Stochasticity influences single species population dynamics, typically elevating extinction risk. On the other hand, stochasticity can also allow for coexistence of multiple species on a limiting resource. However, many forms of stochasticity exist, and there is currently no consensus on how each form of stochasticity may influence the outcome of competition. In many cases, stochasticity can cause competitive indeterminacy, in which the outcome of competition varies even in replicate communities. Here, we examine the role of stochasticity on competitive indeterminacy and extinction risk by extending a set of eight stochastic Ricker models incorporating combinations of four distinct forms of stochasticity; environmental stochasticity, demographic stochasticity, demographic heterogeneity, and stochastic sex determination.
Using replicated and controlled populations of two Tribolium species, we competed the set of stochastic models, finding that demographic stochasticity, environmental stochasticity, and stochastic sex determination were the prominent causes of population variability. While the standard Poisson Ricker model incorporating demographic stochasticity does not allow for competitive indeterminacy or coexistence given fitness differences between competitors, our best fit model suggests that stochastic forces reduce mean extinction times, and allow for multiple possible competitive outcomes (coexistence or exclusion of either species). This probabilistic view of competitive outcome dependent on the initial abundance of competing species could explain the competitive coexistence in Park's classic Tribolium experiments. Further, the incorporation of the various stochastic forces into demographic models suggest that current estimates of extinction risk, coexistence, and biological invasion probabilities may be underestimates when based on models only incorporating demographic stochasticity.