This research serves to advance our understanding of the complex of vegetative, root-related, and reproductive components of perenniality in O. rufipogon and O. nivara and to associate these traits with genomic regions to further the identification and characterization of the molecular pathways involved in a perennial life habit in the grasses. Establishing a standardized set of traits with which to phenotypically characterize the accessions in our association mapping panel as annual, perennial, or intermediates has allowed us to propose and clarify life habit phenotyping methodology, and provided specific phenotypic data which will used for high-resolution association mapping. Characterizing and defining the traits associated with life cycle habit, as well as determining their relation to a seed vs. clonal reproductive habit and to genetic variation, also assists us in defining the species/ecotype classification of these wild ancestors. This background information allows us to better organize future studies examining the effect of water status and availability on life habit, and the range in phenotypic plasticity of different accessions of O. rufipogon and O. nivara, and how environments, population structure, and genetic factors may be responsible for that phenotypic plasticity. A strong understanding of the genetic, reproductive, developmental, and ecological factors allows us to better determine whether these two wild ancestors are more precisely classified as ecotypes instead of completely divergent species. This will in turn assist us in the reclassification, better management, and more effective use of wild germplasm resources for breeding. By pinpointing sequence variation underlying the molecular control of growth and reproductive habit in O. rufipogon and O. nivara, we hope to identify traits conferring growth habit-related yield stability and abiotic stress resistance traits useful for introgression in elite lines of cultivated rice or other cereal crops for enhanced resistance to climate change and unpredictable weather patterns.