Molecular taxonomy of guitarfishes (Rhinobatidae: Acroteriobatus)

Molecular taxonomy of guitarfishes (Rhinobatidae: Acroteriobatus) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Molecular taxonomy of guitarfishes (Rhinobatidae: Acroteriobatus) Mia Jo Groeneveld, Juliana D. Klein, Michaela van Staden, Rhett H. Bennett, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7379127/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Jan, 2026 Read the published version in Marine Biodiversity → Version 1 posted 6 You are reading this latest preprint version Abstract Guitarfish species (genus Acroteriobatus ) display restricted distributions in undermanaged regions of intense fishing pressure, which is exacerbated by taxonomic uncertainty due to morphological similarity. The importance of accurate specimen identification is well established, especially in the context of conservation management. However, guitarfishes remain poorly understood. We therefore aimed (1) to identify molecular operational taxonomic units (MOTUs) within Acroteriobatus by analysing sampled specimens as well as publicly available sequence data for the cytochrome c oxidase subunit I ( COI ) and nicotinamide adenine dehydrogenase subunit 2 (ND2 ) genes, and (2) to augment and review the representation of these sequences on public databases. A molecular taxonomic approach integrating species delimitation and specimen assignment methods revealed 14 MOTUs. These MOTUs aligned with current species descriptions, displaying no evidence of cryptic diversity. Both genes demonstrated similar interspecific relationships that broadly reflected current distribution ranges, underscoring sub-regional endemism. Moreover, discrepancies in public sequence repositories were identified, attributed to misidentified specimens and the usage of outdated taxonomic nomenclature. Genetic diversity indices were substantially inflated when specimens were grouped based on reported species versus delimited MOTUs, thus overestimating genetic diversity. We highlight the need for extensive, curated DNA reference libraries, including revising earlier sequence entries in light of new taxonomic insights, to enable reliable identification of morphologically conserved species. The molecular resolution illustrated in this study can aid in clarifying taxonomic uncertainties in the genus Acroteriobatus . Elasmobranchii mitochondrial DNA Rhinopristiformes rhino rays species delimitation taxonomic uncertainty Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The growing emphasis on species boundaries in conservation and management reflects an increasing recognition of the critical role that species interactions and ecological relationships play in shaping biodiversity and ecosystem function (Le Bagousse-Pinguet et al. 2019 ; Zhang et al. 2023 ). Species boundaries however remain a controversial topic in evolutionary biology, while several key principles are widely acknowledged. For instance, phenotypic traits, genes and genomic regions that remain distinct despite hybridisation and introgression show that these boundaries are semipermeable (Harrison and Larson 2014 ). Distinct species can converge on similar morphologies, while cryptic species may remain morphologically indistinguishable and display significant genetic divergence (Mayr 1992 ; Knowlton 1993 ; Palumbi and Lessios 2005 ; Ferrari et al. 2023 ). Thus, the degree of morphological difference cannot be the only species criterion. Elasmobranchs (sharks and batoids) demonstrate notable endemism and species richness (Stein et al. 2018 ), yet accurate and unambiguous species identification has proven particularly challenging due to the low intrinsic variation and conserved nature of their ecological and external traits (Ball et al. 2016 ; Cariani et al. 2017 ; Bache-Jeffreys et al. 2021 ). Traditional morphology-based identification methods may fail to detect cryptic, hybrid or rare species (Cerutti-Pereyra et al. 2012 ), discern specimens at different ontogenetic stages (Steinke et al. 2016 ) or address cases of phenotypic plasticity (Compagno et al. 1989 ; Human 2007 ; Séret et al. 2016 ). Molecular systematics has recently been integrated with traditional methods to more effectively assess phylogenetic relationships between elasmobranch taxa (Palumbi and Lessios 2005 ; Cariani et al. 2017 ; Ferrari et al. 2023 ), shedding light on cryptic and sibling species (Bickford et al. 2007 ; Vilasboa et al. 2022 ; Melis et al. 2023 ) and the role of biogeographical barriers in speciation (Sandoval-Castillo et al. 2004 ; Hirschfeld et al. 2021 ). Guitarfishes from the family Rhinobatidae remain understudied. These batoids’ conserved morphology and vague original descriptions necessitate molecular scrutiny to address taxonomic challenges (Last et al. 2016; Jabado 2018 ; Weigmann et al. 2021 ; van Staden et al. 2022 ; Aitchison et al. 2024 ). Earlier studies have found recurrent polyphyletic topologies within Rhinobatidae based on mitochondrial and nuclear data (Aschliman et al. 2012 ; Naylor et al. 2012a , 2016 ). This is supported by morphometric analyses and, to a large extent, the biogeography of the genus-level taxa, which necessitated a taxonomic revision of the group (Naylor et al. 2012a ). This led to the establishment of the new order Rhinopristiformes (i.e., rhino rays or shark-like rays) and three Rhinobatid genera ( Acroteriobatus , Rhinobatos and Pseudobatos ), which was formally revised by Last et al. (2016) and substantiated by subsequent studies (van Staden et al. 2022 ; Groeneveld et al. 2023 ; Wang et al. 2023 ; Aitchison et al. 2024 ). These smaller rhinobatids are also increasingly being targeted and retained for their fins and flesh. This growing economic significance (Seidu et al. 2022 ) is primarily due to the overexploitation of species from the larger-bodied sister families of this order such as wedgefishes from the family Rhinidae (Moore 2017 ; Daly et al. 2021 ; Pytka et al. 2024 ). All rhino rays were also included in Appendix II of the Convention on International Trade in Endangered Species of Fauna and Flora (CITES 2025 ), but enforcement of this listing and the management measures that are already in place remains challenging in the absence of species-level data. Guitarfishes are typically found in temperate to tropical coastal regions, which are often characterised by low levels of food security in local communities, substantial fishing pressure (artisanal and industrial) and limited capacity to manage catches (Pytka et al. 2024 ; Kyne et al. 2024 ). Such hotspots of overlap between the distribution of these species and fishing pressure should be considered priorities for management (Kyne et al. 2020 ). It is now understood that Acroteriobatus species are predominantly confined to the Western Indian Ocean (WIO), except for two species occurring in the Southeast Atlantic, while Pseudobatos species are restricted to the amphi-American region (encompassing both the Atlantic and Pacific coasts of the Americas) and Rhinobatos species occur mostly in the Indo-Western Pacific and Eastern Atlantic (Weigmann et al. 2021 and references therein). The three genera can be differentiated molecularly and morphologically, where oronasal morphology currently appears to hold the greatest potential as a diagnostic trait (Last et al. 2016) - but not to the species level. Currently, Acroteriobatus comprises 10 described species, with the International Union for Conservation of Nature’s (IUCN 2024 ) Red List assessments ranging from Data Deficient (DD) to Critically Endangered (CR) while some species have not been evaluated (NE; Kyne et al. 2024 ; Online Resource 1 - Table S1 ). Weigmann et al. ( 2021 ) recently provided a key for distinguishing between Acroteriobatus species based on snout shape, disc form and spot or stripe colour patterns, which will prove useful for identification. Species exhibiting elongated bluish-grey spots on the dorsal surface of the snout typically display a stripe-nosed pattern, whereas those lacking this pattern have a plain light to white ventral surface without a dark blotch (Weigmann et al. 2021 ). The WIO is classified as a biodiversity hotspot (Tittensor et al. 2010 ; Worm and Branch 2012 ) and encompasses many Important Shark and Ray Areas (ISRAs, ISRA region 7), spanning from KwaZulu-Natal in South Africa, along East Africa, to the Red Sea, Persian Gulf, Arabian Sea, western India and the Maldives archipelago (Jabado et al. 2023 ). A re-evaluation of the greyspotted guitarfish A. leucospilus (Norman 1926 ) species complex led to the description of two new bluespotted guitarfishes: Socotra guitarfish A. stehmanni and Malagasy guitarfish A. andysabini Weigmann, Ebert & Séret 2021 . Only A. salalah (Randall & Compagno, 1995 ), recently confirmed in the Socotra Islands, is known to co-occur with A. stehmanni within its range (Bogorodsky et al. 2021 ). Acroteriobatus leucospilus is now thought to occur from the Eastern Cape, South Africa, to at least Tanzania, extending its previously reported range beyond Mozambique and South Africa (Compagno et al. 1989 ; Séret et al. 2016 ; Weigmann et al. 2021 ) but not in Madagascar (Ebert et al. 2021 ). The current distribution of the lesser guitarfish A. annulatus (Müller & Henle 1841 ) is recognised as extending from Namibia to KwaZulu-Natal, but recent assessments may indicate its absence in Namibia (Leeney 2023 , 2024 ), and Ebert et al. ( 2021 ) lists the distribution as Langebaan (Western Cape) to the Transkei coast (Eastern Cape) and potentially central KwaZulu-Natal. This distribution is poorly defined as A. annulatus has often been misidentified with other South African guitarfish species including the bluntnose guitarfish A. blochii (Müller & Henle 1841 ), A. leucospilus and the DD speckled guitarfish A. ocellatus (Norman 1926 ) (Ebert et al. 2021 ). Limited information is available on A. ocellatus , and the distribution map from Séret et al. ( 2016 ) is inaccurate as the only verified specimens are from Algoa Bay (Ebert et al. 2021 ). Although both are currently considered valid species based on molecular data (Yang et al., unpubl.), uncertainties persist regarding the poorly known A. zanzibarensis (Norman 1926 ) and the CR stripenose guitarfish A. variegatus (Nair & Lal Mohan 1973 ) (Weigmann et al. 2021 ). The four species that are known from the northern Indian Ocean - A. variegatus , A. stehmanni , A. salalah and the Oman guitarfish A. omanensis Last, Henderson & Naylor 2016 - all exhibit narrow distribution ranges (Séret et al. 2016 ; Weigmann et al. 2021 ). Accurate specimen identification at the finest possible taxonomic resolution is required for robust conservation management, as poorly defined biological and geographical species boundaries lead to unreliable species-specific data (e.g., Dayrat 2005 ; Porcu et al. 2020 ; Johri et al. 2020 ; Bellodi et al. 2022 ). Consequently, true species diversity is under- or overestimated, impeding the assessment of population status, trends (Kyne et al. 2024 ) and the impact of fisheries on species (Melis et al. 2023 ). Enforcement of protective regulations requires an unambiguous definition of a species that accounts for all natural variation. This issue is exemplified in the mislabelling of commercial landings in markets (Iglésias et al. 2010 ; Alvarenga et al. 2021 ) and in catch monitoring, which is frequently reported at highly aggregated taxonomic levels (Sherman et al. 2023 ; Pytka et al. 2024 ), masking overfishing and local extinctions. Furthermore, resolving taxonomic uncertainties would provide a stronger foundation for future research on all aspects of rhino ray biology (Dayrat 2005 ; Kyne et al. 2024 ). A molecular taxonomic approach that implements both species delimitation and specimen assignment methods has the potential to flag undocumented species and/or misidentified specimens. Delimitation analyses are increasingly utilised to determine the number of species-level entities or cohesive genealogical lineages within a dataset (Dayrat 2005 ; Dellicour and Flot 2018 ) by clustering orthologous sequences into molecular operational taxonomic units (MOTUs). These probabilistic models offer insights into intra- and interspecific relationships without needing a priori species boundaries or standardised distance thresholds (Ramirez et al. 2023 ). Specimen assignment methods are employed to match a query sequence from an unidentified specimen to a known species (Zhang et al. 2012b ). Such approaches have proven effective in managing and validating DNA reference libraries in cases of taxonomic uncertainties (Carugati et al. 2022 ; Bellodi et al. 2022 ; van Staden et al. 2023 ), which can result in published sequences from misidentified specimens (Benson et al. 2012 ; Cardeñosa et al. 2020 ; Sherman et al. 2023 ). Although barcode cytochrome c oxidase subunit I ( COI ) sequences are the norm in molecular taxonomy (Hubert and Hanner 2015 ), elasmobranchs are known for their slow evolutionary rates (Hara et al. 2018 ). Hence, it is recommended that at least one faster-evolving DNA region be analysed in combination with COI , such as nicotinamide adenine dehydrogenase subunit 2 ( ND2 ) (Naylor et al. 2012b ; Henderson et al. 2016 ; Petean et al. 2020 ). If intraspecific genetic variation overlaps with interspecific variation, delimiting specimens based solely on molecular data becomes challenging. Therefore, the presence of a barcode gap - a distinct difference between the intra- and interspecific distances - is crucial for reliably defining species boundaries using genetic thresholds. Considering the taxonomic challenges associated with this marine group and the scarcity of species-specific data, the aim of this study was twofold: (1) to identify MOTUs in the Acroteriobatus genus by analysing sampled species as well as online-available sequence data using molecular taxonomic techniques based on the COI and ND2 genes, and (2) to review and contribute to the availability of COI and ND2 sequences for guitarfishes. These findings can serve as molecular pieces to the taxonomic puzzle of the threatened Acroteriobatus genus. Materials and methods Samples and laboratory procedures Samples were obtained from 54 guitarfish specimens ( Acroteriobatus spp.) representing five species assigned using external morphology and colour patterns following Séret et al. (2016): A. andysabini ( n = 1), A. annulatus ( n = 16), A. blochii ( n = 14), A. leucospilus ( n = 7) and A. zanzibarensis ( n = 16) (Online Resource 1 - Table S2). Specimens were caught using rod and line fishing gear, collected during research trawl surveys, or sampled at fish landing sites or markets. For each individual, muscle tissue or fin clips were sampled and preserved in 90% ethanol at room temperature. Total genomic DNA was extracted using a standard cetyltrimethylammonium bromide extraction (CTAB) protocol (Sambrook and Russell 2001). The purity and quantity were assessed using a NanoDrop™ ND 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Polymerase chain reactions (PCRs) were carried out in a SimpliAmp™ Thermal Cycler in a 15-μl reaction volume. The COI gene region was PCR-amplified using combinations of FishF1/FishF2/FishF2_t1 (forward) and FishR1/FishR2/FR1d_t1 (reverse) as well as the COI -3 primer cocktail (Ward et al. 2005; Ivanova et al. 2007), but predominantly FishF2/FishR2. The ILEM_SeqF/ASNM_SeqR primer pair was used for ND2 (Fernando et al. 2019); see Online Resource 1 - Table S3 for primer details. For COI , the reaction mixture included 50 ng of template DNA, 1 X PCR buffer, 200 μM of each dNTP, 0.3 µM of forward and reverse primers, 2.5 mM of MgCl 2 and 0.625 U of GoTaq® DNA polymerase (Promega, Madison, WI, USA). The thermocycling conditions comprised an initial denaturing step at 94 °C for 5 min, followed by 35 cycles of 94 °C for 30 s, 54 °C for 30 s, 72 °C for 90 s and a final extension step at 72 °C for 10 min. When the COI -3 primer cocktail was used, the protocol followed Ivanova et al. (2007). For ND2 , the reaction mixture consisted of 50 ng template DNA, 1 X PCR buffer, 200 μM of each dNTP, 0.33 µM of forward and reverse primers, 2 mM of MgCl 2 and 0.5 U of GoTaq®. The thermocycling conditions were: 94 °C for 2 min, followed by 30 cycles of 94 °C for 30 s, 60 °C for 30 s, 72 °C for 90 s and a final extension step at 72 °C for 15 min. The PCR amplicons were evaluated through electrophoresis on 1.5% agarose gels. The amplicons were sequenced with the appropriate forward primer, including M13 (Messing 1983) when tailed primers were used, using standard Sanger sequencing chemistry (BigDye® Terminator v.3.1 Cycle Sequencing Kit, Life Technologies, South Africa), whereafter capillary electrophoresis was performed at the Central Analytical Facility of Stellenbosch University, South Africa. Genetic data analyses Previously published sequences of COI and ND2 attributed to the species listed in Online Resource 1 - Table S2 were retrieved from GenBank® (Benson et al. 2012) as well as the Barcode of Life Data Systems (BOLD) (Ratnasingham and Hebert 2007), and integrated with our sequences to build a comprehensive dataset for guitarfishes. Additionally, the Basic Local Alignment Search Tool (BLAST; https://blast.ncbi.nlm.nih.gov/Blast.cgi; accessed on 15 January 2025) was used to identify congeneric species records with >95% similarity. Sequences were manually curated, aligned using the MAFFT v7.450 (Katoh and Standley 2013) algorithm as implemented in Geneious Prime® v2024.0.5 (Kearse et al. 2012) and trimmed to ensure equal length. The correct amino acid translation was verified to exclude nuclear mitochondrial pseudogenes (Song et al. 2008) and sequences shorter than the trimmed alignment lengths were excluded from downstream analyses. All analyses were carried out on two separate datasets i.e., one dataset per gene ( COI and ND2 ). Species delimitation Species defined based on morphology are termed species, whereas those identified using DNA sequence data are termed MOTUs (Moritz 1994). The following single-locus delimitation methods were used to infer the number of MOTUs present within each dataset: (1) Refined Single Linkage (RESL) as implemented on BOLD (Ratnasingham and Hebert 2013), (2) Assemble Species by Automatic Partitioning (ASAP) (Puillandre et al. 2021), (3) Automatic Barcode Gap Discovery (ABGD) (Puillandre et al. 2012), (4) the multi-rate Poisson Tree Processes (mPTP) (Kapli et al. 2017), (5) the Bayesian Poisson Tree Processes (bPTP) (Zhang et al. 2013) and (6) the Generalized Mixed Yule Coalescent (GMYC) approach (Fujisawa and Barraclough 2013). MOTUs were regarded “concordant” if comprising sequences from the same species, and “discordant” if comprising sequences from different species. To address conflicting results from different methods, we defined consensus MOTUs based on the majority agreement among methods. DNA sequence alignments