美国大陆外来入侵物种斑马纹贻贝(Dreissena polymorpha)潜在生境预测模型

防止外来生物入侵造成危害的重要手段是阻止可能造成入侵的物种进入适合其生存的地区.论文以1864个美国外来入侵物种斑马纹贻贝定点发生数据和开放式基础地理信息数据库Daymet的34个环境变量为主要信息源,采用逻辑斯蒂回归(LR)、分类与回归树模型(CART)、基于规则的遗传算法(GARP)、最大熵法(Maxent)4种途径,建立美国大陆部分潜在生境预测模型,从接受者运行特征曲线下面积(AUC)、Pearson相关系数、Kappa值3个方面来检验模型预测精度,在此基础上分析斑马纹贻贝的空间分布规律及其环境影响因素.研究结果表明:在3个评价指标中,4个生态位模型预测精度均达到优良水平,其中Maxent在物种现实生境模拟、主要生态环境因子筛选、环境因子对物种生境影响的定量描述方面都表现出了优越的性能;距水源距离、海拔高度、降水频率、太阳辐射是影响物种空间分布的主要环境因子.论文提出的研究方法对中国外来入侵物种生境预测具有较强的借鉴意义,研究结果对中国海洋外来入侵物种沙筛贝的预测与防治,具有一定的指导作用.

Modeling potential habitat for alien species of Dreissena polymorpha in the continental USA

The effective measure to minimize the damage from invasive species is to block the potential invasive species entering into suitable areas. Occurrence records from 1864 locations and 34 environmental variables from Daymet datasets were gathered, four modeling methods including Logistic Regression(LR), Classification and Regression Trees (CART), Genetic Algorithm for Rule-Set Prediction (GARP) and maximum entropy method (Maxent) were used to generate potential geographic distributions for Dreissena polymorpha in the continental USA. Then three statistical criteria including area under the Receiver Operating Characteristic curve (AUC), correlation (COR) and Kappa were calculated to evaluate the performance of the models, followed by analyses of major variable contributions. Results showed that in terms of three statistical criteria, the predictions from four modeling methods were either excellent or outstanding, in which Maxent outperformed others in three aspects of predicting potential habitat distribution, selection of major contributing factors, quantifying the influence of environmental variables on habitat. Distance to water, elevation, frequency of precipitation and solar radiation were the four forcing environmental factors. The methods suggested in the paper could be used for modeling habitat of Chinese alien species and provide a direction to prevention of Mytilopsis sallei on Chinese coast line.