Lande's equation for predicting the response of trait means to a shift in optimal trait values is
tested using a stochastic simulation model. The simulated population is finite, and each individual
has a finite number of loci. Therefore, selection may cause allele frequencies and distributions to
change over time. Since the equation assumes constant genetic parameters, the degree to which
such allelic changes affect predictions can be examined. Predictions are based only on information
available at generation zero of directional selection. The quality of the predictions depends on the
nature of allelic distributions in the original population. If allelic effects are approximately
normally distributed, as assumed in Lande's Gaussian approximation to the continuum-of-alleles
model, the predictions are very accurate, despite small changes in the G matrix. If allelic effects
have a leptokurtic distribution, as is likely in Turelli's ‘house-of-cards’ approximation, the
equation underestimates the rate of response and correlated response, and overestimates the time
required for the trait means to reach their equilibrium values. Models with biallelic loci have limits
as to the amount of trait divergence possible, since only two allelic values are available at each of
a finite set of loci. If the new optimal trait values lie within these limits, predictions are good. if
not, singularity in the G matrix results in suboptimal equilibria, despite the presence of genetic
variance for each individual trait.