Big difference between Bootstrap Values and Approximately Unbiased p-values

I'm clustering objects over many different descriptors.

I chose a hierarchical clustering method (specifically average linking algorithm with euclidean distances) because I wanted to use bootstrap values to give statistical significance to my clusters. I used pvclust (in python, it should be equivalent to r package pvclust). The package calculates both Bootstrap values BP and Approximately Unbiased p-values AU. The results are shown in this dendrogram



I don't know how to interpret the fact that UA are relatively high while BP are extremely low, also they don't correlate. Can you please clarify the difference between these 2 indicators in terms of interpretation?