DNA Barcoding of Austria's Biodiversity

DNA Barcoding of Austria’s Biodiversity

KUMULATIVE DISSERTATION

Zur Erlangung des akademischen Grades

Dr. rer. nat.

An der naturwissenschaftlichen Fakultät der

Karl-Franzens-Universität Graz

Institut für Biologie

Eingereicht von

Lukas Zangl, MSc

Unter der Betreuung von

Priv.Doz. Mag. Dr. Stephan Koblmüller

Jänner 2021

Acknowledgments

I would like to thank my many colleagues at the University of Graz and at the Natural History Museum Vienna for their cooperation in the course of my own research and for letting me partake in a range of diverse projects over the last few years. Particularly, among others, Max, Andrea, Sylvia, Gernot, Christoph, Philipp, Anna, Gernot, Wolfi, Tamara, Holger, Angi, Jacky, Marcia, Iris, Oliver, Frank, Lisi and Nikolaus provided me with ideas, help and inspiring discussions. I am also thankful to my mentor Kristina Sefc for her support and encouragement. Furthermore, I am grateful to my loving family and dear friends, among them Lukas, Martin, Rüdiger, Daniel, Bertram and Tina for their great support. Finally, I want to especially thank my supervisor Stephan Koblmüller for his continuous encouragement, support, supervision, inspiration, faith, his untiring motivation to look into something new every other day (and dragging me into it as well) and for being able to rely on him throughout the entire time of my PhD.

Table of contents

Abstract ...... 4

Zusammenfassung ...... 5

Introduction ...... 7

Main part ...... 12 Chapter 1 ...... 12 Chapter 2 ...... 35 Chapter 3 ...... 48 Chapter 4 ...... 78 Chapter 5 ...... 109 Chapter 6 ...... 122 Chapter 7 ...... 134

Discussion ...... 152

References ...... 156

Abstract

DNA barcoding has evolved to one of the prime tools in biodiversity research over the past two decades. This method utilizes reliable reference databases for the comparison of standard marker sequences of unknown samples of specimens in order to facilitate species assignment. Consequently, it can be used for the determination and discrimination of species, for the detection of alien/invasive species or species new to science, to uncover cryptic diversity and pinpoint cases for systematic and/or taxonomic inquiry and for any applied approach in need to determine a biological species. Contrasting to these strengths, it shows some well-known and extensively debated weaknesses like barcode sharing or insufficient resolution in cases of recent divergence, introgressive events or hybridization, issues with wet lab protocols, a need for a certain infrastructure and the competition with the rapidly expanding field of genomics. However, the “Austrian Barcode of Life” initiative (ABOL) aligns to a plethora of other national and international barcoding projects using this very technique in order to create comprehensive national reference species inventories. The quality and completeness of those databases -also a recurrent topic of discussion- poses the basis for all applied approaches as well as methodological alterations of the classical DNA barcoding like the use of mini-barcodes, high-resolution melting analyses (HRM) or non-invasive and community-level assessments via environmental DNA sequencing (eDNA). In the course of my PhD in the framework of ABOL, I used DNA barcoding to i) generate a comprehensive national species inventory for the Austrian amphibians and reptiles, ii) investigate the genetic diversity of a specific fish family in the Austrian Danube system, iii) confirm the description of a fish species new to science and the presence of alien/invasive vertebrate and invertebrate species in Austria, iv) set up a high-resolution melting analysis workflow for the discrimination of closely related beetle species which can be adapted for similar applications and v) to uncover potential cryptic diversity in snow scorpionflies which points to the need of further morphological and genomic investigation to clarify systematic and taxonomic relationships. In summary, I used DNA barcoding for a wide range of applications, harnessing its strengths but also exploring and reaching its limitations. Furthermore, I showed how these weaknesses can be dealt with and what ways there are to supplement classical DNA barcoding in ambiguous cases.

Zusammenfassung

In den vergangenen zwei Jahrzehnten entwickelte sich DNA-Barcoding zu einer der wichtigsten Methoden der Biodiversitätsforschung. Dieses Verfahren basiert auf dem Vergleich der Sequenzen standardisierter genetischer Marker von unbekannten Proben mit Referenzdatenbanken zur Artbestimmung. Somit kann es zur Bestimmung und Unterscheidung von Arten, zum Nachweis gebietsfremder/invasiver Arten oder der Entdeckung bisher unbeschriebener Arten, zum Aufzeigen kryptischer Diversität und von systematisch und/oder taxonomisch interessanten Fragestellungen und für angewandte Bereiche, in denen die Identität einer Probe von Bedeutung ist, verwendet werden. Diesen vermeintlichen Stärken stehen jedoch auch einige wohl bekannte und vielfältig diskutierte Schwächen gegenüber. Darunter finden sich unter anderem Fälle identer DNA-Barcodes, die gleichzeitig unterschiedliche Arten ausweisen („barcode sharing“), ungenügende Unterschiede in den DNA-Sequenzen entwicklungsgeschichtlich junger Arten oder in Fällen von Introgression oder Hybridisierung, Probleme bei der Bearbeitung im Larbor, die Notwendigkeit einer gewissen Infrastruktur oder die zunehmende Konkurrenz durch das stetig wachsende Gebiet der Genomik. Nichtsdestotrotz verwendet die „Austrian Barcode of Life“ Initiative (ABOL), ebenso wie viele andere nationale und internationale Barcoding-Projekte diese Methode zur Erstellung möglichst vollständiger taxonomischer Referenzdatenbanken. Die Qualität und Vollständigkeit dieser Datenbanken -ebenso ein viel diskutiertes Thema- stellt die Grundlage für alle Anwendungen sowie für alternative methodische Zugänge zum konventionellen DNA-Barcoding wie Mini-Barcodes, hochauflösende Schmelzverfahren (HRM) oder nicht-invasive und populationsbezogene Analysen mittels der Sequenzierung von Umwelt-DNA (eDNA) dar. Im Zuge meiner Dissertation im Rahmen von ABOL verwendete ich DNA-Barcoding um i) eine vollständige Referenzdatenbank der österreichischen Amphibien und Reptilien zu erstellen, ii) die genetische Diversität einer bestimmten Fischfamilie im österreichischen Donausystem zu untersuchen, iii) die Artbeschreibung einer bisher unbeschriebenen Fischart sowie die Nachweise gebietsfremder/invasiver Wirbeltiere und wirbelloser Tiere in Österreich zu bestätigen, iv) ein Verfahren basierend auf der Analyse hochauflösender Schmelzkurven zur Unterscheidung nah verwandter Käferarten zu etablieren, das auch für ähnliche Anwendungen adaptiert werden kann und v) um potentielle kryptische Diversität innerhalb der Winterhaften (Insecta: Mecoptera) nachzuweisen, was der 5

Untersuchung weiterer morphologischer sowie genomischer Daten bedurfte, um systematische und taxonomische Zusammenhänge aufzulösen. Somit habe ich DNA- Barcoding für eine Vielzahl unterschiedlicher Anwendungen verwendet und mir dessen Stärken zunutze gemacht, bin aber auch auf die inherenten Schwächen sowie die Limitierungen dieser Methode gestoßen. Darüberhinaus konnte ich Möglichkeiten aufzeigen, wie mit diesen Schwächen umgegangen und das klassische DNA-Barcoding in uneindeutigen Fällen mittels zusätzlicher Daten und Analysemethoden unterstützt werden kann.

Introduction

The term ‘biological diversity’ or ‘biodiversity’ “… includes diversity within species, between species and of ecosystems …” according to the definition of the Convention on Biological Diversity ((CBD), United Nations 1993). In other words, it encompasses species richness (number of species), genetic diversity and the diversity of ecosystems. Austria, despite its small size compared to other European countries, houses a substantial wealth of this diversity due to its geographic location and topological and climatic features. It encompasses glacial mountain tops in the inner Alpine regions in Western and Central Austria, wooded areas at the foothills surrounding the Alps and parts of the Pannonian plains at the Eastern borders. This diversity is also reflected by the different climatic regimes influencing certain parts of Austria, ranging from moist Atlantic and dry-warm continental to submediterranean climates (Rabitsch & Essl 2009). This variety of physical habitat characteristics is mirrored by an estimated amount of approximately 70,000 species of animals, plants and fungi (more than 54,000 of them being animals) that can be found on Austrian soil (https://www.abol.ac.at/en/biodiversity-dna-barcoding/ accessed on September 28, 2020, Geiser 2018).

Recording a country’s biodiversity i.e., the number of species has become an increasingly valuable tool for political decision making with respect to species and ecosystem conservation and is also embedded in national and international wildlife protection laws (e.g., Council of the European Union 1992). Therefore, reliable species identification but also the detection of new/alien/invasive species is of crucial interest to biologists and conservation workers (e.g., Knebelsberger et al. 2015, Hawlitschek et al. 2016). Biodiversity research was also affected by the improvement and increasing application of molecular genetic methods and took a new direction, when Hebert et al. (2003) suggested DNA barcoding as a universal tool for the identification of specimens and the determination and distinction of species. This technique is based on the comparison of the DNA sequence of a standardized marker from a specimen or piece of tissue to sequences of reliably determined reference specimens stored in a database in order to facilitate species assignment. Therefore, specimens need to be collected and determined by taxonomic experts and stored permanently together with the collection information (figure 1). The standard DNA barcoding relies on Sanger sequencing of a specific genetic

marker (cytochrome c oxidase subunit 1 (COI) in animals) in order to create a comparable and simple framework for species identification (e.g., Coissac et al. 2016).

Figure 1: DNA barcoding workflow including the procedures of sampling, handling of metadata, storing of samples and metadata, processing of tissue samples in designated DNA laboratories and handling and storing of the barcoding data and collection information in reference databases. (Figure retrieved from https://www.abol.ac.at/biodiversitaet-dna-barcoding/#was_ist_dna- barcoding, accessed on 04.01.2021).

Ideally, each species in the database is represented by several specimens of various geographic origins to cover potential intraspecific genetic variation (Hebert et al. 2003). The link between the physical object (reference specimen) permanently stored in e.g., a museum collection, the collection and storage information as well as the genetic information (trace files) and the DNA barcode guarantee the quality and retraceability of each single reference specimen and consequently the entire reference database. These criteria have to be met by a specimen’s COI sequence in order to be regarded a valid ‘DNA barcode’, which qualitatively separates barcoding reference databases from other sequence repositories like for example GenBank (Jinbo et al. 2011, Coissac et al. 2016). 8

Meanwhile, DNA barcoding has proven to be a powerful tool for specimen identification (Knebelsberger et al. 2015, Zangl et al. 2020a), species determination (Raupach et al. 2010, Knebelsberger et al. 2015, Zangl et al. 2020b), the discovery of cryptic diversity (Hubert et al. 2012, Vasconcelos et al. 2016, Zangl et al. 2020a), alien invasive species (Briski et al. 2011, Zangl et al. 2020c) and of species new to science (Huemer et al. 2014, Nguyen et al. 2014, Friedrich et al. 2018). All of these strengths can be embraced both on an academic scientific level and on a practical applied level (Madden et al. 2019, Zangl et al. 2020c). Furthermore, it may be utilized with the classical Sanger sequencing targeting specific species or used for conducting community level assessments based on high-throughput sequencing of e.g., eDNA samples (Dejean et al. 2012, Ardura et al. 2017, Kundu & Kumar 2018). The latter approach may yield the advantage of being able to analyze whole communities, species assamblages in a certain habitat or the full spectrum of a stomach content at the same time, but needs special infrastructure in terms of laboratories, bioinformatics and comprehensive reference databases. In addition, methodological alterations like minibarcodes (Alberdi et al. 2012, Doña et al. 2015, Rodrigues et al., 2019), character-based DNA barcoding (Rach et al., 2008, Reid et al., 2011) and bar-high-resolution melting analyses (bar-HRM) (Yanqing et al. 2019, Baudrin et al. 2020, Zangl et al. 2020d), have been derived from the basis that has been provided by the classical DNA barcoding and its respective reference databases. The advantages of these alterations compared to the classical full length (~650 bp fragments) Sanger sequencing DNA barcoding lie in the easier recovery of short fragments, the added information of single mutational sites compared to plain ‘homogenized’ distance values and in the case of bar-HRM analyses in the reduction of costs and infrastructure due to the independence from the actual sequencing step of PCR products (Baudrin et al. 2020, Zangl et al. 2020d).

