to effectively prevent the further spread of invasive plants. BackgroundPredicting the potential habitat of Phytolacca americana, a high-risk invasive species, can help provide a scientific basis for its quarantine and control strategies. Using the optimized MaxEnt model, we applied the latest climate data, CMIP6, to predict the distribution of potential risk zones and their change patterns for P. americana under current and future (SSP126, SSP245, SSP585) climate conditions, followed by invasion potential analysis.ResultsThe predictions of MaxEnt model based on R language optimization were highly accurate. A significantly high area of 0.8703 was observed for working characteristic curve (AUC value) of subject and the kappa value was 0.8074. Under the current climate conditions, the risk zones for P. americana were mainly distributed in Sichuan, Chongqing, Guizhou, Hunan, and Guangxi provinces. The contribution rate of each climatic factor of P. americana was calculated using the jackknife test. The four factors with the highest contribution rate included minimum temperature of coldest month (bio6, 51.4%), the monthly mean diurnal temperature difference (bio2, 27.9%), precipitation of the driest quarter (bio17, 4.9%), and the warmest seasonal precipitation (bio12, 4.3%).ConclusionUnder future climatic conditions, the change in the habitat pattern of P. americana generally showed a migration toward the Yangtze River Delta region and the southeastern coastal region of China. This migration exhibited an expansion trend, highlighting the strong future invasiveness of the species. Based on the predictions, targeted prevention and control strategies for areas with significant changes in P. americana were developed. Therefore, this study emphasizes the need of an integrated approach to effectively prevent the further spread of invasive plants. |
ArticleNumber | 1 |
Author | Ahmad, Sagheer Ye, Xingzhuang Weng, Huiying Huang, Qiuliang Yang, Qianyue Liu, Yipeng Zhang, Tianyu Xu, Yifeng Liu, Bao Zhang, Guofang |
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CitedBy_id | crossref_primary_10_1016_j_ijbiomac_2024_135155 crossref_primary_10_3390_agronomy13102498 crossref_primary_10_3390_plants13060883 crossref_primary_10_1007_s11252_024_01658_3 crossref_primary_10_1016_j_scitotenv_2024_173532 crossref_primary_10_1016_j_envres_2023_117270 crossref_primary_10_1186_s13717_023_00477_2 crossref_primary_10_3390_f15091624 crossref_primary_10_1007_s12517_025_12195_4 crossref_primary_10_3390_plants13081082 |
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SSID | ssj0000941497 |
Score | 2.3043976 |
Snippet | Background
Predicting the potential habitat of
Phytolacca americana,
a high-risk invasive species, can help provide a scientific basis for its quarantine and... BackgroundPredicting the potential habitat of Phytolacca americana, a high-risk invasive species, can help provide a scientific basis for its quarantine and... BACKGROUND: Predicting the potential habitat of Phytolacca americana, a high-risk invasive species, can help provide a scientific basis for its quarantine and... Abstract Background Predicting the potential habitat of Phytolacca americana, a high-risk invasive species, can help provide a scientific basis for its... |
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SubjectTerms | China Climate Climate change Climate prediction Climatic conditions Climatic data climatic factors Coastal zone coasts Earth and Environmental Science Ecological distribution Ecological niches Environment Environmental effects Habitats Introduced species Invasive plants Invasive species Invasiveness MaxEnt meteorological data Niches Optimization Phytolacca americana Precipitation quarantine Risk river deltas species temperature Temperature differences Temperature gradients Yangtze River |
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Title | Ecological niche shifts affect the potential invasive risk of Phytolacca americana (Phytolaccaceae) in China |
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