The high diversity and limited floral information in tropical forests often pose a challenge for species identification. However, over the past decade, DNA barcoding has been employed in tropical forests, including Sumatran forests, to enhance floristic surveys. This technique facilitates the discrimination of morphologically similar species and addresses the limitations of conventional species identification, which relies on short-lived reproductive structures. This study aimed to evaluate the efficiency of matK, rbcL, and the combination of both chloroplast markers for species identification in Burseraceae by employing genetic distance and species tree inference. In this study, we collected 197 specimens representing 20 species from five genera of Burseraceae. The highest percentage of specimens' identification (36%) at the species level was obtained using matK + rbcL, followed by matK (31%), and rbcL (7%). The matK dataset presented the highest interspecific divergence with a mean of 0.008. In addition, a lack of barcode gap was observed in both markers, suggesting potential limitations of the core barcodes for distinguishing Sumatran species within Burseraceae. The monophyly test confirmed five species as monophyletic using Bayesian species tree inferences for matK. Overall, our results demonstrate that matK outperforms rbcL in species identification of Burseraceae, whereas their combination did not enhance species delimitation. To improve the molecular species assignments of this family, future studies may consider including more DNA markers in conjuction with matK, and broadening the availability of reference sequences for species that have not yet been included in the databases. The outcomes of molecular species identification vary depending on the taxonomic group under investigation. Implementation of phylogenomics for species delimitation and diagnostic marker development is strongly recommended for tropical biodiversity assessments, especially for poorly studied clades.
Keywords: barcode gap; genetic distance; matK; species identification; tropical biodiversity.
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