Ge\\ Nature YS) Conservation Nature Conservation 56: 19-36 (2024) DOI: 10.3897/natureconservation.56.111745 Research Article Phylogeography and genetic population structure of the endangered bitterling Acheilognathus tabira tabira Jordan & Thompson, 1914 (Cyprinidae) in western Honshu, Japan, inferred from mitochondrial DNA sequences Gen Ito'2©, Naoto Koyama?, Ryota Noguchi?, Ryoichi Tabata’, Seigo Kawase’, Jyun-ichi Kitamura?25, Yasunori Koya® nD oF WO NYP Center for Biodiversity Science, Ryukoku University, 1-5 Yokotani, Seta Oe-cho, Otsu, Shiga 520-2194, Japan Japan Watershed Conservation Network, 1281 Chuma-cho, Matsusaka, Mie 519-2143, Japan TAKAYASU Study group of Japanese rose bitterling, 4-28 Koorigawa, Yao, Osaka 581-0872, Japan Lake Biwa Museum, 1091 Oroshimo, Kusatsu, Shiga 525-0001, Japan Mie Prefectural Museum, 3060 Isshinden-kouzubeta, Tsu, Mie 514-0061, Japan Faculty of Education, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan Corresponding author: Gen Ito (sakurahayabusa6647@gmail.com) OPEN Qaccess Academic editor: Valter Azevedo-Santos Received: 28 August 2023 Accepted: 4 July 2024 Published: 8 August 2024 ZooBank: https://zoobank. org/94926935-451 5-4A64-80DD- 990C35832BB1 Citation: Ito G, Koyama N, Noguchi R, Tabata R, Kawase S, Kitamura J-i, Koya Y (2024) Phylogeography and genetic population structure of the endangered bitterling Acheilognathus tabira tabira Jordan & Thompson, 1914 (Cyprinidae) in western Honshu, Japan, inferred from mitochondrial DNA sequences. Nature Conservation 96: 19-36. https://doi.org/10.3897/ natureconservation.56.111745 Copyright: © Gen Ito et al. This is an open access article distributed under terms of the Creative Commons Attribution License (Attribution 4.0 International - CC BY 4.0). Abstract We examined the genetic population structure of the endangered freshwater cyprinid Acheilognathus tabira tabira in the Japanese archipelago, which has only been analyzed in limited sampling in previous studies, based on cytochrome b region of the mitochon- drial gene. We confirmed the existence of the same three lineages determined in the previous study, the natural distribution area of Lineage | and II+lIl were considered to be the Seto Inland Sea and Ise Bay regions, respectively. Furthermore, the Seto Inland Sea region population was divided into five groups inhabiting neighboring water sys- tems using the spatial analysis of molecular variance (SAMOVA). We estimated that populations in the Seto Inland Sea region migrated through a single paleowater system during the last glacial period and were then separated and genetically differentiated due to marine transgression. The Yoshino River system population was estimated to be a non-native population because it belonged to the same group as the Lake Biwa-Yodo River system, which is the only separate water system across the Seto Inland Sea. This study provides new evidence of genetic differentiation in A. t. tabira populations with- in the Seto Inland Sea region, where genetic differentiation has not been detected in previous studies, corresponding to five different groups by significantly increasing the number of individuals and sites compared with previous studies. Therefore, we propose these five groups as conservation units in the Seto Inland Sea region. Key words: Artificial introduction, biogeography, conservation, Cytochrome b, SAMOVA Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira Introduction The distribution of many freshwater fishes of the Japanese archipelago has been strongly influenced by geomorphic changes such as uplift of mountains (e.g., Watanabe et al. 2017). In particular, western Japan, including the Ise Bay and Seto Inland Sea regions, was significantly affected by mountainous up- lift and transgression during the Pleistocene (Ota et al. 2004; Machida et al. 2006). It is known that these geomorphic changes have caused populations of freshwater fish to become fragmented and genetically differentiated within localized areas (Watanabe et al. 2017). Previous phylogeographic and genet- ic population structure studies of freshwater fishes in these regions suggest that geological events, such as uplift of mountains and marine transgression that influence the distribution of freshwater fishes may differ among species (Kitagawa et al. 2001; Watanabe et al. 2010, 2014; Tominaga et al. 2016, 2020; Nakagawa et al. 2016; Ito et al. 2019; Ito and Koya 2022). Identifying the phylo- geographic patterns and genetic population structure of each species inhabit- ing the same region is an effective approach to identify the factors shaping the genetic diversity of freshwater fish (Avise 2000). The tabira bitterling, Acheilognathus tabira Jordan & Thompson, 1914 (Cy- prinidae: Acheilognathinae), is a freshwater fish endemic to Honshu, Japan. It has been classified into five subspecies, mainly due to their different nupital color patterns (Arai et al. 2007). Each subspecies has an allopatric distribution, differs in egg shape, and is clearly distinguishable by mitochondrial DNA (mtD- NA) and nuclear DNA (Arai et al. 2007; Kitamura et al. 2012). Therefore, each subspecies is thought to have followed its own evolutionary path. The white tabira bitterling, Acheilognathus tabira tabira Jordan & Thompson, 1914, is a subspecies of A. tabira. The natural distribution range of A. t. tabira is the Ise Bay waters and the Seto Inland Sea regions on the Pacific side, with some rivers flowing into the Sea of Japan in western Japan (Kitamura and Uchiyama 2020). Previous phylogeographical studies of A. t. tabira have identified three lineages (Kitamura et al. 2012; Umemura et al. 2012), of which two are thought to be naturally distributed in the Ise Bay region (Nobi Plain groups | and II), and one lineage is thought to occur in the Seto Inland Sea region (Kinki-Sanyo group). However, the populations of the Seto Inland Sea region analyzed in previous studies were restricted to only two river systems; therefore, knowledge of the ranges of natural distribution in each lineage of A. t. tabira is incomplete. In addition, A. t. tabira is listed as Endangered on the Red List of Japan be- cause its population has been decreasing owing to improvements in rivers and agricultural canals (Ministry of the Environment of Japan 2020). However, the Kinki-Sanyo group has been artificially introduced into several regions as a re- sult of incidental introductions associated with fishery releases of Plecoglossus altivelis altivelis (Temminck & Schlegel, 1846) and private releases, which raises concerns about the impact of genetic introgression on the