The family Sciaenidae, known as croakers or drums, is one of the largest perciform fish families. A recent multi-gene based study investigating the phylogeny and biogeography of global sciaenids revealed that the origin and early diversification of this family occurred in tropical America during the Late Oligocene—Early Miocene before undergoing range expansions to other seas including the Indo-West Pacific, where high species richness is observed. Despite this clarification of the overall evolutionary history of the family, knowledge of the taxonomy and phylogeny of sciaenid genera endemic to the Indo-West Pacific is still limited due to lack of a thorough survey of all taxa. In this study, we used DNA-based approaches to investigate the evolutionary relationships, to explore the species diversity, and to elucidate the taxonomic status of sciaenid species/genera within the Indo-West Pacific clade. Three datasets were herein built for the above objectives: the combined dataset (248 samples from 45 currently recognized species) from one nuclear gene (RAG1) and one mitochondrial gene (COI); the dataset with only RAG1 gene sequences (245 samples from 44 currently recognized species); and the dataset with only COI gene sequences (308 samples from 51 currently recognized species). The latter was primarily used for our biodiversity exploration with two different species delimitation methods (Automatic Barcode Gap Discovery, ABGD and Generalized Mixed Yule Coalescent, GMYC). The results were further evaluated with help of four supplementary criteria for species delimitation (genetic similarity, monophyly inferred from individual gene and combined data trees, geographic distribution, and morphology). Our final results confirmed the validity of 32 currently recognized species and identified several potential new species waiting for formal descriptions. We also reexamined the taxonomic status of the genera, Larimichthys, Nibea, Protonibea and Megalonibea, and suggested a revision of Nibea and proposed a new genus Pseudolarimichthys.
Citation: Lo P-C, Liu S-H, Nor SAM, Chen W-J (2017) Molecular exploration of hidden diversity in the Indo-West Pacific sciaenid clade. PLoS ONE12(4): e0176623. https://doi.org/10.1371/journal.pone.0176623
Editor: Zuogang Peng, Southwest University, CHINA
Received: August 31, 2016; Accepted: April 13, 2017; Published: April 28, 2017
Copyright: © 2017 Lo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data (DNA sequences) obtained in this study are available in the NCBI GenBank (http://www.ncbi.nlm.nih.gov/genbank/) under accession numbers KX777879 – KX778099 (COI sequences) and KX777663 – KX777878 (RAG1 sequences). This statement was mentioned in the Material and Methods section.
Funding: This work was supported by research grants from the Ministry of Science and Technology, Taiwan (https://www.most.gov.tw/en/public) (MOST 101-2611-M-002-016-MY3 and MOST 104-2611-M-002-002-MY3 to Wei-Jen Chen). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Over the past few decades, the development of new and diverse DNA-based approaches has made great advances in systematic biology at all taxonomic levels [1–5]. For example, phylogenetic inference based on evidence from multiple gene loci (known as phylogenomic approach) has been utilized for reconstructing the well-supported “Tree of Life” that provides a comparative framework for tests of hypotheses of organismal evolution and for classification of living organisms . On the other hand, the approach of DNA barcoding that uses DNA sequences from a short fragment of mitochondrial cytochrome oxidase subunit I (COI) gene as “barcodes” for bio-identification is also well established . These approaches have increased the pace and rigor of biodiversity assessments, especially for traditional methods (e.g., morphological) which sometimes fail to provide a sound resolution [1, 7]. Other obvious advantages include ease of use, applicability at any stage of development/state of the specimen as well as transmissibility .
In this study, we conducted a DNA-based survey on a diverse group of predominantly marine/brackish fishes from the family Sciaenidae, commonly known as croakers or drums . This family contains 68 currently recognized genera and approximately 292 species, distributed in temperate and tropical regions worldwide [10–13]. Most of the species are targeted by local fisheries and their global fishery production in the past two decades is around one million ton per year . However, many sciaenid species are vulnerable to overfishing [15–20] and habitat degradation [18, 21, 22]. In 2007, the IUCN-Species Survival Commission identified this family as a conservation priority and called for the urgent establishment of a Sciaenidae Red List Authority to assess the risk of extinction of all sciaenid species and to recommend actions needed for the next decade to ensure their well-being . However, without a solid framework for the systematics of the Sciaenidae, prospective work with species stock management and conservation cannot be properly understood.
Recently, Lo et al.  reconstructed the first comprehensive phylogeny of global sciaenids with rigorous taxonomic and molecular character sampling (6619 bp from two mitochondrial and four nuclear genes for 93 taxa). The constructed phylogeny was subsequently used as a framework to examine their origin and historical biogeography. They found that the Sciaenidae first originated and diversified in the tropical American waters in the Late Oligocene and dispersed outward in the Early Miocene, hypothesizing that the ancestor of the Indo-West Pacific endemic sciaenid genera underwent a single invasion event to the Indo-West Pacific (IWP) that evolved to form a diversified clade that today contains approximately 91 species [10, 24]. However, knowledge of the taxonomy and phylogeny of the sciaenids within this IWP clade is still limited due to lack of a thorough survey of all taxa. Most previous studies have focused on the investigation of the population structure of certain species and DNA barcoding studies at a regional scale [25–28], and in the past decade, only two taxonomic studies have reported new species [29, 30]. Possible cryptic species may exist in the IWP realm that await further discovery.
Traditionally, biodiversity exploration relies on morphology-based species identification. However, such a task is challenging for congeneric species in the Sciaenidae because of similarity in their external morphology and overlapping meristic counts. The use of DNA-based approaches for species identification represents a novel perspective to complement traditional taxonomic practices that are generally time consuming even for experts. In the present study, a combined approach with multi-locus phylogenetic and DNA barcoding analyses was employed to investigate evolutionary relationships, explore species diversity, and to elucidate the taxonomic status of sciaenid species/genera within the IWP clade.
Materials and methods
The research was performed at National Taiwan University in accordance with the National Taiwan University’s guidelines regarding animal research. As this project did not involve experiments on live fishes, no ethics statement is required. Most of the specimens examined in the present study were purchased from local fish markets, fish landing sites or directly from professional fishermen (see Fig 1 and S1 Table for the details); others were museum specimens. The taxonomic sampling was completed through legal tissue donations from International Research Institutes (see “acknowledgments” section).
The four regions used for considering the sympatry of sister OTUs (A), and map of the Indo-West Pacific region indicating the sampling sites for the taxa examined in the present study (B). Abbreviations: IO, Indian Ocean; ECS, East China Sea; SCS, South China Sea; CT, Coral Triangle region; SAS, Sahul Shelf and Australia. Dots in different color represent the examined samples from different sources. Red dots: our own collections; green dots: online databases.
The sciaenid samples (n = 249) of 45 recognized species from the IWP clade were collected from 96 localities (Fig 1 and S1 Table). The collected specimens were identified using morphological characters, primarily based on the Fishes of Taiwan  and FAO (Food and Agriculture Organization of the United Nations) and other species identification guides [32, 33]. After identification, a small piece of muscle-tissue was excised from each specimen, preserved in 95% ethanol, and for most of the samples, voucher specimens (n = 143) were preserved and deposited in the National Taiwan University Museums (NTUM), Taipei, Taiwan and in the Centre for Marine and Coastal studies in the Universiti Sains Malaysia (USM_CEMACS), Penang, Malaysia (S1 Table).
DNA extraction, PCR amplification and sequencing
Total genomic DNA was extracted from each tissue sample using DNeasy Blood and Tissue Kit (Qiagen, Hilden, Germany) or LabTurbo DNA Mini Kit LGD480-220, (TAIGEN Bioscience Corporation, Taipei, Taiwan) following the manufacturer’s protocols. Polymerase chain reaction (PCR) was used to amplify the following targeted gene markers: mitochondrial cytochrome c oxidase I (COI) gene and exon 3 of nuclear recombination-activating gene 1 (RAG1). These two gene markers were selected for their ability to provide valuable phylogenetic information (RAG1) and to delimit species (COI) based on previous studies investigating fish systematics [24, 34–38]. These two markers were also part of the gene set used in a previous study on the Sciaenidae  and provide consistent results from PCR to sequencing processes. Information on the primers for these gene markers are listed in S2 Table. Laboratory protocols to obtain the sequences followed Lo et al. . The short amplicons from COI were sequenced with only forward or reverse primer because current Sanger sequencing technique has no issue of sequencing accuracy for a relatively short fragment. However, the longer amplicons from RAG1 were sequenced with both forward and reverse primers in order to robustly assemble the sequences.