Consequently, over the last two decades many different national and international barcoding initiatives have been established across the globe in order to generate reference databases for their respective countries and concomitantly comprehensive species inventories of various taxonomic groups have been generated (e.g., Raupach et al. 2010, Huemer et al. 2014, Knebelsberger et al. 2015, Hawlitschek et al. 2016, Hawlitschek et al. 2017, Huemer et al. 2019, Galimberti et al. 2020). In 2012, Austria started its own national barcoding initiative called ‘Austrian Barcode of Life’ (ABOL, www.abol.ac.at) with the goal to generate a comprehensive reference database for all native species of

animals, plants and fungi. This initiave operates through a nationwide network of universities, natural history museums, private companies and public agencies uniting scientists, amateur taxonomists, conservation workers and applied biologists in their effort to catalogue Austria’s biodiversity (Haring et al. 2015). In the light of the latest IPBES (Intergovernmental Platform on Biodiversity and Ecosystem Services) global assessment report, describing a dramatic loss of biodiversity and biomass (IPBES, 2019), this task is of key importance and pressing urgency, given, that global species number estimates ranging from 0.5 to > 100 million still remain speculative (Kassas 2002, Caley et al. 2014). Hence, ABOL is not only increasing the knowledge on Austrian species assemblages, but also contributing to a global network sharing DNA barcoding data. This data, because it is made publicly available, can serve for a broad range of applications

Figure 2: Potential fields for the application of DNA barcoding. (Kindly provided by Nikolaus Szucsich)

including not only basic scientific purposes but also international legal obligations and socioeconomic aspects (figure 2) and therefore, its generation should be considered an endeavor worthwhile funding also in the interest of the general public.

In the course of my PhD in the framework of ABOL, I worked on i) generating and completing comprehensive national species inventories for several vertebrate and invertebrate taxonomic groups, ii) applying DNA barcoding in various cases that required the identification, determination or discrimiation of species (e.g. proving the presence of alien/invasive species), and iii) exploring potential weaknesses of this technique and augmenting critical cases by investigating additional genetic, genomic or morphological data in order to resolve taxonomic and/or systematic uncertainties.

Main part

Chapter 1 ISSN 1175-5326 (print edition) ZO O TA X A ISSN 1175-5334 (online edition)

Romanogobio skywalkeri, a new gudgeon (Teleostei: Gobionidae) from the upper Mur River, Austria

Friedrich, T., Wiesner, C., Zangl, L., Daill, D., Freyhof, J., & Koblmueller, S. (2018). Romanogobio skywalkeri, a new gudgeon (Teleostei: Gobionidae) from the upper Mur River, Austria. Zootaxa, 4403(2), 336-350.

THOMAS FRIEDRICH1, CHRISTIAN WIESNER1, LUKAS ZANGL2, DANIEL DAILL2,3, JÖRG FREYHOF4 & STEPHAN KOBLMÜLLER2

1Institute of Hydrobiology and Aquatic Ecosystem Management, University of Natural Resources and Life Sciences, Vienna, Gregor-Mendelstraße 33, 1180 Vienna, Austria.

E-mail: [email protected], [email protected]

2Institute of Biology, University of Graz, Universitätsplatz 2, 8010 Graz, Austria.

E-mail: [email protected], [email protected]

3Aquatic Ecology and Engineering—blattfisch e.U., Gabelsbergerstraße 7, 4600 Wels, Austria

E-mail: [email protected]

4Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), 12587 Berlin, Germany.

E-mail: [email protected]

ABSTRACT

Romanogobio skywalkeri, new species, is described from the upper Mur River in the Austrian Danube drainage. It is related to R. banarescui from the Mediterranean basin. Romanogobio skywalkeri is distinguished from R. banarescui by lacking epithelial crests on the predorsal back, having 12–14 total pectoral-fin rays (vs. 10–11) and usually 8½ branched dorsal-fin rays (vs. 7½). It is distinguished from other Romanogobio species in the Danube drainage by having a very slender body; a moderately long barbel, extending slightly beyond the posterior eye margin; and no epithelial crests on the predorsal back. Romanogobio skywalkeri is distinguished by a minimum net divergence of 6.3% (uncorrected p-distance against R. banarescui) in the COI barcoding region from other European Romanogobio species. A key to the Romanogobio species of the Danube drainage is provided. Romanogobio banarescui from the Vardar drainage and R. carpathorossicus from the Danube drainage are treated as valid species.

KEY WORDS: Freshwater fish, taxonomy, Cytochrome oxidase I, Europe, hydropower

INTRODUCTION

Kottelat & Freyhof (2007) recognize 12 European species within the genus Romanogobio and two additional species (R. macropterus and R. persus) are known from the Caspian Sea basin in Asia (Naseka et al. 1999). Kottelat & Freyhof (2007) considered four Romanogobio species to occur in the Danube drainage, R. kesslerii, R. uranoscopus and R. vladykovi being widespread and R. antipai being restricted to the Lower Danube in Romania and Ukraine. Romanogobio antipai has not been found since the 1960s and is considered to be extinct (Kottelat & Freyhof, 2007).

In 2007, nine individuals of a very slender Romanogobio were caught in the upper Mur River in Austria. The Mur is a tributary of the Drava which flows to the Danube at Osijek. Initially, these were considered to be hybrids between Gobio obtusirostris and R. uranoscopus. In 2014, more than 80 of these slender gudgeons were caught in the course

of several sampling trips to the upper Mur. No R. uranoscopus were found in the area, making the initial hybrid hypothesis unlikely. In total, 21 individuals were kept for morphological analysis and 27 samples used for molecular characterisation. Molecular data (COI) placed these gudgeons separate from any of the Romanogobio species previously found in the Danube or elsewhere in Europe and the adjacent southern Caspian basin. Also, the gudgeon from the Mur River could not be identified by the key given by Kottelat & Freyhof (2007) and the descriptions of Romanogobio species by Bănărescu (1999). These findings suggested that the gudgeon from the Mur represents a new species, which is described here. Furthermore, molecular data presented by Geiger et al. (2014) indicate that R. banarescui from Greece represents a valid species previously synonymised with the Greek R. elimeius (Kottelat & Freyhof 2007), and our own molecular data (Fig. 1) strongly suggest that R. carpathorossicus might be a valid species, distinct from R. kesslerii.

FIGURE 1. Phylogenetic relationships among European Romanogobio species based on 553 bp of the COI gene. Shown is the ML tree; identical interspecific relationships were recovered in the BI tree (not shown). As measures of nodal support bootstrap replicates (BS, ML) and posterior probabilities (PP, BI) are shown above the branches (BS and PPs > 50 and 0.70, respectively, are shown)

MATERIAL AND METHODS

All fish were caught using a portable electroshocker (1.5 kW) or a stationary generator (13 kW) from a boat. After anesthesia, fishes were fixed in 5% formaldehyde and stored in 70% ethanol, or directly fixed in 99% ethanol. Measurements were made with a dial caliper and rounded to 1 mm. All measurements were made point to point (never by projections). Methods for counts and measurements follow Kottelat & Freyhof (2007). Scales along the lateral line were counted from the first one just behind the pectoral girdle to the last one at the end of the hypural complex. Scales on the caudal-fin base were excluded. Standard length (SL) was measured from the tip of the snout to the end of the hypural complex. The length of the caudal peduncle was measured from behind the base of the last anal-fin ray to the end of the hypural complex, at mid-height of the caudal-fin base. The last two branched rays articulating on a single pterygiophore in the dorsal and anal fins were counted as "1½".

Abbreviations used: SL, standard length; TL, total length. Collection codes: FSJF, Fischsammlung J. Freyhof, Berlin; KFUG, University of Graz (Institute of Biology); NMW, Museum of Natural History, Vienna; NMPC, National Museum, Prague; UAIC, University of Alabama Ichthyological Collection; ZFMK:ICH TIS, Zoological Research Museum Alexander Koenig, Ichthyology, Tissue Collection, Bonn.

DNA extraction and PCR. Total genomic DNA was extracted from fin clips of 27 individuals of R. skywalkeri, as well as from representatives of the other three extant Romanogobio species native to the Danube drainage (R. carpathorossicus n=4, R. vladykovi n=15, R. uranoscopus n=2) following a rapid Chelex protocol (Richlen & Barber 2005). The barcoding region of the cytochrome c oxidase subunit I (COI) gene was amplified and sequenced using the primers VF2_t1 and FishR2_t1 (Ward et al. 2005), following Koblmüller et al. (2011) and Duftner et al. (2005), respectively. DNA fragments were purified with SephadexTM G-50 (Amersham Biosciences) and visualized on an ABI 3130xl capillary sequencer (Applied Biosystems). Additional sequences from Romanogobio species were downloaded from BOLD and NCBI GenBank (Tang et al. 2011, Geiger et al. 2014, Knebelsberger et al. 2015, Table 1), or were provided by Matthias Geiger (ZFMK). Sequences were aligned by eye (COI) in Mega 6.06 (Tamura

et al. 2013) and trimmed to the shortest sequence. The length of the final alignment was 553 bp.

TABLE 1. List of COI-sequences of European Romanogobio species downloaded from BOLD, with information on drainage and country of origin.

