This brief note considers the problem of estimating temporal synergy and integrated information in dyadic dynamical processes. One of the standard estimators of dynamic synergy is based on the minimal mutual information between sets of elements, however, despite it's increasingly widespread use, the mathematical features of this redundancy function have largely gone unexplored. Here, we show that it has two previously unrecognized limitations: it cannot disambiguate between truly integrated systems and disintegrated systems with first-order autocorrelation. Second, paradoxically, there are some systems that become more synergistic when dis-integrated (as long as first-order autocorrelations are preserved). In these systems, integrated information can decrease while synergy simultaneously increases. We derive conditions under which this occurs and discuss the implications of these findings for past and future work in applied fields such as neuroscience.