Introduction

In the past, prevailing pest management methodologies emphasized the use of simple analytical and mathematical models. Recent advancements in computing technology have provided an opportunity for the ecological insect modeling community to advance beyond these methodologies and create new simulation approaches for use in integrated pest management (IPM) strategies. These new approaches usually emphasize greater complexity and detail in the models and better model evaluation using experimental data. Complex simulation models are often more accurate (realistic) and more applicable to field situations than simpler analytical models. Although commonly assumed in the past that measuring and calibrating the many parameters used in complex simulation models would reduce their practicability and efficacy, it is worth noting that these issues also can be a problem for simpler models. Creating valid, complex numerical models to address specific problems remains a valuable step in the advancement of new theory. An important example of this is the recent development of a suite of insect models to simulate the dynamics of pest adaptation to crop rotation and transgenic corn. Future improvements in computing technology will continue to facilitate the use of complex numerical insect models incorporating extensive ecological and biophysical knowledge. The collective experiences of insect model developers and users show that, even though they are far from perfect, insect models can be very useful in guiding field research, aiding decision making for new IPM policies, and generating credible assessments of various pest impacts (e.g., yield losses, resistance to pesticides) on farming systems. In this article, the role of models in ecological- and insecticide-based pest control strategies are first discussed, followed by a description of the major types of insect/pest models available. Current insect modeling approaches (e.g., pest-crop interactions, pesticide effectiveness, pest adaptation to crop rotation and transgenic corn) are then presented, followed by future research needs for insect models.

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