Species Drainage Country Genbank Reference Acc. No. or BOLD ID Romanogobio Vardar Greece KJ554311 Geiger et al. 2014 banarescui Vardar Greece KJ554440 Geiger et al. 2014 Vardar Greece KJ554158 Geiger et al. 2014 Vardar Greece KJ554326 Geiger et al. 2014 Vardar Greece KJ554238 Geiger et al. 2014 Vardar Greece KJ554240 Geiger et al. 2014 Romanogobio Danube Czech Republic IFCZE910-11* Papousek unpublished carpathorossicus Danube Czech Republic IFCZE912-11* Papousek unpublished Danube Czech Republic IFCZE913-11* Papousek unpublished Danube Czech Republic IFCZE917-11* Papousek unpublished Romanogobio Oder Germany KM287055 Knebelsberger et al. belingi 2015 Rhine Germany KM287053 Knebelsberger et al. 2015 Elbe Germany KM287052 Knebelsberger et al. 2015 Elbe Germany KM287051 Knebelsberger et al. 2015 Rhine Germany KM287050 Knebelsberger et al. 2015 Rhine Germany KM287054 Knebelsberger et al. 2015 Rhine Germany KM287056 Knebelsberger et al. 2015 Elbe Czech Republic IFCZE906-11* Papousek unpublished Elbe Czech Republic IFCZE908-11* Papousek unpublished Elbe Czech Republic IFCZE909-11* Papousek unpublished Romanogobio Po Italy KJ554213 Geiger et al. 2014 benacensis Romanogobio Terek Russia JN003365 Tang et al. 2011 ciscaucasicus Romanogobio Aliakmon Greece KJ554225 Geiger et al. 2014 elimeius Aliakmon Greece KJ554544 Geiger et al. 2014 Aliakmon Greece KJ554330 Geiger et al. 2014 Aliakmon Greece KJ554218 Geiger et al. 2014 Aliakmon Greece KJ554345 Geiger et al. 2014 Aliakmon Greece KJ554100 Geiger et al. 2014 Aliakmon Greece KJ554523 Geiger et al. 2014 Romanogobio Don Russia JN003366 Tang et al. 2011 tanaiticus Romanogobio Danunbe Germany HM392089 Knebelsberger et al. 2015 uranoscopus 17

Danube Germany HM392090 Knebelsberger et al. 2015 Danube Germany HM392091 Knebelsberger et al. 2015 Danube Germany KM373679 Knebelsberger et al. 2015 Danube Germany KM373685 Knebelsberger et al. 2015 Danube Germany KM373663 Knebelsberger et al. 2015 Romanogobio Danube Germany HM392085 Knebelsberger et al. 2015 vladykovi Danube Germany HM392088 Knebelsberger et al. 2015 Danube Germany HM392092 Knebelsberger et al. 2015 Danube Germany HM392093 Knebelsberger et al. 2015 Danube Germany HM392094 Knebelsberger et al. 2015 Danube Germany HM392096 Knebelsberger et al. 2015 Danube Czech Republic HQ960505 Papousek unpublished Danube Czech Republic HQ960506 Papousek unpublished Danube Czech Republic HQ960507 Papousek unpublished Danube Czech Republic HQ960508 Papousek unpublished Danube Czech Republic HQ960509 Papousek unpublished Danube Czech Republic HQ960513 Papousek unpublished Danube Czech Republic HQ960514 Papousek unpublished *, no GenBank accession numbers, but BOLD-IDs were available for these samples

Molecular data analysis. Prior to phylogenetic analysis, identical sequences were collapsed into haplotypes using DNACollapser implemented in FaBox (Villesen, 2007). Phylogenetic analyses by means of Maximum Likelihood (ML) and Bayesian Inference (BI) were performed in PhyML 3.0 (Guindon et al. 2010) and MrBayes 3.2 (Ronquist et al. 2012), respectively, employing the best-fitting models of sequence evolution selected by the Bayesian Information Criterion (BIC) in the model selection module implemented in PhyML (Lefort et al. 2017). Nodal support for the ML tree was assessed by means of 1000 bootstrap replicates. For Bayesian phylogenetic inference, posterior trees and model parameters were obtained from Metropolis coupled Markov chain Monte Carlo (MCMC) simulations (2 independent runs; 2 million generations; 8 chains; 25% burn-in). Stationarity of the chains and convergence of the trees and parameter values were assessed in Tracer 1.6 (available at http:// tree.bio.ed.ac.uk/software/tracer) prior to constructing a 50% majority rule consensus tree. The post-burn-in Effective Sample Sizes (ESS) for all parameters exceeded 200, indicating that the sampled parameter values accurately represented the posterior distribution (Kuhner, 2009). Pairwise COI net divergences (based on uncorrected p- distances) among species were calculated in Mega.

Results. Phylogenetic analysis of the partial COI gene from all currently recognized extant European Romanogobio species places R. skywalkeri in a well-supported, distinct clade (Fig. 1). Its closest related congener, based on COI data, is R. banarescui. The net divergence between R. skywalkeri and R. banarescui amounted to 6.3% (uncorrected p- distance). Within R. skywalkeri, two haplotypes were found that differed by a single substitution. The low level of genetic diversity observed in R. skywalkeri indicates a small effective population size and/or a recent genetic bottleneck.

Key to specoes of Romanogobio in the Danube River drainage

1a Epithelial crests on the predorsal back absent…………………………………………………………,,,…….2

1b Epithelial crests on the predorsal back present………………………….……..,,……………………………..3

2a Barbel reaching to posterior eye margin or just shortly beyond; 8½ branched dorsal-fin rays; midlateral dark- grey blotches isolated from the dark-grey saddles on the back; breast usually naked……………………………………………………………………………….……..………R. skywalkeri

2b Barbel reaching always beyond posterior eye margin, often to operculum; 7½ branched dorsal-fin rays; midlateral dark-grey blotches usually fused to dark-grey saddles behind the dorsal-fin base; breast covered by scales...... R. uranoscopus

3a Usually 7½ branched dorsal-fin rays; caudal peduncle strongly compressed; pectoral fin reaching to middle between pectoral- and pelvic-fin origins……………………………………………………………………………..…………….…R. vladykovi

3b Usually 8½ branched dorsal-fin rays; caudal peduncle slightly compressed, pectoral fin reaching to or almost to pelvic-fin origin……………………………………………………………………………………………………….….4

4a 4 scales between lateral line and pelvic fin origin; eye diameter 17–23 % HL……….……………R. antipai

4b 3 scales between lateral line and pelvic-fin origin; eye diameter 20–28 % HL…………………………………………………………………………………R. kesslerii & R. carpathorossicus

Romanogobio skywalkeri, new species

(Fig.2–3)

Holotype: NMW 99058, 64 mm SL; Austria: Styria prov.: River Mur at Unteraich; 47.403°N 15.240°E; T. Friedrich, 24 Nov 2016. Paratypes: FSJF 3688, 5, 83–96 mm SL; NMW 99059, 2, 73–88 mm SL; Austria: Styria prov.: River Mur at Foirach; 47.403°N 15.176°E; T. Friedrich, 24 Nov 2016.—NMW 98639, 1, 95 mm SL; NMW 98641, 3, 47–51 mm SL; NMW 99060, 5, 46–60mm SL; Austria: Styria Prov.: Mur at Unteraich;

47.403°N 15.240°E; T. Friedrich, 4 Nov 2014.—NMW 98640, 9, 40–53 mm SL; Austria: Styria Prov.: Mur at Unteraich; 47.403°N 15.240°E; Mur at St. Dionysen; 47.413°N 15.204°; Mur at Proleb; 47.395°N 15.142°E; Mur at Fisching; 47.171°N 14.731°E; T. Friedrich, 4 Nov 2014. Diagnosis. Based on our COI data, R. skywalkeri is most closely related to R. banarescui. It is distinguished from this species by lacking epithelial crests on the predorsal back (vs. present), having 12–14 total pectoral-fin rays (vs. 10–11) and 8½ branched dorsal-fin rays (vs. usually 7½). Romanogobio skywalkeri is distinguished from R. antipai, R. carpathorossicus, R. kesslerii and R. vladykovi from Danube drainage by lacking epithelial crests on the predorsal back (vs. present). Romanogobio skywalkeri is distinguished from R. uranoscopus from the Danube drainage by having a shorter barbel (barbel reaching to the posterior eye margin or just shortly beyond vs. reaching always beyond the posterior eye margin, often to the operculum), 8½ branched dorsal- fin rays (vs. 7½, Table 3) and the midlateral dark-grey blotches being usually isolated from the dark-grey saddles on the back (vs. usually fused behind the dorsal-fin base). The breast was naked in all but one individuals of R. skywalkeri examined for this character (n=20). Only one individual had one single scale on the breast. A very variable breast squamation pattern was observed in the R. uranoscopus examined (see below) and this is also reported by Bănărescu et al. (1999). Squamation pattern is ranging from a fully scaled breast to an almost naked breast with few isolated scales. A fully naked breast was not found in R. uranoscopus. Romanogobio skywalkeri is further distinguished from R. vladykovi and R. belingi from the North Sea, Baltic and Black Sea basins, by having 8½ branched dorsal-fin rays (vs. usually 7½), the barbel reaching to the posterior eye margin or just shortly beyond (vs. reaching to the middle of the eye or slightly beyond, never beyond the posterior eye margin), a longer pectoral fin (pectoral fin reaching to or almost to the pelvic-fin origin vs. usually reaching to the middle between the pectoral- and pelvic-fin origins). In R. skywalkeri the posteriormost caudal peduncle is slightly deeper than wide (vs. much deeper than wide in R. vladykovi and R. belingi).

FIGURE 2. Romanogobio skywalkeri, NMW 99058, holotype, 65 mm SL; Austria: River Mur at Bruck a.d. Mur. (photographs by Maria Bräuner)

Description. See figures 2–3 for general appearance and Table 2 for morphometric data. Very elongate species, with streamlined body shape. Greatest body depth at dorsal-fin origin, almost continuously decreasing towards caudal-fin base. Greatest body width at pectoral-fin base. Section of head trapezoidal, flattened on ventral surface. Body and caudal peduncle slightly compressed. Depth of caudal peduncle 3– 4 times in its length. Caudal peduncle slender and moderately compressed. Pelvic-fin origin below first or second branched dorsal-fin ray. Anal- fin origin clearly behind vertical of dorsal-fin base. Pectoral fin reaching to or almost to pelvic-fin origin. Pelvic fin reaching to anal-fin origin. Anus closer to anal-fin base than to pelvic-fin base. Dorsal-fin margin concave, caudal fin forked. Mouth inferior, horseshoe shaped. Upper lips thin and smooth. Lower lip shallow, fused with throat. A single pair of maxillary

barbels reaching to posterior eye margin or slightly beyond. Largest recorded specimen 138 mm TL. Dorsal fin with 7½ (1), 8½ (19) or 9½ (1) branched rays. Anal fin with 6½ (19) or 7½ (2) branched rays. Caudal fin with 9+8 (21) branched rays. Pectoral fin with 12 (7) 13 (5) or 14 (9) branched rays. Pelvic fin with 7 (21) branched rays. Body covered by cycloid scales. Breast without scales, in one individual, one scale on middle of breast. No epithelial crests on scales. Lateral line complete, with 40–43 scales on body and 1–3 on caudal-fin base. Scale rows between lateral line and dorsal-fin origin 5 (4), 6 (16) or 7 (1) and between lateral line and pelvic fin origin 3 (7) or 4 (14).

TABLE 2. Morphometric data of Romanogobio skywalkeri (holotype: NMW 99058; paratypes: NMW 98639–98641, NMW 99058–99060; n=21).

