**1. Introduction**

Africa includes the second largest tropical forest block in the world, considered as one of the most important pool of biological diversity [1]. Yet, African forests are threatened by expanding human activities such as industrial logging, mining, agriculture, and road networks [2,3], but are also highly susceptible to the impact of climate change [4]. Despite the growing international concern about the future of these forests, the diversity, the ecology and the evolutionary processes that have shaped African forests remain relatively poorly understood, compared to the Amazon forest block [5]. In this regard, there is an urgen<sup>t</sup> need to increase our efforts in documenting and describing the diversity of these forests as many of the species might go extinct before they are discovered. Therefore, large-scale biodiversity inventories of African forests will be critical to develop sound conservation strategies for these forests [6]. During the past decades, significant progress has been made in the study of the biodiversity of African forests using classic floristic inventories and longterm monitoring plots grouped into two main networks, the African Tropical Rainforest Observation Network (AfriTRON, http://www.afritron.org/) (accessed on 10 February 2022)and the Africa program of the Forest Global Earth Observatory Network (ForestGEO, https://forestgeo.si.edu/, accessed on 10 February 2022). In forest inventories, the species are identified merely on the basis of morphological characters, and this is challenging even for expert botanists. Often, up to 30% of the individuals in the plots remain unidentified

**Citation:** Kenfack, D.; Abiem, I.; Chapman, H. The Efficiency of DNA Barcoding in the Identification of Afromontane Forest Tree Species. *Diversity* **2022**, *14*, 233. https:// doi.org/10.3390/d14040233

Academic Editors: W. John Kress, Morgan Gostel and Michael Wink

Received: 16 February 2022 Accepted: 21 March 2022 Published: 23 March 2022

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

for years [7] due to the absence during field surveys of flowers and fruits that are needed to achieve accurate identifications [8].

Biological identification through "DNA barcode" was proposed, first in the animal kingdom [9,10] and later on for land plants [11,12] as a molecular method that could supplement morphological identifications. DNA barcodes are short and standardized fragments of DNA that should be easy to amplify and to sequence, and that can rapidly and reliably distinguish species from each other. DNA barcoding slowly gained ground in Africa, with over 21,000 vascular plants and 3000 animal records in the Barcode of Life Data System in 2019 [13,14], and has been used to elucidate the systematics and ecology of several plant groups, e.g., [15–17]. Existing African DNA barcodes for plants have been concentrated in forest ecosystems in Southern and West Africa [14,18] and more recently in savanna ecosystems [13]. Furthermore, inferences on the effectiveness of DNA barcode to identify African forest trees have been mostly based on lowlands. Whereas montane forests significantly differ floristically and structurally from lowland forests, the effectiveness of DNA barcoding in identifying tree species in these forests is still lacking.

We constructed a local DNA barcode database to aid the identification of tree species and reconstruct their community phylogeny in a 20.28 ha plot located in montane forest in Northeastern Nigeria. Here, we test the ability of this DNA barcode to identify the plot species and genera.
