NMDS or PCA are usually employed for visualization of a (complex) beta diversity matrix. However, PCA try to maximize variation in several "ORTHOGONAL" axes (they should be independent between them).

When a factor has several groups, PCO (e.g. samples from 17 different environments) is not able to separate into the same number of clusters (even when statistics have a strong effect and high correlation).

Is there a way to visualize those complex data? Residuals? Discriminant Analyses?

Thanks

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