Holotype Paratypes mean min max SD SL (mm) 64.7 51.0 39.8 95.4 In percent of SL Head length (HL) 26.6 24.4 22.4 26.6 1.1 Body depth at dorsal-fin origin 15.5 15.6 14.2 17.8 1.0 Body width at dorsal-fin origin 12.4 10.7 8.6 14.4 1.5 Predorsal length 47.0 44.7 42.2 47.1 1.5 Prepelvic length 50.1 46.1 43.0 50.1 1.7 Preanal length 65.0 64.7 60.2 67.7 1.8 Distance between anus and anal-fin origin 9.1 6.3 4.2 9.1 1.2 Depth of caudal peduncle 6.8 7.1 6.7 7.8 0.3 Width of caudal peduncle 3.9 2.7 1.9 4.7 0.7 Length of caudal peduncle 23.3 24.8 22.1 27.6 1.5 Dorsal-fin base length 15.4 14.0 12.9 16.6 1.0 Anal-fin base length 9.9 8.9 6.4 10.4 1.0 Pectoral-fin length 24.4 23.2 20.7 24.8 1.1 Pelvic-fin length 19.3 18.1 15.1 19.9 1.2 In percent of HL Snout length 36 38.6 32 45 3.0 Eye diameter 21 22.7 19 26 2.2 Barbel length 38 30.9 22 38 4.6

Coloration. In life: A greenish hue when freshly caught. Top of head and back pale- brown with indistinct brown, rounded or irregularly-shaped blotches; 1–2 blotches on predorsal back, one at dorsal-fin origin, 2–3 behind dorsal-fin base, not fused with

midlateral blotches. Flank silvery or grey with 6–9 dark-grey, roundish mid-lateral blotches, fading in individuals larger than 75 mm SL. A whitish blotch on upper and lower caudal-fin base interrupted by a brown extension of last midlateral blotch along lateral line. Pigment cells denser on upper and lower extremities of exposed part of flank scales forming dark-grey lines on back and upper flank in some individuals. In other individuals, scale margins brown forming a reticulate pattern or scale pockets brown forming a spotted pattern. A short black band between middle of upper lip and eye margin and a black, irregularly shaped blotch below eye. Operculum with a dark- grey or dark brown blotch. Dorsal- and pectoral-fin rays with 2–3 and caudal fin with 2–4 bands of elongated blotches. Pelvic and anal fins without or with few small black blotches. Fins hyaline in juveniles, usually yellowish in adults. Etymology. Named for Luke Skywalker, the hero of the movie “Star Wars: Episode IV—A New Hope” (Lucasfilms, Twentieth Century Fox, 1977). As common name emerald gudgeon fits the line with common names of other Romanogobio species and reflects the green hue of the fish when observed in his natural habitat or freshly caught. Distribution. Known from a river section of about 85 km in the upper Mur between the villages Fisching and Laufnitzdorf (Fig.4). Ecology and conservation. Romanogobio skywalkeri occurs together with Gobio obtusirostris. Romanogobio skywalkeri is highly rheophilic and was found to be most abundant on gravel banks with high flow velocities and water depths between 0.1 and 0.4 meters (Fig.5). All age classes were found in this type of habitat. Here it co-occurs with juvenile (0+ and 1+) Thymallus thymallus and Barbatula barbatula. Juvenile (0+) R. skywalkeri were also found in small side channels with high current velocities together with juvenile T. thymallus. Around 50% of the distribution area of R. skywalkeri is situated in the Natura 2000 Site “Ober- und Mittellauf der Mur mit Puxer Auwald, Puxer Wand und Gulsen” with no migration obstacles. Nevertheless, with several additional hydropower projects in the planning or even construction stages in the Mur River, it is of urgent necessity to critically assess human impacts, which may directly affect the habitat of this species which, as currently understood, appears to be endemic to Austria.

FIGURE 3. Romanogobio skywalkeri, from the top, not preserved, 109 mm SL; FSJF 3688, 91 mm SL, 96 mm SL; Austria: River Mur at Oberaich.

FIGURE 4. Distribution of R. skywalkeri, Mur River, Austria

TABLE 3. Frequency of meristic data in selected Romanogobio species.

Branched dorsal-fin ray N 6½ 7½ 8½ 9½ R. banarescui 7 7 R. carpathorossicus/kesslerii 36 33 3 R. elimeius 7 6 1 R. skywalkeri 21 1 20 R. uranoscopus 15 14 1 R. vladykovi 5 5 Branched pectoral-fin ray N 10 11 12 13 14 R. banarescui 7 6 1 R. carpathorossicus/kesslerii 36 3 14 18 1 R. elimeius 7 4 3

R. skywalkeri 21 7 5 9 R. uranoscopus 15 4 11 R. vladykovi 5 1 4 Lateral line scales N 37 38 39 40 41 42 43 R. banarescui 7 1 2 3 1 R. carpathorossicus/kesslerii 36 7 17 9 3 R. elimeius 7 1 1 3 2 R. skywalkeri 21 2 7 9 3 R. uranoscopus 15 2 10 3 R. vladykovi 5 1 1 2 1 Scales between lateral line and N 4 5 6 7 base of dorsal fin R. banarescui 7 7 R. carpathorossicus/kesslerii 36 6 30 R. elimeius 7 7 R. skywalkeri 21 4 16 1 R. uranoscopus 15 13 2 R. vladykovi 5 4 1 Scales between lateral line and N 3 4 5 6 base of pelvic fin R. banarescui 7 5 2 R. carpathorossicus/kesslerii 26 19 17 R. elimeius 7 1 6 R. skywalkeri 21 7 14 R. uranoscopus 15 5 9 1 R. vladykovi 5 2 3

FIGURE 5. Mur River, Austria, habitat of R. skywalkeri.

DISCUSSION

We follow Stout et al. (2016) and authors cited therein in treating the cyprinid subfamily Gobioninae as a family in its own right, Gobionidae.

Our molecular data as well as those presented by Geiger et al. (2014) strongly suggest that Kottelat & Freyhof (2007) erred in synonymising R. banarescui with R. elimeius and R. carpathorossicus with R. kesslerii. We examined materials of all these species (see below). Romanogobio banarescui (Fig. 6) is immediately distinguished from R. elimeius (Fig. 7) by having epithelial keels on the predorsal back (vs. absent), a shorter barbel (barbel reaching to the posterior eye margin or just shortly beyond vs. reaching always beyond the posterior eye margin, often to the operculum) and a silvery colour pattern with a distinct midlateral row of blotches (vs. yellowish-brown colour pattern and midlateral blotches usually faded or absent). Bănărescu et al. (1999) treat R. elimeius as a subspecies of R. uranoscopus. Our molecular analysis revealed both as closely related. The two species are distinguished by the squamation pattern on the breast. Romanogobio uranoscopus always has scales on the breast and we found a very variable breast 26

squamation pattern, ranging from a fully scaled breast to an almost naked breast with few isolated scales, while in all R. elimeius examined the breast was naked. We follow Bănărescu et al. (1999) and treat Gobio persus stankoi from the Vardar River as a synonym of R. elimeius. Romanogobio banarescui is related to R. skywalkeri and not to R. kesslerii as suspected by Bănărescu (1999). Romanogobio banarescui is immediately distinguished from R. kesslerii and its (former) subspecies by having usually 7½ branched dorsal-fin rays (vs. usually 8½). Therefore, we treat R. banarescui and R. elimeius as valid species.

Bănărescu (1964) and Bănărescu (1999) recognised four subspecies in R. kesslerii. Romanogobio kesslerii banarescui is discussed above. Kottelat & Freyhof (2007) treat R. k. antipai as a valid species and we have no arguments to reject this hypothesis. Our molecular data distinguish R. carpathorossicus, from the Danube River drainage well from R. kesslerii, described from the Dniester River drainage. It is beyond the aims of this study to clarify how both species are distinguished by morphological characters. Naseka & Freyhof (2004) treat R. banaticus, from the Danube drainage in western Romania, as a valid species. However, if the Danubian populations are distinguished from R. kesslerii, as our molecular data strongly suggest, the first available name is not R. banaticus but R. carpathorossicus, a species described from the Tiza, a tributary of the Danube. Indeed, the populations previously identified as R. kesslerii in the Danube drainage are in a need of a more detailed study as we could identify one population from the Ialomita River, a lower tributary of the Danube, as R. kesslerii, demonstrating that R. kesslerii is not endemic to the Dniester River but might be more widespread at least in the lower Danube drainage.

FIGURE 6. From the top. Romanogobio banarescui, not preserved, about 80 mm SL; Greece: Axios at Axioupoli; R. carpathorossicus, about 100 mm SL; Romania: Sapanta downstream of Sapanta; R. kesslerii, about 80 mm SL; Romania: Ialomita near Branesti;

Material examined for morphological comparisons

Romanogobio banarescui: ZFMK 50742–50748, 7, 54–65 mm SL; Greece: Axios at Axioupoli, 40.99111°N 22.56277°E. Romanogobio carpathorossicus: ZFMK 51907–51910, 6, 68–82 mm SL; Romania: Mura near Gelmar, 46.0025°N 23.273°E.—ZFMK 54616–54617, 4, 39–92 mm SL; Romania: Iza near Sighetu Marmatia, 48.19083°N 23.91166°E.—ZFMK 51981– 51982, 3, 68–69 mm SL; Romania: Nera near Sasca Montana, 44.92138°N 21.83388°E.—ZFMK 087614–087623, 10, 59–80 mm SL; Slovenia: Kolpa near Prizemlj, 45.67416°N 15.43500°E.—ZFMK 087607–087613, 7, 40–70 mm SL; Croatia: Kolpa near Komanje, 45.650°N 15.366°E.

ZFMK 087255–087258, 4, 70–85 mm SL; Slovakia: Ublianka near Ubla.—NMW 96527, 1; Austria: Mur near Bad Radkersburg.—NMW 98493, 1, 70 mm SL; Austria: Mur near near Bad Radkersburg, 46.678°N 16.002°E. Romanogobio elimeius: ZFMK 50664–50670, 7, 60–73 mm SL; Greece: Aliakmon north of Neapoli, 40.33361°N 21.41527°E. Romanogobio uranoscopus: ZFMK 087515–087519, 5, 46–53 mm SL; Croatia: Kolpa near Komanje, 45.650°N 15.366°E.—ZFMK 054625–054629, 5, 31–36 mm SL; Romania: Iza near Sighetu Marmatia, 48.19083°N 23.91166°E.—NMW 96530, 1; Austria: Mur near Radkersburg.—NMW 98489–98490, 2, 72–89 mm SL; Austria: Mur near Bad Radkersburg, 46.678°N 16.002°E.—NMW 92951, 1, 78 mm SL; Austria: Lavant near Lavamünd.—NMW 88096, 1, 54 mm SL; Austria: Danube near Klosterneuburg. Romanogobio vladykovi: NMW 98446, 1, 82 mm SL; Austria: Mur near Obervogau.— NMW 98435–98436, 2, 69– 78 mm SL; Austria: Danube near Engelhartszell, 48.507°N 13.731°E.—NMW 96525, 1, 98 mm SL; Austria: Drava near Lavamünd.—NMW 96523, 1, 76 mm SL; Austria: Mur near Bad Radkersburg.

FIGURE 7. From the top. Romanogobio elimeius, not preserved, about 90 mm SL; Greece: Aliakmon north of Neapoli; R. uranoscopus, about 90 mm SL; Romania: Nera at Sasca Montana.

