Pollen grains are usually counted in discrete samples of ≈£300 specimens which, allowing for taphonomic filtering, provide proxy data on both parent floral composition and taxonomic diversity. However, there are no taxonomically independent (i.e. neutral) ways to determine environment and climate based on pollen data. I present an attempt to extract information from the modern pollen record that ignores the assumed systematic affinity of the pollen grains. My approach centres on the abundance distribution of pollen grains within counted samples. I posit that the abundance distributions will reflect plant community (biome) characteristics and especially pollination syndromes£ samples should have increasing equitability with increasing latitude. The data set is constructed from 48 eastern North American localities which are isotaphonomically sampled along a latitudinal transect from the subtropics to the tundra. Pollen composition, taxonomic richness and pollen co-occurrence patterns change significantly between biomes. Evenness metrics (including Hurlbert’s PIE) indicate that equitability shows only minor changes from one biome to another—all localities have positively skewed, leptokurtic abundance patterns and conform to a truncated log-normal distribution. Hence, sampled pollen equitability can not determine parent communities and has few, if any, predictive powers.