In a mediation analysis with multiple mediators, can the indirect effects be added together? I was looking at the following question, which appears to suggest that multiple indirect effects can be added together to calculate a total indirect effect.
Multiple mediation analysis in R
But reading the abstract of this paper leads me to believe that there is a way to calculate the total indirect effects all together, and that calculating them separately and adding them together may be incorrect.
What would be the proper way to calculate a total indirect effect?
In this example, could you add the indirect effects from ACY, ADY, BCY and BDY? Would it be more appropriate to keep A and B separate? Or is there a different way to summarize the indirect effects? 
If I want to know how much of CY is not explained by and indirect effect of A or B, could I subtract ACY and BCY from CY?

It only makes sense to calculate the sum of indirect effects from the same predictor to the same outcome.  OLS regressions decompose variance into explained and unexplained components.  SEMs decompose covariances, too.
Your mediation model decomposes the total effect of (e.g.) A on Y (given B) into a direct effect (AY) and multiple indirect effects (ACY and ADY).  If you add AY+ACY+ADY, that total effect should match an OLS regression slope regressing Y on A (controlling for B), assuming your model is saturated by allowing A to covary with B and C to covary with D.