Newly-sequenced material

Romanogobio albipinnatus: FSJF DNA-129, 2; Russia: Bachtěmir near Svetloje,

45.900°N 47.633°E (GenBank accession numbers: MF960796, MF960797). Romanogobio belingi: FSJF DNA-388, 2; Ukraine: Sluch near Anastasivka, 50.768°N 27.383°E (GenBank accession numbers: MF960799, MF960800). Romanogobio carpathorossicus: KFUG ABOL4, 1; Austria: Mur near Bad Radkersburg, 46.662°N 16.013°E (GenBank accession number: MG786152).— KFUG ABOL5, 1; Austria: Sulm near Leibnitz, 46.783°N 15.517°E (GenBank accession number: MG786169).—NMW 98493, 1; Austria: Mur near Bad Radkersburg, 46.662°N 16.013°E (GenBank accession number: MG786184).— NMW 98715, 1; Austria: Sulm near Leibnitz, 46.783°N 15.517°E (GenBank accession number: MG786158).—FSJF DNA-2169, 2; Slovenia: Kolpa at Podzemelj, 45.604°N 15.277°E (GenBank accession numbers: MF960802, MF960803).— ZFMK:ICH 5404, 1; Romania: Timiş near Constantin Daicoviciu, 45.546°N 22.154°E (GenBank accession number: MF960809).—ZFMK:ICH 5405, 1; Romania: Timiş near Constantin Daicoviciu, 45.546°N 22.154°E (GenBank accession number: MF9608010). Romanogobio ciscaucasicus: 2; Russia, Kuma near Artezian, 44.866°N 46.631°E (GenBank numbers: MF960813, MF960814). Romanogobio kesslerii: FSJF DNA-343, 1; Ukraine: Murafa at Hal’zhbiivka, 48.265°N 28.202°E (GenBank accession number: MF960798).—FSJF DNA-461, 1; Dniester at Torchynovychi, 49.457°N 23.053°E (GenBank accession number: MF960801). Romanogobio macropterus: FSJF DNA-752, 1; Georgia: Alazani near Kalkva, 41.767°N 45.924°E (GenBank accession number: MF960804). Romanogobio parvus: Russia: FSJF DNA-32, 2; Kuban at Ubezhenskaya, 44.914°N 41.278°E (GenBank accession numbers: MF960792, MF960793). Romanogobio pentatrichus: 2; Russia: Kuban drainage (GenBank accession numbes: MF960816, MF960817). Romanogobio skywalkeri: NMW 98639, 1; Austria: Mur at Unteraich, 47.402°N 15.240°E (GenBank accession number: MG797658).—NMW 98641, 3; Austria: Mur at Unteraich, 47.402°N 15.240°E (GenBank accession numbers: MG786142, MG786162, MG786178).—NMW 98716, 1; Austria: Mur at Unteraich, 47.402°N 15.240°E (GenBank accession number: MG786143). —NMW 98640, 9; Austria:

Mur at Unteraich, 47.402°N 15.240°E, Mur at St. Dionysen, 47.413°N 15.204°E, Mur at Proleb, 47.395°N 15.142°E, Mur at Fisching, 47.171°N 14.731°E (GenBank accession numbers: MG786146, MG786156, MG786161, MG786171, MG786172, MG786173, MG786176, MG786183, MG786186).—NMW 99058, 1; Austria: Mur at Unteraich, 47.402°N 15.240°E (GenBank accession number: MG786145).—NMW 99059, 2; Austria: Mur at Foirach, 47.403°N 15.176°E (GenBank accession numbers: MG786160, MG786187).—NMW 99060, 5; Austria: Mur at Unteraich, 47.402°N 15.240°E (GenBank accession numbers: MG786154, MG786159, MG786163, MG786168, MG786181).—NMW 99061, 3; Austria: Mur at Unteraich, 47.402°N 15.240°E (GenBank accession numbers: MG786147, MG786151, MG786177).—KFUG ABOL6, 1; Austria: Mur at Unteraich, 47.402°N 15.240°E (GenBank accession number: MG786182).—without voucher, 1; Austria: Mur at Laufnitzdorf, 47.290°N 15.326°E (GenBank accession number: MG751105). Romanogobio tanaiticus: ZFMK ICH 55284, 2; Russia: Don, Ust’-Khoperskaya, 49.574°N 42.432°E (GenBank accession numbers: MF960811, MF960812). Romanogobio uranoscopus: NMW 98489, 2; Austria: Mur near Bad Radkersburg, 46.678°N 16.002°E (GenBank accession numbers: MG786153, MG786180).— ZFMK:ICH 52015, 1; Romania: Bistriţa at Frumosu, 47.144°N 25.864°E (GenBank accession number: MF960905).—ZFMK:ICH 52016, 1; Romania: Bistriţa at Frumosu, 47.144°N 25.864°E (GenBank accession number: MF960906). Romanogobio valdykovi: NMW 98339, 1; Austria: Mur near Gralla, 46.805°N 15.588°E (GenBank accession number: MG786157).—NMW 98417, 1; Austria: Naarn near Labing, 48.189°N 14.716°E (GenBank accession number: MG786148).—NMW 98421, 1; Austria: Danube at Engelhartszell, 48.507°N 13.731°E (GenBank accession number: MG786175).—NMW 98425, 1; Austria: Danube at Engelhartszell, 48.507°N 13.731°E (GenBank accession number: MG786170).—NMW 98435, 1; Austria: Danube at Engelhartszell, 48.507°N 13.731°E (GenBank accession number: MG786167).—NMW 98436, 1; Austria: Danube at Engelhartszell, 48.507°N 13.731°E (GenBank accession number: MG786155).—NMW 98446, 1; Austria: Mur between Obervogau and Gralla, 46.805°N 15.588°E (GenBank accession number: MG786166).—NMW 98698, 3; Austria: Sulzbach near Bad Radkersburg, 46.767°N 15.889°E (GenBank accession 31

numbers: MG786144, MG786149, MG786164).—NMW 98953, 2; Austria: Sulzbach near Bad Radkersburg, 46.767°N 15.889°E (GenBank accession numbers: MG786179, MG786185).—NMW 99071, 1; Austria: Danube in Vienna/ Freudenau, 48.179°N 16.483°E (GenBank accession number: MG786174).— withouth voucher, 1; Austria: March at Zwerndorf, 48.350°N 16.844°E (GenBank accession number: MG751104).—withouth voucher, 1; Slovenia: Sava at Dolsko, 46.091°N 14.695°E (GenBank accession number: MF960815).—FSJF DNA-77, 2; Romania: Danube at Feteşti, 44.367°N 27.900°E (GenBank accession numbers: MF960794, MF960795).— ZFMK:ICH 52042, 1; Romania: Siret near Huţani, 47.699°N 26.460°E (GenBank accession number: MF960807).—ZFMK:ICH 52042, 1; Romania: Siret near Huţani, 47.699°N 26.460°E (GenBank accession number: MF960808). Gobio sp.: NMW 98315, 1; Austria: Lobenbach at Rohrbrunn, 47.121°N 16.105°E (Genbank accession number: MG786165).—NMW 98437, 1; Austria: Hüttinger Altarm at Labing, 48.180°N, 14.715°E (Genbank accession number: MG786150).

ACKNOWLEDGEMENTS

We thank Fabian Herder (ZFMK) for allowing us to examine fishes under his care. For providing yet unpublished sequences of various Romanogobio species (GenBank accession numbers MF960792-MF960817), we are especially grateful to Matthias Geiger (ZFMK). For help during field work and for correspondence, literature, pictures, suggestions and comments we thank Maria Bräuner, Lina Florian, Simon Führer, Michael Gallowitsch, Pamela Gumpinger, Gertrud Haidvogl, Carina Mielach, Kurt Pinter, Florian Pletterbauer, Erika Thaler, Günther Unfer, Christian Witt, Bernhard Zeiringer (all from Institute of Hydrobiology and Aquatic Ecosystem Management, Vienna), Klaus Berg and Franz Lumesberger-Loisl (Consultants in Aquatic Ecology and Engineering—blattfisch e.U.), Wolfgang Hauer, Reinhard Haunschmid and Brigitte Sasano (Bundesamt für Wasserwirtschaft), Wolfgang Gessl (University of Graz), Dirk Neumann (Bavarian State Collection of Zoology) and Clemens Ratschan (Technisches Büro Zauner GmbH). We are particularly grateful to Steven Weiss (University of Graz) for his comments on previous versions of the manuscript and for forwarding the phone call that started this 32

collaboration. Financial support for the molecular phylogenetic work was provided by the Austrian Federal Ministry of Science, Research and Economy in the frame of the Austrian Barcode of Life (ABOL) pilot project on vertebrates (www.abol.ac.at). This study benefitted from the FREDIE project, supported by the Leibniz Association Joint Initiative for Research and Innovation (SAW).

LITERATURE CITED

Bănărescu, P.M. (1961) Weitere systematische Studien über die Gattung Gobio (Pisces, Cyprinidae) insbesondere im Donaubecken. Věstník Československé zoologické společnosti, 25 (4), 318–346.

Bănărescu, P.M. (1999) Gobio kessleri Dybowski, 1862. In: Bănărescu, P.M. (Ed.), The freshwater fishes of Europe. Vol. 5/I, Cyprinidae 2. Aula, Wiebelsheim, pp. 135–162.

Bănărescu, P.M., Bless, R. & Economidis, P.S. (1999) Gobio uranoscopus Agassiz, 1828. In: Bănărescu, P.M. (Ed.), The freshwater fishes of Europe. Vol. 5/I, Cyprinidae 2. Aula, Wiebelsheim, pp. 183–202.

Duftner, N., Koblmüller S. & Sturmbauer, C. (2005) Evolutionary relationships of the Limnochromini, a tribe of benthic deepwater cichlid fish endemic to Lake Tanganyika, East Africa. Journal of Molecular Evolution, 60, 277–289. https://doi.org/10.1007/s00239-004-0017-8

Geiger, M.F., Herder, F., Monaghan, M.T., Almada, V., Barbieri, R., Bariche, M., Berrebi, P., Bohlen, J., Casal-Lopez, M., Delmastro, G.B., Denys, G.P.J., Dettai, A., Doadrio, I., Kalogianni, E., Kärst, H., Kottelat, M., Kovačić, M., Laporte, M., Lorenzoni, M., Marčić, Z., Özuluğ, M., Perdices, A., Perea, S., Persat, H., Porcelotti, S., Puzzi, C., Robalo, J., Šanda, R., Schneider, M., Šlechtová, V., Stoumboudi, M., Walter, S. & Freyhof, J. (2014) Spatial heterogeneity in the Mediterranean Biodiversity Hotspot affects barcoding accuracy of its freshwater fishes. Molecular Ecology Resources, 14, 1210–1221. https://doi.org/10.1111/1755-0998.12257

Guindon, S., Dufayard, J.F., Lefort, V., Anisimova, M., Hordijk, W. & Gascuel. O. (2010) New algorithms and methods to estimate maximum-likelihood phylgoenies: assessing the performance of PhyML 3.0. Systematic Biology, 59, 307–21. https://doi.org/10.1093/sysbio/syq010

Knebelsberger, T., Dunz, A.R., Neumann, D. & Geiger, M.F. (2015) Molecular diversity of Germany’s freshwater fishes and lampreys assessed by DNA barcoding. Molecular Ecology Resources, 3, 562– 572.https://doi.org/10.1111/1755-0998.12322 Koblmüller, S., Salzburger, W., Obermüller, B., Eigner, E., Sturmbauer, C. & Sefc, K.M. (2011) Separated by sand, fused by dropping water: habitat barriers and fluctuating water levels steer the evolution of rock-dwelling cichlid populations. Molecular Ecology, 20, 2272–2290. https://doi.org/10.1111/j.1365-294X.2011.05088.x

Kottelat, M. & Freyhof, J. (2007) Handbook of European freshwater fishes. Kottelat, Cornol and Freyhof, Berlin, xiv + 646 pp. Kuhner, M.K. (2009) Coalescent genealogy samples: window into population history. Trends in Ecology and Evolution, 24, 86–93. https://doi.org/10.1016/j.tree.2008.09.007

Lefort, V., Longueville, J.-E. & Gascuel, O. (2017) SMS: smart model selection in PhyML. Molecular Biology and Evolution, 34, 2422–2424. https://doi.org/10.1093/molbev/msx149

Naseka, A.M., Bănărescu, P.M. & Bogutskaya, N. (1999) Gobio persus Gunther, 1899. In: Bănărescu, P.M. (Ed.), The freshwater fishes of Europe. Vol. 5/I, Cyprinidae 2. Aula, Wiebelsheim, pp. 163–181.

