Datasets from boreal (Denali National Park, United States), temperate (Great Smoky Mountains National Park, United States) and tropical (La Selva Biological Station, Costa Rica) regions of North America were subjected to analysis. The complete dataset, composed primarily of field data, consisted of 3558 records, with 46% temperate, 29% boreal and 23% tropical. A total of 208 species were recorded for the three regions, with 69% temperate, 49% boreal and 40% tropical. A high significant correlation between the number of records and the number of species (r2=0.99, P=0.001) suggested that the latter was a function of the former, independent of location. However, this relationship was stable at low survey efforts, as it was observed in a model obtained with 25 independent datasets from the northern hemisphere of the Americas. Diversity values, calculated with the Shannon Index, ranged from 3.4 to 4.0 and were different for all pairwise combinations (all cases P<0.05) of the three datasets, but when calculated with the Simpson Index they were not different for the combination of temperate and boreal datasets. At the species level, the smallest value (0.38) for coefficient of community was observed for the boreal-tropical pair and highest (0.56) for the temperate-tropical pair. The taxonomic diversity indices were 2.68 and 2.83 for the boreal and tropical datasets, but 3.76 for the temperate dataset. The latter may be an indication of higher fruiting propensity in temperate regions rather than an indication of intraspecific diversity, an idea that deserves further examination. The boreal dataset had the highest number of unique genera (7), followed by the temperate (6) and the tropical (2) datasets. However, the temperate dataset showed the highest number of unique species (57), followed by the boreal (37) and tropical (26) datasets. When analyzed in a comparative context, standard experiments with similar field efforts and techniques are still required to document patterns of reproductive occurrence of myxomycetes in different regions of the world. For macroecological purposes, all regions represented by the datasets analyzed herein still remain understudied.