were used for the distance-based delimitation methods (RESL, ASAP and ABGD). The RESL method was only applied to the COI data as it is based on Barcode Index Numbers (BINs) as implemented in BOLD (Ratnasingham and Hebert 2013). The ASAP (https://bioinfo.mnhn.fr/abi/public/asap/asapweb.html; accessed on 20 February 2025) and ABGD (https://bioinfo.mnhn.fr/abi/public/abgd/abgdweb.html; accessed on 20 February 2025) methods were implemented on the respective web applications with default settings under the uncorrected pairwise distance model and a relative gap width (X) of 1.0 for ABGD. For the tree-based delimitation methods, sequences were collapsed into haplotypes utilising the R packages ape v5.6-2 (Paradis and Schliep 2019) and pegas v1.3 (Paradis 2010) for R v4.1.3 (R Development Core Team, 2015; all scripts available on request), with Rhinobatos rhinobatos (Linnaeus 1758) and Pseudobatos horkelii (Müller & Henle 1841) selected as outgroups (JQ518913, KF564313 and PQ014263 - whole mitogenome record). A maximum likelihood (ML) analysis was conducted using the PhyML v.3.0 web server (http://www.atgc-montpellier.fr/phyml/; accessed on 21 February 2025) (Guindon et al. 2010), employing default settings and automatic selection for the best substitution model as determined by the Akaike Information Criterion (AIC) using the Smart Model Selection program (SMS) (Lefort et al. 2017) integrated into PhyML ( COI = GTR+I and ND2 = TN93+G+I). The bPTP (https://species.h-its.org/ptp/; accessed on 21 February 2025) and mPTP (https://mptp.h-its.org/#/tree; accessed on 21 February 2025) methods were performed based on the obtained ML trees. For the GMYC approach, BEAST v2.7.7 (Drummond et al. 2012; Suchard et al. 2018) was used to obtain an ultrametric tree wherein tips (i.e., the taxa) are equidistant from the root (Michonneau 2016). The input file was prepared in BEAUTi, with substitution models set according to those identified by SMS, a strict molecular clock, a Yule speciation model (Yule 1925) and a Markov Chain Monte Carlo (MCMC) length of 10 000 000 generations. After two independent runs in BEAST, LogCombiner v2.7.7 was used to merge the runs whereafter log files were analysed with Tracer v.1.7.2 (Rambaut et al. 2018) to evaluate the robustness of the results. TreeAnnotator v2.7.6 was used to summarise the Bayesian trees sampled from the posterior distribution with a 10% burn-in and subsequently, the consensus tree was visualised with The Interactive Tree Of Life (iTOL) v5 (Letunic and Bork 2021). GMYC was run in R using the splits v1.0-20 package (Ezard et al. 2009) with the credible ultrametric tree. Finally, MOTU designations from the various algorithms along with the consensus MOTUs, were visualised using Evolview v.3 (Subramanian et al. 2019). Specimen assignment Four complementary algorithms were used to evaluate the accuracy of specimen assignments in the delimited datasets i.e., specimens grouped according to consensus MOTUs. First, (1) the distance-based approach “best close match analysis” (BCMA) (Meier et al. 2006) from the R package spider v1.5.0 (Brown et al. 2012) was applied, utilising the threshOpt() function to determine the optimal threshold values for both datasets (Meyer and Paulay 2005). Thereafter, the following methods from the R package BarcodingR v1.0.3 (Zhang et al. 2017) were employed: (2) the back-propagation neural networks method (BP) (Zhang et al. 2008), operating under a machine learning-based framework, (3) the fuzzy-set based approach (FZ) (Zhang et al. 2012b) that uses many-valued logic to assign a degree of membership, and (4) the kmer-based approach (FZKMER) (Zhang et al. 2012a) that classifies specimens independently of sequence alignments. These three methods require a reference dataset, thus the R package dplyr v1.0.10 (Wickham et al. 2022) was used to randomly select one representative for each MOTU and extract the corresponding sequences from the original alignment data. Consensus assignments were designated when a minimum of two methods converged between BP, FZ and FZKMER. Distribution of genetic variation Intra- and interspecific genetic distances were calculated using the p -distance model (Nei and Kumar 2000) with the pairwise deletion option for the treatment of gaps and missing data, employing the dist.dna function from ape . The simple p -distance model was chosen as it is more suitable for short, closely related sequences (Nei and Kumar 2000), and outperforms the Kimura 2-parameter and Jukes-Cantor models in such cases (Srivathsan and Meier 2012; Collins et al. 2012). The presence of a barcode gap (interspecific diversity > intraspecific diversity) was assessed by plotting the maximum intraspecific p -distance against the nearest neighbour (NN; the closest congeneric) distance for each individual in both datasets using the R package ggplot2 v3.4.0 (Wickham 2016). The R packages ape and pegas were used to estimate the principal diversity indices for mitochondrial DNA (the number of haplotypes [ H ], haplotype diversity [ hd ], nucleotide diversity [ π ] and relative standard deviations [SD]). To compare the patterns of genetic variation between species and consensus MOTUs, the above-mentioned approach was repeated using the delimited datasets. Lastly, median-joining inference networks were constructed to visualise the evolutionary relationships between MOTU-haplotypes, as implemented in PopART (Leigh and Bryant 2015). Results A total of 50 COI and 48 ND2 sequences were generated for five species from the genus Acroteriobatus and uploaded to the “Guitarfish delineation ( Acroteriobatus )” project (project code: MTACR), accessible on BOLD (Online Resource 1 - Table S2). The BLAST search for congeneric species with >95% similarity resulted in the inclusion of four COI records from the genus Rhinobatos (OQ361659, FJ158557, FJ158556 and HQ171694). Finally, the two datasets, including publicly available sequences, consisted of 83 individuals and an alignment length of 531 bp for COI and 61 individuals with an alignment length of 839 bp for ND2 . Species delimitation A total of 14 MOTUs were revealed based on species delimitation methods. For the COI dataset, a consensus of six MOTUs were delimited, with algorithms presenting very similar results: RESL = 6; ASAP = 5; ABGD = 6; PTP = 8; mPTP = 4; bPTP = 8 and GMYC = 6 (Fig. 1a). Discordance was observed when MOTUs included haplotypes assigned to different species (MOTU 1 = A. annulatus and A. blochii; MOTU 6 = A. variegatus and R. annandalei Norman 1926, MOTU 5 = A. zanzibarensis and R. annandalei ) or when a single species was divided into multiple MOTUs ( A. leucopilus = MOTU 3 and MOTU 4; R. annandalei = MOTU 5 and MOTU 6). The primary cause was conflicting species identifications in public databases and in one case, the use of a provisional species name ( Rhinobatos sp. = part of MOTU 4; Fig. 1a; see Online Resource 1 - Table S2 for haplotype assignments). Nevertheless, the molecular data supported the grouping of sequences into single species-level MOTUs, even when those MOTUs included sequences with different published species names. Regarding the ND2 dataset, eight consensus MOTUs were delimited, showing no discordance between MOTUs and species: ASAP = 8; ABGD = 7; PTP = 9; mPTP = 6; bPTP = 9 and GMYC = 9 (Fig. 1b). Thus overall, the estimated number of MOTUs was largely concordant with the number of species and described distribution ranges (Fig. 2). Specimen assignment Applying the BCMA to each dataset with an optimised threshold of 0.4% ( COI ) and 1.1% ( ND2 ) resulted in correct assignment of 100% ( COI ) and 98.4% ( ND2 ) of specimens to their delimited MOTUs (Online Resource 1 - Table S4). One specimen ( A. andysabini , PV812493) in the ND2 dataset was indeterminate due to being the only representative sequence of that species group (Online Resource 1 - Table S4). The reliability of the datasets for specimen assignment was 100%, 100% and 72.2% for COI and 100%, 100% and 93.1% for ND2 using the BP, FZ and FZKMER approaches, respectively (Online Resource 1 - Table S5). Although the probability values differed amongst the methods, a consensus assignment was reached for all analysed specimens, with the methods converging in all but seven cases. The observed discrepancies were due to specimen assignment errors associated exclusively with the FZKMER approach, rather than any particular species group. The FZKMER method may lack the resolution to accurately delineate closely related taxa due to its reliance on kmer-based (as opposed to alignment-based) comparisons, especially in datasets with lower interspecific divergence or limited taxon sampling (Gao et al. 2017; Boddé et al. 2022). Barcode gap Based on the COI dataset, four species groups ( A. blochii , A. variegatus , R. annandalei and Rhinobatos sp.) showed lower minimum NN distances than maximum intraspecific distances when sequences were grouped according to reported species (Fig. 3; Online Resource 1 - Table S6). When grouped according to consensus MOTUs, there was a clear decrease in maximum intraspecific distances (3.58% to 1.32%) and increase in minimum NN distances (0.00% to 2.07%). Thus, all lineages displayed a barcode gap after delimitation. For the ND2 dataset, no species initially lacked a barcode gap as the maximum intraspecific distances (1.55%) were consistently smaller than the minimum NN distances (2.03%). Genetic diversity Final genetic diversity statistics were based on the delimited MOTUs, however, for ND2 , these groups correlated fully with the reported species groups. The newly generated sequences increased the number of haplotypes observed by seven for the COI dataset and 22 for the ND2 dataset (Table 1). Overall, the number of haplotypes and haplotype diversity were higher for ND2 sequences ( H = 29; hd = 0.647; π = 0.002) compared to COI sequences ( H = 18; hd = 0.410; π = 0.002), with nucleotide diversity being similar (Table 1). Populations of A. blochii consistently exhibited the lowest levels of genetic diversity ( COI : H = 3; hd = 0.186; π = 0.000; ND2 : H = 4; hd = 0.455; π = 0.001) despite consisting of more than ten individuals and being sampled from two geographically distant locations namely Namibia and South Africa. Regarding COI , there is a marked difference in statistics when comparing reported species to MOTUs, with the reported grouping showing notably higher values (reported: H = 21; hd = 0.528; π = 0.007; delimited: H = 18; hd = 0.410; π = 0.002). Table 1 . Number of sequences ( N ) and diversity indices for both the cytochrome c oxidase subunit I ( COI ) and nicotinamide adenine dehydrogenase subunit 2 ( ND2 ) datasets for the Acroteriobatus species analysed in this study, based on specimens grouped according to (a) reported species names and (b) MOTUs (molecular operational taxonomic units). For ND2 , MOTUs were the same as the reported species. H = number of haplotypes (number of new species haplotypes discovered in brackets); hd = haplotype diversity; π = nucleotide diversity. Species COI (a) MOTUs COI (b) MOTUs ND2 N H hd π N H hd π N H hd π A. andysabini - - - - MOTU 4 2 1 0 0 MOTU 11 1 1 (1) - - R. annandalei 3 2 0.667 ± 0.315 0.018 ± 0.008 - - - - - - - - - - A. annulatus 27 4 (1) 0.561 ± 0.093 0.013 ± 0.003 MOTU 2 21 3 (1) 0.338 ± 0.122 0.002 ± 0.001 MOTU 7 16 7 (5) 0.8 ± 0.086 0.003 ± 0.001 A. blochii 15 3 (2) 0.256 ± 0.144 0.001 ± 0.0002 MOTU 1 21 3 (2) 0.186 ± 0.112 0.000 MOTU 8 12 4 (3) 0.455 ± 0.166 0.001 ± 0.0006 A. leucopilus 11 3 0.473 ± 0.165 0.008 ± 0.005 MOTU 3 10 2 0.356 ± 0.160 0.002 ± 0.001 MOTU 10 7 6 (6) 0.952 ± 0.095 0.006 ± 0.002 A. omanensis - - - - - - - - - MOTU 9 3 1 0 0 A. salalah - - - - - - - - - MOTU 12 3 1 0 0 A. variegatus 10 4 0.734 ± 0.125 0.004 ±0.001 MOTU 5 12 4 0.652 ± 0.135 0.003 ± 0.001 MOTU 13 4 2 0.5 ± 0.265 0.001 ± 0.0003 A. zanzibarensis 16 4 (4) 0.642 ± 0.078 0.004 ± 0.001 MOTU 6 17 5 (4) 0.684 ± 0.084 0.005 ± 0.001 MOTU 14 15 7 (7) 0.838 ± 0.068 0.003 ± 0.0006 Rhinobatos sp. 1 1 - - - - - - - - - - - - Total/average 83 21 0.528 0.007 83 18 0.410 0.002 61 29 0.647 0.002 No haplotypes were shared between delimited MOTUs (Fig. 4). Both genes displayed similar relationships between species, forming clear species-specific haplogroups. Species with geographically closer distributions generally clustered together e.g., A. annulatus and A. blochii , as well as A. variegatus and A. zanzibarensis . Acroteriobatus leucospilus was positioned between these groups, potentially reflecting a geographic gradient that distinguishes more southern from more northern WIO species. The two major clusters in both networks may also correspond to morphological variation in colouration and spot/stripe patterning. Species exhibiting bluish-grey spots and striped snouts - A. andysabini , A. leucospilus , A. salalah , A. variegatus and A. zanzibarensis - were separated from those characterised by whiter spots and lighter ventral colouration - A. annulatus , A. blochii and A. omanensis . Acroteriobatus variegatus and A. zanzibarensis are also the only two species with orange tones and were most closely related based on interspecific genetic distance. Finally, a greater number of interspecific mutation steps can be noted for the ND2 gene. Discussion The combined use of species delimitation and specimen assignment analyses in a molecular taxonomic approach based on the COI and ND2 mitochondrial genes, mostly coincided with the accepted taxonomic nomenclature and distribution ranges for the genus Acroteriobatus . Although there were slight differences in the number of delimited species recovered by the various methods, this was not unexpected as these approaches are based on distinct theoretical frameworks and algorithmic assumptions (Carstens et al. 2013 ; Kapli et al. 2017 ; Luo et al. 2018 ; Guo and Kong 2022 ). We considered areas of congruence as more robust, and based on the consensus assignments, the number of provisionally distinct congeners investigated was neither artificially inflated nor arbitrarily synonymised, supporting the number of described species. Moreover, by collating all public and newly generated COI and ND2 sequences for Acroteriobatus , we were able to identify possible misidentifications and pinpoint taxonomic issues that require further investigation. On genetic diversity The analyses validated the morphological identifications of newly sequenced specimens of A. andysabini , A. annulatus , A. blochii , A. leucospilus and A. zanzibarensis . This increased the molecular data already available for Acroteriobatus species, illustrated by the addition of new mitochondrial haplotypes. Notably, we generated the first publicly available ND2 sequences for A. andysabini , A. leucospilus and A. zanzibarensis , along with novel COI barcodes for A. zanzibarensis . These results depict otherwise hidden genetic diversity, although not of undocumented or cryptic species, and increases the geographic representation of guitarfishes. For DNA barcoding and similar applications, reference sequences should not only be representative of the taxa but also capture the genetic diversity of their regional populations to avoid false assignments (Mugnai et al. 2023 ). Furthermore, the use of two mitochondrial gene regions resulted in a more informative dataset for the delineation of genetic clusters. In both cases ( COI and ND2 ), all investigated species could be delimited, demonstrated by the interspecific variation exceeding the intraspecific variation for all specimens. The ND2 gene generally exhibits more variation than COI due to a higher mutation rate (Broughton and Reneau 2006 ; Naylor et al. 2012b ), which was also observed in this study. This is suggestive of higher resolution at the ND2 locus, but both haplotype networks still demonstrated similar relationships between species with clustering patterns corresponding to geographical distribution and, more notably, differences in colouration and patterning that corresponds with the species key in Weigmann et al. ( 2021 ). Clear clustering of species was observed based on colour patterns: bluish-grey spotting and striped snouts, whiter spots and lighter colouration, and (on a finer phylogenetic scale) orange pigmentation. Such genetic patterns can inform the identification of distinct morphological traits among delimited species or, in this case, confirm key morphometrics that may aid in-field specimen identification (Weigmann et al. 2021 ). Overall, the diversity estimates are consistent with those reported for other rhinopristiformes (e.g., Tapilatu et al. 2023 ; Groeneveld et al. 2024 ; Kipperman et al. 2024 ), although it may be premature to draw many conclusions without additional species-specific data. In this context, minimal intraspecific genetic variation was detected for A. blochii across samples from both Namibia and South Africa, corroborating the findings of van Staden ( 2023 ). The genetic similarity between Namibian and South African A. blochii is likely due to continuous coastal habitat, lack of major barriers and historical connectivity that enabled gene flow. Since A. blochii is a temperate-water species, the Benguela barrier at the Luderitz upwelling zone is not expected to dramatically limit its dispersal as the southwest African coast has relatively uniform cold-water conditions (unlike the Agulhas-Benguela transition). Nevertheless, the observed low genetic diversity could suggest a recent population bottleneck, potentially driven by environmental fluctuations or fishing pressure (Mirimin et al. 2016 ; Forde et al. 2025 ). While the species is currently assessed as Least Concern (LC) and suspected to have a stable population, no empirical estimates of population size or trends exist (Pollom et al. 2018a ). Therefore, the lack of genetic diversity could be interpreted as a precautionary signal in guitarfish conservation planning. All ND2 sequences within A. omanensis and within A. salalah were genetically identical ( H = 1; hd = 0.000; π = 0.000), which should also be noted even though both species groups comprised only three individuals. The importance and utility of genetic information in fisheries management and conservation policies have been widely acknowledged (Domingues et al. 2018 and references therein). Equally, taxonomic uncertainty can undermine the accuracy and applicability of biodiversity data in these contexts (Guedes et al. 2025 ). This issue is clearly demonstrated in the present study by the marked differences in observed genetic diversity when the same specimens were grouped according to species names versus delimited MOTUs. In such cases, misidentifications resulting from taxonomic uncertainty can lead to inflated and ultimately inapplicable estimates of genetic diversity. The Southern African endemics Previously published records of A. annulatus from Namibia (MT895763, MT895762, MT895761, JN313472, JN313438, JN313421 and HM422916) as