Reconstructing the Invasive History and Potential Distribution Prediction of <i>Amaranthus palmeri</i> in China
Palmer Amaranth (<i>Amaranthus palmeri</i>, Amaranthaceae) is one of the most competitive, troublesome, and noxious weeds causing significant yield reductions in various crops. <i>A. palmeri</i> was also a herbicide-resistant weed causing a serious eco-environmental problem....
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-09-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/13/10/2498 |
| _version_ | 1827722074934738944 |
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| author | Xinyu Jiao Mei Long Jiayi Li Qingyu Yang Zhixiong Liu |
| author_facet | Xinyu Jiao Mei Long Jiayi Li Qingyu Yang Zhixiong Liu |
| author_sort | Xinyu Jiao |
| collection | DOAJ |
| description | Palmer Amaranth (<i>Amaranthus palmeri</i>, Amaranthaceae) is one of the most competitive, troublesome, and noxious weeds causing significant yield reductions in various crops. <i>A. palmeri</i> was also a herbicide-resistant weed causing a serious eco-environmental problem. Given that the process of invasion is dynamic, the <i>A. plamer</i> invasion may already be quite severe where invasive species management and surveys are chronically lacking. Predicting the potential habitat of <i>A. palmeri</i> can help to develop effective measures for early warning and long-term detection. However, the invasive history and distribution patterns of <i>A. palmeri</i> in China remain largely unknown. Here, the invasive history and distribution patterns of <i>A. palmeri</i> from 1985 to 2022 in China were reconstructed, and then the potential geographical distribution of <i>A. palmeri</i> was predicted under current and future climate scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5) using the optimal MaxEnt model (V 3.4.4) and ArcGIS 10.8.2. The mean AUC values of <i>A. palmeri</i> were 0.967. Under the current climate conditions, the suitable habitat areas for <i>A. palmeri</i> reached 1,067,000 km<sup>2</sup> in China and were mainly distributed in north and central China. Under the future scenarios, the highly suitable habitats were mainly distributed in Beijing, Tianjin, and Hebei. Under SSP2–4.5, the future suitable areas will reach the maximum and expand to 1,411,100 km<sup>2</sup> in the 2060s. The centroid distribution would northwestward extend under future climate scenarios. The human footprint index, mean temperature of the warmest quarter (Bio_10), April wind speed (Wind_4), temperature seasonality (standard deviation × 100) (bio_4), topsoil gravel content (T_gravel), and precipitation of warmest quarter (Bio_18) were key environmental variables affecting distribution and growth of <i>A. palmeri</i>. Climate change would increase the risk of <i>A. palmeri</i> expanding to high latitudes. Our results will help in developing effective strategies for the early warning, prevention, control, and management of <i>A. palmeri</i> in China. |
| first_indexed | 2024-03-10T21:30:36Z |
| format | Article |
| id | doaj.art-a9c72b091adf4aecb6687273fd43bd63 |
| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-10T21:30:36Z |
| publishDate | 2023-09-01 |
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| series | Agronomy |
| spelling | doaj.art-a9c72b091adf4aecb6687273fd43bd632023-11-19T15:21:02ZengMDPI AGAgronomy2073-43952023-09-011310249810.3390/agronomy13102498Reconstructing the Invasive History and Potential Distribution Prediction of <i>Amaranthus palmeri</i> in ChinaXinyu Jiao0Mei Long1Jiayi Li2Qingyu Yang3Zhixiong Liu4College of Horticulture and Gardening, Yangtze University, Jingzhou 434025, ChinaCollege of Horticulture and Gardening, Yangtze University, Jingzhou 434025, ChinaCollege of Horticulture and Gardening, Yangtze University, Jingzhou 434025, ChinaCollege of Horticulture and Gardening, Yangtze University, Jingzhou 434025, ChinaCollege of Horticulture and Gardening, Yangtze University, Jingzhou 434025, ChinaPalmer Amaranth (<i>Amaranthus palmeri</i>, Amaranthaceae) is one of the most competitive, troublesome, and noxious weeds causing significant yield reductions in various crops. <i>A. palmeri</i> was also a herbicide-resistant weed causing a serious eco-environmental problem. Given that the process of invasion is dynamic, the <i>A. plamer</i> invasion may already be quite severe where invasive species management and surveys are chronically lacking. Predicting the potential habitat of <i>A. palmeri</i> can help to develop effective measures for early warning and long-term detection. However, the invasive history and distribution patterns of <i>A. palmeri</i> in China remain largely unknown. Here, the invasive history and distribution patterns of <i>A. palmeri</i> from 1985 to 2022 in China were reconstructed, and then the potential geographical distribution of <i>A. palmeri</i> was predicted under current and future climate scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5) using the optimal MaxEnt model (V 3.4.4) and ArcGIS 10.8.2. The mean AUC values of <i>A. palmeri</i> were 0.967. Under the current climate conditions, the suitable habitat areas for <i>A. palmeri</i> reached 1,067,000 km<sup>2</sup> in China and were mainly distributed in north and central China. Under the future scenarios, the highly suitable habitats were mainly distributed in Beijing, Tianjin, and Hebei. Under SSP2–4.5, the future suitable areas will reach the maximum and expand to 1,411,100 km<sup>2</sup> in the 2060s. The centroid distribution would northwestward extend under future climate scenarios. The human footprint index, mean temperature of the warmest quarter (Bio_10), April wind speed (Wind_4), temperature seasonality (standard deviation × 100) (bio_4), topsoil gravel content (T_gravel), and precipitation of warmest quarter (Bio_18) were key environmental variables affecting distribution and growth of <i>A. palmeri</i>. Climate change would increase the risk of <i>A. palmeri</i> expanding to high latitudes. Our results will help in developing effective strategies for the early warning, prevention, control, and management of <i>A. palmeri</i> in China.https://www.mdpi.com/2073-4395/13/10/2498invasive alien plants<i>Amaranthus palmeri</i>optimize Maxent modeldriving factorsclimate change |
| spellingShingle | Xinyu Jiao Mei Long Jiayi Li Qingyu Yang Zhixiong Liu Reconstructing the Invasive History and Potential Distribution Prediction of <i>Amaranthus palmeri</i> in China Agronomy invasive alien plants <i>Amaranthus palmeri</i> optimize Maxent model driving factors climate change |
| title | Reconstructing the Invasive History and Potential Distribution Prediction of <i>Amaranthus palmeri</i> in China |
| title_full | Reconstructing the Invasive History and Potential Distribution Prediction of <i>Amaranthus palmeri</i> in China |
| title_fullStr | Reconstructing the Invasive History and Potential Distribution Prediction of <i>Amaranthus palmeri</i> in China |
| title_full_unstemmed | Reconstructing the Invasive History and Potential Distribution Prediction of <i>Amaranthus palmeri</i> in China |
| title_short | Reconstructing the Invasive History and Potential Distribution Prediction of <i>Amaranthus palmeri</i> in China |
| title_sort | reconstructing the invasive history and potential distribution prediction of i amaranthus palmeri i in china |
| topic | invasive alien plants <i>Amaranthus palmeri</i> optimize Maxent model driving factors climate change |
| url | https://www.mdpi.com/2073-4395/13/10/2498 |
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