利用规则集遗传算法生态位模型预测秃病蚤蒙冀亚种适宜分布
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摘要
目的通过对气候环境因素与秃病蚤蒙冀亚种空间分布的相关性研究,有效预测秃病蚤蒙冀亚种的适宜分布区,为动物间鼠疫防控提供科学依据。方法 2005-2014年鼠疫常规监测鼠体蚤和窝巢蚤调查秃病蚤蒙冀亚种信息,数据来源于中国疾病预防控制系统的子系统鼠疫防治管理信息系统,采用Logistic回归筛选秃病蚤蒙冀亚种的气候环境危险因素,利用规则集遗传算法(GARP)生态位模型预测秃病蚤蒙冀亚种适宜分布区,利用受试者工作特征曲线(ROC曲线)验证模型。结果经过筛选有21个气候环境因素纳入模型,GARP模型ROC曲线下面积(AUC)为0.978,模型预测效果较好,秃病蚤蒙冀亚种适宜分布区位于内蒙古自治区中部、河北省张家口市西北部、陕西省榆林市西部、宁夏回族自治区北部、山西省北部和甘肃省东北部。结论利用GARP生态位模型预测秃病蚤蒙冀亚种适宜分布区,得到较好的预测结果,结果准确可靠。
Objective To study the association of the spatial distribution of Nosopsyllus laeviceps kuzenkovi with climate and environmental factors, to effectively predict the suitable distribution area for N. laeviceps kuzenkovi,and to provide a scientific basis for the prevention and control of animal plague. Methods From 2005 to 2014, the information on N. laeviceps kuzenkovi was collected from the survey of rat flea and nest flea in routine plague surveillance. The information source was the plague prevention and management information system, which was a subsystem of the Chinese Disease Prevention and Control System. Logistic regression was used to explore the climate and environmental factors for N. laeviceps kuzenkovi. The genetic algorithm for rule-set prediction(GARP) ecological niche model was used to predict the suitable distribution area for N. laeviceps kuzenkovi. The receiver operating characteristic(ROC) curve was used to validate the model. Results After screening, 21 climate and environmental factors were enrolled in the model. The area under ROC curve was 0.978, suggesting a strong prediction capability of the CARP model. The suitable distribution area for N. laeviceps kuzenkovi was located in the central part of Inner Mongolia Autonomous Region, northwest of Zhangjiakou in Hebei province, west of Yulin in Shaanxi province, north of Ningxia Hui Autonomous Region, northern of Shanxi province, and northeast of Gansu province. Conclusion The CARP ecological niche model is accurate and reliable in the prediction of the suitable distribution area for N. laeviceps kuzenkovi.
Objective To study the association of the spatial distribution of Nosopsyllus laeviceps kuzenkovi with climate and environmental factors, to effectively predict the suitable distribution area for N. laeviceps kuzenkovi,and to provide a scientific basis for the prevention and control of animal plague. Methods From 2005 to 2014, the information on N. laeviceps kuzenkovi was collected from the survey of rat flea and nest flea in routine plague surveillance. The information source was the plague prevention and management information system, which was a subsystem of the Chinese Disease Prevention and Control System. Logistic regression was used to explore the climate and environmental factors for N. laeviceps kuzenkovi. The genetic algorithm for rule-set prediction(GARP) ecological niche model was used to predict the suitable distribution area for N. laeviceps kuzenkovi. The receiver operating characteristic(ROC) curve was used to validate the model. Results After screening, 21 climate and environmental factors were enrolled in the model. The area under ROC curve was 0.978, suggesting a strong prediction capability of the CARP model. The suitable distribution area for N. laeviceps kuzenkovi was located in the central part of Inner Mongolia Autonomous Region, northwest of Zhangjiakou in Hebei province, west of Yulin in Shaanxi province, north of Ningxia Hui Autonomous Region, northern of Shanxi province, and northeast of Gansu province. Conclusion The CARP ecological niche model is accurate and reliable in the prediction of the suitable distribution area for N. laeviceps kuzenkovi.
引文
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[3]Stockwell D.The GARP modelling system:problems and solutions to automated spatial prediction[J].Int J Geogr Inf Sci,1999,13(2):143-158.DOI:10.1080/136588199241391.
[4]赵文娟.玉米霜霉病在中国的适生性分析[D].合肥:安徽农业大学,2009.
[5]高孟绪,王卷乐,曹春香,等.基于地理信息系统和生态位模型的青海省喜马拉雅旱獭空间分布预测[J].中华地方病学杂志,2015,34(5):318-321.DOI:10.3760/cma.j.issn.2095-4255.2015.05.003.
[6]刘欣.基于GARP和MAXENT的空心莲子草在中国的入侵风险预测[D].济南:山东师范大学,2012.
[7]Williams RAJ,Fasina FO,Peterson AT.Predictable ecology and geography of avian influenza(H5Nl)transmission in Nigeria and West Africa[J].Trans Roy Soc Trop Med Hyg,2008,102(5):471-479.DOI:10.1016/j.trstmh.2008.01.016.
[8]毛志远,张兆金,周坚.基于生态位模型的石蒜适生区预测[J].林业科技开发,2014,28(6):50-53.DOI:10.13360/j.issn.1000-8101.2014.06.012.
[9]吴淇铭.6种重要果实蝇的适生区预测和风险分析[D].福州:福建农林大学,2014.
[10]闫东.基于生态位模型预测长爪沙鼠鼠疫动物间疫情的潜在风险[D].北京:中国疾病预防控制中心,2016.
[11]陈璐,孙希华,林泽民.基于GARP的大薸潜在适生区预测[J].安徽农业科学,2015,43(2):243-245.DOI:10.3969/j.issn.0517-6611.2015.02.086.
[12]吴厚永.中国动物志.昆虫纲.蚤目[M].2版.北京:科学出版社,2007:1868-1874.