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机构地区:[1]中国科学院沈阳应用生态研究所,沈阳110164 [2]中国科学院大学,北京100049
出 处:《干旱区资源与环境》2017年第7期172-176,共5页Journal of Arid Land Resources and Environment
基 金:科技部科技基础性工作专项重点项目(2014FY110600)资助
摘 要:文中利用最大熵生态位模型(MaxEnt)与地理信息系统(Arc GIS),结合豚草地理分布数据及19个环境因子,对入侵植物豚草在我国东北地区潜在分布和适生等级进行预测。结果表明:豚草的潜在分布区大致呈现以辽河平原腹地为中心,其适生等级向外辐射状递减趋势分布。根据豚草适生系数,确定赤峰-阿荣旗-伊春-黑河一线为豚草扩散风险的分界线。ROC曲线中AUC值为0.986,表明预测结果"非常好"。应用刀割法计算各环境变量对最大熵模型建立贡献率,结果表明影响豚草分布的主要环境因子为最暖季度平均温度和最湿季度平均温度。豚草在不同适生等级分布区域的比较分析,表明豚草在低海拔地区比在高海拔地区分布多。本研究为监测与控制外来入侵植物豚草的扩散提供了依据。In this study, Ambrosia artemisiifolia occurrence records, 19 climatic factors were used to predict the potential distribution and suitable levels of Ambrosia artemisiifolia in Northeast China based on the MaxEnt model and geographical information system. The results show that the highly suitable distribution is mainly located in Liaoning province; Liaoning eastern mountain and Liaohe Plain coast are the two highly suitable areas for the po- tential distribution of invasive plants in Northeast China. The overall trend is gradually decreasing outward cen- tered on Liaohe Plain. According to suitable index, Chifeng -Arongqi -Yichun -Heihe line is the spread risk boundary of the Ambrosia artemisiifolia distribution. The AUC of ROC curve separately is 0.986, indicating that the predictive results with the MaxEnt model are " Very Good". The main environmental factors that determine the potential distribution are mean temperature of warmest quarter and mean temperature of wettest quarter by Jackknife test. By comparing the area percentage of Ambrosia artemisiifolia in different suitable areas, it is shown that Ambrosia artemisiifolia distributes in low elevation is more than in high elevation. This predicting provides a powerful basis for supervising and controlling the invasive plant of Ambrosia artemisiifolia.
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