目的 构建中华按蚊潜在分布和生物气候因子关系模型,研究影响中华按蚊潜在分布的主导气候因子,预测中华按蚊在中国的潜在分布,为在中国消除疟疾提供媒介分布的数据支持。方法 根据2005－2010年媒介按蚊监测数据,应用最大熵模型(MaxEnt),采用“10%训练存在逻辑阈值”定义最小适生环境阈值,划分中华按蚊的适生区和非适生区。利用地理信息系统(GIS)估算暴露于中华按蚊分布区内的人群数量。结果 采用受试者工作特征曲线(ROC曲线)分析方法来检验模型精度,得到的AUC值2005－2010年分别为0.814、0.791、0.783、0.801、0.774和0.802,显示预测精度较好。模型结果表明,年总降雨量、年平均气压、最湿季降雨量、最冷月最低气温对中华按蚊的分布有着重要影响。结论 2005－2010年,中华按蚊在中国的潜在分布和暴露人口均呈缩减趋势。掌握并了解中华按蚊在中国的潜在分布,对于中国消除疟疾和预防相关传染病具有重要意义。
Objective To build a model for the relationship between the potential distribution of Anopheles sinensis and relevant bio-climatic factors, and to identify the main climatic influencing factors as well as predict the potential distribution of An. sinensis in China, thereby providing supporting data of vector distribution for the nationwide elimination of malaria. Methods A MaxEnt model was built to predict the potential distribution of An. sinensis using monitoring data from 2005 to 2010. The potential distribution areas of An. sinensis were divided into suitable and unsuitable areas, where “10 percentile training presence logistic threshold” was used to define the minimum threshold of suitable environment. The size of human population exposed to the distribution area of An. sinensis was evaluated using geographic information system. Results In the MaxEnt model, a receiver operating characteristic (ROC) curve was used to test the precision. The values of area under the ROC curve for 2005 to 2010 were estimated to be 0.814, 0.791, 0.783, 0.801, 0.774, and 0.802, respectively, indicative of good prediction precision. The modeling data showed that total annual precipitation, mean annual air pressure, precipitation of the wettest quarter, and minimum temperature of the coldest month strongly influenced the distribution of An. sinensis. Conclusion In China, the suitable area of An. sinensis and the exposed human population both showed a decreasing trend from 2005 to 2010. It is of great significance to the nationwide elimination of malaria and the prevention of related infectious diseases by grasping and understanding the potential distribution of An. sinensis in China.
[1] 丁俊. 疟疾流行现状研究进展[J]. 中国公共卫生,2012,28(5):717-718.
[2] 朱继民,汤林华. 疟疾及其蚊媒的预测方法研究进展[J]. 中国寄生虫学与寄生虫病杂志,2007,25(2):153.
[3] 车河龙,林栋. 疟疾的防控现状及进展[J]. 热带医学杂志,2010,10(2):218-220.
[4] 世界卫生组织. 2013年世界疟疾报告[EB/OL]. [2012-12-11]. http://www.who.int/zh/.
[5] 刘起勇,刘小波. 媒介按蚊防控:中国疟疾消除的关键措施[J]. 中国媒介生物学及控制杂志,2010,21(5):409-413.
[6] Chow CY. Malaria vectors in China[J]. Chin J Entomol,1991,6(6):67-79.
[7] 潘波. 我国主要传疟媒介的形态特征、生态习性及传疟作用[J]. 热带医学杂志,2003,3(4):447-451.
[8] Ward D. Modelling the potential geographic distribution of invasive ant species in New Zealand[J]. Biol Invasions,2007,9(6):723-735.
[9] Elith J, Catherine HG, Robert PA, et al. Novel methods improve prediction of species’ distributions from occurrence data[J]. Ecography,2006,29(2):129-151.
[10] 徐卫华,欧阳志云,蒋泽银. 大相岭山系大熊猫生境评价与保护对策研究[J]. 生物多样性,2006,14(3):223-231.
[11] 朱耿平,刘国卿,卜文俊,等. 生态位模型的基本原理及其在生物多样性保护中的应用[J]. 生物多样性,2013,21(1):90-98.
[12] Peterson AT. Uses and requirements of ecological niche models and related distributional models[J]. Biodiversity Informatics,2006,3:59-72.
