To visualize multivariate patterns revealed by PERMANOVA, canonical analysis of principal coordinates was applied (CAP, Anderson and Willis, 2003). In this study was used a specific case of CAP (canonical correlation) since the objective was to perceive how well the biotic data (zooplankton community) differentiated the samples along a quantitative mercury gradient. Based on this, it was performed a Principal Components Analysis (PCA) with mercury concentrations (sediment, dissolved and SPM) and selected the single variable with the scores for samples along PC1. This information was used to run the CAP and relate the pollution gradient to the biotic matrix. The abiotic data was previously logtransformed while the biotic matrix was square-root transformed for posterior calculation of Bray-Curtis distances (Anderson et al., 2008).