native population of A. t. tabira (Umemura et al. 2012; Kumagai and Hagiwara 2013; Kitamura and Uchi- yama 2020; Ito et al. 2021). In the Ise Bay region, the non-native lineage known as the Kinki-Sanyo group has been artificially introduced into the Nagara, Kiso, and Kushida Rivers, which are the natural distribution areas of the Nobi Plain Groups | and II (Kitamura et al. 2012; Umemura et al. 2012; Kitamura and Uchiyama 2020). Therefore, the native population of A. t. tabira in the Ise Bay region may have Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 20 Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira become extinct due to genetic introgression (Kitamura and Uchiyama 2020). In the Yoshino River system in northeastern Shikoku, located in the Seto Inland Sea region, the past freshwater fish fauna is unknown; therefore, it has been diffi- cult to determine whether the population of A. t. tabira is naturally distributed or originated from artificial introduction (Kitamura and Uchiyama 2020). Phylogeo- graphic patterns and genetic population structures can help identify whether the population is naturally distributed or originates from non-native populations (Mi- yake et al. 2011; Umemura et al. 2012; Matsuba et al. 2014; Uemura et al. 2018; Tominaga et al. 2020; Ito et al. 2021, 2022). Therefore, understanding the phylo- geographic patterns and genetic population structure across the natural distribu- tion of A. t. tabira is essential for promoting appropriate conservation activities. In the present study, we attempted to elucidate the factors responsible for distribution patterns of A. t. tabira by estimating its phylogeographic and ge- netic population structures covering its whole distribution range using the cy- tochrome b (cytb) region of the mtDNA. In addition, we discuss the artificial in- troduction and conservation units of A. t. tabira based on the results obtained. Materials and methods Sample collection In total, 140 individuals were collected from 12 localities in 10 river systems in the Seto Inland Sea and Ise Bay regions from 2015 to 2020 (Fig. 1, Suppl. material 1), covering the whole geographic range of A. t. tabira. The unsampled sites in this study are the Nagara, Kiso, and Kushida river systems investigated by previous studies (Kitamura et al. 2012; Umemura et al. 2012), and rivers that flow into the Sea of Japan, which are probably extinct. For the populations in the Nagara, Kiso, and Kushida River, we cited base sequence data from previous studies (Kitamura et al. 2012; Umemura et al. 2012, Table 1). Additionally, a captive population from the Gifu World Freshwater Aquarium was included in this study. This captive pop- ulation is believed to have originated from a population collected and cultured by a citizen from the Nagara River system in the Ise Bay area, which was donated to the Gifu World Freshwater Aquarium in 2004 (Koki Ikeya, personal communica- tion). The mtDNA lineage of this population is described as native to the Ise Bay region by Mukai (2019). However, it is not indicated whether it belongs to the Nobi Plain group | or Il. Individual bitterling were collected using hand nets and fishing methods. Each specimen was subjected to caudal fin clipping, and the remaining specimens were fixed in 10% formalin and preserved in 70% ethanol. For habitat conservation, the number of individuals collected was limited to 20 or fewer. The fin clips were preserved in 99% ethanol and stored at -20 °C. The specimens were registered with the Gifu and Mie Prefectural Museum along with collection site information (GPM-Z-22109, MIE-Fi3500, 3506-3512, 3519-3534, 3536-3540, 3543-3579, 3581-3604, 3606-3624, 3626, 3630-3633, 3718, 4272). mtDNA analysis Total genomic DNA was extracted from a portion of each caudal fin using the Kaneka Easy DNA extraction kit version 2 (Kaneka, Hyogo, Japan) or the DNeasy Blood & Tissue Kit (Qiagen, Hilden, Germany). Total genomic DNA was Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 21 Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira 133.00 134.00 135.00 136.00 137.00 a A. t. tohokuensis (¥p \ O Lineage | olf : *Nagara R. S @ @ Lineage |! O Lineage 11! € | "Pacific Ocean |yp.s A hike » *Kiso R. A. t. tabira he & | 6 Kako R. | | lle 7 YoshiiR. Si © Muko R-@ Co gk Hf | 13)A captive population 5 ee ra of the Aquarium 8 Asahi R: afi 35.00 7 11 Takahashi R. , AR? og . 10 Kurashiki R. e Ph §©=6._: 2-4 Yodo R.. *Kushida 12-Yoshino R. Figure 1. Sampling localities of Acheilognathus tabira tabira. The asterisks indicate localities used by Kitamura et al. (2012), Umemura et al. (2012), and Kitamura and Uchiyama (2020). Circles show mtDNA lineages (see Fig. 2). Gray areas represent the estimated natural distribution area of the five subspecies of A. tabira based on Kitamura et al. (2012). This altitude map was used with permission from the Geospatial Information Authority of Japan (https://maps.gsi.go.jp/) and digital national and information of Ministry of Land, Infrastructure, Transport and Tourism (https://nlftp.mlit.go.jp). used to amplify DNA fragments using polymerase chain reaction (PCR). For PCR, the following forward primer was used: L14690-Cb-AH, 5'-GGT CAT AAT TCT TGC TCG GA-3' (Kitanishi et al. 2016), and for the reverse primers H15913- Thr-AH, 5'-CCG ATC TTC GGA TTA CAA GAC CG-3' (Kitanishi et al. 2016), or Cytb-Rev, 5'-GAT CTT CGG ATT ACA AGA CC-3' (Hashiguchi et al. 2006). The sequencing protocol was previously described by Ito et al. (2020). All sequenc- es were deposited in the DNA Data Bank of Japan (DDBJ), European Nucleo- tide Archive (EMBL), and GenBank databases under the accession numbers EG7753:7 =“ C77 5s02. Sequence and phylogenetic analyses Multiple alignments of nucleotide sequences were performed using MUSCLE (Edgar 2004). For the phylogenetic analysis, nucleotide sequence data for A. t. tabira were obtained from DDBJ, EMBL, and GenBank (AB620138, AB620141, AB620150, AB620159, AB759881-AB759890, and LC578851, Kitamura et al. 2012; Umemura et al. 2012; Ito et al. 2021; Table 1). In addition, we used Acheilognathus tabira jordani Arai, Fujikawa & Nagata, 2007, a sister group of A. t. tabira, as outgroups (AB620149, and AB620156, Kitamura et al. 2012). Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 yy) Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira Table 1. Sampling location numbers and names and GenBank accession numbers of samples. Species name Achellognathus tabiratabira | __Lake Biwa, Shiga, Japan —~—=ABG20198 Ast. tabira ~ Harai River Mie, Japan ABOZOTAT = Ast. tabira ~ Yoshii R, Okayama, Japan| AB620150. Aut. tabira ~ Kizu, Kyoto, Japan ABO201S9 Ast. tabira Kiso, Gifu. Japan —ABT59@1. =~ Ast. tabira Kiso, Gifu. Japan —==CABTSOBB2 Ast. tabia Kiso, Gifu, Japan| AB75963. = Ast. tabira KisoR, Gifu Japan ABTSOBGA Ast. tabia ~ Kiso, Gifu. Japan ——=—AB7598®S A.t. tabira Nagara R., Gifu, Japan - AB759886 = - A.t. tabira Nagara R., Gifu, Japan — AB759887, Ast. tabira ~NagaraR, Gifu, Japan = ABTS9BSB A.t. tabira Nagara R., Gifu, Japan AB759889 A.t. tabira Nagara R., Gifu, Japan AB759890 A.t. tabira Northern district, Mie, Japan LC578851 A.t. tabira Lake Biwa, Shiga, Japan EST Soe 1 Act. taba Act. taba Act taba Act. taba Act taba Act. taba 7 —| a Act taba At. taba Act. taba Act. taba Act. taba Act. taba At. taba At. taba At taba Act. taba At. taba Act. taba Act taba Act. taba Act taba Act. taba Act. taba 125 Act. taba At taba At. taba 128 A. tabira At. taba At. taba r31 Act. taba Ast taba Act. taba 134 Yodo R. Kyoto, Japan —|—«LC775351__ A.t. tabira Yodo R., Kyoto, Japan LOZZ53S1 $5 A.t. tabira Gifu R., Japan LC775352 A.t. jordani Oohara R., Shimane, Japan AB620149 Fo A.t. jordani Kuzuryu R., Fukui, Japan AB620156 = Cd Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 Reference Kitamura et al. Kitamura et al. Kitamura et al. Kitamura et al. Umemura et al Umemura et al Umemura et al Umemura et al Umemura et al Umemura et al Umemura et al Umemura et al Umemura et al Umemura et al Ito et al. 2021 This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study This study Kitamura et al. 2012 Kitamura et al. 2012 2012 2012 2012 2012 s2012 £2012 2OAZ . 2012 . 2012 . 2012 . 2012 F2012 . 2012 22012 23 Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira Phylogenetic analyses were conducted using maximum likelihood (ML) and Bayesian inference (BI) methods. Search for the best evolutionary model each partition and ML analyses were performed using IQ-TREE 2.2.2.6 (Minh et al. 2020), with the TIM2 + F + |, K2P + I, and F81 + F models for the first, sec- ond, and third codon positions as selected by ModelFinder (Chernomor et al. 2016; Kalyaanamoorthy et al. 2017) based on the Bayesian information cri- terion (BIC). The reliability of each internal branch was evaluated using Shi- modaira-Hasegawa-like approximate likelihood ratio test (SH-aLRT, Guindon et al. 2010) and ultrafast bootstrap (UFBoot, Hoang et al. 2018) and with 1000 replicates. In this study, according to the manual, support values of 80% or higher for SH-aLRT and 95% or higher for UFBoot were considered as high support values. BI analyses were performed using MrBayes v3.2.7a (Ronquist et al. 2012), with the HKY + I, K80 + 1+ G4, F81 models for the first, second, and third codon positions as selected by ModelTest-NG (Darriba et al. 2017) based on the BIC. The MCMC analyses were performed using the following settings: ngen = 10000000, sample freq = 100, and burnin = 25000. Statistical parsimo- ny networks were constructed using TCS v1.2.1 (Clement et al. 2000). In this study, the Bayesian posterior probability (PP) of 80% or higher was considered to indicate high support values. Genetic structure analyses In populations of the Kinki-Sanyo region, we calculated genetic differentiation, estimated by genetic differentiation coefficient (®,,; Excoffier et al. 1992) using Arlequin version 3.5 (Excoffier and Lischer 2010). Critical significance levels for multiple testing were corrected using the sequential Bonferroni procedure (Rice 1989). In addition, we identified groups of populations using the spa- tial analysis of molecular variance version 2.0 (SAMOVA 2.0) (Dupanloup et al. 2002). To detect the number K of groups with the largest F., value, K was user-defined between 2 and 8, and 100 independent simulated annealing pro- cesses were performed in each run. However, collection sites with two or few- er individuals (the Kurashiki and Takahashi River systems) were excluded from the ®,, and SAMOVA. Estimation of divergence time The divergence times of intraspecific lineage of Acheilognathus tabira tabi- ra were estimated using BEAST ver. 2.7.6 (Bouckaert et al. 2019). We used sequences of A. t. jordani, A. cyanostigma Jordan & Fowler, 1903, and Opsa- riichthys platypus (Temminck & Schlegel, 1846) as outgroups. We adopted the estimated clock rate of cytb (0.76%, Zardoya and Doadrio 1999) that has been applied to the Acheilognathinae (Tominaga et al. 2020; Miyake et al. 2021). Divergence times were calibrated using the first appearance in the fossil re- cord of Acheilognathinae from the early Miocene (ca. 20 Mya) found in Japan (Yasuno 1984). Constraints of the fossil were specified as a log-normal distri- bution, ranging from 16.5-23.0 Mya in the 95% range. Estimation was carried out using an optimised relaxed clock and applied the substitution model HKY+1 selected by the BIC in ModelTest-NG. MCMC chains were run for 50000000 generations and sampled every 1000 generations, with the exclusion of the first Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 24 Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira 5000000 generations as burn-in. The convergence of MCMC was checked by calculating ESS values (> 200) using Tracer ver. 1.7.2 (Rambaut et al. 2018). TreeAnnotator ver. 2.7.6 in the BEAST package was used to obtain a maximum credibility tree with the annotation of average node ages and 95% highest pos- terior density (HPD) interval. The phylogenetic tree was visualized with FigTree ver. 1.4.4 (Rambaut 2018). Results Genetic structure We sequenced 1069-bp mtDNA cytb gene nucleotide fragments from 140 indi- viduals of A. t. tabira collected from 10 river systems and the captive population. As a result, 36 haplotypes were detected (T1-36), 5 of which [T1: AB759882 (Kiso River system), T3: AB759884 (Kiso R.), T4: AB620138, AB620159, and LC578851 (Lake Biwa, Kizu R., Kiso R., and northern Mie Prefecture), T23: AB759887 (Nagara R.), and T36: AB759888 (Nagara R.)] had been detected in previous studies (Kitamura et al. 2012; Umemura et al. 2012; Ito et al. 2021). The topologies of the ML and BI phylogenetic trees were partially different (Fig. 2, Suppl. material 2). In the ML tree, Lineage | and IIl were supported as monophyletic with high values, respectively (SH-aLRT > 94%, UFBoot > 96%). The monophyletic clade of Lineage | and III was supported with high values (88.5%) by SH-aLRT, however with slightly lower value (88%) by UFBoot. In the BI tree, the monophyletic clade of Lineage | was supported by PP with a low val- ue (0.54), while Lineage III was supported with a high value (0.99). The mono- phyletic clade of Lineage | and II was not supported, whereas the monophyletic clade of