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Background The “Baru” tree (Dipteryx alata Vogel) is an endemic species from the Cerrado biome, but widely distributed within the biome and abundant in several of its habitats [1].The species is also important in commercial terms for recover of degraded areas, and seeds are consumed in natura and are source of raw material for small and middle-sized food industries [2].Thus, a more detailed knowledge of its population variability and structure is needed for better establishing both in situ and ex situ conservation efforts. Data for such analyses can be provided by new molecular markers, such as microsatellites, whereas spatial analyses and optimization procedures can be applied to analyze these data and thus improve conservation efforts. Here we investigate the genetic variability within the germplasm bank of D. alata based on microsatellite data and compared it with a large sample of 25 widely distributed natural populations of the species. We then used a simulated annealing algorithm to find the smallest number of these natural populations that should be sampled to conserve the full genetic variability of the species.

Optimizing sampling efforts for ex situ conservation of genetic variability of Dipteryx alataVogel