This article presents a scientific overview of biological control models. The first section introduces the broad types of general population models before specific biological control models are explored. The penultimate section of the article considers the applied uses to which biological control models have been put and assesses broad future directions for research in this field.
Biological control uses predatory, parasitic, or pathogenic agents to reduce the population of a target (usually a weed or herbivorous animal). A discrete branch of biological control targets plant diseases using antagonistic microorganisms that inhibit the disease process. The general aim of biological control is to reduce the target's population density either indefinitely or, in the case of augmentative, inoculative, and inundative approaches (see below), for a defined period. Ideally, the new population density of the target should be such that the mortality caused by the agents maintains it below the economic injury level (EIL), that is, there is no need to use pesticidal applications or other methods to avoid economic loss in agriculture or environmental impact in the case ofpests of conservation areas.
In practice, however, many biological control programs fail to give consistently high levels of target population suppression. In terms of population dynamics, the target's new equilibrium density is either too high or unstable. In cases where only partial control of the target is achieved, however, the contribution of biological control may still be valuable. Modern pest management tends to be integrated in nature such that a range of pest control methods are often brought to bear on a given pest species; none individually is completely effective but together a sufficient level of control is achieved. Despite this pragmatism, there are well-known cases of unilateral use of biological control of weed and insect targets where the level of success has been so high that practitioners naturally aim to emulate this in subsequent attempts. Though this quest has sometimes been ad hoc in nature, researchers have turned to ecological theory and modeling to enhance success rates through better understanding of the mechanisms of biological control and to provide predictive ability.
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