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Both the Cambrian explosion, more than half a billion years ago, and its Ordovician aftermath some 35 Myr later, are often framed as episodes of widespread ecological opportunity, but not all clades originating during this interval showed prolific rises in morphological or functional disparity. In a direct analysis of functional disparity, instead of the more commonly used proxy of morphological disparity, we find that ecological functions of Class Bivalvia arose concordantly with and even lagged behind taxonomic diversification, rather than the early-burst pattern expected for clades originating in supposedly open ecological landscapes. Unlike several other clades originating in the Cambrian explosion, the bivalves' belated acquisition of key anatomical novelties imposed a macroevolutionary lag, and even when those novelties evolved in the Early Ordovician, functional disparity never surpassed taxonomic diversity. Beyond this early period of animal evolution, the founding and subsequent diversification of new major clades and their functions might be expected to follow the pattern of the early bivalves—one where interactions between highly dynamic environmental and biotic landscapes and evolutionary contingencies need not promote prolific functional innovation. 

Team structures---roles, norms, and interaction patterns---define how teams work. HCI researchers have theorized ideal team structures and built systems nudging teams towards them, such as those increasing turn-taking, deliberation, and knowledge distribution. However, organizational behavior research argues against the existence of universally ideal structures. Teams are diverse and excel under different structures: while one team might flourish under hierarchical leadership and a critical culture, another will flounder. In this paper, we present DreamTeam: a system that explores a large space of possible team structures to identify effective structures for each team based on observable feedback. To avoid overwhelming teams with too many changes, DreamTeam introduces multi-armed bandits with temporal constraints: an algorithm that manages the timing of exploration--exploitation trade-offs across multiple bandits simultaneously. A field experiment demonstrated that DreamTeam teams outperformed self-managing teams by 38%, manager-led teams by 46%, and teams with unconstrained bandits by 41%. This research advances computation as a powerful partner in establishing effective teamwork.