well as all newly generated sequences from Namibia (PV814402, PV814403, PV812470, PV812461 and PV812460) were grouped under the same MOTUs as A. blochii . Although both species are regarded as endemic to southern Africa, records of A. annulatus outside South Africa should be interpreted with caution due to frequent misidentification with sympatric species (Ebert et al. 2021 ; Leeney 2023 , 2024 ). The distribution of A. annulatus in Namibia is generally considered to extend southwards from Walvis Bay. However, guitarfishes along this coast are referred to as "lessers" ( A. annulatus ) among fishers, regardless of the species, and it was only following the recent work of Ruth Leeney (Leeney 2023 , 2024 ) that attention was drawn to the fact that these specimens may be more accurately identified as A. blochii (Jörg Walter, pers. comm.). As such, A. annulatus may ultimately prove to be a South African endemic (Ebert et al. 2021 ). Our results support this hypothesis, meaning that A. annulatus is likely more geographically restricted than previously thought. Species with smaller distribution ranges are usually less resilient against environmental and/or anthropogenic pressures across taxa and space due to a limited dispersal capacity (Chichorro et al. 2019 ). Moreover, the lesser guitarfish, representing both A. annulatus and A. blochii in catch statistics, is prevalent in South African fisheries including recreational line fishing, demersal trawl fisheries and bycatch. It accounts for a substantial proportion of elasmobranch catches, ranging between 11–100 tonnes per annum (da Silva et al. 2015 ; DFFE 2023 ). Due to fishing pressure and a potential climate change-driven range shift that might indicate a range contraction, the overall population size of A. annulatus has declined by 30–49% over three past generation lengths (15 years), leading to an updated IUCN status from LC to Vulnerable (VU) in 2019 (Pollom et al. 2019 ; Pollom et al. 2024 ). Yet, these smaller “less charismatic” rhinobatids often remain overlooked in conservation management efforts compared to their larger sister species, despite an increase in attention towards rhino rays as a group (Moore 2017 ; Jabado 2018 ). It is therefore important to discriminate between these two species, because if all records of A. annulatus in Namibia are in fact A. blochii , and A. annulatus only occurs in South Africa, population trend estimates and other key parameters such as catch-per-unit-effort (CPUE) and conservation status may be inaccurate. These two species are reasonably easy to distinguish morphologically based on to the relatively blunt snout and reduced spotting pattern of A. blochii and the number of spiracle folds (one in A. blochii and two in A. annulatus ). Our results clearly delineate between them despite the distribution overlap in the Western Cape Province of South Africa. Here they may partition habitats, with A. annulatus favouring warmer waters influenced by the Agulhas Current, while A. blochii prefers cooler, temperate waters associated with the Benguela Current, leading to interspecific differences. Lastly, A. annulatus has been observed to exhibit regional colour variations within South Africa (Séret et al. 2016 ), which can further complicate in-field identification. Populations found in KwaZulu-Natal present with dark spots and those in the Cape region (Western Cape and Eastern Cape provinces) are characterised by small ocelli, each with a central dark spot surrounded by a dark-edged pale ring (Weigmann et al. 2021 ). Three of the four KwaZulu-Natal specimens included in the COI dataset (JF494379, PV814390 and PV814391) shared a unique haplotype (H3) not found in A. annulatus specimens from the Cape region. Similarly, the only two Natal specimens in the ND2 dataset (PV812457 and PV812458) were assigned a unique haplotype (H25). Still, there was no clear separation between KwaZulu-Natal and Cape sequences in any of the other analyses, which consistently grouped them together. These differences may therefore reflect environmental influences/phenotypic plasticity rather than cryptic diversity or population structure. Lastly, A. ocellatus is described from KwaZulu-Natal to Mozambique in Séret et al. ( 2016 ), but there are only a handful of verified specimens from off the Eastern Cape Province, South Africa, suggesting a restricted and possibly endemic distribution. Here it potentially overlaps with A. annulatus and A. leucospilus . However, A. ocellatus is classified as DD (Pollom et al. 2018c ), thus its distribution and validity as a species need to be clarified (Ebert et al. 2021 ). The East African species The recently described A. andysabini is supposedly endemic to Madagascar (Weigmann et al. 2021 ). This is consistent with our findings, with sequences from Madagascar falling under MOTU 4 ( COI ) and MOTU 10 ( ND2 ). This included the previously published sequence listed as Rhinobatos sp. (HQ171694). The authors employed DNA barcoding and species-specific PCR assays to characterise shark fisheries in northeastern Madagascar, but they were only able to identify this sample to the genus level (Doukakis et al. 2011 ). At the time, it was likely classified as Rhinobatos as the study predated the taxonomic revision, there were insufficient comparable sequences available online and A. andysabini was not yet described. The other COI sequence on BOLD reported as A. leucospilus collected in southeastern Madagascar in 2010 (SAIAD201-11) was also reclassified under MOTU 4. Upon further investigation, this sequence is from the holotype specimen for A. andysabini (SAIAB 97396) as described by Weigmann et al. ( 2021 ); the metadata from the sequence entry corresponds fully with the information in the article. These were the only available sequences for A. andysabini , albeit misnamed. The two documented guitarfish species in Madagascar, A. andysabini and R. austini , account for approximately 75% of elasmobranch landings in some areas and are collectively referred to as “guitarfishes”. This reflects the limited management and lack of species-specific information pertaining to Madagascan fisheries (Humber et al. 2017 ). The distribution of A. leucospilus appears to be more restricted than published literature suggests, extending from South Africa’s east coast to Tanzania (including Zanzibar), while former records of this species from Madagascar (Fricke et al. 2018 ; Ghilardi et al. 2019 ) are now confirmed to be A. andysabini (Ebert et al. 2021 ; Weigmann et al. 2021 ). The Mozambique Channel divides Madagascar from the East African coast, and ocean circulation within the channel is marked by the periodic formation of turbulent eddies. For species with long-lived larvae, this can create a connecting corridor (Ockhuis et al. 2017 ), but for species with no pelagic larval stage, localised connectivity barriers such as strong upwelling cells can contribute to phylogeographic breaks (Lett et al. 2024 ). Since Acroteriobatus species exhibit aplacental viviparity and are primarily coastal, the Channel likely further reinforces the allopatric separation between A. andysabini and A. leucospilus. All sequences of A. leucospilus from Mozambique and South Africa clustered together based on both datasets, supporting the presently described range - although none of the Acroteriobatus samples collected in Tanzania was molecularly identified as A. leucospilus . This Endangered (EN) guitarfish species has likely undergone a population reduction of 50% over the past three generations (Pollom et al. 2018b ), which may even be higher due to the IUCN assessment being undertaken prior to the new species descriptions and updated distribution range of A. leucospilus (Sherman et al. 2023 ). Overall, A. leucospilus was genetically distinct from other geographically proximate congeners with no haplotype sharing, namely A. annulatus and A. zanzibarensis. This can signify parapatric speciation where populations remain in adjacent but slightly different environments with gradual ecological shifts rather than absolute barriers. Acroteriobatus leucospilus seems to have the largest range among the focal species, which could be an indication of ecological flexibility. Both A. variegatus and A. zanzibarensis lack baseline information, which raised questions about the relationship between them (Séret et al. 2016 ; Weigmann et al. 2021 ; Sherman et al. 2023 ). These species have previously been confused due to their comparable snout shape and stripe-nosed colour pattern. However, A. zanzibarensis has a greenish-brown dorsal surface densely covered in large dark brown blotches and may have dark spots ventrally, whereas A. variegatus displays a sandy-brown dorsal surface with a very distinct striped orange snout and typically has no ventral spotting apart from the underside of the snout (Weigmann et al. 2021 ). Our results further confirm the validity of A. zanzibarensis as a distinct species based on molecular data. The delimitation and specimen assignment analyses also support the allopatry of A. zanzibarensis and A. variegatus , with sequences from Tanzania (mainland and Zanzibar) grouping together as the former, along with one sequence reported as A. variegatus from Tanzania (OQ359491), while all sequences from Sri Lanka grouped together as the latter. Regarding previously published sequences listed as Rhinobatos annandalei , one from Tanzania (OQ361659) clustered under the same MOTUs as A. zanzibarensis , while two from India (FJ158557 and FJ158556) clustered with all sequences reported as A. variegatus . Rhinobatos annandalei is not known to occur in Tanzanian waters (Séret et al. 2016 ), and the two sequence entries from India were published before the order reclassification. It is crucial to validate and amend, when applicable, the taxonomic identifications of specimens in public databases because misidentifications can bias data analyses and the interpretations thereof (van Staden et al. 2023 ). Acroteriobatus zanzibarensis has been reported only from off Zanzibar and Kenya (Weigmann et al. 2021 ), while A. variegatus is confined to southern India and Sri Lanka (Séret et al. 2016 ). Both species have extremely limited ranges in the WIO region that lack appropriate management regimes despite intense fishing pressure. Notably, A. variegatus is the most abundant species found in trawl bycatch along the south Indian coast (Bhagyalekshmi and Kumar 2021 ), while A. zanzibarensis is prevalent in elasmobranch catches in southwestern Indian Ocean small-scale fisheries and is considered one of the most vulnerable batoids across and within gear type (Temple et al. 2019 ). The other species that are known to occur in more northern Indian Ocean waters along with A. variegatus , were also classified into distinct MOTUs based on the ND2 dataset (as no COI sequences were available) that match the reported species, namely A. omanensis (MOTU 9) and A. salalah (MOTU 12). Our dataset did not include any sequences of the recently described A. stehmanni . Acroteriobatus stehmanni displays few bluish-grey spots and a faint striped pattern, thus it can be confused with the non-striped species. Nevertheless, it can be distinguished from its only known sympatric congener, A. salalah , by snout and disc shape as well as dorsal colour pattern (Weigmann et al. 2021 ). These species face similar threats, driven by limited knowledge, highly restricted distributions in regions of intense fishing pressure and inadequate management, all of which are exacerbated by taxonomic uncertainty. The name of the game Curated reference libraries that are representative of all target biodiversity are fundamental to molecular taxonomy - to assign unknown to known and compile biodiversity inventories. The main limitations of online sequence databases are insufficient entries that have been taxonomically validated and the presence of sequence records with inconsistent names (Cerutti-Pereyra et al. 2012 ; Hubert and Hanner 2015 ; Delrieu-Trottin et al. 2020 ). These errors also apply to Acroteriobatus sequences, for example, misreporting A. blochii from Namibia as A. annulatus . Moreover, many entries are still listed as Rhinobatos instead of Acroteriobatus . In the era of big biological data (Li and Chen 2014 ), it is important to ensure the veracity of publicly accessible data. This includes continuously updating these resources as new information becomes available, such as when new species are described or revisions are made (e.g., Last et al. 2008 , 2016; Weigmann et al. 2021 ). A re-evaluation of ND2 sequences from a decade-old study in south-eastern Arabia using updated taxonomic frameworks, revealed 28 distinct shark and 28 batoid lineages, many of which had undergone recent revisions (Henderson et al. 2025 ). This highlights the importance of reassessing legacy genetic data as taxonomic knowledge improves. As such, see Table S7 (Online Resource 1) of previously published sequence data that warrants updating based on the analyses of this study. The nomenclatural ambiguity of guitarfishes can further pose obstacles to public engagement and conservation management. These species are often mislabelled, with overlapping colloquial names (some of which even reference sharks) (Moore 2017 ), thus, local names are generally not reliable proxies for fishery monitoring (Doukakis et al. 2011 ). Guitarfishes are also reported under highly aggregate taxonomic categories and commodity codes (Sherman et al. 2023 ). Ideally, all data should be unified into a single platform with a transparent and reproducible pipeline or shared framework. Regarding taxonomic nomenclature, the authoritative Eschmeyer's Catalog of Fishes ( https://www.calacademy.org/scientists/projects/eschmeyers-catalog-of-fishes ) offers an opportunity to overcome these gaps, whereas BOLD ( https://boldsystems.org/ ) can potentially bridge the gap on the molecular side. Towards integrative taxonomy An integrative taxonomic approach incorporating genetic, morphological, ecological and geographical data is ultimately recommended. Such methods, which typically only combine morphological and molecular data, have proven useful for defining species boundaries in elasmobranchs (White et al. 2018 ; Hausdorf and Hennig 2020 ; Petean et al. 2020 ; Crobe et al. 2021 ; Lim et al. 2022 ; Bellodi et al. 2022 ). This is particularly true for smaller elasmobranchs that exhibit limited dispersal potential and contiguous coastal distributions (Lim et al. 2022 ), like guitarfishes. Delimited entities should generally be considered a proxy for species only; however, in this study, three independent lines of evidence broadly converged to support the same number of species-level groups in our dataset: (1) described species classified based on morphology, (2) MOTUs that clustered together based on genetic similarity and (3) geographically structured distribution patterns indicative of sub-regional endemism. Additionally, we found no cases of cryptic or sibling species, only errors pertaining to published entries on sequence repositories. We also contributed to the availability of COI and ND2 sequences for underrepresented guitarfishes. This information can support species-level data collection and reporting, especially when used alongside simple field guides and regional/national species checklists, which are crucial for improving species-specific identification in the field. Actions needed Fisheries managers in Acroteriobatus range states need to consider these results in their management and conservation efforts. Recommendations for research priorities are also indicated. The molecular data (i.e., MOTUs) in this paper align with the ten described species and underscore endemicity at both national and sub-regional levels, introducing another layer to extinction risk. This supports the demarcation of species distributions, which is important for clarifying the extent of each country's conservation responsibility. Considering the possibility that Acroteriobatus species in Namibia may only represent A. blochii , South Africa must manage A. blochii and A. annulatus on the western coast, and A. annulatus and A. leucospilus on the eastern coast. Research should focus on confirming if A. annulatus occurs in Namibia. This should be relatively straightforward when engaging with fishers - for example, during a recreational fishing competition - where obtaining a photograph or even a biological sample would enable accurate species identification. The mechanisms behind the different colour variations of A. annulatus in KwaZulu-Natal and the Cape provinces also need to be resolved. Acroteriobatus leucospilus appears to be the only species occurring in Mozambique. However, the species’ range spans national jurisdictions, including South Africa and potentially Tanzania, therefore it should be considered a shared management unit necessitating coordinated conservation planning. Further work is required to identify in which country the majority of its range lies and to confirm whether A. leucospilus extends north into Tanzania and where its northern boundary lies in Mozambique. There seems to be an oceanographic feature causing a break in northern Mozambique for several coastal elasmobranchs, which can be further investigated. Whether A. zanzibarensis extends south into northern Mozambique needs to be clarified to determine clear geographic boundaries and regions of overlap with other Acroteriobatus species (if any). If this is not the case, bilateral cooperation between Kenya and Tanzania (including Zanzibar) is necessary, ideally embedded within existing frameworks. Acroteriobatus salalah is restricted to Oman, Pakistan and Socotra (part of Yemen) and is therefore a shared management unit. Effective protection requires regional cooperation and cross-border enforcement. Oman also has the responsibility to manage A. omanensis as a national endemic. Madagascar should consider the endemism of A. andysabini and manage this species as a local endemic, although further sampling is needed to confirm whether this is the only Acroteriobatus species here. Madagascar is constrained by limited enforcement and scientific capacity, but community-based management holds promise (Gardner et al. 2020 ). The IUCN Red List provides a robust assessment of extinction risk, thus Not Evaluated (NE) species need to be assessed within this framework namely: A. andysabini and A. stehmanni . Following this, DD species need to be prioritised for research, specifically A. omanensis and A. ocellatus . Declines in these sensitive guitarfish species could be masked by insufficient species-level fisheries data. A precautionary but realistic approach is key (Pollom et al. 2024 ). We recommend that governments prioritise interventions for CR and EN species if not in place yet i.e., A. variegatus in India and Sri Lanka and A. leucospilus in Mozambique, South Africa and possibly