中国媒介生物学及控制杂志 ›› 2017, Vol. 28 ›› Issue (5): 496-498.DOI: 10.11853/j.issn.1003.8280.2017.05.024

• 调查研究 • 上一篇    下一篇

长沙市2006-2015年蝇类密度监测结果分析

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
  • 收稿日期:2017-06-29 出版日期:2017-10-20 发布日期:2017-10-20
  • 作者简介:彭莱,女,中级检验师,主要从事病媒生物防治工作,Email:457668914@qq.com

Analysis on the fly 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:2017-06-29 Online:2017-10-20 Published:2017-10-20

摘要: 目的 掌握长沙市蝇类种群构成及季节消长情况,为蝇类防治提供科学依据。方法 2006-2015年在辖区内随机选择农贸市场、餐饮店外环境、绿化带和居民区4种生境进行监测。采用笼诱法,每年的4-12月每月监测1次,并对数据进行统计学分析。结果 共捕获蝇类6969只,平均密度为5.16只/笼,家蝇为优势蝇种,占捕获总数的26.24%(1829/6969);不同生境蝇密度依次为绿化带>居民区>农贸市场>餐饮店外环境;10年间月平均蝇密度高峰期在6月。结论 基本掌握了长沙市蝇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,合理制定蝇类防制方案,并坚持长期监测。

关键词: 蝇密度, 监测, 种群构成, 季节消长

Abstract: Objective To investigate the community composition of the flies and their densities in different seasons and habitats in Changsha city, China, and to provide a scientific basis for fly control. Methods From April to December of each year, the cage traps were set up in the following habitats:farm produce markets, restaurants, greenbelts and residential areas. Then the statistical analysis was carried out on different kinds of data. Results A total of 6 969 flies were captured from 2006 to 2015, with a mean density of 5.16 flies/cage. Of all the flies, the predominant species was Musca domestica, reaching 26.24%(1 829/6 969). The fly density was the highest in the greenbelts, followed by in residential areas, farm product markets and in restaurants. The seasonal peak of the fly mean density was in June based on 10-year data. Conclusion Community composition and seasonal density fluctuation of the fly in Changsha city were acquired. It is suggested to take integrated fly control measures and enhance long-term monitoring, according to the habits and characteristics of the fly and their seasonality.

Key words: Fly density, Monitoring, Species composition, Seasonal fluctuation

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