Genetic diversity of endangered populations of Butia capitata: Implications for conservation
Keywords: Arecaceae, inter simple sequence repeats (ISSR) molecular markers, Bayesian analysis, management measures.
AbstractThe flora and fauna of the Cerrado biome in central Brazil both show great diversity and high levels of endemism. Butia capitata is a palm native to this biome that has significant economic, social, and environmental value. We sought to identify and quantify the genetic diversity of four fragmented populations of B. capitata growing in northern Minas Gerais State, Brazil, as well as one located at the Institute of Agricultural Sciences (ICA) at UFMG, assessing 93 genotypes using 11 ISSR markers. The relationships among populations were evaluated by constructing dendrograms, principal coordinate analysis, genetic distances, as well as Bayesian inference, including and excluding the ICA population. High genetic diversity was found in the populations studied, with most of that diversity occurring within populations. Bayesian inference regrouped the original populations into four populations, redistributing the ICA individuals to the Abóboras and Cristália populations. The analysis that excluded the ICA population arranged the original populations into two groups - with the Abóboras and Cristália populations together in the same group. The ICA population was found to be a repository for future reintroductions into the Abóboras and Cristália regions, as they genetically resemble those populations. It should be noted that other management measures outlined in this study should be adopted before these palm populations enter critical decline phases, such as: stimulus to plants seedlings derived from seeds originated in each area (principally the Abóboras site); quantification of the genetic diversity of neighboring populations to the Mirabela site for future reintroductions as this population showed low intrapopulation diversity.
Key words: Arecaceae, inter simple sequence repeats (ISSR) molecular markers, Bayesian analysis, management measures.
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