Chines Journal of Vector Biology and Control ›› 2016, Vol. 27 ›› Issue (6): 617-619.DOI: 10.11853/j.issn.1003.8280.2016.06.025

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Analysis of the rodent density monitoring in Changsha city from 2006 to 2015

PENG Lai, HE Jun, XIAO Shan, LONG Jian-xun   

  1. Changsha Center for Disease Control and Prevention, Changsha 410000, Hunan Province, China
  • Received:2016-08-24 Online:2016-12-20 Published:2016-12-20


彭莱, 何俊, 肖珊, 龙建勋   

  1. 长沙市疾病预防控制中心消毒与病媒生物防治科, 长沙 410000
  • 作者简介:彭莱,女,中级检验师,主要从事病媒生物防制工作,


Objective To investigate the community composition of the rodents and their densities in different seasons and habitats in Changsha city, China, and to provide a scientific basis for rodent control measures. Methods Once in every month of each year, the night trapping method was used to monitor the rodent densities at randomly selected sites, one in special industry, one in natural village, and one in residential community. The statistical analysis was applied to gathered data, which was used to predict rodent density from 2016 to 2017 by autoregressive integrated moving average model. Results A total of 676 rodents were captured from 2006 to 2015, with a mean density of 1.06%. Of all the rodents, the predominant species was Rattus norvegicus, amounting 50.15% (339/676). The density of the rodent was the highest in the special industry followed by the natural village and residential community. The monthly seasonal fluctuations of the rodent mean density during a 10-year period showed the first peak in March and the second peak in June. The density was found decreasing with time during the study period. Conclusion Community composition and seasonal density fluctuation of the rodents in Changsha city were acquired. It is suggested to take integrated rodent control measures and enhance long-term monitoring, according to the habits and characteristics of the rodents and their seasonal density fluctuations.

Key words: Rodent density, Monitoring, Autoregressive integrated moving average model


目的 掌握长沙市鼠类分布情况,为制定科学合理的鼠类防制方案提供依据。方法 2006-2015年随机选取长沙市居民区、特殊行业和农村3种类型的监测点各1个,采用夹夜法,全年每月监测1次,并对数据进行统计学分析。利用差分自回归移动平均模型预测2016-2017年鼠密度。结果 共捕获鼠类676只,平均密度为1.06%,褐家鼠为优势鼠种,占捕获总数的50.15%(339/676);不同生境鼠密度依次为特殊行业 > 农村 > 居民区;10年的月平均鼠密度高峰在3月,次高峰在6月;鼠密度随时间推移呈降低趋势。结论 基本掌握了长沙市鼠类种群构成及季节消长情况,应根据不同生境及季节消长规律,合理制定鼠类防制方案,并坚持长期监测。

关键词: 鼠密度, 监测, 差分自回归移动平均模型

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