Acknowledgements A.B.K. acknowledges support from the NSF (BRC-BIO DBI-2233416). A.M.B. was supported by the H. Mason Keeler Endowed Professorship in Sports Fisheries Management. Outstanding questions 9 When do simple wisdom of crowds mechanisms (such as averaging) lead to better timing decisions, and when do they fail? When do emergent mechanisms (such as collective sensing or collective learning) lead to better timing decisions, and when do they fail? For both simple and emergent mechanisms for collective temporal decisions, how does accuracy scale with group size? Can we create models with testable predictions to guide empirical work? What new collective decision making mechanisms allow for collective intelligence in timing contexts but not spatial ones? How can we distinguish among collective decision making mechanisms that govern

How can we design experiments with a known optimal time to perform an action or identify this time in data from the field? What are the population-level or ecological implications (e.g., Allee effects) of organisms making collective temporal decisions? How is temporal collective intelligence distinct from, and/or complementary to, consensus mechanisms used to simply maintain synchrony? What other differences between time and space make temporal decisions distinct from spatial decisions? 10

Box 1. Model of asymmetric costs of too-early and too-late errors We illustrate through a simple mathematical model how the asymmetry of costs often observed in timing decisions confounds the prediction made by typical wisdom of crowds models (which is based on spatial decision-making). Consider a species of animal foraging in a tidally-flooded estuary. The amount of food that an individual consumes increases linearly with the amount of time spent in the estuary, but the risk of being stranded (and therefore death) increases exponentially the longer they remain. The overall fitness, as a function of time spent in the estuary, is described by f = t exp(t)/b for this illustrative example, with b = 20. The optimal time t* spent foraging in the estuary that maximizes fitness is t* = log(b) ~ 3.00 (Figure B1a, black curve).