Diversidade genética e modelagem preditiva de distribuição de mimosa tenuiflora (Willd) Poiret

• Ano de defesa: 2018
• Autor(a) principal: Chagas, Kyvia Pontes Teixeira das
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Brasil; UFRN; PROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIAS FLORESTAIS
• Palavras-chave em Português: Jurema-preta; Nicho ecológico; Marcador molecular; Caatinga; CNPQ::CIENCIAS AGRARIAS::RECURSOS FLORESTAIS E ENGENHARIA FLORESTAL
• Link de acesso: https://repositorio.ufrn.br/jspui/handle/123456789/26582

Mimosa tenuiflora (Fabaceae), known as jurema-preta, has high economic and ecological potential. It is widely used as firewood for the production of red ceramics. Due to the high development capacity in compacted soils, people considered the species an indicator of the initial stages of succession and the recovery of the forest cover. The objective of the study was to evaluate the genetic diversity in natural populations and to predict climatically adequate areas for the occurrence of M. tenuiflora in a climate change scenario. We sampled fifteen natural populations in the state of Rio Grande do Norte, totaling 225 individuals, obtaining diversity indexes and genetic structure by means of 70 ISSR (Inter Simple Repeat Intervals). The maximum entropy algorithm (Maxent) was used in the modeling of the distribution of the species, with the use of geographic occurrence points and 19 bioclimatic variables. The genetic diversity of Nei and the Shannon index presented averages of 0.21 (± 0.02) and 0.35 (± 0.03), respectively. The most genetically diverse populations were ACU (Assú), CRV (Caiçara do Rio do Vento) and MAR (Martins), and the least diversified was CAR (Caraúbas). These populations showed significant population decreases in the infinite allele model and should be a priority for conservation. Bayesian analysis indicated the formation of four groups with the greatest genetic differentiation, with ESP (Espirito Santo) being the most differentiated, explained by the genetic discontinuity with the other populations. We selected eleven bioclimatic variables for the distribution models of the species after multicollinearity analysis. Modeling for the present period presented AUC (area under the curve) of 0.94 (± 0.02), indicating good fit of the model used. For the future period (2070), the AUC value ranged from 0.88 to 0.89 for the optimistic scenario, and 0.87 to 0.88 for the pessimistic scenario. The highest percentage of contribution was for the annual precipitation variable (58.3%). The areas of suitability occurred in greater intensity and almost completely in the states of Ceará and Rio Grande do Norte. In relation to the predictions of the future, the territory with high adequacy presented a reduction ranging from 28.7% to 53.7% and 30.9% to 59.4%, for the optimistic and pessimistic scenarios, respectively. The results obtained can contribute as a subsidy for the establishment of commercial plantations, and in the definition of management and conservation strategies.