Tanzania. The abundance and catch of A. blochii as a LC species in Angola, Namibia and South Africa, and VU ( A. annulatus ) and Near Threatened (NT; A. salalah and A. zanzibarensis ) species should be monitored long-term to sustainably and proactively maintain ecologically functional populations. Declarations Acknowledgements This work was supported by the National Research Foundation of South Africa (MCR240422215314) and partly by the Shark Conservation Fund, a philanthropic collaborative pooling expertise and resources to meet the threats facing the world’s sharks and rays. The Shark Conservation Fund is a project of the Rockefeller Philanthropy Advisors. We acknowledge collaboration with the Ministry of Blue Economy and Fisheries of the Revolutionary Government of mainland Tanzania and Zanzibar. We thank Stellenbosch University Postgraduate Scholarship Programme for supporting MJG. DAE would like to thank the Save Our Seas Foundation for funding support through Keystone Grants 431 and 594, and the South African Institute for Aquatic Biodiversity and California Academy of Sciences for institutional support. We would also like to thank Henri Groeneveld for help with the figures. Competing interests : The authors have no relevant financial or non-financial interests to disclose. Compliance with ethical standards: Ethical clearance was provided by the Research Ethics (Animal Care and Use) committee of Stellenbosch University in the form of an Animal Notification with reference number #ACU-2024-29892. This research complies with IUCN and CITES policy statements. Data availability: The sequence data that support the findings of this study are openly available in NCBI GenBank (https://www.ncbi.nlm.nih.gov/) under accession numbers PV812446-PV812493, PV814376-PV814425 and in BOLD (https://boldsystems.org/) project code: MTACR. Author contributions: Conceptualisation and methodology: MJG, JDK, MvS, RHB and AEB-vdM; project administration and supervision: JDK and AEB-vdM; funding acquisition: JDK, RHB and AEB-vdM; resources: JDK, MvS, RHB, MLD, BQM, RGAW and AEB-vdM; validation: KP; formal analysis, visualisation and writing - original draft: MJG; data curation, investigation and writing - review and editing: MJG, JDK, MvS, MLD, DAE, BQM, KP, RGAW and AEB-vdM. Details of programs used to create figures : Fig1: Evolview and Canva; Fig2: QGIS, Canva and Adobe Illustrator; Fig3: R Studio; Fig4: PopArt, Canva and Adobe Illustrator. References Aitchison R, Ebert D, Séret B, Weigmann S (2024) Review of three southwestern Indian Ocean species of Rhinobatos (Rhinopristiformes: Rhinobatidae). Endanger Species Res 53:67–87. https://doi.org/10.3354/esr01286 Alvarenga M, Solé-Cava AM, Henning F (2021) What’s in a name? Phylogenetic species identification reveals extensive trade of endangered guitarfishes and sharks. 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Geography and Sustainability 4:232–243. https://doi.org/10.1016/j.geosus.2023.05.002 Supplementary Files MoleculartaxonomyofguitarfishesOnlineResource1.xlsx Cite Share Download PDF Status: Published Journal Publication published 26 Jan, 2026 Read the published version in Marine Biodiversity → Version 1 posted Editorial decision: Minor Revisions Needed 12 Oct, 2025 Reviewers agreed at journal 19 Sep, 2025 Reviewers invited by journal 15 Sep, 2025 Editor invited by journal 10 Sep, 2025 Editor assigned by journal 29 Aug, 2025 First submitted to journal 14 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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19:39:14","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":322985,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7379127/v1/b1a3e7f4239334a74649d979.html"},{"id":92028174,"identity":"667bd32a-4609-4267-af45-9ba89cb786af","added_by":"auto","created_at":"2025-09-23 19:39:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":277022,"visible":true,"origin":"","legend":"\u003cp\u003eMaximum likelihood trees of haplotypes for the \u003cem\u003eAcroteriobatus\u003c/em\u003egenus based on (a) the \u003cem\u003ecytochrome c oxidase subunit I\u003c/em\u003e(\u003cem\u003eCOI\u003c/em\u003e) dataset and (b) the\u003cem\u003e nicotinamide adenine dehydrogenase subunit 2\u003c/em\u003e (\u003cem\u003eND2\u003c/em\u003e) dataset, with \u003cem\u003ePseudobatos horkelii\u003c/em\u003e and \u003cem\u003eRhinobatos rhinobatos\u003c/em\u003e as outgroups. Results for the delimitation methods are indicated by black bars and the consensus (CONS) species-level MOTUs (molecular operational taxonomic units) are in colour. RESL = Refined Single Linkage; ASAP = Assemble Species by Automatic Partitioning; ABGD = Automatic Barcode Gap Discovery; mPTP = multi-rate Poisson Tree Processes; bPTP = Bayesian Poisson Tree Processes; GMYC = Generalized Mixed Yule Coalescent.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7379127/v1/151bcb7591eeac3340050495.png"},{"id":92028759,"identity":"bb824d34-e233-40f5-b86c-3ec9f50084bf","added_by":"auto","created_at":"2025-09-23 19:55:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":299030,"visible":true,"origin":"","legend":"\u003cp\u003eApproximate\u003cstrong\u003e \u003c/strong\u003edistribution ranges and sampling locations (circles) of \u003cem\u003eAcroteriobatus\u003c/em\u003e species included in this study, grouped according to species-level MOTUs (molecular operational taxonomic units).\u003cstrong\u003e \u003c/strong\u003eCircles are not proportionate to sample size.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7379127/v1/e8ab89e806c38c24ef2b90bc.png"},{"id":92028459,"identity":"f81d0752-603e-4102-921e-a36dc2e234b9","added_by":"auto","created_at":"2025-09-23 19:47:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":95550,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between the maximum intraspecific and minimum nearest neighbour (NN) genetic distances among species within the genus \u003cem\u003eAcroteriobatus\u003c/em\u003ebased on the (a) the \u003cem\u003ecytochrome c oxidase subunit I\u003c/em\u003e(\u003cem\u003eCOI\u003c/em\u003e) and (b) the\u003cem\u003e nicotinamide adenine dehydrogenase subunit 2\u003c/em\u003e (\u003cem\u003eND2\u003c/em\u003e) datasets. Points above the diagonal indicate the presence of a barcode gap. Black = species; blue = molecular operational taxonomic units.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7379127/v1/fb3c950d7dd178f9d3dca317.png"},{"id":92028175,"identity":"6c486113-1e85-492f-86d9-e28d7c38b620","added_by":"auto","created_at":"2025-09-23 19:39:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":251656,"visible":true,"origin":"","legend":"\u003cp\u003eMedian Joining haplotype network based on \u003cem\u003ecytochrome c oxidase subunit I\u003c/em\u003e (\u003cem\u003eCOI\u003c/em\u003e; a; \u003cem\u003en\u003c/em\u003e = 83) and \u003cem\u003enicotinamide adenine dehydrogenase subunit 2 \u003c/em\u003e(\u003cem\u003eND2\u003c/em\u003e; b; \u003cem\u003en \u003c/em\u003e= 61) sequence data for \u003cem\u003eAcroteriobatus\u003c/em\u003especies: \u003cem\u003eA. andysabini \u003c/em\u003e(Madagascar); \u003cem\u003eA. annulatus \u003c/em\u003e(South Africa); \u003cem\u003eA. blochii \u003c/em\u003e(South Africa and Namibia); \u003cem\u003eA. leucospilus\u003c/em\u003e (South Africa and Mozambique); \u003cem\u003eA. omanensis \u003c/em\u003e(Oman); \u003cem\u003eA. salalah \u003c/em\u003e(Oman); \u003cem\u003eA. variegatus \u003c/em\u003e(India and Sri Lanka) and \u003cem\u003eA. zanzibarensis \u003c/em\u003e(Tanzania, including Zanzibar). Mutations separating haplotypes are indicated as slashes and for mutation steps \u0026gt; 4, the number is also indicated in brackets. Size of each circle is proportional to the number of individuals carrying each haplotype where the largest haplotype (H4) represents 19 sequences.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7379127/v1/74fa1fdb718ebd7751921afa.png"},{"id":101690678,"identity":"0959d386-4f4e-4aa0-9234-5f4c88f4aa16","added_by":"auto","created_at":"2026-02-02 16:07:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2088897,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7379127/v1/95586a60-39c4-430d-abaf-c6af12b54d68.pdf"},{"id":92028180,"identity":"36ac4914-c324-4264-bc10-f38cdcc3ab44","added_by":"auto","created_at":"2025-09-23 19:39:14","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":438083,"visible":true,"origin":"","legend":"","description":"","filename":"MoleculartaxonomyofguitarfishesOnlineResource1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7379127/v1/450f584155a6eb177e02f7f1.xlsx"}],"financialInterests":"","formattedTitle":"Molecular taxonomy of guitarfishes (Rhinobatidae: Acroteriobatus)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe growing emphasis on species boundaries in conservation and management reflects an increasing recognition of the critical role that species interactions and ecological relationships play in shaping biodiversity and ecosystem function (Le Bagousse-Pinguet et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR150\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Species boundaries however remain a controversial topic in evolutionary biology, while several key principles are widely acknowledged. For instance, phenotypic traits, genes and genomic regions that remain distinct despite hybridisation and introgression show that these boundaries are semipermeable (Harrison and Larson \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Distinct species can converge on similar morphologies, while cryptic species may remain morphologically indistinguishable and display significant genetic divergence (Mayr \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Knowlton \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Palumbi and Lessios \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Ferrari et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Thus, the degree of morphological difference cannot be the only species criterion. Elasmobranchs (sharks and batoids) demonstrate notable endemism and species richness (Stein et al. \u003cspan citationid=\"CR126\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), yet accurate and unambiguous species identification has proven particularly challenging due to the low intrinsic variation and conserved nature of their ecological and external traits (Ball et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Cariani et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Bache-Jeffreys et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Traditional morphology-based identification methods may fail to detect cryptic, hybrid or rare species (Cerutti-Pereyra et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), discern specimens at different ontogenetic stages (Steinke et al. \u003cspan citationid=\"CR127\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) or address cases of phenotypic plasticity (Compagno et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Human \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; S\u0026eacute;ret et al. \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Molecular systematics has recently been integrated with traditional methods to more effectively assess phylogenetic relationships between elasmobranch taxa (Palumbi and Lessios \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Cariani et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ferrari et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), shedding light on cryptic and sibling species (Bickford et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Vilasboa et al. \u003cspan citationid=\"CR136\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Melis et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and the role of biogeographical barriers in speciation (Sandoval-Castillo et al. \u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Hirschfeld et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGuitarfishes from the family Rhinobatidae remain understudied. These batoids\u0026rsquo; conserved morphology and vague original descriptions necessitate molecular scrutiny to address taxonomic challenges (Last et al. 2016; Jabado \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Weigmann et al. \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; van Staden et al. \u003cspan citationid=\"CR133\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Aitchison et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Earlier studies have found recurrent polyphyletic topologies within Rhinobatidae based on mitochondrial and nuclear data (Aschliman et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Naylor et al. \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2012a\u003c/span\u003e, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This is supported by morphometric analyses and, to a large extent, the biogeography of the genus-level taxa, which necessitated a taxonomic revision of the group (Naylor et al. \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2012a\u003c/span\u003e). This led to the establishment of the new order Rhinopristiformes (i.e., rhino rays or shark-like rays) and three Rhinobatid genera (\u003cem\u003eAcroteriobatus\u003c/em\u003e, \u003cem\u003eRhinobatos\u003c/em\u003e and \u003cem\u003ePseudobatos\u003c/em\u003e), which was formally revised by Last et al. (2016) and substantiated by subsequent studies (van Staden et al. \u003cspan citationid=\"CR133\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Groeneveld et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR137\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Aitchison et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These smaller rhinobatids are also increasingly being targeted and retained for their fins and flesh. This growing economic significance (Seidu et al. \u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) is primarily due to the overexploitation of species from the larger-bodied sister families of this order such as wedgefishes from the family Rhinidae (Moore \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Daly et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Pytka et al. \u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). All rhino rays were also included in Appendix II of the Convention on International Trade in Endangered Species of Fauna and Flora (CITES \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), but enforcement of this listing and the management measures that are already in place remains challenging in the absence of species-level data.\u003c/p\u003e\u003cp\u003eGuitarfishes are typically found in temperate to tropical coastal regions, which are often characterised by low levels of food security in local communities, substantial fishing pressure (artisanal and industrial) and limited capacity to manage catches (Pytka et al. \u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Kyne et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Such hotspots of overlap between the distribution of these species and fishing pressure should be considered priorities for management (Kyne et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). It is now understood that \u003cem\u003eAcroteriobatus\u003c/em\u003e species are predominantly confined to the Western Indian Ocean (WIO), except for two species occurring in the Southeast Atlantic, while \u003cem\u003ePseudobatos\u003c/em\u003e species are restricted to the amphi-American region (encompassing both the Atlantic and Pacific coasts of the Americas) and \u003cem\u003eRhinobatos\u003c/em\u003e species occur mostly in the Indo-Western Pacific and Eastern Atlantic (Weigmann et al. \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e and references therein). The three genera can be differentiated molecularly and morphologically, where oronasal morphology currently appears to hold the greatest potential as a diagnostic trait (Last et al. 2016) - but not to the species level. Currently, \u003cem\u003eAcroteriobatus\u003c/em\u003e comprises 10 described species, with the International Union for Conservation of Nature\u0026rsquo;s (IUCN \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) Red List assessments ranging from Data Deficient (DD) to Critically Endangered (CR) while some species have not been evaluated (NE; Kyne et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Online Resource 1 - Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Weigmann et al. (\u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) recently provided a key for distinguishing between \u003cem\u003eAcroteriobatus\u003c/em\u003e species based on snout shape, disc form and spot or stripe colour patterns, which will prove useful for identification. Species exhibiting elongated bluish-grey spots on the dorsal surface of the snout typically display a stripe-nosed pattern, whereas those lacking this pattern have a plain light to white ventral surface without a dark blotch (Weigmann et al. \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe WIO is classified as a biodiversity hotspot (Tittensor et al. \u003cspan citationid=\"CR132\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Worm and Branch \u003cspan citationid=\"CR143\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and encompasses many Important Shark and Ray Areas (ISRAs, ISRA region 7), spanning from KwaZulu-Natal in South Africa, along East Africa, to the Red Sea, Persian Gulf, Arabian Sea, western India and the Maldives archipelago (Jabado et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). A re-evaluation of the greyspotted guitarfish \u003cem\u003eA. leucospilus\u003c/em\u003e (Norman \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e1926\u003c/span\u003e) species complex led to the description of two new bluespotted guitarfishes: Socotra guitarfish \u003cem\u003eA. stehmanni\u003c/em\u003e and Malagasy guitarfish \u003cem\u003eA. andysabini\u003c/em\u003e Weigmann, Ebert \u0026amp; S\u0026eacute;ret \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e. Only \u003cem\u003eA. salalah\u003c/em\u003e (Randall \u0026amp; Compagno, \u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e1995\u003c/span\u003e), recently confirmed in the Socotra Islands, is known to co-occur with \u003cem\u003eA. stehmanni\u003c/em\u003e within its range (Bogorodsky et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). \u003cem\u003eAcroteriobatus leucospilus\u003c/em\u003e is now thought to occur from the Eastern Cape, South Africa, to at least Tanzania, extending its previously reported range beyond Mozambique and South Africa (Compagno et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; S\u0026eacute;ret et al. \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Weigmann et al. \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) but not in Madagascar (Ebert et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The