Artificial selection on phenotypically plastic traits

Many phenotypes respond physiologically or developmentally to continuously distributed environmental variables such as temperature and nutritional qua lity. Information about phenotypic plasticity can be used to improve the ef ficiency of artificial selection. Here we show that the quantitative geneti c theory for 'infinite-dimensional' traits such as reaction norms provides a natural framework to accomplish this goal. It is expected to improve sele ction responses by making more efficient use of information about environme ntal effects than do conventional methods. The approach is illustrated by d eriving an index for mass selection of a phenotypically plastic trait. We s uggest that the same approach could be extended directly to more general an d efficient breeding schemes, such as those based on general best linear un biased prediction. Methods for estimating genetic covariance functions are reviewed.