The obtained DNA sequences were edited with the sequence assembly and alignment software, CodonCode Aligner v.6.0.2 (CodonCode Corporation, Dedham, MA, USA) and Se-Al v.2.0 . The sequences (usually at both extreme ends) with low quality or problematic base calls, i.e. below Q (phred quality value) 20, were verified visually and trimmed. In addition, the possibility of sequencing errors resulting from sample mix-up or contamination was checked by comparing the topologies of the resulting phylogenetic trees individually inferred from each gene fragment and/or comparing to GenBank archived sequences of a putatively closely related taxon using BLAST (http://www.ncbi.nlm.nih.gov/BLAST/). Manipulation and/or species identification errors were further checked by examining the voucher specimens if possible or the additional sequence of a second exemplar from the same (or nearby) locality of the sample collection. The newly obtained sequences were deposited in the NCBI GenBank under accession numbers, KX777879 –KX778099 (221 COI sequences) and KX777663 –KX777878 (216 RAG1 sequences).
Molecular datasets and phylogenetic reconstruction.
For the molecular analyses, three different datasets were compiled and used: 1) COI dataset (308 samples) comprising the COI gene sequences newly obtained in the present study (n = 219) and those retrieved from three online databases (see section below) (n = 89); 2) RAG1 dataset (245 samples) including the RAG1 gene sequences obtained in the present study (n = 214) plus several from GenBank (n = 31); 3) the combined dataset (248 samples) including the sequences from the common taxon set of the first and second datasets (n = 245) plus the COI sequences from three taxa (Collichthys niveatus CN545, Johnius heterolepis CN557 and Nibea soldado WJC1935) whose RAG1 sequences were missing due to the PCR/sequencing failure of the gene. The samples from these three compiled datasets represented taxa from 18 of 25 IWP endemic sciaenid genera. Six non-IWP, but closely related sciaenids, Aplodinotus grunniens, Pseudotolithus brachygnathus, P. elongatus, P. senegalensis, Pteroscion peli and Totoaba macdonaldi were selected as outgroups following Lo et al.  for the phylogenetic analyses. The distant outgroup, Aplodinotus grunniens, was used to root the inferred phylogenetic trees.
The sequence alignment for each gene dataset was achieved with the automatic multiple alignment program MUSCLE , then adjusted manually by eye using the software Se–Al v2.0 . The descriptive statistics (sequence variation, base composition, genetic distances, etc.) for the compared sequences of each gene were calculated using the tools in PAUP*4.0a147 . To infer phylogenetic trees, the partitioned Maximum Likelihood (ML) method , as implemented in the sequential and parallel program RAxML v.0.93  was used. Because RAxML only provides GTR-related models of rate heterogeneity for nucleotide data , the nucleotide substitution model GTR+Γ+I  was employed for the analyses by following the decision from our previous study . For each ML search, five independent runs were conducted and the final tree with the best ML score was selected among the five ML trees of these runs. Nodal support was assessed with bootstrapping  under the ML criterion, based on 1000 pseudo-replicates generated from each of the five separate runs. All RAxML analyses with bootstrapping were conducted with the CIPRES Science Gateway at http://www.phylo.org .
Biodiversity assessment through species delimitation analyses.
To explore the sciaenid species diversity within the IWP clade, two DNA-based analytical methods applying different algorithms of species delimitation were primarily used (see below). Both methods determine the sequence clusters, as operational taxonomic units (OTUs) or putative species without a priori species hypothesis based on the COI sequence dataset compiled in this study. In this dataset, 219 new plus 89 published sequences retrieved from NCBI GenBank , BOLD system (The Barcode of Life Data System; ) and CRYOBANK (Taiwan Wildlife Genetic Material Cryobank; ) were included (see list of examined taxa in S1 Table).
The Automatic Barcode Gap Discovery (ABGD)  method is an exploratory tool based on pairwise genetic distances. Under the premise that the intraspecific diversity of the COI gene is lower than the interspecific diversity, this tool applies clustering algorithms to automatically detect the significance between intra- and inter-specific variations (called barcode gap). A default setting of relative gap width (X) as 1.5, intraspecific divergence (P) value from 0.001 to 0.1 with 50 steps under both available distance metrics, JC69  and the Kimura-2-parameter distance model (K2P) , were employed at the ABGD web interface (http://wwwabi.snv.jussieu.fr/public/abgd).
The Generalized Mixed Yule Coalescent (GMYC)  method is a likelihood solution that calculates the transition point between the speciation and coalescence processes with the assumption of a constant species rate and no extinction on an ultrametric gene tree. A single-threshold GMYC analysis was performed using RStudio v.0.99.486 software , an integrated development environment for R software v.3.2.1  using the APE  and SPLITS  packages. An input tree for GMYC method with ultrametric, bifurcating and no zero branch lengths was generated using BEAST v.1.8.3  based on a relaxed molecular clock using a Bayesian approach. Nine independent runs of 5 x 107 generations each were performed. Estimation of trees and divergence time were sampled once every 5000 generations and the parameters of each run were checked for convergence using Tracer v.1.6 . For each run, two inferred ages, 12.8 Ma and 16.6 Ma, respectively according to the previous study , were set as calibration points and were used to constrain the tMRCAs of West African sciaenids and endemic IWP sciaenids based on a GTR+Γ substitution model to infer the time tree. The burn-in parts of each run (= 10%, i.e., 103 trees per run) were removed and the tree samples from the remaining nine runs were used to reconstruct the maximum clade credibility tree with mean divergence times using TreeAnnotator v.1.8.3 .
Congruent results between these two methods are considered as robust support of any OTU as suggested by Carstens et al. . Other species delimitation criteria  were taken into account to minimize the bias from these two analyses for the final validation. In this study, we employed four criteria to aid a final decision on the status of any incongruent OTU: reciprocal monophyly found in gene trees (both COI and RAG1 tree), genetic similarity, geographical distributions, and morphology.
Here, monophyly of each incongruent OTU was further evaluated based on the phylogenetic trees reconstructed based on COI, RAG1, and combined datasets (see method described below). The analysis of unlinked markers (mitochondrial vs. nuclear genes) allowed evaluation of the absence of gene flow between putative species or their presence of reproductive isolation “in situ”.
Genetic similarity was evaluated by the K2P genetic distances  estimated using PAUP*4.0a147 . The maximum genetic distances within and among each OTU consistently defined from the ABGD analysis were calculated and set as our threshold of evaluation. Multiple OTUs in the same recognized species with less than the maximal sequence divergences would be merged if there were no other evidences against the prior species definition by morphology.
In addition, as the establishment of reproductive isolation between putative species in the field can only be tested in sympatric species , we took the sympatry of the sister OTUs into consideration and merged the allopatric sister OTUs as a single one. Because sciaenids are non-coral reef fishes and always have restricted migratory habits; only their pelagic larval stage has potential high dispersal along coastal areas [25, 26, 28, 62]. Thus, we defined four geographic regions based on the landmass or boundaries of coral reefs, currents and levels of regional endemicity, i.e. East China Sea, ECS; South China Sea + Coral Triangle, SCS + CT; Sahul Shelf and Australia, SAS; Indian Ocean, IO (Fig 1). The designation of the sympatry of inferred sister OTUs is based on these four regions.
Finally, morphological measurements and counts of the major diagnostic characteristics of the sciaenid species were obtained following methodologies of Hubbs and Lagler . The compared specimens were from our collected samples (S1 Table) and those from the holotype specimen of Nibea soldado (Lacepède 1802) (MNHN 5550). Gill raker counts were taken from the first right-hand side arch of the specimens except where this arch was damaged; denticulate flat plates above and below the rakers were not counted, and the middle raker counts were included in the lower raker numbers.
Results and discussion
Characteristics of sequence data
The COI dataset comprised 308 sequences retrieved from public databases and those generated from our collected samples (S1 Table). Indels and stop codons were absent from all amplified sequences. Within the COI dataset, the total 618 bp contained 311 (50.3%) variable sites, 287 of them parsimony-informative. Most of the variable sites were found in the third codon positions (206/311; 66.2%). All of the sites in the third codon positions were variable and parsimony-informative (S3 Table).