current distribution of the lesser guitarfish \u003cem\u003eA. annulatus\u003c/em\u003e (M\u0026uuml;ller \u0026amp; Henle \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e1841\u003c/span\u003e) is recognised as extending from Namibia to KwaZulu-Natal, but recent assessments may indicate its absence in Namibia (Leeney \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and Ebert et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) lists the distribution as Langebaan (Western Cape) to the Transkei coast (Eastern Cape) and potentially central KwaZulu-Natal. This distribution is poorly defined as \u003cem\u003eA. annulatus\u003c/em\u003e has often been misidentified with other South African guitarfish species including the bluntnose guitarfish \u003cem\u003eA. blochii\u003c/em\u003e (M\u0026uuml;ller \u0026amp; Henle \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e1841\u003c/span\u003e), \u003cem\u003eA. leucospilus\u003c/em\u003e and the DD speckled guitarfish \u003cem\u003eA. ocellatus\u003c/em\u003e (Norman \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e1926\u003c/span\u003e) (Ebert et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Limited information is available on \u003cem\u003eA. ocellatus\u003c/em\u003e, and the distribution map from S\u0026eacute;ret et al. (\u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) is inaccurate as the only verified specimens are from Algoa Bay (Ebert et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Although both are currently considered valid species based on molecular data (Yang et al., unpubl.), uncertainties persist regarding the poorly known \u003cem\u003eA. zanzibarensis\u003c/em\u003e (Norman \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e1926\u003c/span\u003e) and the CR stripenose guitarfish \u003cem\u003eA. variegatus\u003c/em\u003e (Nair \u0026amp; Lal Mohan \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e1973\u003c/span\u003e) (Weigmann et al. \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The four species that are known from the northern Indian Ocean - \u003cem\u003eA. variegatus\u003c/em\u003e, \u003cem\u003eA. stehmanni\u003c/em\u003e, \u003cem\u003eA. salalah\u003c/em\u003e and the Oman guitarfish \u003cem\u003eA. omanensis\u003c/em\u003e Last, Henderson \u0026amp; Naylor 2016 - all exhibit narrow distribution ranges (S\u0026eacute;ret et al. \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Weigmann et al. \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccurate specimen identification at the finest possible taxonomic resolution is required for robust conservation management, as poorly defined biological and geographical species boundaries lead to unreliable species-specific data (e.g., Dayrat \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Porcu et al. \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Johri et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Bellodi et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Consequently, true species diversity is under- or overestimated, impeding the assessment of population status, trends (Kyne et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and the impact of fisheries on species (Melis et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Enforcement of protective regulations requires an unambiguous definition of a species that accounts for all natural variation. This issue is exemplified in the mislabelling of commercial landings in markets (Igl\u0026eacute;sias et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Alvarenga et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and in catch monitoring, which is frequently reported at highly aggregated taxonomic levels (Sherman et al. \u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Pytka et al. \u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), masking overfishing and local extinctions. Furthermore, resolving taxonomic uncertainties would provide a stronger foundation for future research on all aspects of rhino ray biology (Dayrat \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Kyne et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA molecular taxonomic approach that implements both species delimitation and specimen assignment methods has the potential to flag undocumented species and/or misidentified specimens. Delimitation analyses are increasingly utilised to determine the number of species-level entities or cohesive genealogical lineages within a dataset (Dayrat \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Dellicour and Flot \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) by clustering orthologous sequences into molecular operational taxonomic units (MOTUs). These probabilistic models offer insights into intra- and interspecific relationships without needing \u003cem\u003ea priori\u003c/em\u003e species boundaries or standardised distance thresholds (Ramirez et al. \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Specimen assignment methods are employed to match a query sequence from an unidentified specimen to a known species (Zhang et al. \u003cspan citationid=\"CR147\" class=\"CitationRef\"\u003e2012b\u003c/span\u003e). Such approaches have proven effective in managing and validating DNA reference libraries in cases of taxonomic uncertainties (Carugati et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Bellodi et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; van Staden et al. \u003cspan citationid=\"CR135\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), which can result in published sequences from misidentified specimens (Benson et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Carde\u0026ntilde;osa et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sherman et al. \u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Although barcode \u003cem\u003ecytochrome c oxidase subunit I\u003c/em\u003e (\u003cem\u003eCOI\u003c/em\u003e) sequences are the norm in molecular taxonomy (Hubert and Hanner \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), elasmobranchs are known for their slow evolutionary rates (Hara et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Hence, it is recommended that at least one faster-evolving DNA region be analysed in combination with \u003cem\u003eCOI\u003c/em\u003e, such as \u003cem\u003enicotinamide adenine dehydrogenase subunit 2\u003c/em\u003e (\u003cem\u003eND2\u003c/em\u003e) (Naylor et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2012b\u003c/span\u003e; Henderson et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Petean et al. \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). If intraspecific genetic variation overlaps with interspecific variation, delimiting specimens based solely on molecular data becomes challenging. Therefore, the presence of a barcode gap - a distinct difference between the intra- and interspecific distances - is crucial for reliably defining species boundaries using genetic thresholds.\u003c/p\u003e\u003cp\u003eConsidering the taxonomic challenges associated with this marine group and the scarcity of species-specific data, the aim of this study was twofold: (1) to identify MOTUs in the \u003cem\u003eAcroteriobatus\u003c/em\u003e genus by analysing sampled species as well as online-available sequence data using molecular taxonomic techniques based on the \u003cem\u003eCOI\u003c/em\u003e and \u003cem\u003eND2\u003c/em\u003e genes, and (2) to review and contribute to the availability of \u003cem\u003eCOI\u003c/em\u003e and \u003cem\u003eND2\u003c/em\u003e sequences for guitarfishes. These findings can serve as molecular pieces to the taxonomic puzzle of the threatened \u003cem\u003eAcroteriobatus\u003c/em\u003e genus.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSamples and laboratory procedures\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSamples were obtained from 54 guitarfish specimens (\u003cem\u003eAcroteriobatus\u003c/em\u003e spp.) representing five species assigned using external morphology and colour patterns following S\u0026eacute;ret et al. (2016): \u003cem\u003eA. andysabini\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e = 1), \u003cem\u003eA. annulatus\u0026nbsp;\u003c/em\u003e(\u003cem\u003en\u003c/em\u003e = 16), \u003cem\u003eA. blochii\u0026nbsp;\u003c/em\u003e(\u003cem\u003en\u003c/em\u003e = 14), \u003cem\u003eA. leucospilus\u0026nbsp;\u003c/em\u003e(\u003cem\u003en\u003c/em\u003e = 7) and \u003cem\u003eA. zanzibarensis\u0026nbsp;\u003c/em\u003e(\u003cem\u003en\u0026nbsp;\u003c/em\u003e= 16) (Online Resource 1 - Table S2).\u0026nbsp;Specimens were caught using rod and line fishing gear, collected during research trawl surveys, or sampled at fish landing sites or markets. For each individual, muscle tissue or fin clips were sampled and preserved in 90% ethanol at room temperature.\u003c/p\u003e\n\u003cp\u003eTotal genomic DNA was extracted using a standard cetyltrimethylammonium bromide extraction (CTAB) protocol (Sambrook and Russell 2001). The purity and quantity were assessed using a NanoDrop\u0026trade; ND 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Polymerase chain reactions (PCRs) were carried out in a SimpliAmp\u0026trade; Thermal Cycler in a 15-\u0026mu;l reaction volume. The \u003cem\u003eCOI\u003c/em\u003e gene region was PCR-amplified using combinations of FishF1/FishF2/FishF2_t1 (forward) and FishR1/FishR2/FR1d_t1 (reverse) as well as the \u003cem\u003eCOI\u003c/em\u003e-3 primer cocktail (Ward et al. 2005; Ivanova et al. 2007), but predominantly FishF2/FishR2. The ILEM_SeqF/ASNM_SeqR primer pair was used for \u003cem\u003eND2\u003c/em\u003e (Fernando et al. 2019); see Online Resource 1 - Table S3 for primer details. For \u003cem\u003eCOI\u003c/em\u003e, the reaction mixture included 50 ng of template DNA, 1 X PCR buffer, 200 \u0026mu;M of each dNTP, 0.3 \u0026micro;M of forward and reverse primers, 2.5 mM of MgCl\u003csub\u003e2\u003c/sub\u003e and 0.625 U of GoTaq\u0026reg; DNA polymerase (Promega, Madison, WI, USA). The thermocycling conditions comprised an initial denaturing step at 94 \u0026deg;C for 5 min, followed by 35 cycles of 94 \u0026deg;C for 30 s, 54 \u0026deg;C for 30 s, 72 \u0026deg;C for 90 s and a final extension step at 72 \u0026deg;C for 10 min. When the \u003cem\u003eCOI\u003c/em\u003e-3 primer cocktail was used, the protocol followed Ivanova et al. (2007). \u0026nbsp;For \u003cem\u003eND2\u003c/em\u003e, the reaction mixture consisted of 50 ng template DNA, 1 X PCR buffer, 200 \u0026mu;M of each dNTP, 0.33 \u0026micro;M of forward and reverse primers, 2 mM of MgCl\u003csub\u003e2\u003c/sub\u003e and 0.5 U of GoTaq\u0026reg;. The thermocycling conditions were: 94 \u0026deg;C for 2 min, followed by 30 cycles of 94 \u0026deg;C for 30 s, 60 \u0026deg;C for 30 s, 72 \u0026deg;C for 90 s and a final extension step at 72 \u0026deg;C for 15 min. The PCR amplicons were evaluated through electrophoresis on 1.5% agarose gels.\u003c/p\u003e\n\u003cp\u003eThe amplicons were sequenced with the appropriate forward primer, including M13 (Messing 1983) when tailed primers were used, using standard Sanger sequencing chemistry (BigDye\u0026reg; Terminator v.3.1 Cycle Sequencing Kit, Life Technologies, South Africa), whereafter capillary electrophoresis was performed at the Central Analytical Facility of Stellenbosch University, South Africa.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGenetic data analyses\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePreviously published sequences of \u003cem\u003eCOI\u003c/em\u003e and \u003cem\u003eND2\u003c/em\u003e attributed to the species listed in Online Resource 1 - Table S2 were retrieved from GenBank\u0026reg; (Benson et al. 2012) as well as the Barcode of Life Data Systems (BOLD) (Ratnasingham and Hebert 2007), and integrated with our sequences to build a comprehensive dataset for guitarfishes. Additionally, the Basic Local Alignment Search Tool (BLAST; https://blast.ncbi.nlm.nih.gov/Blast.cgi; accessed on 15 January 2025) was used to identify congeneric species records with \u0026gt;95% similarity. Sequences were manually curated, aligned using the MAFFT v7.450 (Katoh and Standley 2013) algorithm as implemented in Geneious Prime\u0026reg; v2024.0.5 (Kearse et al. 2012) and trimmed to ensure equal length. The correct amino acid translation was verified to exclude nuclear mitochondrial pseudogenes (Song et al. 2008)\u003cem\u003e\u0026nbsp;\u003c/em\u003eand sequences shorter than the trimmed alignment lengths were excluded from downstream analyses. All analyses were carried out on two separate datasets i.e., one dataset per gene (\u003cem\u003eCOI\u003c/em\u003e and \u003cem\u003eND2\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSpecies delimitation\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSpecies defined based on morphology are termed species, whereas those identified using DNA sequence data are termed MOTUs (Moritz 1994). The following single-locus delimitation methods were used to infer the number of MOTUs present within each dataset: (1) Refined Single Linkage (RESL) as implemented on BOLD (Ratnasingham and Hebert 2013), (2) Assemble Species by Automatic Partitioning (ASAP) (Puillandre et al. 2021), (3) Automatic Barcode Gap Discovery (ABGD) (Puillandre et al. 2012), (4) the multi-rate Poisson Tree Processes (mPTP) (Kapli et al. 2017), (5) the Bayesian Poisson Tree Processes (bPTP) (Zhang et al. 2013) and (6) the Generalized Mixed Yule Coalescent (GMYC) approach (Fujisawa and Barraclough 2013). MOTUs were regarded \u0026ldquo;concordant\u0026rdquo; if comprising sequences from the same species, and \u0026ldquo;discordant\u0026rdquo; if comprising sequences from different species. To address conflicting results from different methods, we defined consensus MOTUs based on the majority agreement among methods. DNA sequence alignments were used for the distance-based delimitation methods (RESL, ASAP and ABGD). The RESL method was only applied to the \u003cem\u003eCOI\u003c/em\u003e data as it is based on Barcode Index Numbers (BINs) as implemented in BOLD (Ratnasingham and Hebert 2013). The ASAP (https://bioinfo.mnhn.fr/abi/public/asap/asapweb.html; accessed on 20 February 2025) and ABGD (https://bioinfo.mnhn.fr/abi/public/abgd/abgdweb.html; accessed on 20 February 2025) methods were implemented on the respective web applications with default settings under the uncorrected pairwise distance model and a relative gap width (X) of 1.0 for ABGD.\u003c/p\u003e\n\u003cp\u003eFor the tree-based delimitation methods, sequences were collapsed into haplotypes utilising the R packages \u003cem\u003eape\u003c/em\u003e v5.6-2 (Paradis and Schliep 2019) and \u003cem\u003epegas\u003c/em\u003e v1.3 (Paradis 2010) for R v4.1.3 (R Development Core Team, 2015; all scripts available on request), with \u003cem\u003eRhinobatos rhinobatos\u003c/em\u003e (Linnaeus 1758) and \u003cem\u003ePseudobatos horkelii\u0026nbsp;\u003c/em\u003e(M\u0026uuml;ller \u0026amp; Henle 1841) selected as outgroups (JQ518913, KF564313 and PQ014263 - whole mitogenome record). A maximum likelihood (ML) analysis was conducted using the PhyML v.3.0 web server (http://www.atgc-montpellier.fr/phyml/; accessed on 21 February 2025) (Guindon et al. 2010), employing default settings and automatic selection for the best substitution model as determined by the Akaike Information Criterion (AIC) using the Smart Model Selection program (SMS) (Lefort et al. 2017) integrated into PhyML (\u003cem\u003eCOI\u003c/em\u003e = GTR+I and \u003cem\u003eND2\u003c/em\u003e = TN93+G+I). The bPTP (https://species.h-its.org/ptp/; accessed on 21 February 2025) and mPTP (https://mptp.h-its.org/#/tree; accessed on 21 February 2025) methods were performed based on the obtained ML trees. For the GMYC approach, BEAST v2.7.7 (Drummond et al. 2012; Suchard et al. 2018) was used to obtain an ultrametric tree wherein tips (i.e., the taxa) are equidistant from the root (Michonneau 2016). The input file was prepared in BEAUTi, with substitution models set according to those identified by SMS, a strict molecular clock, a Yule speciation model (Yule 1925) and a Markov Chain Monte Carlo (MCMC) length of 10 000 000 generations. After two independent runs in BEAST, LogCombiner v2.7.7 was used to merge the runs whereafter log files were analysed with Tracer v.1.7.2 (Rambaut et al. 2018) to evaluate the robustness of the results. TreeAnnotator v2.7.6 was used to summarise the Bayesian trees sampled from the posterior distribution with a 10% burn-in and subsequently, the consensus tree was visualised with The Interactive Tree Of Life (iTOL) v5 (Letunic and Bork 2021). GMYC was run in R using the \u003cem\u003esplits\u003c/em\u003e v1.0-20 package (Ezard et al. 2009) with the credible ultrametric tree. Finally, MOTU designations from the various algorithms along with the consensus MOTUs, were visualised using Evolview v.3 (Subramanian et al. 2019).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSpecimen assignment\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFour complementary algorithms were used to evaluate the accuracy of specimen assignments in the delimited datasets i.e., specimens grouped according to consensus MOTUs. First, (1) the distance-based approach \u0026ldquo;best close match analysis\u0026rdquo; (BCMA) (Meier et al. 2006) from the R package \u003cem\u003espider\u003c/em\u003e v1.5.0 (Brown et al. 2012) was applied, utilising the \u003cem\u003ethreshOpt()\u0026nbsp;\u003c/em\u003efunction to determine the optimal threshold values for both datasets (Meyer and Paulay 2005). Thereafter, the following methods from the R package BarcodingR v1.0.3 (Zhang et al. 2017) were employed: (2) the back-propagation neural networks method (BP) (Zhang et al. 2008), operating under a machine learning-based framework, (3) the fuzzy-set based approach (FZ) (Zhang et al. 2012b) that uses many-valued logic to assign a degree of membership, and (4) the kmer-based approach (FZKMER) (Zhang et al. 2012a) that classifies specimens independently of sequence alignments. These three methods require a reference dataset, thus the R package \u003cem\u003edplyr\u003c/em\u003e v1.0.10 (Wickham et al. 2022) was used to randomly select one representative for each MOTU and extract the corresponding sequences from the original alignment data. Consensus assignments were designated when a minimum of two methods converged between BP, FZ and FZKMER.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eDistribution of genetic variation\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIntra- and interspecific genetic distances were calculated using the \u003cem\u003ep\u003c/em\u003e-distance model\u0026nbsp;(Nei and Kumar 2000)\u0026nbsp;with the pairwise deletion option for the treatment of gaps and missing data, employing the \u003cem\u003edist.dna\u003c/em\u003e function from \u003cem\u003eape\u003c/em\u003e. The simple \u003cem\u003ep\u003c/em\u003e-distance model was chosen as it is more suitable for short, closely related sequences (Nei and Kumar 2000), and outperforms the Kimura 2-parameter and Jukes-Cantor models in such cases\u0026nbsp;(Srivathsan and Meier 2012; Collins et al. 2012).