While the human gut microbiome has been intensely studied, we have yet to obtain a sufficient understanding of the genetic diversity harbored by this complex system. This difficulty is compounded by the confluence of forces operating within the gut, where the dynamics of a given allele can be driven by evolutionary forces (drift, selection, etc.) or by the ecology of the strain on which said allele is a constituent. To make progress towards this goal, I identified and characterized statistically invariant patterns of genetic diversity in a large cohort of unrelated hosts across 22 prevalent microbial species. The existence of said patterns allows for the set of feasible models to be pared down to those that can reproduce observed patterns without the use of free parameters. Using a feasible distribution of allele frequencies, I evaluated the extent that a model of ecological dynamics was capable of predicting the fraction of hosts harboring a given allele (i.e., prevalence), a statistic that allows for the effect of sampling to be taken into account. I found that the Stochastic Logistic Model (SLM), an ecological model that has been shown to successfully predict the dynamics of strains, succeeded across all species. The accuracy of the predictions was correlated with independent estimates of strain structure, validating the ecological implications of the SLM. This work indicates that a large number of detectable genetic variants in the human gut are subject to ecological, as opposed to evolutionary, dynamics.