UNCERTAINTY ANALYSIS APPLIED TO SUPERVISED CONTROL OF APHIDS AND BROWN RUST IN WINTER-WHEAT .2. RELATIVE IMPORTANCE OF DIFFERENT COMPONENTSOF UNCERTAINTY

The components of an existing model for supervised control of aphids ( especially Sitobion avenae) and brown rust (Puccinia recondita) in win ter wheat contain uncertainty. Their contribution to uncertainty about model output is assessed. The model simulates financial loss associat ed with a time sequence of decisions on chemical control as a function of crop development, population growth, and damage. Four sources of u ncertainty were quantified: model parameters, incidence sample estimat es, future average daily temperature, and white noise. Uncertainty abo ut the first two sources is controllable because it decreases when mor e information is collected. Uncertainty about the last two sources is uncontrollable, given the structure of the model. Uncertainty about mo del output, characterized by its variance, is calculated by repeatedly drawing realizations of the various sources of uncertainty, and calcu lating financial loss after each draw. By processing new realizations of these sources one by one, the contribution of each component to tot al variance can be assessed using an adapted Monte Carlo procedure. Fo r most relevant initial conditions and decision strategies the sources of uncontrollable uncertainty cause more than half of the uncertainty about model output. White noise in the relative growth rates of aphid s and brown rust is the most important source of uncertainty. Resource s for improvement of the model are most effectively allocated to studi es of the population dynamics of aphids and brown rust.