\u0026nbsp;The presence of a barcode gap (interspecific diversity \u0026gt; intraspecific diversity) was assessed by plotting the maximum intraspecific \u003cem\u003ep\u003c/em\u003e-distance against the nearest neighbour (NN; the closest congeneric) distance for each individual in both datasets using the R package \u003cem\u003eggplot2\u003c/em\u003e v3.4.0 (Wickham 2016). The R packages \u003cem\u003eape\u003c/em\u003e and \u003cem\u003epegas\u003c/em\u003e were used to estimate the principal diversity indices for mitochondrial DNA (the number of haplotypes [\u003cem\u003eH\u003c/em\u003e], haplotype diversity [\u003cem\u003ehd\u003c/em\u003e], nucleotide diversity [\u003cem\u003e\u0026pi;\u003c/em\u003e] and relative standard deviations [SD]). To compare the patterns of genetic variation between species and consensus MOTUs, the above-mentioned approach was repeated using the delimited datasets. Lastly, median-joining inference networks were constructed to visualise the evolutionary relationships between MOTU-haplotypes, as implemented in PopART (Leigh and Bryant 2015).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 50 \u003cem\u003eCOI\u003c/em\u003e and 48 \u003cem\u003eND2\u003c/em\u003e sequences were generated for five species from the genus \u003cem\u003eAcroteriobatus\u003c/em\u003e and uploaded to the \u0026ldquo;Guitarfish delineation (\u003cem\u003eAcroteriobatus\u003c/em\u003e)\u0026rdquo; project (project code: MTACR), accessible on BOLD (Online Resource 1 - Table S2). The BLAST search for congeneric species with \u0026gt;95% similarity resulted in the inclusion of four \u003cem\u003eCOI\u003c/em\u003e records from the genus \u003cem\u003eRhinobatos\u0026nbsp;\u003c/em\u003e(OQ361659, FJ158557, FJ158556 and HQ171694). Finally, the two datasets, including publicly available sequences, consisted of 83 individuals and an alignment length of 531 bp for \u003cem\u003eCOI\u003c/em\u003e and 61 individuals with an alignment length of 839 bp for \u003cem\u003eND2\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSpecies delimitation\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 14 MOTUs were revealed based on species delimitation methods. For the \u003cem\u003eCOI\u003c/em\u003e dataset, a consensus of six MOTUs were delimited, with algorithms presenting very similar results: RESL = 6; ASAP = 5; ABGD = 6; PTP = 8; mPTP = 4; bPTP = 8 and GMYC = 6 (Fig. 1a). Discordance was observed when MOTUs included haplotypes assigned to different species (MOTU 1 = \u003cem\u003eA. annulatus\u003c/em\u003e and \u003cem\u003eA. blochii;\u0026nbsp;\u003c/em\u003eMOTU 6 =\u003cem\u003e\u0026nbsp;A. variegatus\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;R. annandalei\u0026nbsp;\u003c/em\u003eNorman 1926, MOTU 5\u003cem\u003e\u0026nbsp;\u003c/em\u003e=\u003cem\u003e\u0026nbsp;A. zanzibarensis\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;R. annandalei\u003c/em\u003e) or when a single species was divided into multiple MOTUs (\u003cem\u003eA. leucopilus\u0026nbsp;\u003c/em\u003e= MOTU 3 and MOTU 4; \u003cem\u003eR. annandalei\u003c/em\u003e = MOTU 5 and MOTU 6). The primary cause was conflicting species identifications in public databases and in one case, the use of a provisional species name (\u003cem\u003eRhinobatos\u003c/em\u003e sp. = part of MOTU 4; Fig. 1a; see Online Resource 1 - Table S2 for haplotype assignments). Nevertheless, the molecular data supported the grouping of sequences into single species-level MOTUs, even when those MOTUs included sequences with different published species names.\u003c/p\u003e\n\u003cp\u003eRegarding the \u003cem\u003eND2\u003c/em\u003e dataset, eight consensus MOTUs were delimited, showing no discordance between MOTUs and species: ASAP = 8; ABGD = 7; PTP = 9; mPTP = 6; bPTP = 9 and GMYC = 9 (Fig. 1b). Thus overall, the estimated number of MOTUs was largely concordant with the number of species and described distribution ranges (Fig. 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSpecimen assignment\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApplying the BCMA to each dataset with an optimised threshold of 0.4% (\u003cem\u003eCOI\u003c/em\u003e) and 1.1% (\u003cem\u003eND2\u003c/em\u003e) resulted in correct assignment of 100% (\u003cem\u003eCOI\u003c/em\u003e) and 98.4% (\u003cem\u003eND2\u003c/em\u003e) of specimens to their delimited MOTUs (Online Resource 1 - Table S4). One specimen (\u003cem\u003eA. andysabini\u003c/em\u003e, PV812493) in the \u003cem\u003eND2\u003c/em\u003e dataset was indeterminate due to being the only representative sequence of that species group (Online Resource 1 - Table S4). The reliability of the datasets for specimen assignment was 100%, 100% and 72.2% for \u003cem\u003eCOI\u0026nbsp;\u003c/em\u003eand 100%, 100% and 93.1% for \u003cem\u003eND2\u003c/em\u003e using the BP, FZ and FZKMER approaches, respectively (Online Resource 1 - Table S5). Although the probability values differed amongst the methods, a consensus assignment was reached for all analysed specimens, with the methods converging in all but seven cases. The observed discrepancies were due to specimen assignment errors associated exclusively with the FZKMER approach, rather than any particular species group. The FZKMER method may lack the resolution to accurately delineate closely related taxa due to its reliance on kmer-based (as opposed to alignment-based) comparisons, especially in datasets with lower interspecific divergence or limited taxon sampling (Gao et al. 2017; Bodd\u0026eacute; et al. 2022).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBarcode gap\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the \u003cem\u003eCOI\u003c/em\u003e dataset, four species groups (\u003cem\u003eA. blochii\u003c/em\u003e, \u003cem\u003eA. variegatus\u003c/em\u003e, \u003cem\u003eR. annandalei\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;Rhinobatos\u0026nbsp;\u003c/em\u003esp.) showed lower minimum NN distances than maximum intraspecific distances when sequences were grouped according to reported species (Fig. 3; Online Resource 1 - Table S6). When grouped according to consensus MOTUs, there was a clear decrease in maximum intraspecific distances (3.58% to 1.32%) and increase in minimum NN distances (0.00% to 2.07%). Thus, all lineages displayed a barcode gap after delimitation. For the \u003cem\u003eND2\u0026nbsp;\u003c/em\u003edataset, no species initially lacked a barcode gap as the maximum intraspecific distances (1.55%) were consistently smaller than the minimum NN distances (2.03%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGenetic diversity\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFinal genetic diversity statistics were based on the delimited MOTUs, however, for \u003cem\u003eND2\u003c/em\u003e, these groups correlated fully with the reported species groups. The newly generated sequences increased the number of haplotypes observed by seven for the \u003cem\u003eCOI\u003c/em\u003e dataset and 22 for the \u003cem\u003eND2\u003c/em\u003e dataset (Table 1). Overall, the number of haplotypes and haplotype diversity were higher for \u003cem\u003eND2\u003c/em\u003e sequences (\u003cem\u003eH\u003c/em\u003e = 29; \u003cem\u003ehd\u003c/em\u003e = 0.647; \u003cem\u003e\u0026pi;\u003c/em\u003e = 0.002) compared to \u003cem\u003eCOI\u003c/em\u003e sequences (\u003cem\u003eH\u003c/em\u003e = 18; \u003cem\u003ehd\u003c/em\u003e = 0.410; \u003cem\u003e\u0026pi;\u003c/em\u003e = 0.002), with nucleotide diversity being similar (Table 1). Populations of \u003cem\u003eA. blochii\u003c/em\u003e consistently exhibited the lowest levels of genetic diversity (\u003cem\u003eCOI\u003c/em\u003e: \u003cem\u003eH\u003c/em\u003e = 3; \u003cem\u003ehd\u003c/em\u003e = 0.186; \u003cem\u003e\u0026pi;\u003c/em\u003e = 0.000; \u003cem\u003eND2\u003c/em\u003e: \u003cem\u003eH\u003c/em\u003e = 4; \u003cem\u003ehd\u003c/em\u003e = 0.455; \u003cem\u003e\u0026pi;\u003c/em\u003e = 0.001) despite consisting of more than ten individuals and being sampled from two geographically distant locations namely Namibia and South Africa. Regarding \u003cem\u003eCOI\u003c/em\u003e, there is a marked difference in statistics when comparing reported species to MOTUs, with the reported grouping showing notably higher values (reported: \u003cem\u003eH\u003c/em\u003e = 21; \u003cem\u003ehd\u003c/em\u003e = 0.528; \u003cem\u003e\u0026pi;\u003c/em\u003e = 0.007; delimited: \u003cem\u003eH\u003c/em\u003e = 18; \u003cem\u003ehd\u003c/em\u003e = 0.410; \u003cem\u003e\u0026pi;\u003c/em\u003e = 0.002).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e. Number of sequences (\u003cem\u003eN\u003c/em\u003e) and diversity indices for both the \u003cem\u003ecytochrome c oxidase subunit I\u003c/em\u003e (\u003cem\u003eCOI\u003c/em\u003e) and \u003cem\u003enicotinamide adenine dehydrogenase subunit 2\u003c/em\u003e (\u003cem\u003eND2\u003c/em\u003e) datasets for the \u003cem\u003eAcroteriobatus\u003c/em\u003e species analysed in this study, based on specimens grouped according to (a) reported species names and (b) MOTUs (molecular operational taxonomic units). For \u003cem\u003eND2\u003c/em\u003e, MOTUs were the same as the reported species. \u003cem\u003eH\u003c/em\u003e = number of haplotypes (number of new species haplotypes discovered in brackets); \u003cem\u003ehd\u003c/em\u003e = haplotype diversity; \u003cem\u003e\u0026pi;\u003c/em\u003e = nucleotide diversity.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCOI\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e(a)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eMOTUs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCOI\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e(b)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eMOTUs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eND2\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eN\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eH\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ehd\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026pi;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eN\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eH\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ehd\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026pi;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eN\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eH\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ehd\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026pi;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eA. andysabini\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMOTU 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMOTU 11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eR. annandalei\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.667 \u0026plusmn; 0.315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.018 \u0026plusmn; 0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eA. annulatus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.561 \u0026plusmn; 0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.013 \u0026plusmn; 0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMOTU 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.338 \u0026plusmn; 0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.002 \u0026plusmn; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMOTU 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.8 \u0026plusmn; 0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.003 \u0026plusmn; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eA. blochii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.256 \u0026plusmn; 0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001 \u0026plusmn; 0.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMOTU 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.186 \u0026plusmn; 0.112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMOTU 8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.455 \u0026plusmn; 0.166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001 \u0026plusmn; 0.0006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eA. leucopilus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.473 \u0026plusmn; 0.165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.008 \u0026plusmn; 0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMOTU 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.356 \u0026plusmn; 0.160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.002 \u0026plusmn; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMOTU 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.952 \u0026plusmn; 0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.006 \u0026plusmn; 0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eA. omanensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMOTU 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eA. salalah\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMOTU 12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eA. variegatus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.734 \u0026plusmn; 0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.004 \u0026plusmn;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMOTU 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.652 \u0026plusmn; 0.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.003 \u0026plusmn; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMOTU 13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5 \u0026plusmn; 0.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001 \u0026plusmn; 0.0003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eA. zanzibarensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.642 \u0026plusmn; 0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.004 \u0026plusmn; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMOTU 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.684 \u0026plusmn; 0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.005 \u0026plusmn; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMOTU 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.838 \u0026plusmn; 0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.003 \u0026plusmn; 0.0006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eRhinobatos sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTotal/average\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.410\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNo haplotypes were shared between delimited MOTUs (Fig. 4). Both genes displayed similar relationships between species, forming clear species-specific haplogroups. Species with geographically closer distributions generally clustered together e.g., \u003cem\u003eA. annulatus\u003c/em\u003e and \u003cem\u003eA. blochii\u003c/em\u003e, as well as \u003cem\u003eA. variegatus\u003c/em\u003e and \u003cem\u003eA. zanzibarensis\u003c/em\u003e. \u003cem\u003eAcroteriobatus leucospilus\u003c/em\u003e was positioned between these groups, potentially reflecting a geographic gradient that distinguishes more southern from more northern WIO species. The two major clusters in both networks may also correspond to morphological variation in colouration and spot/stripe patterning. Species exhibiting bluish-grey spots and striped snouts - \u003cem\u003eA. andysabini\u003c/em\u003e, \u003cem\u003eA. leucospilus\u003c/em\u003e, \u003cem\u003eA. salalah\u003c/em\u003e, \u003cem\u003eA. variegatus\u003c/em\u003e and \u003cem\u003eA. zanzibarensis\u003c/em\u003e - were separated from those characterised by whiter spots and lighter ventral colouration - \u003cem\u003eA. annulatus\u003c/em\u003e, \u003cem\u003eA. blochii\u003c/em\u003e and \u003cem\u003eA. omanensis\u003c/em\u003e. \u003cem\u003eAcroteriobatus variegatus\u003c/em\u003e and \u003cem\u003eA. zanzibarensis\u003c/em\u003e are also the only two species with orange tones and were most closely related based on interspecific genetic distance. Finally, a greater number of interspecific mutation steps can be noted for the \u003cem\u003eND2\u003c/em\u003e gene.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe combined use of species delimitation and specimen assignment analyses in a molecular taxonomic approach based on the \u003cem\u003eCOI\u003c/em\u003e and \u003cem\u003eND2\u003c/em\u003e mitochondrial genes, mostly coincided with the accepted taxonomic nomenclature and distribution ranges for the genus \u003cem\u003eAcroteriobatus\u003c/em\u003e. Although there were slight differences in the number of delimited species recovered by the various methods, this was not unexpected as these approaches are based on distinct theoretical frameworks and algorithmic assumptions (Carstens et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Kapli et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Luo et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Guo and Kong \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). We considered areas of congruence as more robust, and based on the consensus assignments, the number of provisionally distinct congeners investigated was neither artificially inflated nor arbitrarily synonymised, supporting the number of described species. Moreover, by collating all public and newly generated \u003cem\u003eCOI\u003c/em\u003e and \u003cem\u003eND2\u003c/em\u003e sequences for \u003cem\u003eAcroteriobatus\u003c/em\u003e, we were able to identify possible misidentifications and pinpoint taxonomic issues that require further investigation.