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A simple criterion for successful biological control on annual crops
Authors:Satoru Urano  Katsuya Shima  Koichi Hongo  Yoshito Suzuki
Institution:(1) National Agricultural Research Center for Kyushu Okinawa Region, Nishigoshi, Kumamoto 861-1192, Japan;(2) Faculty of Agriculture, Kyushu University, Fukuoka, Japan;(3) Toyama Prefectural Central Agricultural High School, Toyama, Japan;(4) National Agricultural Research Center, Tsukuba, Japan;(5) Present address: Toyamachubu High School, Toyama, Japan;(6) Present address: Arysta Life Science Corporation Biosystems, Tsukuba, Japan
Abstract:Population dynamics of pest insect-natural enemy systems on annual crops is quite different from those seen in classic biological control programes. On an annual crop, for example, the persistence of populations of pest insects is forced to terminate when crops are harvested. Pest control on annual crops aims to suppress the maximum density of the pest below a certain level, and a low level equilibrium is not always the aim. It is important to determine the initial impact just after release of a natural enemy in order to determine the success of a biological control program. Therefore, effectiveness of natural enemies should be evaluated by prediction of such short-term population dynamics. This paper presents a new and simple analytical model for successful biological control on annual crops. A criterion of successful biological control is given as the ratio of the pest and natural enemy populations just when the pest begins to decrease. This ratio is derived from the intrinsic rates of natural increase of both populations and the daily total predation by natural enemies. Using this model, criteria on appropriate number and time of release of natural enemies are obtained. The practical applications of this model are discussed with respect to evaluating the success or failure of natural enemy releases in future biological control programs.
Keywords:Natural enemy  Predator-prey  Population dynamics  Release ratio  Inoculative release  Analytical model
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