Predicting Insect Adaptation to a Resistant Crop

Abstract

Microevolutionary predictions of pest population change may help to quantify the risk of control loss as a result of pest evolution. By using quantitative genetic estimates of genetic variation and selection intensity, I constructed 2 models for predicting the adaptation of the dipteran leafminer Liriomyza trifolii (Burgess) to a resistant cultivar of chrysanthemum, Dendranthema grandiflora (Tzvel.). In the 1st model the genetic variance was held constant as the generations were iterated forward and in the 2nd model the genetic variance was reduced to reflect the effects of linkage disequilibrium. These predictions were evaluated with a replicated selection experiment performed on the same leafminer populations from which the prediction parameters were estimated. Predictions and selection experiments for a 10-generation period are presented for 3 types of leafminer populations that differed in their history of host plant use. Overall, the predicted evolutionary trajectories of the leafminer populations on the resistant host plant were very similar to the trajectories observed in the selection experiment. Two of the population types had very good agreement between the predicted and the observed trajectories, differing by ±2 generations. Evolutionary prediction of the 3rd population was systematically too rapid, due in part to an overestimate of its genetic variance. Prediction was improved after correcting the genetic variance in the prediction model with an estimate of realized heritability calculated after the 5th generation of the selection experiment. Predictions that accounted for reduced genetic variance as a result of selection (Bulmer effect predictions) were closer to the observed trajectories in all cases. This study demonstrates the potential of quantitative genetic methods for predicting the evolution of pest insects in the face of selection by resistant crops and other control measures. This success under laboratory conditions should encourage the further evaluation and development of these methods under heterogeneous field conditions.