The RAG1 dataset comprised 245 sequences retrieved from public databases and those generated from our collected samples (S1 Table). Indels and stop codons were absent from all amplified sequences. Within the RAG1 dataset, the total of 1472 bp contained 348 (23.6%) variable sites, 269 of them parsimony-informative. Most of the variable sites were found in the third codon positions (249/348; 71.6%). About a half of sites in the third codon positions were variable (249/490; 50.8%) and 195 of them were parsimony-informative (S3 Table).
The combined dataset (2090 bp) in the present study contained the sequences of COI gene (618 bp) and RAG1 gene (1472 bp) from a total of 248 examined samples. Indels and stop codons were not found along the sequences. Among the nucleotide sites, 640 were variable (30.6%) and 548 of them were parsimony-informative (S4 Table).
Inferred phylogenetic trees
We tested the monophyly of the IWP sciaenid clade and examined the validity of 18 of 25 IWP endemic sciaenid genera, and 51 of 91 recognized species from the IWP clade. The inferred mitochondrial COI gene tree is shown in S1 Fig and summarized in Fig 2. In this tree, the IWP sciaenid clade revealed by Lo et al.  is confirmed with high bootstrap support (BS = 91%). While 23 of 31 examined species that contain more than two representative taxa sampled for each species are monophyletic with high bootstrap supports, six others are paraphyletic (Atrobucca nibe, Otolithes ruber, Protonibea diacanthus, Nibea soldado, Johnius amblycephalus, J. heterolepis) and two are polyphyletic (J. borneensis and J. belangerii) (Fig 2 and S1 Fig).
Branch lengths are proportional to the inferred nucleotide substitutions. Numbers at nodes represent bootstrap values in percentage. Values below 70% are not shown; * indicates 100%. Taxa name in bold indicates problematic or probable misidentification samples. Numbers within the parentheses shown after the taxon names indicate number of sequences being contained within each collapsed clade or lineage. The tree is rooted with Aplodinotus grunniens according to Lo et al. . Summary of the determined OTUs (vertical bars) is presented on the right side of the phylogenetic tree. Black bar indicates congruent OTUs as suggested by both species delimitation methods (i.e. robust results). White bar with a cross inside indicates the presence of multiple OTUs determined by GMYC in the particular genetic lineage that is incongruent to ABGD result. Missing data are marked by black crosses. Abbreviations for geographic distribution of the taxa: IO, Indian Ocean; ECS, East China Sea; SCS, South China Sea; CT, Coral Triangle region; SAS, Sahul Shelf and Australia.
The nuclear RAG1 gene analysis involved fewer taxa (245 samples from 44 species) than the COI gene analysis. The result showed that the resolution of the relationships among closely related species and within species or species complexes inferred from RAG1 is less pronounced than that inferred from COI because of its conservative rate of gene evolution. However, the RAG1 gene tree (S2 Fig) still confirms most of the species monophyly found in the COI gene tree (S1 Fig) and the results of species delimitations based on COI dataset when the concerned sequence data are available (see further discussion below).
The combined gene analysis (Fig 3) contained 248 samples from 44 recognized species including 6 outgroups. The IWP sciaenid clade received the highest bootstrap value (BS = 100%) in the inferred tree. In contrast to the COI and RAG1 individual gene datasets, the combined gene dataset provided better overall signals for resolving both shallow and deep nodes in the inferred phylogenetic tree, as revealed by the presence of a high proportion of well-supported nodes (BP > 80) from the analysis (Fig 3). Here, we primarily use the results from the combined gene tree to evaluate the higher-level taxonomic status of the sciaenids within the IWP clade as discussed below.
Branch lengths are proportional to the inferred nucleotide substitutions. Numbers at nodes represent bootstrap values in percentage. Values below 70% are not shown; * indicates 100%. Different colors in genus Johnius show that the taxa are either from the pre-recognized subgenus, Johnius (in blue) or subgenus Johnieops (in red). The tree is rooted with Aplodinotus grunniens according the result shown in Lo et al. . Abbreviations for geographic distribution of the taxa: IO, Indian Ocean; ECS, East China Sea; SCS, South China Sea; CT, Coral Triangle region; SAS, Sahul Shelf and Australia.
Higher-level taxonomic implications and revised classification
The combined gene tree confirms the monophyly of the following genera where more than two samples and/or recognized species for each of the following genera were included and examined: Collichthys, Atrobucca, Otolithes, Pennahia, and Johnius (BS = 96–100%; Fig 3).
For the Larimichthys (yellow croakers), three out of four recognized species of the genus, including the recently discovered species, L. terengganui, that is endemic to eastern Peninsula Malaysia , were analyzed. While L. polyactis and L. crocea appear to be sister-group with strong bootstrap support for the relationship (BS = 91%), the monophyly of the Larimichthys when L. terengganui is included is not supported (BS < 70%; Fig 3). This makes the assignment of the recently described species to the genus Larimichthys problematic. As the swimbladder morphology is often considered a key feature for the diagnosis at generic level in sciaenids , we further compared the swimbladder morphology of Larimichthys spp. as well as their relatives, Collichthys spp. (Fig 3). We observed that the swimbladder appendages from these taxa showed significant differences in their pattern and number. The swimbladder appendages of the L. terengganui are similar to L. pamoides (not sampled in this study), with two equally short branches without elongation at the ventral limb and each have 26 appendage pairs in total . In contrast, the branches of Collichthys spp. and two other Larimichthys species, L. polyactis and L. crocea, have elongated ventral limbs (at least for one of them) and the number of their appendage pairs is either < 21 (in Collichthys) or > 30 (in L. polyactis and L. crocea), which do not overlap with L. terengganui and L. pamoides [30–32]. Based on the phylogenetic results (i.e. three genetically distinct [or separately evolving] lineages appearing in the Larimichthys/Collichthys clade), concomitant with the morphological evidence, we suggest that L. terengganui and perhaps L. pamoides should be assigned to a different genus.
For Johnius species, Trewavas  recognized two subgenera, Johnius and Johnieops, according to the morphology of their teeth. The lower jaw teeth of Johnius spp. are either uniform in size or molariform, while Johnieops spp. possess enlarged conical teeth appearing on the inner row of their lower jaw [35, 62]. This morphological difference led Lal Mohan et al.  to suggest both subgenera were worthy of generic ranking. Based on our phylogenetic results, however, such classification should be rejected as grouping based on teeth morphology is not supported (Fig 3).
For the “Nibea” species, eleven currently recognized species are included in this genus, of which seven were sampled for the analyses in this study. Based on a multi-gene dataset, Lo et al.  demonstrated that this genus was polyphyletic and the examined Nibea taxa formed two distantly related clades: Nibea A and Nibea B. Nibea A contains the Nibea species commonly found in the Northwest Pacific, the South China Sea, and the eastern Indian Ocean, while Nibea B contains Nibea species restricted to the coasts of New Guinea and northern Australia. The most closely related sciaenid genus to the Nibea B is a monotypic genus, Austronibea, endemic to Australia, and another monotypic genus, Dendrophysa, is sister to them (Figs 2 and 3). With more included taxa than the previous study , notably N. mitsukurii from Japan and N. chui from Fujian, China, the present phylogeny reveals the same distinct clades for the Nibea species (Figs 2 and 3). In addition, a third clade based on a GenBank sequence from N. maculata collected from India, is found in the COI gene tree (Fig 2 and S1 Fig). This particular taxon appears to be the sister group of Daysciaena albida, but does not show a close affinity with Nibea A or Nibea B (Fig 2 and S1 Fig). As the sequence of this species was retrieved from GenBank (accession no. EU014250), and because no further taxonomic and morphological information about the specimen was given in the paper which reported the sequence , we were not able to investigate its taxonomic status.
Based on the inferred phylogeny presented here, we suggest separating the “Nibea” species into at least two different groups or genera. The genus Nibea should be used only for species of the Nibea A clade as it includes the type species of the genus, N. mitsukurii. We suggest that the two Nibea B species, N. squamosa and N. microgenys examined here, should be included in the newly redefined Austronibea. Austronibea contains phylogenetically related, morphologically similar, and geographically co-distributed species, including A. oedogenys (type species), the two Nibea B species, plus possibly another northern Australian distributed “Nibea” species, N. leptolepis (not sampled in this study). Our tree also suggests that Nibea maculata might represent another (new) genus, which requires further examination when more data are available. Herein, we propose the following revised classification.