Naseka, A.M. & Freyhof, J. (2004) Romanogobio parvus, a new gudgeon from River Kuban, southern Russia (Cyprinidae, Gobioninae). Ichthyological Exploration of Freshwaters, 15, 17–23. 33

Richlen, M.L. & Barber, P.H. (2005) A technique fort the rapid extraction of microalgal DNA from single live and preserved cells. Molecular Ecology Notes, 5, 688–691. https://doi.org/10.1111/j.1471- 8286.2005.01032.x

Ronquist, F., Teslenko, M., van der Mark, P., Ayres, D.L., Darling, A., Höhna, S., Larget, B., Liu, L., Suchard M.A. & Huelsenbeck J.P. (2012) MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across large model space. Systematic Biology, 61, 539–542. https://doi.org/10.1093/sysbio/sys029

Stout, C.C., Tan, M., Lemmon, A.R., Lemmon, E.M. & Armbruster, J.W. (2016) Resolving Cypriniformes relationships using an anchored enrichment approach. BMC Evolutionary Biology, 16, 244. https://doi.org/10.1186/s12862-016-0819-5

Tamura, K.G. Stecher, D. Peterson, A. Filipski, A. & Kumar, S. (2013) MEGA6: molecular evolutionary genetic analysis version 6.0. Molecular Biology and Evolution, 30, 2725–2729. https://doi.org/10.1093/molbev/mst197

Tang, K.L., Agnew, M.K., Chen, W.-J., Hirt, M.V., Raley, M.E., Sado, T., Schneider, L.M., Yang, L., Bart, H.L., He, S., Liu, H., Miya, M., Saitoh, K., Simons, A.M., Wood, R.M. & Mayden, R.L. (2011) Phylogeny of the gudgeons (Teleostei: Cyprinidae: Gobioninae). Molecular Phylogenetics and Evolution, 61, 103–124. https://doi.org/10.1016/j.ympev.2011.05.022

Villesen, P. (2007) FaBox: an online toolbox for fasta sequences. Molecular Ecology Notes, 7, 965–968. https://doi.org/10.1111/j.1471-8286.2007.01821.x

Ward, R.D., Zemlak, T.S., Innes, B.H., Last, P.R. & Hebert, P.D.N. (2005) DNA barcoding Australia’s fish species. Philosophical Transactions of the Royal Society B—Biological Sciences, 360, 1847–1857. https://doi.org/10.1098/rstb.2005.1716

Chapter 2

First records of the parthenogenetic Surinam cockroach Pycnoscelus surinamensis (Insecta: Blattodea: Blaberidae) for Central Europe

Zangl L, Kunz G, Berg C, Koblmüller S. First records of the parthenogenetic Surinam cockroach Pycnoscelus surinamensis (Insecta: Blattodea: Blaberidae) for Central Europe. J Appl Entomol. 2019; 143:308–313. https://doi. org/10.1111/jen.12587

LUKAS ZANGL, GERNOT KUNZ, CHRISTIAN BERG, STEPHAN KOBLMÜLLER

Institute of Biology, University of Graz, Graz, Austria

ABSTRACT

Sixteen species of cockroaches have been reported for Austria so far. This study is the first record of the parthenogenetic Surinam cockroach, Pycnoscelus surinamensis (L.) for Austria (and thus Central Europe). The species is natively distributed in Indo-Malaysia but has been unintentionally introduced in many, mainly tropical, countries throughout the world. Sequencing the DNA barcoding region revealed that all Austrian P. surinamensis samples had the same haplotype, which they shared with samples from the United States of America, Guyana and French Polynesia, indicating that all these samples/populations belong to the same clonal lineage. Even though in temperate regions, the occurrence of P. surinamensis is currently limited to greenhouses, we advocate proper monitoring of the populations with respect to global warming and the expected increasing independence of this species from greenhouses that comes along with it.

K E Y WO R D S distribution range expansion, global warming, greenhouse, neozoon, pest

INTRODUCTION

Cockroaches (Blattodea) are an insect order that comprises many highly adaptable species, some of which are feared as peridomestic pest species that were unintentionally introduced in many countries throughout the world. Even though most of these pest species are of tropic origin, some species such as the American cockroach, Periplaneta americana (Linnaeus 1758), the German cockroach, Blattella germanica (Linnaeus 1758) and the oriental cockroach Blatta orientalis (Linnaeus 1758) even established populations in temperate regions (Cochran, 1999).

Sixteen species of cockroaches have been reported for Austria so far (Table 1). Only seven of these species are native to the country and found in the wild and not considered pests. They belong to the family Ectobiidae and are placed in two genera, Ectobius (4 species) and Phyllodromica (3). The remaining nine species, all of which are alien, belong to three families: Ectobiidae (2), Blaberidae (2) and Blattidae (5). Of Nyctibora sp. (Ectobiidae) and Rhyparobia maderae (Fabricius, 1781) (Blaberidae), only one specimen was ever found in Austria (Ebner, 1946). Most of the alien cockroach species are not (yet) present in the wild, but mainly found in syn-anthropic indoor habitats such as houses, tropical green houses, gardening shops or supermarkets. Several of these species are known to undergo mass reproductions. They can not only destroy and contaminate food reserves, but, because of their potential for transmitting diseases and triggering allergies, might also pose a risk to human health (Baur, Landau Lüscher, Müller, Schmidt, & Coray, 2004; Hubert, Stejskal, Athanassiou, & Throne, 2018; Pospischil, 2010).

Here, we report the first records of the originally tropic Surinam cockroach, P. surinamensis (L.), for Austria and thus Central Europe, which were encountered by chance when capturing P. australasiae at the botanical garden in Graz for a student’s course and amongst other cockroaches in the Butterfly House in Vienna.

TA B L E 1 Cockroach species recorded in Austria so far Taxon and author Red list Note Published in Ectobiidae Ectobius erythronotus Burr, 1898 VU Native Ebner (1951) and Derbuch and Berg (1999)

Ectobius lapponicus Not listed Native Ebner (1951) and Derbuch and Berg (Linnaeus, 1758) (1999) Ectobius supramontes Not listed Native Bohn (2004) Bohn, 2004 Ectobius sylvestris (Poda, 1761) Not listed Native Ebner (1951) and Derbuch and Berg (1999) Ectobius vittiventris (A. Costa, 1847) Not Introduced Zimmermann (2014) listed NE Nyctibora sp. Burmeister, 1838 Not Introduced Ebner (1946) listed NE Phyllodromica brevipennis Not listed Native Derbuch and Berg (1999) (Fischer, 1853) Phyllodromica maculata Not listed Native Ebner (1951), Kreissl (1975), Ressl (Schreber, 1781) (1983) and Bohn and Chladek (2011)

Phyllodromica megerlei VU Native Ebner (1951), Vidlicka and Majzlan (Fieber, 1853) (1997) Blaberidae Panchlora nivea (Linnaeus, Not listed Introduced Ebner (1946) 1758) NE Pycnoscelus Not listed Introduced This study surinamensis (Linnaeus, 1758) NE Rhyparobia maderae Not listed Introduced Ebner (1946) NE Blattidae Blatta orientalis Linnaeus, 1758 Not listed Introduced Ebner (1946, 1951) and Ressl NE (1983) Blattella germanica NE Introduced Ebner (1951) and Ressl (1995) (Linnaeus, 1767) Periplaneta americana Not listed Introduced Ebner (1946, 1951, 1953) and (Linnaeus, 1758) NE Kanzler (1998) Periplaneta australasiae NE Introduced Ebner (1946, 1951, 1953) and (Fabricius, 1775) Ressl (1983) This study Supella longipalpa Not listed Introduced Rabitsch and Essl (2010) (Fabricius, 1798) NE Note. NE: Neozoa; VU: Vulnerable according to Adlbauer and Kaltenbach (1994). The new record of Pycnosculus surinamensis is highlighted in bold.

MATERIAL AND METHODS

We first discovered the Surinam cockroach in the Tropic House of the botanical garden in Graz (47°4ʹ53.75ʺN, 15°27ʹ24.88ʺE) on May 30, 2015. A single specimen (Figure 1a) was found among several Australian cockroach, Periplaneta australasiae (Fabricius, 1775), individuals. Three years later, on March 11, 2018, only a few Australian cockroaches remained, whereas numerous P. surinamensis were observed. On March 5, 2018, another population of the Surinam cockroach, including both adults and nymphs

(Figure 1b,c), was discovered in the Butterfly House in Vienna (48°12ʹ19.26ʺN, 16°21ʹ59.74ʺE). The morphologically indistinguishable but bisexually reproducing Indian cockroach (P. indicus) was excluded as only females (and nymphs) were found. Three and four specimens of P. surinamensis were collected in the botanical garden in Graz and the Butterfly House in Vienna, respectively, put in >99% ethanol and deposited in the collection of the Natural History Museum in Vienna (Supporting Information Table S1). Total genomic DNA was extracted using the DNeasy® Blood & Tissue Kit (Quiagen) from leg muscle tissue. A 684 bp fragment of the first part of the mitochondrial COI gene, corresponding to the typical DNA barcoding region (Hebert, Cywinska, Ball, & de Waard, 2003), was amplified using the Phusion polymerase (Thermo Fischer Scientific) protocol, following the manufacturer’s instructions using the primers LCO1490 and HCO2198 (Folmer, Black, Lutz, & Vrijenhoek, 1994). PCR products were purified with ExoSAP-IT (Thermo Fisher Scientific). The sequencing reaction followed the protocol in Duftner, Koblmüller, and Sturmbauer (2005), using the same primers as for PCR. Sequencing products were purified with SephadexTM G-50 (Amersham Biosciences) and visualized on an ABI 3130xl capillary sequencer (Applied Biosystems). Sequences were aligned using MUSCLE (Edgar, 2004), as implemented in MEGA6 (Tamura, Stecher, Peterson, Filipski, & Kumar, 2013). Additional sequences of P. surinamensis and other Pycnoscelus species that were available on GenBank and/or BOLD were downloaded and added to the alignment. A neighbour-joining tree (Saitou & Nei, 1987) applying the K2P model (Kimura, 1980)—the model typically employed in DNA barcoding studies—and 1,000 bootstrap replicates for statistical node support (Felsenstein, 1985) was inferred using MEGA6. Following Bourguignon et al. (2018), the tree was rooted with P. femapterus. MEGA6 was also used for calculating K2P- distances among species and within P. surinamensis.

(a (d ) )

(b )

(c )

F I G U R E 1 Surinam cockroaches, Pycnoscelus surinamensis, from Austria. Photographs of (a) the first specimen found in the Tropic House of the botanical garden in Graz (2015-05-30), (b) a female collected in the Butterfly House in Vienna and (c) a nymph from the same locality. (d) neighbour-joining tree, (based on K2P-distances) including all sequences of P. surinamensis and other Pycnoscelus species available from GenBank and BOLD, including our new records from Austria (in bold). Acronyms indicate origin of the specimen (Thailand: T; French Polynesia: FP; Australia: Aus; United States of America: USA; Guyana: G and Austria: Aut; see Supporting Information Table S1). Numbers at nodes indicate bootstrap support values (only values >70 are shown) [Colour figure can be viewed at wileyonlinelibrary.com]

RESULTS

DNA barcodes grouped the Austrian samples with previously published COI sequences of P. surinamensis, thus confirming the morphology-based identification. Furthermore, all specimens from Austria shared a single haplotype, which was identical to specimens from the United States of America, Guyana and French Polynesia (Figure 1d). Haplotypes were also shared between P. surinamensis and its bisexually reproducing ancestor P.

indicus. Pairwise K2P distances ranged from 0% to 3.9% within P. surinamensis, and from 0% to 11.9% among the Pycnoscelus species included in our study.

