Evolutionary analysis of herbivorous insects in natural and agricultural environments

Abstract

Herbivorous insects offer a remarkable example of the biological diversity that formed the foundation for Darwin's theory of evolution by natural selection. The ability of insects to evolve resistance rapidly to insecticides and host-plant resistance present a continual challenge for pest management. This paper considers the manner in which genetic constraints, host-plant availability and trade-offs affect the evolution of herbivorous insects in natural and agricultural environments, and the extent to which lessons learned from studying natural systems may be applied to improve insect resistance management in agricultural systems. Studies on the genetic architecture of adaptation by herbivores to host plants and to insecticides are reviewed. The genetic basis of resistance is an important component of simulation models that predict the evolution of resistance. These models often assume monogenic resistance, but available data suggest that this assumption may be overly narrow and that modeling of resistance as oligogenic or polygenic may be more appropriate. As omics (e.g. genomics and proteomics) technologies become more accessible, a better understanding of the genetic basis of resistance will be possible. Trade-offs often accompany adaptations by herbivores. Trade-offs arise when the benefit of a trait, such as the ability to feed on a novel host plant or to survive in the presence of an insecticide, is counterbalanced by fitness costs that decrease fitness in the absence of the selective agent. For resistance to insecticides, and resistance to insecticidal transgenic crops in particular, fitness costs may act as an evolutionary constraint and delay or prevent the evolution of resistance. An important observation is that certain ecological factors such as host plants and entomopathogens can magnify fitness costs, which is termed ecological negative cross-resistance. The application of omics technologies may allow for more efficient identification of factors that will impose ecological negative cross-resistance, thereby bolstering insect resistance management.