Genus Pseudolarimichthys gen. nov. Lo, Liu, Mohd Nor and Chen
Type species: Pseudolarimichthys terengganui (Seah, Hanafi, Mazlan and Chao 2015)
Diagnosis: This new name applies to Larimichthys terengganui. A former genus name “Larimichthys” was assigned to this species by Seah et al.  who described it without giving a clear reason. Our phylogenetic results show it is only distantly related to Larimichthys species (Figs 2 and 3). This genus can be generally distinguished from other sciaenid genera by having a specific carrot-shaped swimbladder with a number of branched appendages that contain well-developed dorsal and ventral limbs along its entire lateral side, and having cycloid scales on anterior half of body. This genus can be further distinguished from its two related genera (Larimichthys Jordan and Starks 1905 and Collichthys Günther 1860) by deep genetic differences (Figs 2 and 3) and the pattern of swimbladder morphology which has two equally short branches without elongation of the ventral limb and 26 appendage pairs in total (versus > 30 and < 21 in Larimichthys and Collichthys, respectively).
Etymology: Pseudolarimichthys. A noun in apposition. Latin pseudo, meaning false, and similar to species of Larimichthys of the originally described species .
Composition: The genus contains P. terengganui and possibly “Larimichthys” pamoides (Munro 1964). The inclusion of the latter species in the genus needs to be further studied.
Distribution: East coast of Peninsular Malaysia.
Genus Austronibea Trewavas 1977, new definition
Type species: Austronibea oedogenys Trewavas 1977.
Diagnosis: The revised genus also includes species of Nibea clade B according to our molecular phylogenetic results (Figs 2 and 3) and in Lo et al. . The diagnostic characters used for the type species can, in part, be considered for characterizing this genus. This species and “Nibea” species share most of the diagnostic characters including meristic counts that can be used to distinguish them from all other sciaenid species  (see below). However, the species of the redefined genus have a distinctly inferior mouth, which is different from the species of Nibea clade A (mouth terminal or slightly inferior). This genus can be diagnosed from the related genus, Dendrophysa Trewavas 1964, by the presence of a mental barbel in the latter.
Composition: The redefined genus includes the type species Austronibea oedogenys, as well as A. squamosa (Sasaki 1992) and A. microgenys (Sasaki 1992) (removed from Nibea, as discussed above). Nibea leptolepis (Ogilby 1918), another species distributed along coasts of northern Australia, might also belong to Austronibea.
Distribution: Northern and northwestern Australia and southern New Guinea
Genus Nibea Jordan and Thompson 1911, new definition
Type species: Nibea mitsukurii (Jordan and Snyder 1900)
Diagnosis: The revised genus includes only species of Nibea clade A according to our molecular phylogenetic results (Figs 2 and 3) and in Lo et al. . Diagnosis for the revised Nibea, generally follows the original diagnoses of Nibea (swimbladder carrot-shaped or fan-like without well-developed dorsal limbs and with a number of branched appendages along its entire lateral side; the first appendage not extending to lateral face of pectoral arch; anterior pair of swimbladder appendages entering into head beyond transverse septum and branching between skull and upper gill arches; sulcus head of sagitta not very oblique, shape of sulcus tail variable but not deepened as a hollow cone; scales on body ctenoid; second anal-fin spine length 38 to 64% of head length except for N. semifasciata; no mental barbel) with some modifications, e.g., in having terminal (and generally large) or slightly inferior mouths and generally enlarged inner lower jaw teeth, which distinguish them from Nibea B (Austronibea) species.
Composition: The redefined genus Nibea contains seven currently recognized species: N. albiflora (Richardson 1846), N. chui Trewavas 1971, N. coibor (Hamilton 1822), N. maculata (Bloch and Schneider 1801), N. mitsukurii, N. semifasciata Chu, Lo & Wu 1963, and N. soldado (Lacepède 1802). The revised genus excludes N. squamosa, N. microgenys, and possibly N. leptolepis, all assigned here to Austronibea. N. soldado is a species complex that contains multiple inferred species (see further discussion below). The taxonomy of N. maculata requires a further investigation.
Distribution: Eastern Indian Ocean, Western Pacific, and Northwest Pacific.
The compiled COI dataset comprising the sequence data from 51 currently recognized sciaenid species for 308 samples (S1 Table) were also used for the species delimitation analyses with ABGD and GMYC tools. The ABGD analysis conducted by partitioning all the individuals with prior maximal distance (P) = 0.0324 results in 50 OTUs by both distance metrics, JC69 and K2P. However, the GMYC analysis determined a higher number, 95 OTUs with the single-threshold GMYC for the transition between coalescence and speciation branching patterns of -1.94618 (S3 Fig). Twenty-five common OTUs resulting from these two analyses were identified and considered here as robust support for the inferred species. Here, the validity of currently recognized species of Bahaba taipingensis, Panna microlepis, “Larimichthys” (= Pseudolarimichthys) terengganui, Pterotolithus maculatus, Nibea mitsukurii, N. maculata, “Nibea” (= Austronibea) squamosa, “N.” (= Austronibea) microgenys, Austronibea oedogenys, Daysciaena albida, Johnius macropterus, J. majan (another recently discovered new species) , J. dussumieri, J. macrorhynus, J. novaeguineae, J. trachycephalus, J. trewavasae and J. carouna is confirmed. Moreover, a few common OTUs (i.e., supported inferred species) are found within the recognized species (e.g., Otolithes ruber), indicating that these “species” contain cryptic or potential new species (Fig 2 and S3 Fig); two others (J. borneensis and J. belangerii) were found to be polyphyletic, further supporting the invalidity of these two species or potential errors in species identification in GenBank sequences (Fig 2 and S3 Fig).
In general, GMYC analysis tends to split more OTUs than the ABGD analysis does [4, 67–70]. Their different algorithms applied to the analyses can explain this incongruence. In fact, GMYC implements a strong theoretical basis that is underpinned by the transition from coalescent to speciation determined based on the inferred ultrametric gene (or time) tree; the variability in rates of genetic change as well the speciation rate and effective population size might affect the result of species delimitation [67, 70]. To avoid overestimating the species diversity suggested by the GMYC results, we firstly resolved the incongruent OTUs found between the two methods by merging the split sister GMYC OTUs and paraphyletic GMYC OTUs to a single one when no evidence of sufficient genetic divergence among samples (K2P < 3.2% in COI) and non-monophyly in the separate gene trees was observed (Fig 2). Based on this analysis, 14 revised OTUs were determined. These OTUs also match and confirm the following morpho-species: Miichthys miiuy, Collichthys niveatus, C. lucidus, Larimichthys crocea, L. polyactis, Pennahia ovata, P. anea, P. pawak, P. argentata, P. macrocephalus, Nibea albiflora, Chrysochir aureus, Dendrophysa russelii and Johnius distinctus (Fig 2).
In the next step for treating the incongruent OTUs, we merged the allopatric sister OTUs (when there was no significant difference in their morphology and no other evidence supporting their reproductive isolation) and separate the sympatric pairs. As a result, 60 species in total are inferred within the IWP sciaenid clade, of which 32 match the current definition of species (Fig 2).
Cryptic diversity and necessity for further taxonomic consideration of species within the IWP clade
From our species delimitation and phylogenetic analyses, two Atrobucca species were examined. Both ABGD and GMYC analyses recognized A. nibe CN211 collected in Kaohsiung, Taiwan as an inferred species, which is further confirmed by topology of individual gene and combined data trees. While ABGD clustered all other samples as a single OTU, GMYC split them into four (Fig 2 and S3 Fig).
According to the identification key proposed by Sasaki and Kailola , the difference in ratio of gill filament to standard length can separate A. trewavasae and A. alcocki (4.5–6.4%) from other Atrobucca spp. (2.4–3.5%) (e.g., A. nibe). For the sample of A. cf. trewavasae WJC6390 (collected from Dubai), its ratio calculated is 3.9%, which does not overlap with that of any known Atrobucca species. In RAG1 gene tree, the sequence of A. cf. trewavasae WJC6390 diverges from other Atrobucca samples (S2 Fig). Based on these observations, it is likely that A. cf. trewavasae WJC6390 might represent a new Atrobucca species awaiting formal description.