Lineage II and IIl was supported, albeit with a lower value (0.69). In addition, Lineage Ill was further subdivided into two sub-lineages: Sub-lineages IIl-i and ii in the ML and BI trees (SH-aLRT = 87.4%, UFBoot = 95%, and PP = 0.96, Fig. 2). In Lineage I, Haplotypes T1-12 and T35 were mainly detected in Lake Biwa and the Yodo River system (Loc. 1-4), four of which (T3, T4, T11, and T12) were detected in the Yoshino River system (Loc. 12). Haplotypes L13—20 were detected only in the Muko River system (Loc. 5). Haplotypes T21 and T22 were only detected in the Kako River system (Loc. 6). Haplotype T23 was detected in the Kako, Yoshii Asahi, Sasagase, and Takahashi River systems (Loc. 6-9, and 11). Haplotypes T24-34 were detected in the Yoshii Asahi, Sasagase, Kurashi- ki, and Takahashi River systems (Loc. 7-11). Haplotype T36 in Lineage II was detected only in a captive Gifu World Freshwater Aquarium population collect- ed from an unknown river system in Gifu Prefecture (Loc. 13). In the statistical parsimony network, A. t. tabira exhibits a bottleneck pattern (Fig. 2). Lineage | was represented by a star-like pattern centered on the ances- tral haplotype T4 (Fig. 2). The results of the pairwise ©, among the local populations are shown in Table 2. The ®,, values of Yodo1 and Muko populations showed significant genetic differentiation between populations, excluding Yodo3 and Biwa pop- ulations, respectively (®,, 0.235-392, 0.269-0.415; P < 0.05). The ®,, value of the Yoshino population also showed significant genetic differentiation between Kako, Yoshii, Asahi, and Sasagase populations (®,, 0.191—-0.301: P < 0.05). Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 25 Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira @Group A (Lake Biwa-Yodo R.) (Group B (Tributary A of Yodo R.) @Group C (Muko R.) @Group D (Kako R.) @Group E (Yoshii, Asahi, Sasagase R.) Lineage | Sub-lineage III-ii Sub-lineage III-i 87.9/92/0. 92.9/-/* 4195/0.96 AB620141, Kushida R. & Sub-lineage IIl-ii 736: 48759888, NagaraR.(®) [fj Lineage II (The Ise Bay region) AB62 89 85.8/95/0.97 84.5/96/0.85 or T21 (5) T16 (3) 91.7/-/1.00 14 (1) 82.8/-/* T15 (1) 82.8/-/* PP T30 (2) h T22 (2) AB759886, Nagara R. 723: AB759887, Nagara R. (27) 728 (2) AB759885, Kiso R. 718 (1) T20 (4) T19(1) T13 (1) T17 (3) Lineage | TA (The Seto Inland Sea region) 732 (1) T33 (1) 729 (1) AB620150, Yoshii R. T2 (2) T10(1) T6 (1) T8 (1) 726 (1) T9 (1) 725 (1) 731 (1) T4: AB620138, Kiso R., etc. (21) T3: AB759884, Kiso R. (4) T12 (5) T5 (11) AB759881, Kiso R. 17 (4) T11 (2) T1: AB759882, Kiso R. (1) 4.9) AB759883, Kiso R. T27 (4) 734 (1) T35 (2) AB759889, Nagara R. mu AB759890, Nagarar. mm SUb-lineage Ill-i I Lineage Ill (The Ise Bay region) 0149: A. t. jordani AB620156: A. t. jordani Figure 2. Maximum likelihood (ML) tree of the 1069-bp cytochrome b gene sequences of Acheilognathus tabira tabira individuals from the Seto Inland Sea and Ise Bay regions. Numbers at nodes indicate Shimodaira-Hasegawaz-like ap- proximate likelihood ratio test values (left), ultrafast bootstrap values (middle) in the ML tree, and Bayesian posterior probabilities (right) in Bayesian inference tree. Each value is indicated when it exceeds 80%, 95%, and 0.80. Numbers in parentheses indicate the number of specimens. The parentheses after each Lineage name indicate the natural distribu- tion area. The statistical parsimony network of A. t. tabira is shown to the left of the tree. Pie charts of Lineage | indicate the relative frequencies of haplotypes of the five groups defined by SAMOVA. Table 2. Pairwise ®,, among local populations of Acheilognathus tabira tabira collected from the Seto Inland Sea region. Site no. Lake Biwa Yodo R. 1 Yodo R. 2 Yodo R. 3 Muko R. Kako R. Yoshii R. Asahi R. [] OO WIN A a PB WN) A 2 Yoshino R. *P < 0.05; **P < 0.001 Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 Sasagase R. Collection site Group > >rimimim volo > >|w 1 0.235* 0.042 0.019 0.266 0.271 0.159 0.282* O.3317* 0.033 0.237* 0.236 0.358** 339° 0.301** Dr3092" Oo 92K* 0.261** -0.004 0.280* 0.298 0.145 0.207% 0.340** 0.093 4 0.261** 0.256** 0.164 0.269"* Oes.Z21%* -0.047 0.281* 0.330** 0.349** 0.415** 0:269** 0.135 0.241 0.186 0.289% 7 8 9 12 -0.006 0.018 0.072 0.191* |0.301** | 0.349%* In addition, the ®,, values of the Asahi and Sasagase populations showed sig- nificant genetic differentiation between Biwa, Yodo2, and Yodo3 populations (®,, 0.269-0.392: P < 0.05), and Kako population showed significant genetic differences from Yodo3 population (,, 0.281—-0.339, P < 0.05). The results of the population group estimation using SAMOVA are shown in Table 3 and Suppl. material 3. The highest F_, value (0.32166; P < 0.001) was ob- tained when the 10 populations were divided into K = 5 groups: Group A (Lake Bi- wa-Yodo River and Yoshino River: Loc. 1, 3, 4, and 12), Group B (tributary A of Yodo River: Loc. 2), Group C (Muko R. Loc. 5), Group D (Kako R.: Loc. 6) and Group E 26 Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira Table 3. Fixation indicating corresponding groups of populations inferred by spatial analysis of molecular variance (SAMOVA). Number groups (K) 2 of Group composition “Biwa’+”Yodo1”"+”Yodo2”+”Yodo3"+”Kako"+’Yoshii”+”Asahi"+"Aasagase’+’Yoshino” | 0 “Muko” “Biwa’+”Yodo2”+”Yodo3"+"Kako"+"Yoshii’+”Asahi"+"”Sasagase”+” Yoshino” “Muko” “Yodo1” “Biwa’+”Yodo2”+”Yodo3"+”Yoshino” “Kako’+"Yoshii”+’Asahi’+”Sasagase” “Muko” “Yodo1” “Biwa’+”Yodo2”+”Yodo3"+’Yoshino” “Yoshii’+”Asahi"+”Sasagase” “Muko” “Yodo1” “Kako” “Biwa’+”Yodo2”+”Yodo3"+”Yoshino” “Voshii’+”Asahi” “Muko” “Yodo1” “Kako” “Sasagase” “Yodo2”+”Yodo3"+"Yoshino” “Voshii’+”Asahi” “Muko” “Yodo1” “Kako” “Sasagase” “Biwa” “Yodo2”+”Yodo3"+"Yoshino” “Muko” “Yodo1” “Yoshii” “Kako” “Sasagase” “Biwa” “Asahi” P< 0.05*) P< 0.014, P<.0.001*** Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 sc AGO .14052*** 0.0344** -0.00438 -0.02137 -0.02246 -0.03234 st 0.42786*** 0.38805*** 0.331.27*** O.31869""* 0.30139""* 0.29394*** O28 725" ct 0.26865** 0.288* 0.30745*** 0.32166*** 0.31601*** 0.30945** 0.30953* (Yoshii, Asahi, and Sasagase Rs: Loc. 7-9), and explained 32.17% of the varia- tion among groups (P < 0.001), -0.3% of the variation among populations within groups (P > 0.1), and 68.13% of the variation within populations (P < 0.001). Divergence time We showed the divergence times of the three lineages of A. t. tabira in Fig. 3. In this tree, the exclusivity of Lineage | was supported (1.00), similar to the ML and BI trees described above, whereas the exclusivity of Lineages II and 27 Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira AB759881 T12 ali