Pool leaf or subtree summaries with Chan's parallel variance merge.

Forest members are correlated views of the same observations. By default their combined weight is divided by the number of contributors, retaining uncertainty as the ensemble grows. Pass independent for disjoint evidence whose weights add. Empty or non-positive-weight summaries contribute no moments but still count as ensemble members. An empty iterable returns an empty summary.