Abstract1. There is an urgent need for large-scale botanical data to improve our understanding of community assembly, coexistence, biogeography, evolution, and many other fundamental biological processes. Understanding these processes is critical for predicting and handling human-biodiversity interactions and global change dynamics such as food and energy security, ecosystem services, climate change, and species invasions.2. The Botanical Information and Ecology Network (BIEN) database comprises an unprecedented wealth of cleaned and standardised botanical data, containing roughly 81 million occurrence records from c. 375,000 species, c. 915,000 trait observations across 28 traits from c. 93,000 species, and co-occurrence records from 110,000 ecological plots globally, as well as 100,000 range maps and 100 replicated phylogenies (each containing 81,274 species) for New World species. Here, we describe an r package that provides easy access to these data. K E Y W O R D S

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Summary1 Advances in both informatics and mobile technology are providing exciting new opportunities for generating, disseminating, and engaging with information in the biological sciences at unprecedented spatial scales, particularly in disentangling information on the distributions and natural history of hyperdiverse groups of organisms. 2 We describe an application serving as a mobile catalog of all of the plants of the Americas developed using species distribution models estimated from field observations of plant occurrences. The underlying data comprise over 3Á5 million standardized observations of over 88 000 plant species. 3 Plant-O-Matic, a free iOS application, combines the species distribution models with the location services built into a mobile device to provide users with a list of all plant species expected to occur in the 100 9 100 km geographic grid cell corresponding to the user's location. The application also provides ancillary information on species' attributes (when available) including growth form, reproductive mode, flower color, and common name. Results can be searched and conditionally filtered based on these attributes. Links to externally sourced specimen images further aid in identification of species by the user. 4 The application's ability to assemble locally relevant lists of plant species and their attributes on demand for anywhere in the Americas provides a powerful new tool for identifying, exploring, and understanding plant diversity. Mobile applications such as Plant-O-Matic can facilitate dynamic new approaches to science, conservation, and science education.