Plant core DNA barcode performance at a local scale: identification of the conifers of the state of Hidalgo, Mexico
DNA barcoding constitutes a fundamental tool for species identification, especially for highly diverse geographic regions. Here, we characterize and evaluate the plant core barcoding regions matK and rbcL to identify the 25 conifer species from the state of Hidalgo, Mexico, including 10 species in various threat categories. Sequence quality, linguistic complexity, and the presence of the barcode gap were estimated. Two methods were compared for successful species identification: BRONX (Barcode Recognition Obtained with Nucleotide eXposés) and the least inclusive clade. We generated 77 sequences for matK and 88 for rbcL. The matK region had higher haplotype diversity and nucleotide diversity (Π), including six indels. The analysis of 77 specimens with complete sequences (matK + rbcL) resulted in 21 nonspecies-specific unique haplotypes for the 25 conifer species. Higher sequence quality and linguistic complexity were observed in rbcL than in matK. Every diagnosable species had a barcode gap. Ninety-seven specimens were assigned unambiguously to family and genus, regardless of the marker or method employed. The analysis of matK with BRONX produced the highest species level identification success (44%). Despite the low specimen identification success at the specific level, it will be possible to establish local management, conservation, and monitoring projects for at least half of the threatened species even when specimens do not exhibit diagnostic morphological characters. The low divergence between closely related species may result from the slow rate of molecular evolution of the core barcoding markers or from hybridization or incomplete lineage sorting. Similar identification success is expected for groups with comparable life history traits under similar conditions as this study. A reduction in the geographic area will not necessarily translate into higher identification success, especially for high-diversity regions and centres of diversification.