aB7soss6 ata 134 Ic AB759885 Lineage | T71 AB620150 129 T13 F C116 Oe F=7117 . E T15 <= O; — + — T35 0.98 AB759889 1 1} 1-AB759890 [incase ll - = Sy -AB620141 736 fi Lineage Il 4 AB620149: A. t. jordani | =|] * AB620156: A.t. jordani 41 AB239347: A. cyanostigma ; AB239348: A. cyanostigma AB366543: Opsariichthys platypus 20 15 10 5 0 Figure 3. Divergence time estimation by Bayesian inference tree of the 1069-bp cytochrome b gene sequences of Achei- lognathus tabira tabira and outgroups. The blue rectangular bars on the nodes indicate the 95% highest probability den- sity. Bayesian posterior probabilities are indicated at nodes, with values exceeding 0.90 shown. The node marked with an asterisk indicates the calibration point based on fossil record for the Acheilognathinae. Nodes with circled numbers are referenced in the text. Ill was supported (0.98), similar to the topology of the BI tree. The estimated divergence time between Lineage | and II+III was approximately 1.53 Mya (95% HPD, 0.71-2.64 Mya; Fig. 3, node 1), while that between Lineage II and III was approximately 0.91 Mya (0.34—1.68 Mya; node 2). The time of the most recent common ancestor (tMRCA) of Lineage | was estimated approximately 0.96 Mya (0.44-—1.66 Mya; Fig. 3, node 3). Discussion Phylogeographic and genetic population structure patterns We estimated the phylogenetic tree of A. t. tabira based on the sequence of the cytochrome b region of the mtDNA, and in the samples used in the present study, three lineages (Lineages |, Il, and III) were identified primarily based on the ML tree. The results were similar to those of a previous study (Umemura et al. 2012), where Lineage | to III were referred to as the Kinki-Sanyo Group, Nobi Plain Group |, and Nobi Plain Group Il, respectively. The populations newly an- alyzed in the present study (Muko, Kako, Sasagase, Takahashi, Kurashiki, and Asahikawa River systems) were all included in Lineage I, and the captive Gifu World Freshwater Aquarium population collected from Gifu Prefecture was in- cluded in Lineage Il. In a previous study, a haplotype of Lineage II was detected Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 28 Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira only in an individual collected from a tributary of the Nagara River system in the previous study (Umemura et al. 2012). Lineages | (non-native lineage) and III (native lineage) were identified in this tributary; therefore, it was unclear wheth- er Lineage II was native to the Ise Bay region or non-native to the Seto Inland Sea region (Umemura et al. 2012). In the present study, the haplotype belong- ing to Lineage II was not identified in any water system in the Seto Inland Sea region; therefore, the natural distribution area of Lineage II was considered to be the Ise Bay region. The populations of many freshwater fishes [e.g., Sarcocheilichthys variega- tus variegatus (Temminck & Schlegel, 1846) and Opsariichthys platypus] in the Ise Bay region are thought to have been divided from the populations of the Seto Inland Sea region by the uplift of the Suzuka Mountains approximately one million years ago (Mya) (Watanabe et al. 2017). The genetic lineages of popu- lations in many freshwater fishes in each region of Ise Bay and the Seto Inland Sea are generally exclusive (e.g., S. v. variegatus, Komiya et al. 2014; O. platy- pus, Kitanishi et al. 2016; Pseudogobio esocinus (Temminck & Schlegel, 1846) and P. agathonectris Tominaga & Kawase, 2019, Tominaga et al. 2016; Tanakia lanceolata (Temminck & Schlegel, 1846), Tominaga et al. 2020). However, in the case of A. t. tabira, the exclusivity of the two native lineages in the Ise Bay region (lineages II and III) was not supported in the ML tree and was supported with low values in the BI tree. In the ML tree, these two lineages were shown as paraphyletic groups, and each branch was highly supported. Furthermore, the results of the statistical parsimony network also indicated that lineages II and Ill were closely related to different haplotypes of Lineage |. On the other hand, the BI tree does not have the same topology as the ML tree. Divergence time estimates suggest that the supported topology is similar to that of the BI tree, with Lineages II and III diverging from Lineage | approximately 1.53 Mya, and Lineages II and Ill diverging approximately 0.91 Mya. However, due to the varying exclusivity of Lineages II and Ill across different phylogenetic trees, ac- cepting this divergence time estimation as it is would be risky. And more, the original distribution range of Lineage II and Ill is unclear, as A. t. tabira in the Ise Bay region has already become extinct in many river systems (Mukai 2019). If DNA analysis of specimens collected decades ago and stored in museums becomes possible, it will be possible to verify this issue. To consider the diver- gence order among the three lineages, further studies using longer sequences, such as mitogenomes, including sequence data from historical specimens, are necessary to re-estimate divergence times. In Lineage |, which was detected only in the Seto Inland Sea region, genet- ic differentiation has not been recognized in previous studies because of the small number of sampling sites and individuals (Kitamura et al. 2012). In the present study, we greatly increased the number of sampling sites and individ- uals; as a result, five genetic groups (A-E) were distinguished within Lineage | using SAMOVA. These five groups comprised adjacent river systems, indicat- ing that the genetic population of A. t. tabira within the Seto Inland Sea region was genetically differentiated into narrow regions. The river systems flowing into the Seto Inland Sea are thought to have connected as a single paleo-river system during the glacial periods of the Pleistocene (ca. 0.01-2.5 Mya) and were isolated during the interglacial periods (Kuwashiro 1959; Ota et al. 2004). Additionally, the uplift of the mountains areas surrounding the Seto Inland Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 29 Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira Sea is thought to have become active since the Pleistocene (Ota et al. 2004), making the migration of freshwater fish between river systems difficult during this period. The tMRCA of Lineage | is estimated to be 0.96 Mya (95% HPD, 0.44-1.66 Mya), overlapping with the periods of connection and isolation of the paleo-river systems and the uplift of mountains around the Seto Inland Sea. Therefore, the isolation factors between the regional groups are suggested to be related to the paleo-river systems and active uplift of