Despite an improving knowledge of species distribution patterns in the Neotropics, the processes that underlie these patterns remain uncertain. The tribe Bignonieae (Bignoniaceae), with 21 genera and c. 400 species, is the largest clade of lianas in the Neotropics. The group is an excellent model for biogeographical and evolutionary studies as it is widely distributed and exhibits high levels of morphological diversity. Here, we investigate the biogeographical history of Bignonieae using a tribe‐wide time‐calibrated phylogenetic tree as a basis for ancestral area reconstructions. We examine four hypotheses for the origin and subsequent biogeographical spread of the tribe. Our analyses suggest that the crown group of Bignonieae originated in South American rainforests approximately 50 Mya. Ancestral area reconstructions for the early divergences are equivocal, although the resulting Adenocalymma–Neojobertia and core Bignonieae clades appear to have occurred in eastern South America and lowland Amazonia, respectively. Our analyses suggest that, following this initial split, most lineages of Bignonieae have been repeatedly exchanged between biogeographical areas. These events occurred over a broad time span and are likely to have had multiple drivers; climate drying and the Andean Orogeny may have been particularly important for shaping overall diversity. In Bignonieae, contemporary distribution patterns appear to have been strongly influenced by Holocene environmental change. © 2012 The Linnean Society of London, Botanical Journal of the Linnean Society, 2013, 171, 154–170.

Understanding the patterns and processes underlying the uneven distribution of biodiversity across space constitutes a major scientific challenge in systematic biology and biogeography, which largely relies on effectively mapping and making sense of rapidly increasing species occurrence data. There is thus an urgent need for making the process of coding species into spatial units faster, automated, transparent, and reproducible. Here we present SpeciesGeoCoder, an open-source software package written in Python and R, that allows for easy coding of species into user-defined operational units. These units may be of any size and be purely spatial (i.e., polygons) such as countries and states, conservation areas, biomes, islands, biodiversity hotspots, and areas of endemism, but may also include elevation ranges. This flexibility allows scoring species into complex categories, such as those encountered in topographically and ecologically heterogeneous landscapes. In addition, SpeciesGeoCoder can be used to facilitate sorting and cleaning of occurrence data obtained from online databases, and for testing the impact of incorrect identification of specimens on the spatial coding of species. The various outputs of SpeciesGeoCoder include quantitative biodiversity statistics, global and local distribution maps, and files that can be used directly in many phylogeny-based applications for ancestral range reconstruction, investigations of biome evolution, and other comparative methods. Our simulations indicate that even datasets containing hundreds of millions of records can be analyzed in relatively short time using a standard computer. We exemplify the use of SpeciesGeoCoder by inferring the historical dispersal of birds across the Isthmus of Panama, showing that lowland species crossed the Isthmus about twice as frequently as montane species with a marked increase in the number of dispersals during the last 10 million years.