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Using automated monitoring systems to uncover pest population dynamics in agricultural fields

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Author Info

  • Okuyama, Toshinori
  • Yang, En-Cheng
  • Chen, Chia-Pang
  • Lin, Tzu-Shiang
  • Chuang, Cheng-Long
  • Jiang, Joe-Air
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    Abstract

    Understanding pest population dynamics is an essential part of pest management programs, but the examination of field pest populations faces many logistical difficulties. Consequently, potentially useful characteristics of pest ecology that can be utilized in the development of pest control strategies are yet to be discovered. In this study, we used an automated pest monitoring system to study a population of the oriental fruit fly and revealed its intriguing population dynamics in the field. The system automatically counts the number of flies captured by traps, and the real-time data are accessible anywhere using the Internet. Data from two time periods (May–June and July–August) were analyzed. Autocorrelation analysis indicated that there was a statistically significant population cycle in May and June, but the population was stationary in July and August. Partial rate correlation analysis and an associated functional analysis revealed the existence of delayed density-dependence that differed between the two periods. These results suggest that the mechanism of population dynamics may change possibly within a short time frame. These patterns were revealed because of the detailed data that were made available by the monitoring system and were unknown prior to the study. The automated monitoring system will be highly valuable for the advancement of pest monitoring and pest management programs.

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    Bibliographic Info

    Article provided by Elsevier in its journal Agricultural Systems.

    Volume (Year): 104 (2011)
    Issue (Month): 9 ()
    Pages: 666-670

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    Handle: RePEc:eee:agisys:v:104:y:2011:i:9:p:666-670

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    Web page: http://www.elsevier.com/locate/agsy

    Related research

    Keywords: Agricultural pests; Oriental fruit fly; Bactrocera dorsalis; Population monitoring; Delayed density-dependence;

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