DISCUSSION

With the detection of the originally Indo-Malaysian Surinam cockroach Pycnoscelus surinamensis in Austria, the number of cockroach species reported for Austria increases to seventeen (Table 1), ten of which are alien. These Austrian P. surinamensis are also the first records of this species for Central Europe. Previously, the species has been reported from mainly tropical and subtropical regions, such as Florida, Louisiana, Texas and Hawaii in the United States, Cuba, Puerto Rico, the Bahama Islands, the Dominican Republic, Trinidad, Barbados, Martinique, Grenada, St. Vincent, Jamaica, Mexico, Costa Rica, Guiana, Brazil, Bermuda, Mauritius, the Central African Republic, Cameroon, Senegal, China, Taiwan, Australia, the Loyalty Islands, Japan, but also Spain and Sweden (Bell, Roth, & Nalepa, 2007; Garanto, 2015; Grandcolas, Dejean, & Deleporte, 1996; Schwabe, 1949). It is considered a peridomestic species that invades households and causes considerable damage to commercial rose, orchid and lily plantations, but also feeds on roots of pineapples, potato tubers, cucumbers, palm, tomatoes, papayas, figs, sweet potatoes and other plants (de Carvalho Moretti, Quirán, Solis, Rossi, & Thyssen, 2011; Schwabe, 1949). Outside its native range, it relies on human-mediated activities, especially transportation of soil, mulch, vegetable mould or plants from one human settlement to the next, to colonize new areas (Bell et al., 2007). Due to its synanthropic or peridomestic lifestyle (Grandcolas et al., 1996), it often finds itself in suitable climatic conditions right away, even when transported to subtropical or temperate regions, as P. surinamensis has been repeatedly reported from greenhouses (Schwabe, 1949; Pellens & Grandcolas, 2002; Yamauchi & Kato, 2009; Komatsu, Kawakami, Banzai, Ooi, & Uchida, 2015; Garanto, 2015; this study).

Pycnoscelus surinamensis is the thelytokous descendant of its bisexually reproducing progenitor P. indicus (Linnaeus 1758) (Bourguignon et al., 2018; Roth, 1967). Its parthenogenetic mode of reproduction facilitates a rapid establishment of new populations, with only a single female being sufficient to found a new population. It is noteworthy that many invasive species are parthenogenetic (e.g., Lombardo & Elkinton, 40

2017; Gutekunst et al., 2018) and that many taxa for which sexual reproduction is common in the native range, tend to switch to obligate or facultative parthenogenesis in introduced populations (e.g., Dybdahl & Kane, 2005; Caron, Ede, & Sunnucks, 2014). Pycnoscelus surinamensis is no exception as its almost global distribution contrasts the restricted distribution of P. indicus in the Indo-Malayan region (plus some introduced populations in Hawaii and Australia; Roth and Willis, 1960).

Numerous clonal lineages have been reported for P. surinamensis. This high clonal diversity and the establishment of general-purpose genotypes are believed to underlie the species’ adaptability and considered one of the main reasons for the species’ colonization success (Parker, Selander, Hudson, & Lester, 1977; Niklasson & Parker, 1994). For Austria, we thus far identified only a single mitochondrial haplotype—likely corresponding to one clone—that is shared with samples from the USA, Guyana and French Polynesia. Overall, genetic distances among P. surinamensis haplotypes published so far are similar to levels of intraspecific divergence in other (sexually reproducing) cockroach taxa (Cho, Suh, & Bae, 2013; Che, Gui, Lo, Ritchie, & Wang, 2017).

Although the prevailing opinion is that this species’ dispersal ability is very limited without human intervention (de Carvalho Moretti et al., 2011; Pellens & Grandcolas, 2002), it may be considered as a potential pest species in Central Europe in the light of the current climate change. Global warming increasingly provides suitable conditions even outside of conditioned greenhouses, likely enhancing winter survival as well as redefining/broadening current species’ distributions (Dukes & Mooney, 1999; Robinet & Roques, 2010). Thus, to prevent an unintended spread of alien species, monitoring of all introduced cockroach species as well as careful handling of plants, soil and food to prevent further accidental dispersal of P. surinamensis and other exotic species is advised.

ACKNOWLEDG EMENTS

We are grateful to the HBLFA (Höhere Bundeslehr- und Forschungsanstalt für Gartenbau) and especially to Renate Wölflmaier for providing the specimens from Vienna. We also thank Iphigenie Jäger for the hint to the population in Vienna. We also

thank Susanne Randolf for checking the collection of the Natural History Museum in Vienna and Wolfgang Rabitsch for additional information on Austrian cockroaches. Financial support was provided by the Austrian Federal Ministry of Education, Science and Research via an ABOL (Austrian barcode of Life; www.abol.ac.at) associated project within the framework of the “Hochschulraum-Strukturmittel” Funds and the University of Graz.

AUTHOR CONTRIBUTION

LZ, GK and SK designed the study. GK and CB collected samples. LZ conducted the laboratory work. LZ and SK analysed the data. LZ, GK and SK wrote the manuscript. All authors read and approved the manuscript.

ORCID

Lukas Zangl http://orcid.org/0000-0002-1175-564X

Gernot Kunz https://orcid.org/0000-0001-7858-0402

Christian Berg https://orcid.org/0000-0002-0587-3316

Stephan Koblmüller https://orcid.org/0000-0002-1024-3220

REFERENCES

Adlbauer, K., & Kaltenbach, A. (1994). Rote Liste gefährdeter Heuschrecken und Grillen, Ohrwürmer, Schaben und Fangschrecken (Saltatoria, Dermaptera, Blattodea, Mantodea). Rote Listen Gefährdeter Tiere Österreichs Grüne Reihe des Bundesministeriums Für Umwelt Jugend Und Familie, 2, 83–92. Baur, H., Landau Lüscher, I., Müller, G., Schmidt, M., & Coray, A. (2004). Taxonomie der Bernstein- Waldschabe Ectobius vittiventris (A. Costa, 1847) (Blattodea: Blattellidae) und ihre Verbreitung in der Schweiz. Revue Suisse De Zoologie, 111, 395–424. https://doi.org/10.5962/bhl. part.80245 Bell, W. J., Roth, L. M., & Nalepa, C. A. (2007). Cockroaches: Ecology, behavior, and natural history. Baltimore, MD: JHU Press. Bohn, H. (2004). The Blattoptera fauna of Switzerland and the adjacent regions of France, Italy, and Austria 1. The species of the sylvestris- group of Ectobius. Spixiana, 27, 253–285. Bohn, H., & Chladek, F. (2011). Revision of the maculata-group of Phyllodromica: Species from Central Europe (Insecta: Blattodea: Blattellidae: Ectobiinae). Arthropod Systematics and Phylogeny, 69, 3–54.

Bourguignon, T., Tang, Q., Ho, S. Y. W., Juna, F., Wang, Z., Arab, D. A., … Lo, N. (2018). Transoceanic dispersal and plate tectonics shaped global cockroach distributions: Evidence from mitochondrial phylogenomics. Molecular Biology and Evolution, 35, 970–983. https://doi. org/10.1093/molbev/msy013 Caron, V., Ede, F. J., & Sunnucks, P. (2014). Unravelling the paradox of loss of genetic variation during invasion: Superclones may explain the success of a clonal invader. PLoS ONE, 9, e97744. https://doi. org/10.1371/journal.pone.0097744 Che, Y., Gui, S., Lo, N., Ritchie, A., & Wang, Z. (2017). Species delimitation and phylogenetic relationships in ectobiid cockroaches (Dictyoptera, Blattodea) from China. PLoS ONE, 12, e0169006. https://doi. org/10.1371/journal.pone.0169006 Cho, S. Y., Suh, K. I., & Bae, Y. J. (2013). DNA barcode library and its efficacy for identifying food- associated insect pests in Korea. Entomological Research, 43, 253–261. https://doi.org/10.1111/1748- 5967.12034 de Carvalho Moretti, T., Quirán, E. M., Solis, D. R., Rossi, M. L., & Thyssen, P. J. (2011). Pycnoscelus surinamensis (Linnaeus, 1758) (Blaberoidea: Blaberidae), a cockroach with a possible association with the ant Brachymyrmex cordemoyi Forel, 1895 (Hymenoptera: Formicidae) and which may be exhibiting a domiciliation trend. Symbiosis, 53, 37–39. https://doi.org/10.1007/s13199-010-0101-3 Derbuch, G., & Berg, H.-M. (1999). Rote Liste der Geradflügler Kärntens (Insecta: Saltatoria, Dermaptera, Blattodea und Mantodea). Rote Listen Gefährdeter Tiere Kärntens Naturschutz in Kärnten, 15, 473–488. Duftner, N., Koblmüller, S., & Sturmbauer, C. (2005). Evolutionary relationships of the Limnochromini, a tribe of benthic deepwater cichlid fish endemic to Lake Tanganyika, East Africa. Journal of Molecular Evolution, 60, 277–289. 0.1007/s00239-004-0017-8 Dukes, J. S., & Mooney, H. A. (1999). Does global change increase the success of biological invaders? Trends in Ecology & Evolution, 14, 135– 139. https://doi.org/10.1016/S0169-5347(98)01554-7 Dybdahl, M., & Kane, S. (2005). Adaptation vs. phenotypic plasticity in the success of a clonal invader. Ecology, 86, 1592–1601. https://doi. org/10.1890/04-0898 Ebner, R. (1946). Die Adventiv-Fauna an Orthopteren in Österreich. Mit 8 Figuren. Zentralblatt Für Das Gesamtgebiet Der Entomologie, Klagenfurt, 1, 109–122. Ebner, R. (1951). Kritisches Verzeichnis der orthopteroiden Insekten von Österreich. Verhandlungen Der zoologisch‐botanischen Gesellschaft in Österreich, 92, 143–165. Ebner, R. (1953). Catalogus Faunae Austriae Teil XIIIa: Saltatoria, Dermaptera, Blattodea, Mantodea. Vienna, Austria: Österreichische Akademie der Wissenschaften. Edgar, R. C. (2004). MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Research, 32, 1792–1797. https://doi.org/10.1093/nar/gkh340 Felsenstein, J. (1985). Confidence limits on phylogenies: An approach using the bootstrap. Evolution, 39, 783–791. https://doi. org/10.1111/j.1558-5646.1985.tb00420 Folmer, O. M., Black, W. H., Lutz, R., & Vrijenhoek, R. (1994). DNA primers for amplification of mitochondrial cytochrome C oxidase subunit I from metazoan invertebrates. Molecular Marine Biology and Biotechnology, 3, 294–299. Garanto, H. (2015). Växthuskackerlackan, Pycnoscelus surinamensis (L.). Bachelor thesis, Swedish University of Agricultural Sciences. Grandcolas, P., Dejean, A., & Deleporte, P. (1996). The invading parthenogenetic cockroach: A natural history comment on Parker and Niklasson's study. Journal of Evolutionary Biology, 9, 1023–1026. https://doi.org/10.1046/j.1420-9101.1996.90612023.x Gutekunst, J., Andriantsoa, R., Falckenhayn, C., Hanna, K., Stein, W., Rasamy, J., & Lyko, F. (2018). Clonal genome evolution and rapid invasive spread of the marbled crayfish. Nature Ecology & Evolution, 2, 567–573. https://doi.org/10.1038/s41559-018-0467-9

