In designing field studies the experimenter must decide how many replicates to run at which concentrations. There is much current debate over the relative merits of different designs including “regression” and “ANOVA” designs. Optimal design techniques provide a framework for addressing choices in the design of field studies, largely because the first step in determining the optimal design is deciding the exact goal for the experiment. If one can specify the goals in a quantified form and specify a model governing the responses, optimal design techniques can be applied to find the best design or set of designs for addressing the question from the available resources. Uncertainty in specifying the model governing the responses can be quantified with a prior distribution of possible models. Numerical optimization techniques can then be used to optimize the objective under the assumed model. Optimal design techniques can be applied to assigning available units to given concentration levels or to the more difficult question of determining which concentration levels optimize the goals of the experiment.