\u003c/p\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eOn genetic diversity\u003c/h2\u003e\u003cp\u003eThe analyses validated the morphological identifications of newly sequenced specimens of \u003cem\u003eA. andysabini\u003c/em\u003e, \u003cem\u003eA. annulatus\u003c/em\u003e, \u003cem\u003eA. blochii\u003c/em\u003e, \u003cem\u003eA. leucospilus\u003c/em\u003e and \u003cem\u003eA. zanzibarensis\u003c/em\u003e. This increased the molecular data already available for \u003cem\u003eAcroteriobatus\u003c/em\u003e species, illustrated by the addition of new mitochondrial haplotypes. Notably, we generated the first publicly available \u003cem\u003eND2\u003c/em\u003e sequences for \u003cem\u003eA. andysabini\u003c/em\u003e, \u003cem\u003eA. leucospilus\u003c/em\u003e and \u003cem\u003eA. zanzibarensis\u003c/em\u003e, along with novel \u003cem\u003eCOI\u003c/em\u003e barcodes for \u003cem\u003eA. zanzibarensis\u003c/em\u003e. These results depict otherwise hidden genetic diversity, although not of undocumented or cryptic species, and increases the geographic representation of guitarfishes. For DNA barcoding and similar applications, reference sequences should not only be representative of the taxa but also capture the genetic diversity of their regional populations to avoid false assignments (Mugnai et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, the use of two mitochondrial gene regions resulted in a more informative dataset for the delineation of genetic clusters. In both cases (\u003cem\u003eCOI\u003c/em\u003e and \u003cem\u003eND2\u003c/em\u003e), all investigated species could be delimited, demonstrated by the interspecific variation exceeding the intraspecific variation for all specimens. The \u003cem\u003eND2\u003c/em\u003e gene generally exhibits more variation than \u003cem\u003eCOI\u003c/em\u003e due to a higher mutation rate (Broughton and Reneau \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Naylor et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2012b\u003c/span\u003e), which was also observed in this study. This is suggestive of higher resolution at the \u003cem\u003eND2\u003c/em\u003e locus, but both haplotype networks still demonstrated similar relationships between species with clustering patterns corresponding to geographical distribution and, more notably, differences in colouration and patterning that corresponds with the species key in Weigmann et al. (\u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Clear clustering of species was observed based on colour patterns: bluish-grey spotting and striped snouts, whiter spots and lighter colouration, and (on a finer phylogenetic scale) orange pigmentation. Such genetic patterns can inform the identification of distinct morphological traits among delimited species or, in this case, confirm key morphometrics that may aid in-field specimen identification (Weigmann et al. \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOverall, the diversity estimates are consistent with those reported for other rhinopristiformes (e.g., Tapilatu et al. \u003cspan citationid=\"CR130\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Groeneveld et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Kipperman et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), although it may be premature to draw many conclusions without additional species-specific data. In this context, minimal intraspecific genetic variation was detected for \u003cem\u003eA. blochii\u003c/em\u003e across samples from both Namibia and South Africa, corroborating the findings of van Staden (\u003cspan citationid=\"CR134\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The genetic similarity between Namibian and South African \u003cem\u003eA. blochii\u003c/em\u003e is likely due to continuous coastal habitat, lack of major barriers and historical connectivity that enabled gene flow. Since \u003cem\u003eA. blochii\u003c/em\u003e is a temperate-water species, the Benguela barrier at the Luderitz upwelling zone is not expected to dramatically limit its dispersal as the southwest African coast has relatively uniform cold-water conditions (unlike the Agulhas-Benguela transition). Nevertheless, the observed low genetic diversity could suggest a recent population bottleneck, potentially driven by environmental fluctuations or fishing pressure (Mirimin et al. \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Forde et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). While the species is currently assessed as Least Concern (LC) and suspected to have a stable population, no empirical estimates of population size or trends exist (Pollom et al. \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e). Therefore, the lack of genetic diversity could be interpreted as a precautionary signal in guitarfish conservation planning. All \u003cem\u003eND2\u003c/em\u003e sequences within \u003cem\u003eA. omanensis\u003c/em\u003e and within \u003cem\u003eA. salalah\u003c/em\u003e were genetically identical (\u003cem\u003eH\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1; \u003cem\u003ehd\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.000; \u003cem\u003eπ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.000), which should also be noted even though both species groups comprised only three individuals. The importance and utility of genetic information in fisheries management and conservation policies have been widely acknowledged (Domingues et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e and references therein). Equally, taxonomic uncertainty can undermine the accuracy and applicability of biodiversity data in these contexts (Guedes et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This issue is clearly demonstrated in the present study by the marked differences in observed genetic diversity when the same specimens were grouped according to species names versus delimited MOTUs. In such cases, misidentifications resulting from taxonomic uncertainty can lead to inflated and ultimately inapplicable estimates of genetic diversity.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eThe Southern African endemics\u003c/h2\u003e\u003cp\u003ePreviously published records of \u003cem\u003eA. annulatus\u003c/em\u003e from Namibia (MT895763, MT895762, MT895761, JN313472, JN313438, JN313421 and HM422916) as well as all newly generated sequences from Namibia (PV814402, PV814403, PV812470, PV812461 and PV812460) were grouped under the same MOTUs as \u003cem\u003eA. blochii\u003c/em\u003e. Although both species are regarded as endemic to southern Africa, records of \u003cem\u003eA. annulatus\u003c/em\u003e outside South Africa should be interpreted with caution due to frequent misidentification with sympatric species (Ebert et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Leeney \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The distribution of \u003cem\u003eA. annulatus\u003c/em\u003e in Namibia is generally considered to extend southwards from Walvis Bay. However, guitarfishes along this coast are referred to as \"lessers\" (\u003cem\u003eA. annulatus\u003c/em\u003e) among fishers, regardless of the species, and it was only following the recent work of Ruth Leeney (Leeney \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) that attention was drawn to the fact that these specimens may be more accurately identified as \u003cem\u003eA. blochii\u003c/em\u003e (J\u0026ouml;rg Walter, pers. comm.). As such, \u003cem\u003eA. annulatus\u003c/em\u003e may ultimately prove to be a South African endemic (Ebert et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Our results support this hypothesis, meaning that \u003cem\u003eA. annulatus\u003c/em\u003e is likely more geographically restricted than previously thought. Species with smaller distribution ranges are usually less resilient against environmental and/or anthropogenic pressures across taxa and space due to a limited dispersal capacity (Chichorro et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Moreover, the lesser guitarfish, representing both \u003cem\u003eA. annulatus\u003c/em\u003e and \u003cem\u003eA. blochii\u003c/em\u003e in catch statistics, is prevalent in South African fisheries including recreational line fishing, demersal trawl fisheries and bycatch. It accounts for a substantial proportion of elasmobranch catches, ranging between 11\u0026ndash;100 tonnes per annum (da Silva et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; DFFE \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Due to fishing pressure and a potential climate change-driven range shift that might indicate a range contraction, the overall population size of \u003cem\u003eA. annulatus\u003c/em\u003e has declined by 30\u0026ndash;49% over three past generation lengths (15 years), leading to an updated IUCN status from LC to Vulnerable (VU) in 2019 (Pollom et al. \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Pollom et al. \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Yet, these smaller \u0026ldquo;less charismatic\u0026rdquo; rhinobatids often remain overlooked in conservation management efforts compared to their larger sister species, despite an increase in attention towards rhino rays as a group (Moore \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Jabado \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). It is therefore important to discriminate between these two species, because if all records of \u003cem\u003eA. annulatus\u003c/em\u003e in Namibia are in fact \u003cem\u003eA. blochii\u003c/em\u003e, and \u003cem\u003eA. annulatus\u003c/em\u003e only occurs in South Africa, population trend estimates and other key parameters such as catch-per-unit-effort (CPUE) and conservation status may be inaccurate.\u003c/p\u003e\u003cp\u003eThese two species are reasonably easy to distinguish morphologically based on to the relatively blunt snout and reduced spotting pattern of \u003cem\u003eA. blochii\u003c/em\u003e and the number of spiracle folds (one in \u003cem\u003eA. blochii\u003c/em\u003e and two in \u003cem\u003eA. annulatus\u003c/em\u003e). Our results clearly delineate between them despite the distribution overlap in the Western Cape Province of South Africa. Here they may partition habitats, with \u003cem\u003eA. annulatus\u003c/em\u003e favouring warmer waters influenced by the Agulhas Current, while \u003cem\u003eA. blochii\u003c/em\u003e prefers cooler, temperate waters associated with the Benguela Current, leading to interspecific differences. Lastly, \u003cem\u003eA. annulatus\u003c/em\u003e has been observed to exhibit regional colour variations within South Africa (S\u0026eacute;ret et al. \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), which can further complicate in-field identification. Populations found in KwaZulu-Natal present with dark spots and those in the Cape region (Western Cape and Eastern Cape provinces) are characterised by small ocelli, each with a central dark spot surrounded by a dark-edged pale ring (Weigmann et al. \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Three of the four KwaZulu-Natal specimens included in the \u003cem\u003eCOI\u003c/em\u003e dataset (JF494379, PV814390 and PV814391) shared a unique haplotype (H3) not found in \u003cem\u003eA. annulatus\u003c/em\u003e specimens from the Cape region. Similarly, the only two Natal specimens in the \u003cem\u003eND2\u003c/em\u003e dataset (PV812457 and PV812458) were assigned a unique haplotype (H25). Still, there was no clear separation between KwaZulu-Natal and Cape sequences in any of the other analyses, which consistently grouped them together. These differences may therefore reflect environmental influences/phenotypic plasticity rather than cryptic diversity or population structure.\u003c/p\u003e\u003cp\u003eLastly, \u003cem\u003eA. ocellatus\u003c/em\u003e is described from KwaZulu-Natal to Mozambique in S\u0026eacute;ret et al. (\u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), but there are only a handful of verified specimens from off the Eastern Cape Province, South Africa, suggesting a restricted and possibly endemic distribution. Here it potentially overlaps with \u003cem\u003eA. annulatus\u003c/em\u003e and \u003cem\u003eA. leucospilus\u003c/em\u003e. However, \u003cem\u003eA. ocellatus\u003c/em\u003e is classified as DD (Pollom et al. \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e2018c\u003c/span\u003e), thus its distribution and validity as a species need to be clarified (Ebert et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eThe East African species\u003c/h2\u003e\u003cp\u003eThe recently described \u003cem\u003eA. andysabini\u003c/em\u003e is supposedly endemic to Madagascar (Weigmann et al. \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This is consistent with our findings, with sequences from Madagascar falling under MOTU 4 (\u003cem\u003eCOI\u003c/em\u003e) and MOTU 10 (\u003cem\u003eND2\u003c/em\u003e). This included the previously published sequence listed as \u003cem\u003eRhinobatos\u003c/em\u003e sp. (HQ171694). The authors employed DNA barcoding and species-specific PCR assays to characterise shark fisheries in northeastern Madagascar, but they were only able to identify this sample to the genus level (Doukakis et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). At the time, it was likely classified as \u003cem\u003eRhinobatos\u003c/em\u003e as the study predated the taxonomic revision, there were insufficient comparable sequences available online and \u003cem\u003eA. andysabini\u003c/em\u003e was not yet described. The other \u003cem\u003eCOI\u003c/em\u003e sequence on BOLD reported as \u003cem\u003eA. leucospilus\u003c/em\u003e collected in southeastern Madagascar in 2010 (SAIAD201-11) was also reclassified under MOTU 4. Upon further investigation, this sequence is from the holotype specimen for \u003cem\u003eA. andysabini\u003c/em\u003e (SAIAB 97396) as described by Weigmann et al. (\u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); the metadata from the sequence entry corresponds fully with the information in the article. These were the only available sequences for \u003cem\u003eA. andysabini\u003c/em\u003e, albeit misnamed. The two documented guitarfish species in Madagascar, \u003cem\u003eA. andysabini\u003c/em\u003e and \u003cem\u003eR. austini\u003c/em\u003e, account for approximately 75% of elasmobranch landings in some areas and are collectively referred to as \u0026ldquo;guitarfishes\u0026rdquo;. This reflects the limited management and lack of species-specific information pertaining to Madagascan fisheries (Humber et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe distribution of \u003cem\u003eA. leucospilus\u003c/em\u003e appears to be more restricted than published literature suggests, extending from South Africa\u0026rsquo;s east coast to Tanzania (including Zanzibar), while former records of this species from Madagascar (Fricke et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ghilardi et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) are now confirmed to be \u003cem\u003eA. andysabini\u003c/em\u003e (Ebert et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Weigmann et al. \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The Mozambique Channel divides Madagascar from the East African coast, and ocean circulation within the channel is marked by the periodic formation of turbulent eddies. For species with long-lived larvae, this can create a connecting corridor (Ockhuis et al. \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), but for species with no pelagic larval stage, localised connectivity barriers such as strong upwelling cells can contribute to phylogeographic breaks (Lett et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Since \u003cem\u003eAcroteriobatus\u003c/em\u003e species exhibit aplacental viviparity and are primarily coastal, the Channel likely further reinforces the allopatric separation between \u003cem\u003eA. andysabini\u003c/em\u003e and \u003cem\u003eA. leucospilus.\u003c/em\u003e All sequences of \u003cem\u003eA. leucospilus\u003c/em\u003e from Mozambique and South Africa clustered together based on both datasets, supporting the presently described range - although none of the \u003cem\u003eAcroteriobatus\u003c/em\u003e samples collected in Tanzania was molecularly identified as \u003cem\u003eA. leucospilus\u003c/em\u003e. This Endangered (EN) guitarfish species has likely undergone a population reduction of 50% over the past three generations (Pollom et al. \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e), which may even be higher due to the IUCN assessment being undertaken prior to the new species descriptions and updated distribution range of \u003cem\u003eA. leucospilus\u003c/em\u003e (Sherman et al. \u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Overall, \u003cem\u003eA. leucospilus\u003c/em\u003e was genetically distinct from other geographically proximate congeners with no haplotype sharing, namely \u003cem\u003eA. annulatus\u003c/em\u003e and \u003cem\u003eA. zanzibarensis.\u003c/em\u003e This can signify parapatric speciation where populations remain in adjacent but slightly different environments with gradual ecological shifts rather than absolute barriers. \u003cem\u003eAcroteriobatus leucospilus\u003c/em\u003e seems to have the largest range among the focal species, which could be an indication of ecological flexibility.\u003c/p\u003e\u003cp\u003eBoth \u003cem\u003eA. variegatus\u003c/em\u003e and \u003cem\u003eA. zanzibarensis\u003c/em\u003e lack baseline information, which raised questions about the relationship between them (S\u0026eacute;ret et al. \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Weigmann et al. \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sherman et al. \u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These species have previously been confused due to their comparable snout shape and stripe-nosed colour pattern. However, \u003cem\u003eA. zanzibarensis\u003c/em\u003e has a greenish-brown dorsal surface densely covered in large dark brown blotches and may have dark spots ventrally, whereas \u003cem\u003eA. variegatus\u003c/em\u003e displays a sandy-brown dorsal surface with a very distinct striped orange snout and typically has no ventral spotting apart from the underside of the snout (Weigmann et al. \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Our results further confirm the validity of \u003cem\u003eA. zanzibarensis\u003c/em\u003e as a distinct species based on molecular data. The delimitation and specimen assignment analyses also support the allopatry of \u003cem\u003eA. zanzibarensis\u003c/em\u003e and \u003cem\u003eA. variegatus\u003c/em\u003e, with sequences from Tanzania (mainland and Zanzibar) grouping together as the former, along with one sequence reported as \u003cem\u003eA. variegatus\u003c/em\u003e from Tanzania (OQ359491), while all sequences from Sri Lanka grouped together as the latter. Regarding previously published sequences listed as \u003cem\u003eRhinobatos annandalei\u003c/em\u003e, one from Tanzania (OQ361659) clustered under the same MOTUs as \u003cem\u003eA. zanzibarensis\u003c/em\u003e, while two from India (FJ158557 and FJ158556) clustered with all sequences reported as \u003cem\u003eA. variegatus\u003c/em\u003e. \u003cem\u003eRhinobatos annandalei\u003c/em\u003e is not known to occur in Tanzanian waters (S\u0026eacute;ret et al. \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), and the two sequence entries from India were published before the order reclassification. It is crucial to validate and amend, when applicable, the taxonomic identifications of specimens in public databases because misidentifications can bias data analyses and the interpretations thereof (van Staden et al. \u003cspan citationid=\"CR135\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). \u003cem\u003eAcroteriobatus zanzibarensis\u003c/em\u003e has been reported only from off Zanzibar and Kenya (Weigmann et al. \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), while \u003cem\u003eA. variegatus\u003c/em\u003e is confined to southern India and Sri Lanka (S\u0026eacute;ret et al. \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Both species have extremely limited ranges in the WIO region that lack appropriate management regimes despite intense fishing pressure. Notably, \u003cem\u003eA. variegatus\u003c/em\u003e is the most abundant species found in trawl bycatch along the south Indian coast (Bhagyalekshmi and Kumar \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), while \u003cem\u003eA. zanzibarensis\u003c/em\u003e is prevalent in elasmobranch catches in southwestern Indian Ocean small-scale fisheries and is considered one of the most vulnerable batoids across and within gear type (Temple et al. \u003cspan citationid=\"CR131\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe other species that are known to occur in more northern Indian Ocean waters along with \u003cem\u003eA. variegatus\u003c/em\u003e, were also classified into distinct MOTUs based on the \u003cem\u003eND2\u003c/em\u003e dataset (as no \u003cem\u003eCOI\u003c/em\u003e sequences were available) that match the reported species, namely \u003cem\u003eA. omanensis\u003c/em\u003e (MOTU 9) and \u003cem\u003eA. salalah\u003c/em\u003e (MOTU 12). Our dataset did not include any sequences of the recently described \u003cem\u003eA. stehmanni\u003c/em\u003e. \u003cem\u003eAcroteriobatus stehmanni\u003c/em\u003e displays few bluish-grey spots and a faint striped pattern, thus it can be confused with the non-striped species. Nevertheless, it can be distinguished from its only known sympatric congener, \u003cem\u003eA. salalah\u003c/em\u003e, by snout and disc shape as well as dorsal colour pattern (Weigmann et al. \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These species face similar threats, driven by limited knowledge, highly restricted distributions in regions of intense fishing pressure and inadequate management, all of which are exacerbated by taxonomic uncertainty.