Reconstructing the Invasive History and Potential Distribution Prediction of Amaranthus palmeri in China

栖息地 北京 中国 入侵物种 分布(数学) 气候变化 地理 杂草 生态学 环境科学 生物 数学分析 数学 考古
作者
Xinyu Jiao,Mei Long,Jiayi Li,Qingyu Yang,Zhixiong Liu
出处
期刊:Agronomy [MDPI AG]
卷期号:13 (10): 2498-2498 被引量:5
标识
DOI:10.3390/agronomy13102498
摘要

Palmer Amaranth (Amaranthus palmeri, Amaranthaceae) is one of the most competitive, troublesome, and noxious weeds causing significant yield reductions in various crops. A. palmeri was also a herbicide-resistant weed causing a serious eco-environmental problem. Given that the process of invasion is dynamic, the A. plamer invasion may already be quite severe where invasive species management and surveys are chronically lacking. Predicting the potential habitat of A. palmeri can help to develop effective measures for early warning and long-term detection. However, the invasive history and distribution patterns of A. palmeri in China remain largely unknown. Here, the invasive history and distribution patterns of A. palmeri from 1985 to 2022 in China were reconstructed, and then the potential geographical distribution of A. palmeri 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 A. palmeri were 0.967. Under the current climate conditions, the suitable habitat areas for A. palmeri reached 1,067,000 km2 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 km2 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 A. palmeri. Climate change would increase the risk of A. palmeri expanding to high latitudes. Our results will help in developing effective strategies for the early warning, prevention, control, and management of A. palmeri in China.
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