外来物种入侵已经对世界各国的经济、公共健康、农业生产力和生态完整性造成了越来越大的威胁,描述和预测外来入侵物种的空间分布对物种入侵的防治和早期预警起着重要的作用.生物多样性数据的不对称性以及生物建模过程中模型选择的不确定性给入侵物种空间建模带来了困难和局限.本研究利用统计学和信息理论的方法,从地学空间制图和生物建模的角度研究了外来入侵物种(以豚草Ambrosia Artemisiifolia L.为例)的潜在分布以及环境影响因子,提出了一种改进的logistic回归模型.logistic回归模型的选择基于Akaike信息标准(AIC),针对物种数据的不对称性,本研究提出了一种新的频率统计的方法去划分物种源生地的适应性生存环境.最后,我们把在源生地建立的模型和分类标准投影到入侵地绘制了该物种在入侵地的相对适应性分布图. Invasive alien species have posed increasing threats to the economic, public health, agricultural productivity and ecological integrity of countries in the world. Describing and predicting the spatial distribution of alien invasive species plays an important role in the prevention and early warning of species invasions The asymmetry of biodiversity data and the uncertainty of model selection in the process of biological modeling bring difficulties and limitations to the modeling of invasive species.In this study, using the methods of statistics and information theory, Aiming at the potential distribution of alien invasive species (exemplified by Ambrosia Artemisiifolia L.) and its environmental impact factors, an improved logistic regression model was proposed.The selection of logistic regression model was based on the Akaike Information Criterion (AIC ), Aiming at the asymmetry of species data, a new frequency statistics method is proposed to divide the adaptive living environment of species origin.Finally, we project the models and taxonomic criteria established at the source to the invaded The relative fitness map of the species invaded was drawn.