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eThe name of the game\u003c/h2\u003e\u003cp\u003eCurated reference libraries that are representative of all target biodiversity are fundamental to molecular taxonomy - to assign unknown to known and compile biodiversity inventories. The main limitations of online sequence databases are insufficient entries that have been taxonomically validated and the presence of sequence records with inconsistent names (Cerutti-Pereyra et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Hubert and Hanner \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Delrieu-Trottin et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These errors also apply to \u003cem\u003eAcroteriobatus\u003c/em\u003e sequences, for example, misreporting \u003cem\u003eA. blochii\u003c/em\u003e from Namibia as \u003cem\u003eA. annulatus\u003c/em\u003e. Moreover, many entries are still listed as \u003cem\u003eRhinobatos\u003c/em\u003e instead of \u003cem\u003eAcroteriobatus\u003c/em\u003e. In the era of big biological data (Li and Chen \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), it is important to ensure the veracity of publicly accessible data. This includes continuously updating these resources as new information becomes available, such as when new species are described or revisions are made (e.g., Last et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2008\u003c/span\u003e, 2016; Weigmann et al. \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). A re-evaluation of \u003cem\u003eND2\u003c/em\u003e sequences from a decade-old study in south-eastern Arabia using updated taxonomic frameworks, revealed 28 distinct shark and 28 batoid lineages, many of which had undergone recent revisions (Henderson et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This highlights the importance of reassessing legacy genetic data as taxonomic knowledge improves. As such, see Table S7 (Online Resource 1) of previously published sequence data that warrants updating based on the analyses of this study.\u003c/p\u003e\u003cp\u003eThe nomenclatural ambiguity of guitarfishes can further pose obstacles to public engagement and conservation management. These species are often mislabelled, with overlapping colloquial names (some of which even reference sharks) (Moore \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), thus, local names are generally not reliable proxies for fishery monitoring (Doukakis et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Guitarfishes are also reported under highly aggregate taxonomic categories and commodity codes (Sherman et al. \u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Ideally, all data should be unified into a single platform with a transparent and reproducible pipeline or shared framework. Regarding taxonomic nomenclature, the authoritative Eschmeyer's Catalog of Fishes (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.calacademy.org/scientists/projects/eschmeyers-catalog-of-fishes\u003c/span\u003e\u003cspan address=\"https://www.calacademy.org/scientists/projects/eschmeyers-catalog-of-fishes\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) offers an opportunity to overcome these gaps, whereas BOLD (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://boldsystems.org/\u003c/span\u003e\u003cspan address=\"https://boldsystems.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) can potentially bridge the gap on the molecular side.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eTowards integrative taxonomy\u003c/h2\u003e\u003cp\u003eAn integrative taxonomic approach incorporating genetic, morphological, ecological and geographical data is ultimately recommended. Such methods, which typically only combine morphological and molecular data, have proven useful for defining species boundaries in elasmobranchs (White et al. \u003cspan citationid=\"CR140\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Hausdorf and Hennig \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Petean et al. \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Crobe et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Lim et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Bellodi et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This is particularly true for smaller elasmobranchs that exhibit limited dispersal potential and contiguous coastal distributions (Lim et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), like guitarfishes. Delimited entities should generally be considered a proxy for species only; however, in this study, three independent lines of evidence broadly converged to support the same number of species-level groups in our dataset: (1) described species classified based on morphology, (2) MOTUs that clustered together based on genetic similarity and (3) geographically structured distribution patterns indicative of sub-regional endemism. Additionally, we found no cases of cryptic or sibling species, only errors pertaining to published entries on sequence repositories. We also contributed to the availability of \u003cem\u003eCOI\u003c/em\u003e and \u003cem\u003eND2\u003c/em\u003e sequences for underrepresented guitarfishes. This information can support species-level data collection and reporting, especially when used alongside simple field guides and regional/national species checklists, which are crucial for improving species-specific identification in the field.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eActions needed\u003c/h2\u003e\u003cp\u003eFisheries managers in \u003cem\u003eAcroteriobatus\u003c/em\u003e range states need to consider these results in their management and conservation efforts. Recommendations for research priorities are also indicated. The molecular data (i.e., MOTUs) in this paper align with the ten described species and underscore endemicity at both national and sub-regional levels, introducing another layer to extinction risk. This supports the demarcation of species distributions, which is important for clarifying the extent of each country's conservation responsibility.\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eConsidering the possibility that \u003cem\u003eAcroteriobatus\u003c/em\u003e species in Namibia may only represent \u003cem\u003eA. blochii\u003c/em\u003e, South Africa must manage \u003cem\u003eA. blochii\u003c/em\u003e and \u003cem\u003eA. annulatus\u003c/em\u003e on the western coast, and \u003cem\u003eA. annulatus\u003c/em\u003e and \u003cem\u003eA. leucospilus\u003c/em\u003e on the eastern coast. Research should focus on confirming if \u003cem\u003eA. annulatus\u003c/em\u003e occurs in Namibia. This should be relatively straightforward when engaging with fishers - for example, during a recreational fishing competition - where obtaining a photograph or even a biological sample would enable accurate species identification. The mechanisms behind the different colour variations of \u003cem\u003eA. annulatus\u003c/em\u003e in KwaZulu-Natal and the Cape provinces also need to be resolved.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cem\u003eAcroteriobatus leucospilus\u003c/em\u003e appears to be the only species occurring in Mozambique. However, the species\u0026rsquo; range spans national jurisdictions, including South Africa and potentially Tanzania, therefore it should be considered a shared management unit necessitating coordinated conservation planning. Further work is required to identify in which country the majority of its range lies and to confirm whether \u003cem\u003eA. leucospilus\u003c/em\u003e extends north into Tanzania and where its northern boundary lies in Mozambique. There seems to be an oceanographic feature causing a break in northern Mozambique for several coastal elasmobranchs, which can be further investigated.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eWhether \u003cem\u003eA. zanzibarensis\u003c/em\u003e extends south into northern Mozambique needs to be clarified to determine clear geographic boundaries and regions of overlap with other \u003cem\u003eAcroteriobatus\u003c/em\u003e species (if any). If this is not the case, bilateral cooperation between Kenya and Tanzania (including Zanzibar) is necessary, ideally embedded within existing frameworks.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cem\u003eAcroteriobatus salalah\u003c/em\u003e is restricted to Oman, Pakistan and Socotra (part of Yemen) and is therefore a shared management unit. Effective protection requires regional cooperation and cross-border enforcement. Oman also has the responsibility to manage \u003cem\u003eA. omanensis\u003c/em\u003e as a national endemic.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eMadagascar should consider the endemism of \u003cem\u003eA. andysabini\u003c/em\u003e and manage this species as a local endemic, although further sampling is needed to confirm whether this is the only \u003cem\u003eAcroteriobatus\u003c/em\u003e species here. Madagascar is constrained by limited enforcement and scientific capacity, but community-based management holds promise (Gardner et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eThe IUCN Red List provides a robust assessment of extinction risk, thus Not Evaluated (NE) species need to be assessed within this framework namely: \u003cem\u003eA. andysabini\u003c/em\u003e and \u003cem\u003eA. stehmanni\u003c/em\u003e. Following this, DD species need to be prioritised for research, specifically \u003cem\u003eA. omanensis\u003c/em\u003e and \u003cem\u003eA. ocellatus\u003c/em\u003e. Declines in these sensitive guitarfish species could be masked by insufficient species-level fisheries data.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eA precautionary but realistic approach is key (Pollom et al. \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). We recommend that governments prioritise interventions for CR and EN species if not in place yet i.e., \u003cem\u003eA. variegatus\u003c/em\u003e in India and Sri Lanka and \u003cem\u003eA. leucospilus\u003c/em\u003e in Mozambique, South Africa and possibly Tanzania. The abundance and catch of \u003cem\u003eA. blochii\u003c/em\u003e as a LC species in Angola, Namibia and South Africa, and VU (\u003cem\u003eA. annulatus\u003c/em\u003e) and Near Threatened (NT; \u003cem\u003eA. salalah\u003c/em\u003e and \u003cem\u003eA. zanzibarensis\u003c/em\u003e) species should be monitored long-term to sustainably and proactively maintain ecologically functional populations.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Research Foundation of South Africa (MCR240422215314) and partly by the Shark Conservation Fund, a philanthropic collaborative pooling expertise and resources to meet the threats facing the world\u0026rsquo;s sharks and rays. The Shark Conservation Fund is a project of the Rockefeller Philanthropy Advisors. We acknowledge collaboration with the Ministry of Blue Economy and Fisheries of the Revolutionary Government of mainland Tanzania and Zanzibar. We thank Stellenbosch University Postgraduate Scholarship Programme for supporting MJG. DAE would like to thank the Save Our Seas Foundation for funding support through Keystone Grants 431 and 594, and the South African Institute for Aquatic Biodiversity and California Academy of Sciences for institutional support. We would also like to thank Henri Groeneveld for help with the figures.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e:\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eCompliance with ethical standards:\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eEthical clearance was provided by the Research Ethics (Animal Care and Use) committee of Stellenbosch University in the form of an Animal Notification with reference number #ACU-2024-29892. This research complies with IUCN and CITES policy statements.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eData availability:\u003c/strong\u003e\u003c/em\u003e The sequence data that support the findings of this study are openly available in NCBI GenBank (https://www.ncbi.nlm.nih.gov/) under accession numbers PV812446-PV812493, PV814376-PV814425 and in BOLD (https://boldsystems.org/) project code: MTACR.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e\u0026nbsp;\u003c/em\u003eConceptualisation and methodology: MJG, JDK, MvS, RHB and AEB-vdM; project administration and supervision: JDK and AEB-vdM; funding acquisition: JDK, RHB and AEB-vdM; resources: JDK, MvS, RHB, MLD, BQM, RGAW and AEB-vdM; validation: KP; formal analysis, visualisation and writing - original draft: MJG; data curation, investigation and writing - review and editing: MJG, JDK, MvS, MLD, DAE, BQM, KP, RGAW and AEB-vdM.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eDetails of programs used to create figures\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e: \u003c/strong\u003eFig1: Evolview and Canva; Fig2: QGIS, Canva and Adobe Illustrator; Fig3: R Studio; Fig4: PopArt, Canva and Adobe Illustrator.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAitchison R, Ebert D, S\u0026eacute;ret B, Weigmann S (2024) Review of three southwestern Indian Ocean species of \u003cem\u003eRhinobatos\u003c/em\u003e (Rhinopristiformes: Rhinobatidae). 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The importance of accurate specimen identification is well established, especially in the context of conservation management. However, guitarfishes remain poorly understood. We therefore aimed (1) to identify molecular operational taxonomic units (MOTUs) within \u003cem\u003eAcroteriobatus\u003c/em\u003e by analysing sampled specimens as well as publicly available sequence data for the \u003cem\u003ecytochrome c oxidase subunit I\u003c/em\u003e (\u003cem\u003eCOI\u003c/em\u003e) and \u003cem\u003enicotinamide adenine dehydrogenase subunit 2 (ND2\u003c/em\u003e) genes, and (2) to augment and review the representation of these sequences on public databases. A molecular taxonomic approach integrating species delimitation and specimen assignment methods revealed 14 MOTUs. These MOTUs aligned with current species descriptions, displaying no evidence of cryptic diversity. Both genes demonstrated similar interspecific relationships that broadly reflected current distribution ranges, underscoring sub-regional endemism. Moreover, discrepancies in public sequence repositories were identified, attributed to misidentified specimens and the usage of outdated taxonomic nomenclature. Genetic diversity indices were substantially inflated when specimens were grouped based on reported species versus delimited MOTUs, thus overestimating genetic diversity. We highlight the need for extensive, curated DNA reference libraries, including revising earlier sequence entries in light of new taxonomic insights, to enable reliable identification of morphologically conserved species. The molecular resolution illustrated in this study can aid in clarifying taxonomic uncertainties in the genus \u003cem\u003eAcroteriobatus\u003c/em\u003e.\u003c/p\u003e","manuscriptTitle":"Molecular taxonomy of guitarfishes (Rhinobatidae: Acroteriobatus)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 19:39:09","doi":"10.21203/rs.3.rs-7379127/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor Revisions Needed","date":"2025-10-13T01:53:19+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-09-19T11:22:23+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-15T06:09:11+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Marine Biodiversity","date":"2025-09-10T21:41:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-29T08:53:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Marine Biodiversity","date":"2025-08-15T03:12:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"marine-biodiversity","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"marb","sideBox":"Learn more about [Marine Biodiversity](http://link.springer.com/journal/12526)","snPcode":"12526","submissionUrl":"https://www.editorialmanager.com/marb/default2.aspx","title":"Marine Biodiversity","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4aa5c87a-06bd-489f-a23a-7d6ac2b76e70","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-02T16:04:00+00:00","versionOfRecord":{"articleIdentity":"rs-7379127","link":"https://doi.org/10.1007/s12526-025-01617-x","journal":{"identity":"marine-biodiversity","isVorOnly":false,"title":"Marine Biodiversity"},"publishedOn":"2026-01-26 15:59:20","publishedOnDateReadable":"January 26th, 2026"},"versionCreatedAt":"2025-09-23 19:39:09","video":"","vorDoi":"10.1007/s12526-025-01617-x","vorDoiUrl":"https://doi.org/10.1007/s12526-025-01617-x","workflowStages":[]},"version":"v1","identity":"rs-7379127","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7379127","identity":"rs-7379127","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}