Summary results of a distance-based permutational multiple regression analysis for the association of the prevalence of two coral diseases (<i>Acropora</i> and <i>Porites</i> growth anomalies) with 9 predictor variables across surveys (304 and 602, respectively) throughout the Indo-Pacific Ocean.

The optimal predictors of each disease and the proportion of variability (%) in the data set they explained are shown. Predictor variable codes and units are as per Table 2. Model development was based on step-wise selection and a Bayesian Information Criterion (BIC), with the total variation (r2) explained by each best-fit model shown (% total). Analyses based on 9999 permutations of the residuals under a reduced model.