The main idea...
While the original variables lose their individuality, the results of dbRDA can reveal whether a matrix of explanatory variables has some significant impact on the (dis)similarities derived from the response data as a whole. If the matrix of response variables from which the (dis)similarity matrix was calculated is available, they may be correlated with the PCoA axes to suggest which response variables contribute the most to the PCoA ordination.
Partial dbRDA is available in some implementations. As in partial RDA, this extension of dbRDA allows the influence of a matrix of conditioning variables to be partialledout (approximately, "removed") prior to analysis. If the analysis task can be addressed in ANOVAlike terms (i.e. the explanatory variable(s) define(s) the group membership of objects and the main concern is difference between groups) then dissimilarity or distance matrices may be directly tested using a nonparametric MANOVA (NPMANOVA). Click here for more information on NPMANOVA. Implementations
References

Constrained analyses > Redundancy Analysis >