In our other sampled Atrobucca specimens (excluding A. nibe CN211 [no voucher specimen kept] and A. nibe JF492920 [GenBank sequence; no specimen for examination]), the ratio of gill filament to standard length calculated falls into the range of 2.4–3.5% and the use of other morphological features diagnose our samples to be A. nibe. However, when the ratio of gill raker to gill filament of these A. nibe samples is calculated, we can observe differences between the individuals collected exclusively from eastern Taiwan (ratio = 0.88–1.03) and those collected from several localities in Taiwan (including eastern Taiwan) and in China (ratio = 1.37–1.8). While the COI K2P distances calculated among these samples are lower than 3.2% (0–2.2%), GMYC analysis delimits them as two OTUs that correspond to the observed morphological difference (Fig 2). In the RAG1 gene tree, the corresponding samples from these two OTUs form two separate clades (S2 Fig). Moreover, we also found that the individuals of these OTUs co-occur in eastern Taiwan. Here, the combined evidence indicates that they could represent two reproductively isolated species.
Boesemania is the only freshwater sciaenid genus from the IWP realm and is currently considered to be monotypic. The present study analyzed two samples identified as B. microlepis and the evidence from all analyses suggests that they belong to two different species (Fig 2). The COI sequence of LC064301 was retrieved from GenBank and has been reported by Pringgenis and Susilowati . It was caught in a non-freshwater habitat in Malacca Strait, Sumatra . The COI sequence of KP722706 was obtained from an inland water sample collected in Thailand and was included in the analysis in Lo et al. . The swimbladder of B. microlepis described by Pringgenis and Susilowati  is hammer-shaped without numerous appendages, which is not found in typical B. microlepis. Based on these observations (including the habitat preference), it is very likely that the atypical B. microlepis LC064301 is a new species waiting for formal descriptions.
The present study included all available sequence data from the two known tigertooth croakers of the genus Otolithes: 28 COI sequences of O. ruber (19 newly obtained in the present study with nine others retrieved from online databases) and one COI sequence of O. cuvieri (retrieved from GenBank). Otolithes ruber is a widespread species while O. cuvieri is restricted to the coasts of India and Pakistan in the Indian Ocean. Our combined evidence deduced from both available molecular data and morphological examination (see below) suggest that this genus contains five putative species (Fig 2). One is widely distributed in the IWP (assigned herein as IWP species); four others are locally distributed (e.g., in Bali; Bali species) or regionally distributed (e.g., in the Indian Ocean: West IO I, West IO II, and IO + SAS spp.).
The Bali species (WJC2779) is robustly supported by both ABGD and GMYC species delimitation results (Fig 2). This species is found to be sister to the clade containing exclusively samples from western Indian Ocean that are separated into two OTUs (putative species; i.e. West IO I sp. and West IO II sp.) with significant sequence divergences between them (COI K2P = 6.8–7%). In the RAG1 gene tree, the Bali species is deeply divergent from others (S2 Fig).
For the single O. cuvieri individual sampled in this study, our analyses revealed that its COI sequence (from Maharashtra, western coast of India; retrieved from GenBank, FJ347924) is almost identical to that of O. ruber WJC1929 (from Northern Territory, Australia) and O. ruber (from Queensland, Australia; retrieved from GenBank, DQ107812). These three sequences cluster with two other COI sequences of O. ruber from the western Indian Ocean (their sequence divergences estimated from COI K2P distance are from 0 to 2.1%) (Fig 2 and S1 Fig). As the currently known O. cuvieri are only reported in the western Indian Ocean (along the coasts of India and Pakistan) , the fact that O. cuvieri FJ347924 was found nested within the IO + SAS species clade in our phylogenetic tree indicates a likely misidentification for this specimen. The other possibility could be that the IO + SAS sp. is actually O. cuvieri and the presence of “O. cuvieri” in Australian waters indicates a considerable range extension of the species. Further taxonomic investigation is necessary.
The results from the morphological examination of currently available specimens from Bali sp. (n = 1), West IO II sp. (n = 3), and IWP sp. (n = 10), show that West IO II sp. differs from the IWP sp. by having a reduced number of dorsal fin spines (IX vs. X) but a higher number of dorsal soft fin rays (30 vs. 27–29). In addition, more gill rakers were found on both upper and lower limbs in the West IO II sp. than those found in two other inferred species (5 and 12, respectively in West IO II sp.; 3–4 and 9–10, respectively in Bali sp. and IWP sp.). The swimbladder morphology of the two previously recognized Otolithes species  is characterized by a carrot-shaped swimbladder with 28 appendages or more (28 in O. cuvieri and 32–36 in O. ruber). All of our “O. ruber” specimens examined in this study have a carrot-shaped swimbladder, but with more than 35 pairs of fan-like appendages (37 in Bali sp.; 36–40 in IWP sp.). All the above evidence indicates that O. ruber contains cryptic and potential new species and the taxonomy of this species requires further investigation.
Protonibea and Megalonibea.
Protonibea and Megalonibea are another two ‘monotypic’ sciaenid genera within the IWP clade. Our phylogenetic results show Megalonibea is nested within the Protonibea diacanthus clade. This renders Protonibea paraphyletic (Figs 2 and 3). In the species delimitation analyses based on our COI dataset, we included 15 samples from P. diacanthus and one from M. fusca. ABGD resolved them as a single OTU while GYMC suggested five (Fig 2 and S3 Fig). Whatever the results, all the analyses converge to conclude that M. fusca, a large-size sciaenid distributed in the East China Sea, is invalid (Fig 2). Interestingly, in a previous study , a comparison of the morphology of sagittas (the largest otoliths) of the large-size sciaenids (including P. diacanthus) found in archeological sites and those taken from fresh specimens of different sizes purchased at local fish markets in Pakistan, with that of M. fusca described in the literature, hypothesized that M. fusca are the large-size adult of P. diacanthus. Our study also supports this hypothesis and further reveals that P. diacanthus/M. fusca is a species complex that contains multiple putative species (Fig 2).
Based on our COI results, we merged the two GMYC OTUs comprising the sequences from the samples of P. diacanthus and M. fusca collected from the South China Sea and adjusted regions (assigned as SCS + CT) into a single one because of high similarity among their sequences (K2P = 0–0.5%; divergences lower than 3.2%; shared RAG 1 sequence types). The Gujarat OTU, Mumbai + Australian OTU and south Indian OTU, are considered as separated based on the criteria of sequence divergence (COI K2P = 3.3–4.5%), reciprocal monophyly inferred in the COI gene tree as well as their geographic distribution (sympatric distribution in the Indian Ocean) (Fig 2). In summary, four species are tentatively inferred within the genus Protonibea (here Megalonibea is considered to be invalid), but detail morphological and genetic examinations are needed to clarify the species’ status.
Even though most of the taxonomic status within the genus “Nibea” has been resolved ( and this study), some issues remain to be clarified at the species level. Our phylogenetic analyses find N. soldado to be non-monophyletic because the samples from other species (N. chui and N. coibor) are included in the “N. soldado” clade, which is supported by a high bootstrap value (BS = 95% in COI tree; BS = 80% in combined tree) (Figs 2 and 3). From our results of species delimitation based on the COI dataset, this clade contains multiple OTUs from which one (N. cf. soldado assigned as Nsol I sp.) is robustly supported by both of ABGD and GMYC analyses and the phylogenetic analyses (Figs 2 and 3, S2 Fig). Based on the sequence divergences estimated by COI K2P distance (3.2–14%), we can differentiate the remaining samples into three more OTUs (Nsol II to IV spp.); Nsol II contains the individuals collected from SAS; Nsol III sp. includes N. chui (GenBank accession no. KP722744), N. coibor (GenBank accession no. KM233452) and an undetermined sample (N. sp. WJC1745) collected from Vietnam (Fig 2); Nsol IV sp. comprises widespread individuals (from IO + SCS + CT). The COI sequences of the Nsol III samples are almost identical (K2P = 0–0.2%). While the same four species (Nsol I–IV spp.) are resolved in the combined gene analysis (Fig 3), Nsol III and IV samples cluster together into a single clade in the RAG1 gene tree (S2 Fig).
