Evolutionary forces are known to drive the fixation of locally adaptive genetic variation within populations, and plants provide an excellent model for investigations into its genetic origins, maintenance and adaptive significance. We aim to take advantage of the natural genetic variation that occurs between populations of the genetic model plant Arabidopsis thaliana to identify gene functions that vary between these natural populations. Such a set of polymorphic genes and gene functions will provide the essential tools required to uncover the genetic mechanisms that drive the fixation of locally adaptive genetic variation within a population. To link natural genetic variation to function, we have applied high-throughput Inductively Coupled Plasma – Mass Spectroscopy (ICP-MS) based elemental-profiling, in combination with genome-wide association mapping and traditional linkage mapping to reveal loci that drive natural variation in the plant's elemental-profile or “ionome” including P, Ca, K, Mg (macronutrients); Cu, Fe, Zn, Mn, Co, Ni, Se, Mo, I (micronutrients of significance to plant and human health); Na, As, and Cd (minerals causing agricultural or environmental problems). Using a combination of laboratory and field-based experiments we propose to uncover the adaptive benefit and evolutionary significance of these naturally occurring polymorphic ionomic loci, along with their molecular function, and underlying causal genetic and epigenetic basis. This information will help determine the evolutionary processes involved in adaptation of organisms to local environments. Such insights will help in predicting the extent and limits of possible future adaptations of plants to changes in the surface chemistry of the Earth driven by a changing global climate, and will have applications to optimizing the mineral content of food crops for improved human health. After all, plants provide the major source of nutrition for a large portion of the world’s population.