[13] Phillips SJ, Anderson RP, Schapire RE. Maximum entropy modeling of species geographic distributions[J]. Ecol Model,2006,190(3/4):231-259.
[14] Phillips SJ, Dudík M. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation[J]. Ecography,2008,31(2):161-175.
[15] Oliveira SVd,Escobar LE, Peterson AT, et al. Potential geographic distribution of Hantavirus Reservoirs in Brazil[J]. PLoS One, 2013,8(12):e85137.
[16] Tarjuelo R, Morales MB, Traba J, et al. Are species coexistence areas a good option for conservation management？ applications from fine scale modelling in two steppe birds[J]. PLoS One,2014,9(1):e87847.
[17] Yang XQ, Kushwaha SPS, Saran S, et al. Maxent modeling for predicting the potential distribution of medicinal plant, Justicia adhatoda L. in Lesser Himalayan foothills[J]. Ecol Eng,2013,51: 83-87.
[18] 王碧. 中国两栖动物锥虫、肝簇虫空间分布风险的MaxEnt模型预测[D]. 哈尔滨:东北林业大学,2012.
[19] Saatchi S, Buermann W, Hans TS, et al. Modeling distribution of Amazonian tree species and diversity using remote sensing measurements[J]. Remote Sens Environ,2008,112(5):2000-2017.
[20] Zhang A, Qi QW, Jiang LL, et al. Population exposure to PM2.5 in the urban area of Beijing[J]. PLoS One,2013,8(5):e63486.
[21] 蒋捷,杨昕. 基于DEM中国地势三大阶梯定量划分[J]. 地理信息世界,2009,1(1):9-13.
[22] 丁德峻,张旭晖,赵勇进. 温度对我国中华按蚊世代分布及其传疟有效季节的影响[J]. 生态学杂志,1991,2(4):52-57.
[23] 刘小波,刘起勇. 自然与社会因素对传疟媒介按蚊生态习性的影响[J]. 中国媒介生物学及控制杂志,2012,23(1):1-6.
[24] Brotons L, Thuiller W, Araújo MB, et al. Presence?absence versus presence?only modelling methods for predicting bird habitat suitability[J]. Ecography,2004,27(4):437-448.
[25] McPherson JM, Jetz W, Rogers DJ. The effects of species’ range sizes on the accuracy of distribution models: ecological phenomenon or statistical artefact？[J]. J Appl Ecol,2004,41(5):811-823.
[26] Walther GR, Post E, Convey P, et al. Ecological responses to recent climate change[J]. Nature,2002,416(6879):389-395.
[27] 封志明,唐焰,杨艳昭,等. 中国地形起伏度及其与人口分布的相关性[J]. 地理学报,2007,62(10):1073-1082.
[28] 秦正积,罗超,孟言浦,等. 气温、湿度、降雨量对蚊密度的影响统计分析[J]. 中国媒介生物学及控制杂志,2003,14(6):421-422.
[29] 中华人民共和国环保部. 2005年中国环境状况公报[EB/OL].
[2006-06-02]. http://www.mep.gov.cn/.
[30] 中华人民共和国环保部. 2006年中国环境状况公报[EB/OL].
[2007-06-05]. http://www.mep.gov.cn/.
[31] 中华人民共和国环保部. 2007年中国环境状况公报[EB/OL].
[2008-06-05]. http://www.mep.gov.cn/.
[32] 中华人民共和国环保部. 2008年中国环境状况公报[EB/OL].
[2009-06-09]. http://www.mep.gov.cn/.
[33] 中华人民共和国环保部. 2009年中国环境状况公报[EB/OL].
[2010-06-03]. http://www.mep.gov.cn/.
[34] 中华人民共和国环保部. 2010年中国环境状况公报[EB/OL].
[2011-05-29]. http://www.mep.gov.cn/.
[35] Marco V, Reuben G, Charles FG, et al. The global fight against HIV/AIDS, tuberculosis, and malaria:current status and future perspectives[J]. Am J Clin Pathol,2009,131(6):844-848.
[36] 钱会霖,汤林华. 中国50年疟疾防治工作的成就与展望[J]. 中华流行病学杂志,2000,21(3):225-258.
[37] 高琪. 我国消除疟疾面临的机遇与挑战[J]. 中国血吸虫病防治杂志,2011,23(4):347-349.