Here, our morphological examination from available specimens, including the syntype of N. soldado (MNHN 7606; skin only), reveals that the specimens of Nsol III sp. (n = 2) are different from the other inferred “N. soldado” species (Nsol I, n = 10; Nsol IV, n = 8) and the syntype by having a lower number of dorsal fin soft rays (26–27 in Nsol III; 28–29 in Nsol I; 28–30 in Nsol IV; 29 in the syntype and 27–33 according to the literature [32, 74, 75]) and a lower number of outer gill rakers on first arch from both upper (3 in Nsol III; 4–5 in Nsol I; 4 in Nsol IV; no data from the syntype and the literature [32, 74, 75]) and lower limbs (7 in Nsol III; 8–11 in Nsol I; 9–10 in Nsol IV; no data from the syntype but 7–11 according to the literature [32, 74, 75]). Thus, we consider that Nsol III sp. is different from typical N. soldado.
In addition, Nsol III sp. also differs from N. chui and N. coibor in morphology and meristic counts (e.g., 24–25 of dorsal fin soft rays in N. chui). Based on our results, we suggest that Nsol III sp. likely represents a new Nibea species, and the GenBank sequences of N. chui (KP722744) and N. coibor (KM233452) included in Nsol III clade probably represent misidentification of samples.
Finally, the specimens from Nsol I sp. and Nsol IV sp. are morphologically similar to each other and are diagnosed to be N. soldado based on Sasaki’s identification key . Their ratios of lower jaw length to head length are measured to be 31.2–35.1% in Nsol I and 30–37.1% in Nsol IV, respectively; yet, they are different from the description of N. soldado in the literature (44 to 53%). Overall, our study indicates that N. soldado also contains cryptic and potential new species, and the taxonomic status of this nominal species requires further clarification.
Johnius is the most diverse sciaenid genus whose monophyly has been confirmed [24; this study]. However, identification of species is challenging because of similarity in their external morphology and overlapping meristic counts .
A total of 88 Johnius COI sequences from “16” collected species (S1 Table) were included in the analyses. Without any a priori species hypothesis, based on the analyses of the COI data compiled in this study, we were able to determine 11 robustly supported OTUs (by both ABGD and GMYC analyses), and seven others that were further resolved by other data (genetic similarity, morphology, geography, etc.) (Fig 2). The obtained results led us to confirm the species status of Johnius macropterus, J. majan, J. dussumieri, J. distinctus, J. carouna, J. macrorhynus, J. trachycephalus, J. novaeguineae and J. trewavasae, and to formulate our suspicion of some taxonomic confusion within the genus.
Johnius fuscolineatus is often identified as J. amblycephalus as they are the only two Johnius species with stiff chin barbel, and co-occur in the Indian Ocean. Previous studies once suggested that J. fuscolineatus was a synonym of J. amblycephalus [65, 76]. However, Sasaki  reconsidered it as a valid species. In the COI gene tree, J. fuscolineatus is nested within J. amblycephalus (S1 Fig). The results from advanced species delimitation analyses show that J. fuscolineatus HQ945878 should belong to the GMYC determined OTU that also contains J. amblycephalus samples collected from the Indian Ocean (Dubai in Persian Gulf) (Fig 2). This OTU can be separated from the other identified J. amblycephalus OTUs by its differentiated genetic divergence (COI K2P = 5.2–11.1%; distinct RAG1 sequences; S3 Fig). Additionally, its sympatric distribution with the sister OTU in Indian Ocean (J. amblycephalus May689 collected from Perlis of the west coast of Peninsular Malaysia) (Fig 2) further indicates that it is reproductively isolated from the other OTUs. We thus consider it as a putative species. However, the taxonomy of J. fuscolineatus needs to be further investigated when correctly identified specimens of J. fuscolineatus become available, as the only sequence for the species was retrieved from GenBank.
Johnius borneensis and J. belangerii represent another two problematic species within the genus, because they resolved here as polyphyletic groups (Figs 2 and 3). “J. borneensis” DQ107818 from Queensland, Australia appears to be an independent lineage to the J. borneensis widely sampled in the IWP (Fig 2). Unfortunately, the sequence of this particular taxon was retrieved from GenBank, and we were not able to determine if it was a species misidentification.
Our phylogenetic results resolved J. belangerii as two independent lineages (Fig 2). The J. belangerii EF607410 (GenBank sequence; sample collected from Guangdong, South China Sea) is grouped with our undetermined Johnius sample (May 181) collected from Penang, Malaysia. Based on the results of our species delimitation analyses from the COI dataset, both samples belong to the same putative species (Fig 2). The J. belangerii samples collected in the Indian Ocean (IO), East China Sea (ECS), South China Sea (SCS) and its adjacent region (Coral Triangle: CT) form a monophyletic group and a potential species is inferred according to the species delimitation results and other considerations (Fig 2). Finally, another J. belangerii sequence retrieved from GenBank (accession no. HQ711868) is found to be grouped with our sampled J. heterolepis (identified based on the FAO identification key)  and J. grypotus KC491206 (GenBank sequence) in the COI gene tree (Fig 2). Their sequences are very similar (COI K2P = 0.2–1.4%) and should be considered to be the same putative species (Fig 2). These results indicate that J. grypotus KC491206 and J. belangerii HQ711868 retrieved from GenBank are probably errors in species identification.
Correct species taxonomy is necessary to study the phylogeny, biogeography, fisheries and conservation, and the combined molecular and morphological approach presented in this study assists with delimiting and predicting sciaenid species with some accuracy. From our analyses of 308 samples collected from different locations in the IWP for 51 sciaenid species, we infer a total of 60 species, of which 32 current morpho-species are confirmed. Cryptic and potential new species within Atrobucca nibe, Otolithes ruber, Protonibea diacanthus, Nibea soldado and Johnius amblycephalus were discovered. A new genus Pseudolarimichthys is herein proposed; Nibea and Austronibea are redefined. We also report problematic sequences deposited in public databases, likely due to misidentification of samples.
S1 Fig. Phylogenetic tree of the IWP sciaenids based on the COI gene inferred with the maximum-likelihood method using GTR+Γ+I model.
Branch lengths are proportional to inferred nucleotide substitutions. Numbers at nodes represent bootstrap values in percentage. Values below 70% are not shown. * indicates 100% bootstrap support. Species name in bold indicates the individual might be misidentified. Black bars indicate the species delimitation results match the recognizing species while white bars indicate the monophyletic groups contains potential cryptic species. The tree is rooted with Aplodinotus grunniens according to Lo et al. 
S2 Fig. Phylogenetic tree of the IWP sciaenids based on the RAG1 gene inferred with the maximum-likelihood method using GTR+Γ+I model.
Branch lengths are proportional to inferred nucleotide substitutions. Numbers at nodes represent bootstrap values in percentage. Values below 70% are not shown. * indicates 100% bootstrap support. Black bars indicate the species delimitation results match the recognizing species while white bars indicate the monophyletic groups contains potential cryptic species. The tree is rooted with Aplodinotus grunniens according to Lo et al. 
S3 Fig. Bayesian inference of COI gene tree with delineated OTUs.
White bars present the discordant results of both analyses while black bars indicate the consistent OTU clusters suggested by both delimitation analyses (i.e. robust results). Taxa name with different colors represent the geographical distribution of the samples; yellow: Indian Ocean (IO), green: South China Sea + Coral Triangle (SCS + CT), gray: Sahul Shelf and Australia (SAS) and blue: East China Sea (ECS).
S1 Table. Taxa, gene and online databases numbers and the sample locality of representative species.
The species name with cf. means that specimen is very similar and identified as that species. Asterisk shows the species inhabit freshwater. Sequences from GenBank are bold and underlined. o indicates the out-groups used in phylogenetic analysis.
S2 Table. Primers used in this study.
Abbreviations of genes: COI, Cytochrome oxidase subunit I; RAG 1, Activating gene 1. Reverse primers in italics.
S3 Table. Descriptive statistics of sequences and phylogenetic performance from COI and RAG1 dataset, respectively.
