Phase-locking and environmental fluctuations generate synchrony in a predator–prey community

All together now Understanding what causes populations to fluctuate in synchrony is important, since synchronicity can have marked effects on extinction risk, food web stability and other factors influencing an ecosystem. Adjacent populations involved in similar predator–prey cycles often oscillate in synchrony, and David Vasseur and Jeremy Fox used theory and laboratory microcosms to show that, when predators are present, dispersal between prey populations is responsible for this phase-locking. Dispersal is the ability of individual organisms — Vasseur and Fox worked with snowshoe hares and Canadian lynx — to move from one isolated population to another. The model resulting from this work is robust to wide variations in parameters representing predator–prey and host–pathogen systems, suggesting that it may have general applicability. Adjacent populations that are involved in similar predator–prey cycles often oscillate in synchrony. Here, a general stochastic model of predator–prey spatial dynamics is developed to predict the outcome of a laboratory microcosm experiment testing for interactions among synchronizing factors; both model and data indicate that synchrony depends on cyclic dynamics generated by the predator. Spatially synchronized fluctuations in system state are common in physical and biological systems ranging from individual atoms 1 to species as diverse as viruses, insects and mammals 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 . Although the causal factors are well known for many synchronized phenomena, several processes concurrently have an impact on spatial synchrony of species, making their separate effects and interactions difficult to quantify. Here we develop a general stochastic model of predator–prey spatial dynamics to predict the outcome of a laboratory microcosm experiment testing for interactions among all known synchronizing factors: (1) dispersal of individuals between populations; (2) spatially synchronous fluctuations in exogenous environmental factors (the Moran effect); and (3) interactions with other species (for example, predators) that are themselves spatially synchronized. The Moran effect synchronized populations of the ciliate protist Tetrahymena pyriformis ; however, dispersal only synchronized prey populations in the presence of the predator Euplotes patella . Both model and data indicate that synchrony depends on cyclic dynamics generated by the predator. Dispersal, but not the Moran effect, ‘phase-locks’ cycles, which ot