In the last decades diseases have changed coral communities' structure and function in reefs worldwide. Studies conducted to evaluate the effect of diseases on corals frequently use modified adaptations of sampling designs that were developed to study ecological aspects of coral reefs. Here we evaluate how efficient these sampling protocols are by generating virtual data for a coral population parameterized with mean coral density and disease prevalence estimates from the Caribbean scleractinian Orbicella faveolata at the Mexican Caribbean. Six scenarios were tested consisting of three patterns of coral colony distribution (random, randomly clustered and randomly over-dispersed) and two disease transmission modes (random and contagious). The virtual populations were sampled with the commonly used method of belt-transects with variable sample-unit sizes (10 × 1, 10 × 2, 25 × 2, 50 × 2 m). Results showed that the probability of obtaining a mean coral disease prevalence estimate of ±5% of the true prevalence value was low (range: 11-48%) and that two-sample comparisons achieved rather low power, unless very large effect sizes existed. Such results imply low statistical confidence to assess differences or changes in coral disease prevalence. The main problem identified was insufficient sample size because local mean colony size, density and spatial distribution of targeted coral species was not taken into consideration to properly adjust the sampling protocols.
Keywords: Coral; Disease prevalence; Sampling design; Statistical power.