mountains that oc- curred during the Pleistocene. Genetic differentiation in the same period due to similar factors in the Seto Inland Sea region has also been suggested in P esocinus (Tominaga et al. 2016). A unique genetic group (Group D) was identified in the Kako River system. However, ®,, showed no significant genetic differentiation (P > 0.05) between the Kako River system and the other three river systems (Yoshii, Asahi, and Sasagase) included in Group E. SAMOVA results indicated that most of the ge- netic variation in this subspecies was within populations (68.13%) and that dif- ferentiation among groups was relatively small (32.17%). Genome-wide analy- sis of nuclear DNA may be useful for more detailed elucidation of the genetic population structure of A. t. tabira. Artificially introduced populations Populations collected from the Lake Biwa-Yodo and Yoshino River systems were included in Group A. In addition, four haplotypes detected in the Yoshino River system were similar to those in the Lake Biwa-Yodo River system. This study demonstrates that populations in the Seto Inland Sea region are geneti- cally differentiated by localized areas. The reason for this is thought to be the same as with other species: the disappearance of the paleo-river system and isolation due to the uplift of mountains. Therefore, it is unlikely that the popu- lation in the Yoshino River system has the same haplotype as the population in the Lake Biwa-Yodo River system, which is across the Seto Inland Sea. In the Yoshino River system, non-native freshwater fishes [e.g., Acheilognathus cya- nostigma and Acheilognathus rhombeus (Temminck & Schlegel, 1846)] were estimated to have been artificially introduced from Lake Biwa (Hosoya 2019; Miyake et al. 2021). Ministry of the Environment of Japan (2015) also indicated that A. t. tabira populations were artificially introduced into the Yoshino River system. Therefore, the finding that only haplotypes of the Yoshino River system are common to those of the Lake Biwa-Yodo River system supports the hypoth- esis that the Yoshino River system population was artificially introduced from the Lake Biwa-Yodo River system. Conservation The captive population of the Gifu World Freshwater Aquarium was identified as Lineage II, which is thought to be native to the Ise Bay region. Non-native populations belonging to Lineage | have been artificially introduced into all hab- itats of native populations in the Ise Bay region (Umemura et al. 2012; Kitamu- ra and Uchiyama 2020). Therefore, the captive population of the Gifu World Freshwater Aquarium may be a native population of the Ise Bay region that has not undergone genetic introgression. However, to confirm that the population Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 30 Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira is not genetically introgressed, examining the possibility of hybridization with Lineage | using nuclear DNA is necessary. Conservation units need to focus on levels below species (Moritz 1994, Frankham et al. 2010). Evolutionarily significant units (ESUs) refer to phylogeneti- cally unique intraspecific population groups, established by factors such as mito- chondrial DNA monophyly (Moritz 1994). In the case of A. t. tabira, the exclusivity of Lineages I-III was supported; thus, we propose to designate them as ESUs. Furthermore, Management Units (MUs) are established based on allele fre- quencies among populations (Moritz 1994, Frankham et al. 2010). In the case of A. t. tabira, Groups A-E found within Lineage | were significantly genetically differentiated by SAMOVA. Therefore, we propose that these five groups be conserved as MUs of A. t. tabira in the Seto Inland Sea region. However, it has been proposed that adaptive traits should also be taken into account in the establishment of ESUs and MUs (Crandall et al. 2000). In the future, in order to establish better conservation units, it is necessary to study adaptive traits among populations of A. t. tabira. Acknowledgments We express sincere thanks to Mr. Koki Ikeya, Ms. Chikako Horie, Mr. Kosei Ni- shikawa, and Mr. Jumpei Hamachi for their assistance with obtaining the spec- imens, and to Mr. Ken-ichi Setsuda for registering the specimens. Furthermore, we extend our appreciation to the Division of Genomics Research, Dr. Hiroki Yamanaka, and the Life Science Research Center, Gifu University, for their help with DNA analysis. Additional information Conflict of interest The authors have declared that no competing interests exist. Ethical statement No ethical statement was reported. Funding This study was supported by JSPS KAKENHI (22K14908). Author contributions Gen Ito: Conceptualization, Data curation, Formal Analysis, Funding acquisition, and Writing — original draft. Naoto Koyama, Ryota Noguchi, Ryoichi Tabata, Seigo Kawase, and Jyun-ichi Kitamura: Investigation, Resources, and Writing — review & editing. Yasun- ori Koya: Supervision, Funding acquisition, and Writing — review & editing. Author ORCIDs Gen Ito © https://orcid.org/0000-0002-9781-7206 Data availability All of the data that support the findings of this study are available in the main text or Supplementary Information. Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 31 Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira References Arai R, Fujikawa H, Nagata Y (2007) Four new species of Acheilognathus bitterlings (Cyprinidae: Acheilognathinae) from Japan. Bulletin of the National Museum of Nature and Science, Series A (Supplement 1): 1-28. Avise JC (2000) Phylogeography: the history and formation of species. Harvard Univer- sity Press, Cambridge, 464 pp. https://doi.org/10.2307/j.ctv1nzfgj7 Bouckaert R, Vaughan TG, Barido-Sottani J, Duchéne S, Fourment M, Gavryushkina A, Heled J, Jones G, Kuhnert D, De Maio N, Matschiner M, Mendes FK, Miller NF, Ogilvie HA, du Plessis L, Popinga A, Rambaut A, Rasmussen D, Siveroni |, Suchard MA, Wu CH, Xie D, Zhang C, Stadler T, Drummond AJ (2019) BEAST 2.5: An advanced soft- ware platform for Bayesian evolutionary analysis. PLoS Computational Biology 15(4): e1006650. https://doi.org/10.1371/journal.pcbi.1006650 Chernomor O, von Haeseler A, Minh BQ (2016) Terrace aware data structure for phylog- enomic inference from supermatrices. Systematic Biology 65(6): 997-1008. https:// doi.org/10.1093/sysbio/syw037 Clement M, Posada D, Crandall K (2000) TCS: A computer program to estimate gene genealogies. Molecular Ecology 9(10): 1657-1660. https://doi.org/10.1046/j.1365- 294x.2000.01020.x Crandall KA, Bininda-Emonds ORP, Mace GM, Wayne RK (2000) Considering evolution- ary