| With the acceleration of globalization,biological invasion shows a more complicated risk trend.Climate change may promote the new expansion of invasive alien species.Amaranthus palmeri S.Watson is a malignant invasive weed,which seriously threatens agricultural production and biodiversity.Assessing the potential geographical distribution of A.palmeri is essential for food security and ecological security.At present,the research on the potential distribution of A.palmeri only focus on the current climate conditions,lacking future prediction.Therefore,this study takes A.palmeri as the research object to explore its potential suitable areas and distribution change patterns in China under current and future climate conditions.Firstly,the performance of BIOCLIM,DOMAIN,GARP,and MaxEnt models in simulating the potential distribution of A.palmeri was compared to determine the best model.Secondly,based on the best model,the potential suitable areas of A.palmeri in China under the current climate conditions were evaluated,and the dominant variables affecting its distribution were clarified.Finally,the potential suitable areas and distribution change pattern of A.palmeri in China under future climate scenarios were further predicted.The main findings are as follows:(1)The mean values of AUC,Kappa,and TSS of the four models showed MaxEnt>DOMAIN>BIOCLIM>GARP.The simulation results of the MaxEnt model can better fit the known distribution points of A.palmeri in China than the other three models.Comprehensive evaluation,the MaxEnt model was determined as the best model.(2)Based on the MaxEnt model,the distribution range of the current potential suitable areas of A.palmeri in China evaluated by the two datasets(World Clim1.4 and World Clim2)has certain similarity.The current potential suitable areas of A.palmeri distributed in the central and eastern regions and parts of southwest China,and the high suitable areas distributed in the North China Plain.The potential suitable area of A.palmeri predicted by two datasets accounts for 31.25 % and 31.40 % of China’s total land area,respectively.(3)The dominant environmental variables affecting the potential distribution of A.palmeri include the annual mean temperature,the mean diurnal range,the temperature seasonality,and the precipitation of coldest quarter.Based on the World Clim1.4 and World Clim2.1,the four key variables’ contribution both reached 80 %.And the contribution of the annual mean temperature accounts for more than 40 %,playing a leading role.The temperature-related variables have a greater impact on the distribution of A.palmeri than the precipitation-related variables.The combined effects of the dominant variables limit the potential distribution of A.palmeri.(4)In order to adapt to climate change,the potential suitable areas of A.palmeri showed a trend of northward expansion and migration.With the intensification of climate warming under different climate scenarios,the trend of northward expansion and migration will be more obvious.Under the Representative Concentration Pathways(RCPs),the percentage of the potential suitable area to the China’s total land area increased to 38.91 %,and the centroid of the potential suitable area migrated from Hubei Province to the southeast boundary of Shaanxi Province.Under the Shared Socio-Economic Pathways(SSPs),the potential suitable area maximum increased to 44.93 %,and the centroid of the potential suitable area migrated from Hubei Province to Henan Province.This study investigated the potential distribution of A.palmeri in China under current and future climate conditions based on species distribution models.By quantifying the suitability of A.palmeri in different regions,the risk degree of A.palmeri in China’s different regions was clarified.The results have guiding significance for different regions to formulate management strategies on the early monitoring and warning and the longterm prevention and control of A.palmeri,and help to promote the transformation of biological invasion prevention and control from passive response to active action. |