Within the literature, most discussion of sampling protocols for monitoring aquatic parasites is based on the assumptions of simple random sampling. Recent research has shown that in monitoring parasite abundance on fish farms composed of discrete cages, care must be taken to properly account for the clustering which naturally occurs. This paper illustrates the effect of clustering in the context of monitoring ectoparasitic sea lice Lepeophtheirus salmonis and Caligus elongatus in salmon farms. The degree of clustering of sea lice infections in fish within cages is measured using the intraclass correlation coefficient (ICC). A wide range of ICC values from sites in Scotland and Norway were estimated for the chalimus and mobile stages of L. salmonis, and for C. elongatus mobiles. The analyses indicate that significant clustering of lice infections within cages occurs across lice species and stages on both Scottish and Norwegian farms. A Monte-Carlo simulation using two sets of data from Scottish farms with ICC values for adult L. salmonis of 0.35 [0.08-0.73, 95% CI] and for adult C. elongatus of 0.39 [0.16-0.69, 95% CI] were used to illustrate the implications of clustering. The protocols simulated reflect those typically used across a range of countries and production environments in which salmon are currently reared. The findings demonstrate that the "few fish from many cages" approach results in a marked improvement in precision when sampling aquatic one-host parasites in cage-based production systems.