Technical Abstract: Protein marking is a valuable technique in the study of insect movement in agriculture. It can be implemented on a large scale and is relatively inexpensive to use. Unlike other marking techniques, protein marking is a quantitative method. Whether an individual is considered marked or not is dependant on a threshold that is chosen by the experimenter. The traditional method of choosing a threshold for considering a sampled individual 'marked' results in some risk of false positives, where an unmarked individual is misclassified as marked. In dispersal studies where the recapture rate of marked individuals is low, false positives can significantly affect estimates of dispersal rates. Using simulations, we demonstrate the problems produced by false positives. We introduce two possible approaches that can minimize this problem. First, populations can be doubly marked as a means of reducing the incidence of false positives. Second, we introduce new algorithms for choosing a threshold that will decrease the incidence of false positives and allow data to be corrected for anticipated rates of false positives. Together, these methodologies should enhance researcher confidence in the data generated from dispersal studies using protein marking techniques.