A human body hosts a relatively independent microbiome including five major regionalbiomes (i.e., airway, oral, gut, skin, and urogenital). Each of them may possess differentregional characteristics with important implications to our health and diseases (i.e.,so-termed microbiome associated diseases). Nevertheless, these regional microbiomesare connected with each other through diffusions and migrations. Here, we investigatethe within-body (intra-individual) distribution feature of microbiome diversity via diversityarea relationship (DAR) modeling, which, to the best of our knowledge, has not beensystematically studied previously. We utilized the Hill numbers for measuring alphaand beta-diversities and built 1,200 within-body DAR models with to date the mostcomprehensive human microbiome datasets of 18 sites from the human microbiomeproject (HMP) cohort. We established the intra-DAR profile (z-q pattern: the diversityscaling parameter z of the power law (PL) at diversity order q = 0–3), intra-PDO (pair-wisediversity overlap) profile (g-q), and intra-MAD (maximal accrual diversity) profile (D max -q)for the within-body biogeography of the human microbiome. These profiles constitute the“maps” of the within-body biogeography, and offer important insights on the within-bodydistribution of the human microbiome. Furthermore, we investigated the heterogeneityamong individuals in their biogeography parameters and found that there is not an“average Joe” that can represent majority of individuals in a cohort or population. Forexample, we found that most individuals in the HMP cohort have relatively lower maximalaccrual diversity (MAD) or in the “long tail” of the so-termed power law distribution.In the meantime, there are a small number of individuals in the cohort who possessdisproportionally higher MAD values. These findings may have important implicationsfor personalized medicine of the human microbiome associated diseases in practice,besides their theoretical significance in microbiome research such as establishing thebaseline for the conservation of human microbiome.