The authors wish to thank Hin-Kiu Mok, Kenji Saitoh, Ning Labbish Chao, National Museum of Marine Biology and Aquarium, Taiwan, and Museum and Art Gallery of the Northern Territory, Australia (via Michael Hammer) for the loan or gift of tissue samples, and Dr. Sébastien Lavoué, Dr. Barry C. Russell, and PCL’s Ph.D. committee members for their helpful discussions and comments on the relevance to this work. We would like to thank WJC’s lab members, especially Hsiu-Chen Lin, for assistance in the laboratory and sample management. We also wish to thank the lab members of Molecular Ecology Lab 307 in Universiti Sains Malaysia for arranging the field trip in Peninsula Malaysia. This work was supported by research grants from the Ministry of Science and Technology, Taiwan (MOST 101-2611-M-002-016-MY3 and MOST 104-2611-M-002-002-MY3 to WJC).
- Conceptualization: PCL WJC.
- Data curation: PCL WJC.
- Formal analysis: PCL.
- Funding acquisition: WJC.
- Investigation: PCL SHL WJC SAMN.
- Methodology: PCL WJC.
- Project administration: PCL WJC.
- Resources: PCL SHL WJC SAMN.
- Supervision: WJC.
- Validation: PCL SHL WJC.
- Visualization: PCL SHL WJC SAMN.
- Writing – original draft: PCL.
- Writing – review & editing: PCL SHL WJC SAMN.
- 1. Chen W-J, Mayden RL. A phylogenomic perspective on the new era of Ichthyology. Bioscience. 2010; 60: 421–432.
- 2. Knowles LL, Kubatko LS. Estimating species trees: an introduction to concepts and models. In: Knowles LL, Kubatko LS, editors. Estimating Species Trees: Practical and Theoretical Aspects. Hoboken: John Wiley and Sons 2011. pp. 1–14.
- 3. Puillandre N, Modica MV, Zhang Y, Sirovich L, Boisselier MC, Cruaud C, et al. Large-scale species delimitation method for hyperdiverse groups. Mol Ecol. 2012; 21: 2671–2691. pmid:22494453
- 4. Kekkonen M, Hebert PDN. DNA barcode-based delineation of putative species: Efficient start for taxonomic workflows. Mol Ecol Resour. 2014; 14: 706–715. pmid:24479435
- 5. Drummond AJ, Rambaut A. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol Biol. 2007; 7: 214–222. pmid:17996036
- 6. Heber PDN, Cywinska A, Ball SL, Waard JR. Biological identifications through DNA barcodes. Proc R Soc B Biol Sci. 2003; 270: 313–321.
- 7. Saez AG, Probert I, Geisen M, Quinn P, Young JR, Medlin LK. Pseudo-cryptic speciation in coccolithophores. Proc Natl Acad Sci USA. 2003; 100: 7163–7168. pmid:12759476
- 8. Vij S, Purushothaman K, Gopikrishna G, Lau D, Saju JM, Shamsudheen KV,et al. Barcoding of Asian seabass across its geographic range provides evidence for its bifurcation into two distinct species. Front Mar Sci. 2014; 1: 30.
- 9. Mok H- K, Gilmore RG. Analysis of sound production in estuarine aggregations of Pogonias cromis, Bairdiella chrysoura and Cynoscion nebulosus sciaenidae. Bull Inst Zool Acad Sinica. 1983; 22: 157–186.
- 10. Eschmeyer WN, Fong JD. Species by Family/Subfamily. Catalog of Fishes. 2017. Available from: http://researcharchive.calacademy.org/research/ichthyology/catalog/SpeciesByFamily.asp.
- 11. Nelson JS. Fishes of the World. 4th ed. New York: John Wiley & Sons Press; 2006.
- 12. Froese R, Pauly D. FishBase. World Wide Web electronic publication. 2017. Aviavilable from: http://www.fishbase.org.
- 13. Eschmeyer WN, Fricke R. Genera, species, references. Catalog of fishes. 2017. Available from: http://research.calacademy.org/research/ichthyology/catalog/fishcatmain.asp.
- 14. FAO yearbook. Fishery and Aquaculture Statistics. Rome: Food and Agriculture Organisation of the United Nations; 2016.
- 15. Sadovy Y, Cheung WL. Near extinction of a highly fecund fish: The one that nearly got away. Fish Fish. 2003; 4: 86–99.
- 16. Piner KR Jones CM. Age, growth and the potential for growth overfishing of spot from the Chesapeake Bay, eastern USA. Mar Freshw Res. 2004; 55: 553–560.
- 17. Vasconcellos AV, Lima D, Bonhomme F, Vianna M, Solé-Cava AM. Genetic population structure of the commercially most important demersal fish in the Southwest Atlantic: The whitemouth croaker (Micropogonias furnieri). Fish Res. 2015; 167: 333–337.
- 18. Costa MDP, Muelbert JH, Moraes LE, Vieira JP, Castello JP. Estuarine early life stage habitat occupancy patterns of whitemouth croaker Micropogonias furnieri (Desmarest, 1830) from the Patos Lagoon, Brazil. Fish Res. 2014; 60: 77–84.
- 19. Mirimin L, Macey B, Kerwath S, Lamberth S, Merwe AB, Cowley P, et al. Genetic analyses of overfished silver kob Argyrosomus inodorus (Scieanidae) stocks along the southern African coast. Fish Res. 2016; 176: 100–106.
- 20. Mirimin L, Kerwath S, Macey B, Lamberth SJ, Cowley PD, Merwe AB, et al. Genetic analyses reveal declining trends and low effective population size in an overfished South African sciaenid species, the dusky kob (Argyrosomus japonicus). Mar Freshw Res. 2016; 67: 266–276.
- 21. Dulvy NK, Sadovy Y, Reynolds JD. Extiction vulnerability in marine populations. Fish Fish. 2003; 4: 25–64.
- 22. Silberschneider V, Gray CA. Synopsis of biological, fisheries and aquaculture-related information on mulloway Argyrosomus japonicus (Pisces: Sciaenidae), with particular reference to Australia. J Appl Ichthyol. 2008; 24: 7–17.
- 23. IUCN. The IUCN Red List of Threatened Species. 2004. Available from: http://www.iucnredlist.org.
- 24. Lo P-C, Liu S-H, Chao NL, Nunoo FKE, Mok H-K, Chen W-J. A multi-gene dataset reveals a tropical New World origin and Early Miocene diversification of croakers (Perciformes: Sciaenidae). Mol Phylogenet Evol. 2015; 88: 132–143. pmid:25848970
- 25. Han ZQ, Gao TX, Yanagimoto T, Sakurai Y. Genetic population structure of Nibea albiflora in Yellow Sea and East China Sea. Fish Sci. 2008;74: 544–552.
- 26. Han ZQ, Gao TX, Yanagimoto T, Sakurai Y. Deep phylogeographic break among white croaker Pennahia argentata (Sciaenidae, Perciformes) populations in North-western Pacific. Fish Sci. 2008; 74: 770–780.
- 27. Xu D, Lou B, Shi H, Geng Z, Li S, Zhang Y. Genetic diversity and population structure of Nibea albiflora in the China Sea revealed by mitochondrial COI sequences. Biochem Syst Ecol. 2012; 45: 158–165.
- 28. Lin LS, Ying YP, Han ZQ, Xiao YS, Gao TX. AFLP analysis on genetic diversity and population structure of small yellow croaker Larimichthys polyactis. Afr J Biotechnol. 2009; 8: 2700–2706.
- 29. Iwatsuki Y, Jawad LA, Al-Mamry JM. Johnius (Johnius) majan sp. nov., a sciaenid fish (Pisces: Sciaenidae) from Oman, Indian Ocean. Ichthyol Res. 2012; 59: 151–155.
- 30. Seah YG, Hanafi N, Mazlan ABDG, Chao NL. A new species of Larimichthys from Terengganu, east coast of Peninsular Malaysia (Perciformes: Sciaenidae). Zootaxa. 2015; 3956: 271–280. pmid:26248918
- 31. Shen S-C, Lee S-C, Shao K-T, Mok H-K, Chen C-W, Chen C-T. Sciaenidae. In: Fishes of Taiwan. Taipei: Department of Zoology, National Taiwan University; 1993. pp.374–385.
- 32. Sasaki K. Sciaenidae. In: Carpenter KE, Niem VH, editors. FAO Species Identification Guide for Fishery Purposes. The Living Marine Resources of the Western Central Pacific. Volume 5. Rome: FAO; 2001. pp. 3117–3174.
