BackgroundThe species Zea mays includes both domesticated maize (ssp. mays) and its closest wild relatives known as the teosintes. While genetic and archaeological studies have provided a well-established history of Z. mays evolution, there is currently minimal description of its current and past distribution. Here, we implemented species distribution modeling using paleoclimatic models of the last interglacial (LI; ?135,000 BP) and the last glacial maximum (LGM; ?21,000 BP) to hindcast the distribution of Zea mays subspecies over time and to revisit current knowledge of its phylogeography and evolutionary history.
Methodology/principal findingsUsing a large occurrence data set and the distribution modeling MaxEnt algorithm, we obtained robust present and past species distributions of the two widely distributed teosinte subspecies (ssps. parviglumis and mexicana) revealing almost perfect complementarity, stable through time, of their occupied distributions. We also investigated the present distributions of primitive maize landraces, which overlapped but were broader than those of the teosintes. Our data reinforced the idea that little historical gene flow has occurred between teosinte subspecies, but maize has served as a genetic bridge between them. We observed an expansion of teosinte habitat from the LI, consistent with population genetic data. Finally, we identified locations potentially serving as refugia for the teosintes throughout epochs of climate change and sites that should be targeted in future collections.
Conclusion/significanceThe restricted and highly contrasting ecological niches of the wild teosintes differ substantially from domesticated maize. Variables determining the distributions of these taxa can inform future considerations of local adaptation and the impacts of climate change. Our assessment of the changing distributions of Zea mays taxa over time offers a unique glimpse into the history of maize, highlighting a strategy for the study of domestication that may prove useful for other species.