processes in conservation biology. Trends in Ecology & Evolution 15(7): 290-295. https://doi.org/10.1016/S0169-5347(00)01876-0 Darriba D, Posada D, Stamatakis A (2017) ModelTest-NG: Best-fit evolutionary model selection. https://github.com/ddarriba/modeltest/ [Accessed 9 September 2022] Dupanloup I, Schneider S, Excoffier L (2002) A simulated annealing approach to define the genetic structure of populations. Molecular Ecology 11(12): 2571-2581. https:// doi.org/10.1046/j.1365-294X.2002.01650.x Edgar RC (2004) MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Research 32(5): 1792-1797. https://doi.org/10.1093/nar/ gkh340 Excoffier L, Lischer HE (2010) Arlequin suite ver 3.5: A new series of programs to perform population genetics analyses under Linux and Windows. Molecular Ecology Resources 10(3): 564-567. https://doi.org/10.1111/j.1755-0998.2010.02847.x Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: Application to human mitochondrial DNA re- striction data. Genetics 131(2): 479-491. https://doi.org/10.1093/genetics/131.2.479 Frankham R, Ballou JD, Briscoe DA (2010) Introduction to conservation genetics. Second edition. Cambridge University Press, Cambridge, 618 pp. Guindon S, Dufayard JF, Lefort V, Anisimova M, Hordijk W, Gascuel O (2010) New al- gorithms and methods to estimate maximum-likelihood phylogenies: Assessing the performance of PhyML 3.0. Systematic Biology 59(3): 307-321. https://doi. org/10.1093/sysbio/syq010 Hashiguchi Y, Kado T, Kimura S, Tachida H (2006) Comparative phylogeography of two bitterlings, Tanakia lanceolata and T. limbata (Teleostei, Cyprinidae), in Kyushu and adjacent districts of western Japan, based on mitochondrial DNA analysis. Zoologi- cal Science 23(4): 309-322. https://doi.org/10.2108/zsj.23.309 Hoang DT, Chernomor O, von Haeseler A, Minh BQ, Vinh LS (2018) UFBoot2: Improving the ultrafast bootstrap approximation. Molecular Biology and Evolution 35(2): 518- 522. https://doi.org/10.1093/molbev/msx281 Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 32 Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira Hosoya K (2019) Freshwater fishes of Japan. Extended and revised edition, Yama-kei Publishers, Tokyo, 559 pp. [In Japanese] Ito G, Koya Y (2022) Phylogeographic structure of an endemic lineage of the eight-barbel loach Lefua echigonia around the Suzuka and Yoro Mountains, central Honshu, Ja- pan. Biogeography 24: 31-37. https://doi.org/10.11358/biogeo.24.39 Ito G, Koya Y, Kitanishi S, Horiike T, Mukai T (2019) Genetic population structure of the eight-barbel loach Lefua echigonia in the Ise Bay region, a single paleo-river basin in central Honshu, Japan. Ichthyological Research 66(3): 411-416. https://doi. org/10.1007/s10228-019-00683-z Ito G, Koya Y, Kitanishi S, Horiike T, Mukai T (2020) Genetic population structure of Co- bitis minamorii tokaiensis. Japanese Journal of Ichthyology 67: 41-50. https://doi. org/10.11369/jji.19-028 [In Japanese with English summary] Ito G, Kitamura J, Noguchi R, Nagata N, Koya Y (2021) Records and genetic characteris- tics of exotic bitterling, Acleilognathus tabira subspp., from northern Mie Prefecture, Japan. Japanese Journal of Ichthyology 68: 47-52. https://doi.org/10.11369/jji.20- 034 [In Japanese with English summary] Ito G, Hata K, Kitamura J, Koya Y (2022) Records and genetic characteristics of the bit- terling Tanakia lanceolata established in the Naruse River system, Miyagi Prefecture, Japan. Japanese Journal of Ichthyology 69: 57-62. [In Japanese with English sum- mary] https://doi.org/10.11369/jji.20-24 Kalyaanamoorthy S, Minh BQ, Wong TKF, von Haeseler A, Jermiin LS (2017) ModelFind- er: Fast model selection for accurate phylogenetic estimates. Nature Methods 14(6): 587-589. https://doi.org/10.1038/nmeth.4285 Kitagawa T, Yoshida M, Kashiwagi M, Okazaki T (2001) Population structure and local differentiation in the delicate loach, Niwaella delicate, as revealed by mitochondrial DNA and morphological analyses. Ichthyological Research 48(2): 127-135. https:// doi.org/10.1007/s10228-001-8127-4 Kitamura J, Uchiyama R (2020) Bitterling fishes of Japan-natural history and culture. Yama-kei Publishers, Tokyo, 223 pp. [In Japanese with English summary] Kitamura J, Nagata N, Nakajima J, Sota T (2012) Divergence of ovipositor length and egg shape in a brood parasitic bitterling fish through the use of different mussel hosts. Journal of Evolutionary Biology 25(3): 566-573. https://doi.org/10.1111/j.1420- 9101.2011.02453.x Kitanishi S, Hayakawa A, Takamura K, Nakajima J, Kawaguchi Y, Onikura N, Mukai T (2016) Phylogeography of Opsariichthys platypus in Japan based on mitochondrial DNA sequences. Ichthyological Research 63(4): 506-518. https://doi.org/10.1007/ $10228-016-0522-y Komiya T, Fujita-Yanagibayashi S, Watanabe K (2014) Multiple colonization of Lake Biwa by Sarcocheilichthys fishes and their population history. Environmental Biology of Fishes 97(7): 741-755. https://doi.org/10.1007/s10641-013-01 76-9 Kumagai M, Hagiwara T (2013) Acheilognathus tabira erythropterus and A. t. tabira col- lected from Aomori Prefecture, Japan. Izunuma-Uchinuma Wetland Researches 7: 17-22. [In Japanese with English summary] https://doi.org/10.20745/izu.7.0_17 Kuwashiro | (1959) Submarine topography of Japanese Inland Sea Setonaikai. Geo- graphical Review of Japan 32(1): 24-34. https://doi.org/10.4157/grj.32.24 [In Jap- anese with English summary] Machida H, Matsuda T, Umitsu M, Koizumi T (2006) Geomorphology of Chubu. Regional geomorphology of the Japanese islands, Vol 5. University of Tokyo Press, Tokyo, 385 pp. [In Japanese] Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 33 Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira Matsuba H, Yoshimi S, Inoue M, Hata H (2014) Origin of Tanakia limbata in Ehime Pre- fecture indicated by phylogeographic analysis of mitochondrial cytochrome b gene sequences. Japanese Journal of Ichthyology 61: 89-96. https://doi.org/10.11369/ jji.61.89 [In Japanese with English summary] Minh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD, von Haeseler A, Lan- fear R (2020) IQ-TREE 2: New models and efficient methods for phylogenetic infer- ence in the genomic era. Molecular Biology and Evolution 37(5): 1530-1534. https:// doi.org/10.1093/molbev/msaa015 Ministry of the Environment of Japan (2015) Red data book 2014 — Threatened wildlife of Japan — volume 4, Pisces — Brackish and freshwater fishes. Gyosei Corporation, Tokyo, 414 pp. [In Japanese] Ministry of the Environment of Japan (2020) The Ministry of Environment, Japan Red List. The Ministry of Environment, Japan, Tokyo. https://www.env.go.jp/press/files/ jp/114457.pdf [Accessed 9 September 2022] [in Japanese] Miyake T, Nakajima J, Onikura N, Ikemoto S, Iguchi K, Komaru A, Kawamura K (2011) The genetic status of two subspecies of Rhodeus atremius, an endangered bitterling in Japan. Conservation Genetics 12(2): 383-400. https://doi.org/10.1007/s10592- 010-0146-0 Miyake T, Nakajima J, Umemura K, Onikura N, Ueda T, Smith C, Kawamura K (2021) Genetic diversification of the Kanehira bitterling Acheilognathus rhombeus inferred from mitochondrial DNA, with comments on the phylogenetic relationship with its sister species Acheilognathus barbatulus. Journal of Fish Biology 2021(5): 1-10. https://doi.org/10.1111/jfb.14876 Moritz C (1994) Defining ‘Evolutionarily Significant Units’ for conservation. Trends in Ecology & Evolution 9(10): 373-375. https://doi.org/10.1016/0169-5347(94)90057-4 Mukai T (2019) Fishes of Gifu, 2" edition. Gifu Shimbun Gifu, Gifu, 223 pp. [In Japanese] Nakagawa H, Seki S, Ishikawa T, Watanabe K (2016) Genetic population structure of the Japanese torrent catfish Liobagrus reinii (Amblycipitidae) inferred from mitochon- drial cytochrome b variations. Ichthyological Research 63(3): 333-346. https://doi. org/10.1007/s10228-01 5-0503-6 Ota Y, Naruse T, Tanaka S, Okada A (2004) Geomorphology of Kinki, Chugoku and Shi- koku. Regional geomorphology of the Japanese islands, Vol 6. University of Tokyo Press, Tokyo, 383 pp. [In Japanese] Rambaut A (2018) FigTree v1.4.4. https://github.com/rambaut/figtree/releases [Accessed 1 June 2024] Rambaut A, Drummond AJ, Xie D, Baele G, Suchard MA (2018) Posterior summariza- tion in Bayesian phylogenetics using Tracer 1.7. Systematic Biology 67(5): 901-904. https://doi.org/10.1093/sysbio/syy032 Rice WR (1989) Analyzing tables of statistical test. Evolution; International Journal of Organic Evolution 43(1): 223-225. https://doi.org/10.2307/2409177 Ronquist F, Teslenko M, van der Mark P Ayres DL, Darling A, Hohna S, Larget B, Liu L, Suchard MA, Huelsenbeck JP (2012) MyBayes 3.2: Efficient Bayesian phylogenetic inference and model choice across a large model space. Systematic Biology 61(3): 539-542. https://doi.org/10.1093/sysbio/sys029 Tominaga K, Nakajima J, Watanabe K (2016) Cryptic divergence and phylogeography of the pike gudgeon Pseudogobio esocinus (Teleostei: Cyprinidae): a comprehensive case of freshwater phylogeography in Japan. Ichthyological Research 63(1): 79-93. https://doi.org/10.1007/s10228-015-0478-3 Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 34 Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira Tominaga K, Nagata N, Kitamura J, Watanabe K, Sota T (2020) Phylogeography of the bitterling Tanakia lanceolata (Teleostei: Cyprinidae) in Japan inferred from mito- chondrial cytochrome b gene sequences. Ichthyological Research 67(1): 105-116. https://doi.org/10.1007/s10228-019-00715-8 Uemura Y, Yoshimi S, Hata H (2018) Hybridization between two bitterling fish species in their sympatric range and a river where one species is native and the other is intro- duced. PLOS ONE 13(9): e€0203423. https://doi.org/10.1371/journal.pone.0203423 Umemura K, Futamura R, Takagi M, Ikeya K, Mukai T (2012) Distribution of non-indige- nous mitochondrial DNA lineage in the local populations of an endangered bitterling, Acheilognathus tabira tabira, in the Gifu Prefecture, Japan. Nihon Seibutsu Chiri Gak- kai Kaiho 67: 169-174. Watanabe K, Kawase S, Mukai T, Kakioka R, Miyazaki J, Hosoya K (2010) Population divergence of Biwia zezera (Cyprinidae: Gobioninae) and the discovery of a cryptic species, based on mitochondrial and nuclear DNA sequence analyses. Zoological Science 27(8): 647-655. https://doi.org/10.2108/zsj.27.647 Watanabe K, Mori S, Tanaka T, Kanagawa N, Itai T, Kitamura J, Suzuki N, Tominaga T, Kakioka R, Tabata R, Abe T, Tashiro Y, Hashimoto Y, Nakajima J, Onikura N (2014) Genetic population structure of Hemigrammocypris rasborella (Cyprinidae) inferred from mtDNA sequences. Ichthyological Research 61(4): 352-360. https://doi. org/10.1007/s10228-014-0406-y Watanabe K, Tominaga K, Nakajima J, Kakioka R, Tabata R (2017) Japanese freshwater fishes: Biogeography and cryptic diversity. In: Motokawa M, Kajihara H (Eds) Species Diversity of Animal in Japan, Diversity and Commonality in Animals. Springer Japan, Tokyo, 183-227. https://doi.org/10.1007/978-4-431-56432-4_7 Yasuno K (1984) Fossil pharyngeal teeth of the Rhodeinae fish from the Miocene Katabi- ra Formation of the Kani Group, Gifu Prefecture, Japan. Bulletin of Mizunami Fossil Museum 11: 101-105. Zardoya R, Doadrio | (1999) Molecular evidence on the evolutionary and biogeographi- cal patterns of European cyprinids. Journal of Molecular Evolution 49(2): 227-237. https://doi.org/10.1007/PL00006545 Supplementary material 1 List of collection sites for Acheilognathus tabira tabira and distribution of each haplotype across the 13 collection sites Authors: Gen Ito, Naoto Koyama, Ryota Noguchi, Ryoichi Tabata, Seigo Kawase, Jyun- ichi Kitamura, Yasunori Koya Data type: xlsx Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/natureconservation.56.111745.suppl1 Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 35 Gen Ito et al.: Genetic population structure of Acheilognathus tabira tabira Supplementary material 2 Bayesian inference (BI) tree of the 1069-bp cytochrome b gene sequences of Acheilognathus tabira tabira individuals from the Seto Inland Sea and Ise Bay regions Authors: Gen Ito, Naoto Koyama, Ryota Noguchi, Ryoichi Tabata, Seigo Kawase, Jyun- ichi Kitamura, Yasunori Koya Data type: pdf Explanation note: Numbers at nodes indicate Bayesian posterior probabilities; the value is indicated when it exceeds 0.80. Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/natureconservation.56.111745.suppl2 Supplementary material 3 The distribution map of Groups estimation using SAMOVA of Acheilognathus tabira tabira Authors: Gen Ito, Naoto Koyama, Ryota Noguchi, Ryoichi Tabata, Seigo Kawase, Jyun- ichi Kitamura, Yasunori Koya Data type: pdf Explanation note: Circles show groups (see Fig. 2). Gray areas are the estimated natu- ral distribution area of A. tabira 5 subspecies based on Kitamura et al. (2012). This altitude map was used with permission from the Geospatial Information Authority of Japan (https://maps.gsi.go.jp/) and digital national and information of Ministry of Land, Infrastructure, Transport and Tourism (https://nlftp.mlit.go.jp). The paleo-river system follows Kuwashiro (1959). Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/natureconservation.56.111745.suppl3 Nature Conservation 56: 19-36 (2024), DOI: 10.3897/natureconservation.56.111745 36