- 33. Séret B, Opic P. Poissons de Mer de l’Ouest Africain Tropical. Paris: ORSTOM; 1990.
- 34. López JA, Chen W- J, Ortí G. Esociform phylogeny. Copeia. 2004; 2004: 449–464.
- 35. Ward RD, Zemlak TS, Innes BH, Last PR, Hebert PDN. DNA barcoding Australia’s fish species. Phil Trans R Soc B. 2005; 360: 1847–1857. pmid:16214743
- 36. Durand JD, Chen WJ, Shen KN, Fu C, Borsa P. Genus-level taxonomic changes implied by the mitochondrial phylogeny of grey mullets (Teleostei: Mugilidae). Comptes Rendus Biol. 2012; 335: 687–697.
- 37. Roxo FF, Ochoa LE, Costa-Silva GJ, Oliveira C. Species delimitation in Neoplecostomus (Siluriformes: Loricariidae) using morphologic and genetic approaches. DNA Barcodes. 2015; 3: 110–117.
- 38. Hung K-W, Russell BC, Chen W-J. Molecular Systematics of Threadfin Breams and Relatives (Teleostei, Nemipteridae). Zool Scr. 2017;
- 39. Rambaut A. Se-Al: sequence alignment editor, version 2.0a11. Edinburgh: Institute of Evolutionary Biology. 2002. http://tree.bio.ed.ac.uk/software/seal/.
- 40. Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004; 32: 1792–1797. pmid:15034147
- 41. Swofford DL. PAUP*. Phylogenetic Analysis Using Parsimony (*and Other Methods). Version 4. Sunderland, Massachusetts, USA: Sinauer Associates; 2003.
- 42. Felsenstein J. Evolutionary trees from DNA sequences: A maximum likelihood approach. J Mol Evol. 1981; 17: 368–376. pmid:7288891
- 43. Stamatakis A. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics. 2006; 22: 2688–2690. pmid:16928733
- 44. Yang Z. Estimating the pattern of nucleotide substitution. J Mol Evol. 1994; 39: 105–111. pmid:8064867
- 45. Felsenstein J. Confidence limits on phylogenies: an approach using the bootstrap. Evolution. 1985; 39: 783–791.
- 46. Miller MA, Pfeiffer W, Schwartz T. Creating the CIPRES Science Gateway for inference of large phylogenetic trees. Proceedings of the gateway computing environments workshop (GCE); New Orleans 2010. 1–8.
- 47. Benson DA, Karsch-Mizrachi I, Lipmam DJ, Ostell J, Rapp BA, Wheeler DL. GenBank. Nucleic Acids Res. 2000; 28: 15–18. pmid:10592170
- 48. Ratnasingham S, Hebert PDN. BOLD: The Barcode of Life Data System (www.barcodinglife.org). Mol Ecol Notes. 2007; 7: 355–364. pmid:18784790
- 49. Shao K- T. Taiwan Wildlife Genetic Material Cryobank. Taipei: Biodiversity Research Center, Academia Sinica. 2010. Available from: http://cryobank.sinica.edu.tw.
- 50. Puillandre N, Lambert A, Brouillet S, Achaz G. ABGD, Automatic Barcode Gap Discovery for primary species delimitation. Mol Ecol. 2012; 21: 1864–1877. pmid:21883587
- 51. Jukes TH, Cantor CR. Evolution of protein molecules. In: Munro HN, editor. Mammalian Protein Metabolism. New York: Academic Press; 1969. pp. 21–132.
- 52. Kimura M. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol. 1980; 16: 111–120. pmid:7463489
- 53. Fujisawa T, Barraclough TG. Delimiting species using single-locus data and the Generalized Mixed Yule Coalescent approach: a revised method and evaluation on simulated data sets. Syst Biol. 2013; 62: 707–724. pmid:23681854
- 54. RStudio Team. RStudio: Integrated Development for R. Boston, MA: RStudio Inc.; 2015. Available from: http://www.rstudio.com/.
- 55. R Core Team. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing; 2015. Available from: https://www.r-project.org.
- 56. Paradis E, Claude J, Strimmer K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics. 2004; 20: 289–290. pmid:14734327
- 57. Ezard T, Fujisawa T, Barraclough T. SPLITS: SPecies LImits by Threshold Statistics. version 1. R Packag; 2009.
- 58. Drummond AJ, Suchard MA, Xie D, Rambaut A. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol Biol Evol. 2012; 29: 1969–1973. pmid:22367748
- 59. Carstens BC, Pelletier TA, Reid NM, Satler JD. How to fail at species delimitation. Mol Ecol. 2013; 22: 4369–4383. pmid:23855767
- 60. Queiroz K. Species concepts and species delimitation. Syst Biol. 2007; 56: 879–886. pmid:18027281
- 61. Coyne JA, Orr HA. Speciation. Sunderland, Massachusetts, MA, USA: Sinauer Associates; 2004.
- 62. Santos S, Hrbek T, Farias IP, Schneider H, Sampaio I. Population genetic structuring of the king weakfish, Macrodon ancylodon (Sciaenidae), in Atlantic coastal waters of South America: Deep genetic divergence without morphological change. Mol Ecol. 2006; 15: 4361–4373. pmid:17107470
- 63. Hubbs CL, Lagler KF. Fishes of the Great Lakes Region (Revised). In: Smith GR, editors. Michigan, USA: University of Michigan Press.
- 64. Lal Mohan RS, Trewavas E, Whitehead PJP. Sciaenidae. In: Fisher A, Bianchi G, editoers. FAO Species Identification Sheets for Fishery Purposes: Western Indian Ocean (Fishing Area 51) Vol 4. Food and Agriculture Organization of the United Nations; 1984.
- 65. Trewavas E. The sciaenid fishes (croakers or drums) of the Indo-West-Pacific. Trans Zool Soc Lond. 1977; 33: 253–541.
- 66. Lakra WS, Verma MS, Goswami M, Lal KK, Mohindra V, Punia P, et al. DNA barcoding Indian marine fishes. Mol Ecol Resour. 2011; 11: 60–71. pmid:21429101
- 67. Esselstyn JA, Evans BJ, Sedlock JL, Khan FAA, Heaney LR. Single-locus species delimitation: a test of the mixed Yule-coalescent model, with an empirical application to Philippine round-leaf bats. Proc R Soc B Biol Sci. 2012; 279: 3678–3686.
- 68. Paz A, Crawford AJ. Molecular-based rapid inventories of sympatric diversity: A comparison of DNA barcode clustering methods applied to geography-based vs clade-based sampling of amphibians. J Biosci. 2012; 37: 887–896. pmid:23107924
- 69. Sauer J, Hausdorf B. A comparison of DNA-based methods for delimiting species in a Cretan land snail radiation reveals shortcomings of exclusively. Cladistics. 2012; 28: 300–316.
- 70. Talavera G, Dincă V, Vila R. Factors affecting species delimitations with the GMYC model: insights from a butterfly survey. Methods Ecol Evol. 2013; 4: 1101–1110.
- 71. Sasaki K, Kailola PJ. Three new Indo-Australian species of the sciaenid genus Atrobucca, with a reevaluation of generic limit. Jpn J Ichthyol. 1988; 35: 261–277.
- 72. Pringgenis D, Susilowati R. Highly commercial fisheries tawar fish: molecular analysis DNA mitochondrial COI gene sequence and proximate analysis from malacca Strait, Riau. J Teknol. 2016; 2: 33–38.
- 73. Desse J, Desse-Derset N. Un grand Sciaenidae (Teleostei: Perciformes) du genre Megalonibea présent sur la côte du balouchistan pakistanais? Cybium. 1999; 23: 345–352.
- 74. Kuang Y. The Freshwater and Estuaries Fishes of Hainan Island. Guangzhou: Guangdong Science and Technology Press, China; 1986. pp. 372.
- 75. Jayaprakash AA. A record of Nibea chui Trewavas from India. Indian J Fish. 1975; 22: 259–261.
- 76. Sasaki K. Sciaenid fishes of the Indian Ocean (Teleostei, Perciformes). Mem Fac Sci Kochi Univ Ser D, Biol. 1996; 16/17: 83–96.
- 77. Sasaki K. Resurrection of two East African species of Johnius (Perciformes, Sciaenidae). Ichthyol Res. 1997; 44:311–315.