Hebert, P. D. N., Cywinska, A., Ball, S. L., & de Waard, J. R. (2003). Biological identifications through DNA barcodes. Proceedings of the Royal Society B: Biological Sciences, 270, 313–321. https://doi. org/10.1098/rspb.2002.2218 Hubert, J., Stejskal, V., Athanassiou, C. G., & Throne, J. E. (2018). Health hazards associated with arthropod infestation of stored products. Annual Review of Entomology, 63, 553–573. https://doi.org/10.1146/ annurev-ento-020117-043218 Kanzler, P. (1998). Populationserhebung bei Schaben im Tiergarten Schönbrunn und die Möglichkeiten zu deren Bekämpfung. Dissertation University of Veterinary Medicine Vienna. Kimura, M. (1980). A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. Journal of Molecular Evolution, 16, 111–120. https://doi. org/10.1007/BF01731581 Komatsu, N., Kawakami, Y., Banzai, A., Ooi, H. K., & Uchida, A. (2015). Species clarification of Ogasawara cockroaches which inhabit Japan. Tropical Biomedicine, 32(1), 98–108. Kreissl, E. (1975). Hololampra maculate (SCHREBER) – eine für die Steiermark neue Schabenart (Insecta, Blattaria, Blattidae). Mitteilungen Zoologie Landesmuseum Joanneum, 3, 197–198. Lombardo, J. A., & Elkinton, J. S. (2017). Environmental adaptation in an aseual invasive insect. Ecology and Evolution, 7, 5123–5130. https:// doi.org/10.1002/ece3.2894 Niklasson, M., & Parker, E. D. Jr (1994). Fitness variation in an invading cockroach. Oikos, 71, 47–54. https://doi.org/10.2307/3546171 Parker, E. D. Jr, Selander, R. K., Hudson, R. O., & Lester, L. J. (1977). Genetic diversity in colonizing parthenogenetic cockroaches. Evolution, 31, 836–842. https://doi.org/10.1111/j.1558-5646.1977. tb01076.x Pellens, R., & Grandcolas, P. (2002). Are successful colonizers necessarily invasive species? The case of the so-called invading parthenogenetic cockroach, Pycnoscelus surinamensis, in the Brazilian Atlantic forest. Revue D'ecologie La Terre Et La Vie, 57, 253–261. Pospischil, R. (2010). Schaben (Dictyoptera, Blattodea) - Ihre Bedeutung als Überträger von Krankheitserregern und als Verursacher von Allergien. In H. Aspöck (Ed.), Krank durch Arthropoden (pp. 171–190). Denisia, 30. Rabitsch, W., & Essl, F. (2010). Aliens: Neobiota und Klimawandel ‐ Eine verhängnisvolle Affäre. Weitra, Austria: Bibliothek der Provinz. Ressl, F. (1983). Naturkunde des Bezirkes Scheibbs. Tierwelt (2). Scheibbs, Austria: Verlag R & F. Radinger. Ressl, F. (1995). Naturkunde des Bezirkes Scheibbs. Tierwelt (3). Scheibbs, Austria: Verlag R & F. Radinger. Robinet, C., & Roques, A. (2010). Direct impacts of recent climate warming on insect populations. Integrative Zoology, 5, 132–142. https://doi. org/10.1111/j.1749-4877.2010.00196.x Roth, L. M. (1967). Sexual isolation in parthenogenetic Pycnoscelus surinamensis and application of the name Pycnoscelus indicus to its bisexual relative (Dictyoptera: Blattaria: Blaberidae: Pycnoscelinae). Annals of the Entomological Society of America, 60, 774–779. https:// doi.org/10.1093/aesa/60.4.774 Roth, L. M., & Willis, E. R. (1960). A study of bisexual and parthenogenetic strains of Pycnoscelus surinamensis (Blattaria: Epilamprinae). Annals of the Entomological Society of America, 54, 12–25. Saitou, N., & Nei, M. (1987). The neighbor-joining method: A new method for reconstructing phylogenetic trees. Molecular Biology and Evolution, 4, 406–425. https://doi.org/10.1093/oxfordjournals.molbev.a040454 Schwabe, C. W. (1949). Observations on the life history of Pycnoscelus surinamensis (Linn.), the intermediate host of the chicken eyeworm in Hawaii. Hawaiian Entomological Society, 13, 433–436.

Tamura, K., Stecher, G., Peterson, D., Filipski, A., & Kumar, S. (2013). MEGA6: Molecular evolutionary genetics analysis version 6.0. Molecular Biology and Evolution, 30, 2725–2729. https://doi. org/10.1093/molbev/mst197 Vidlicka, L., & Majzlan, O. (1997). Revision of the megerlei-group of the cockroach genus Phyllodromica Fieber (Blattaria: Blattellidae, Ectobiinae). Insect Systematics & Evolution, 28, 163–173. https://doi. org/10.1163/187631297X00033 Yamauchi, T., & Kato, H. (2009). Cockroaches inhabiting greenhouses of a botanical garden in Toyama Prefecture, Japan. Medical Entomology and Zoology, 60, 305–310. https://doi.org/10.7601/mez.60.305 Zimmermann, K. (2014). Scientific experience from pest advisory in Vorarlberg, Austria. In G. Müller, R. Pospischil, & W.-H. Robinson (Eds.), Proceedings of the International Conference on Urban Pests (pp. 315–318). Kft., Hungary: OOK-Press.

SUPPORTING INFORMATION

Supplementary Table 1 Sequences used in the present study, with sample IDs, species name, information on origin of samples, BOLD-IDs and GenBank accession numbers (when available), and reference to the original study that generated the DNA sequence.

ID Species Sampling location BOLD-ID GenBank Reference Accession-No. P.surinamensis_Aut1 P. surinamensis Austria, Vienna ABLAT001-18 MK074953 This study

P.surinamensis_Aut2 P. surinamensis Austria, Vienna ABLAT002-18 MK074952 This study

P.surinamensis_Aut3 P. surinamensis Austria, Vienna ABLAT003-18 MK074951 This study

P.surinamensis_Aut4 P. surinamensis Austria, Vienna ABLAT004-18 MK074950 This study

P.surinamensis_Aut5 P. surinamensis Austria, Graz ABLAT005-18 MK074949 This study

P.surinamensis_Aut6 P. surinamensis Austria, Graz ABLAT006-18 MK074948 This study

P.surinamensis_Aut7 P. surinamensis Austria, Graz ABLAT007-18 MK074947 This study

P.surinamensis_T1 P. surinamensis Thailand ENTJR320-08 - unpublished

P.surinamensis_T2 P. surinamensis Thailand ENTJR321-08 - unpublished

P.surinamensis_T3 P. surinamensis Thailand ENTJR322-08 - unpublished

P.surinamensis_T4 P. surinamensis Thailand ENTJR323-08 - unpublished

P.surinamensis_T5 P. surinamensis Thailand ENTJR324-08 - unpublished

P.surinamensis_T6 P. surinamensis Thailand ENTJR325-08 - unpublished

P.surinamensis_T7 P. surinamensis Thailand ENTJR326-08 - unpublished

P.surinamensis_T8 P. surinamensis Thailand ENTJR327-08 - unpublished

P.surinamensis_T9 P. surinamensis Thailand ENTJR328-08 - unpublished

P.surinamensis_T10 P. surinamensis Thailand ENTJR329-08 - unpublished

P.surinamensis_G1 P. surinamensis Guyana GBA14674-14 KF155121 Evangelista et al., 2015

P.surinamensis_G2 P. surinamensis Guyana GBA23158-15 KF155065 Evangelista et al., 2015

P.surinamensis_FP1 P. surinamensis French Polynesia SYC10665-14 KX054560 Ramage et al., 2017

P.surinamensis_FP4 P. surinamensis French Polynesia SYC1786-14 KX054561 Ramage et al., 2017

P.surinamensis_FP3 P. surinamensis French Polynesia SYC1442-14 KX054562 Ramage et al., 2017

P.surinamensis_FP2 P. surinamensis French Polynesia SYC10664-14 KX054563 Ramage et al., 2017

P.surinamensis_USA1 P. surinamensis USA JSBTW169-12 - unpublished

P.surinamensis_USA2 P. surinamensis USA PHFLO251-15 - unpublished

P.surinamensis_USA3 P. surinamensis USA UNI37103-17 - unpublished

P.surinamensis_Aus1 P. surinamensis Australia VAQT054-08 - unpublished

P.surinamensis_Aus2 P. surinamensis Australia VAQT129-08 - unpublished

P.surinamensis_Aus3 P. surinamensis Australia VAQT180-08 - unpublished

P.surinamensis_Aus4 P. surinamensis Australia VAQT181-08 - unpublished

P.surinamensis_Aus5 P. surinamensis Australia VAQT182-08 - unpublished

P.surinamensis_Aus6 P. surinamensis Australia VAQT223-08 - unpublished

P.surinamensis_Aus7 P. surinamensis Australia VAQT242-08 - unpublished

P. indicus P. indicus ? - MG882158.1 Bourguignon et al. 2018

P. femapterus P. femapterus ? - MG882157.1 Bourguignon et al. 2018

P. nigra P. nigra ? - MG882159.1 Bourguignon et al. 2018

Supplementary References

Bourguignon, T., Tang, Q., Ho, S. Y. W., Juna, F., Wang, Z., Arab, D. A., Cameron, S. L., Walker, J., Rentz, D., Evans, T. A. & Lo, N. (2018). Transoceanic dispersal and plate tectonics shaped global cockroach distributions: evidence from mitochondrial phylogenomics. Molecular Biology and Evolution, 35, 970-983.

Evangelista, D. A., Ch, K., Kaplan, K. L., Wilson, M. M. & Ware, J. L. (2015) The Blattodea s.s. (Insecta, Dictyoptera) of the Guiana Shield. Zookeys 475, 37-87.

Ramage, T., Martins-Simoes, P., Mialdea, G., Allemand, R., Duplouy, A., Rousse, P., Davies, N., Roderick, G. K. & Charlat, S. (2017) A DNA barcode-based survey of terrestrial arthropods in the Society Islands of French Polynesia: host diversity within the SymbiCode Project. European Journal of Taxonomy, 272, 1- 13.

How to cite this article: Zangl L, Kunz G, Berg C, Koblmüller S. First records of the parthenogenetic Surinam cockroach Pycnoscelus surinamensis (Insecta: Blattodea: Blaberidae) for Central Europe. J Appl Entomol. 2019;143:308–313. https://doi. org/10.1111/jen.12587

Chapter 3

Austrian gudgeons of the genus Gobio (Teleostei: Gobionidae): A mixture of divergent lineages

Zangl L, Daill D, Gessl W, Friedrich T, Koblmüller S. Austrian gudgeons of the genus Gobio (Teleostei: Gobionidae): A mixture of divergent lineages. J Zool Syst Evol Res. 2020;58:327–340. https://doi.org/10.1111/jzs.12340

LUKAS ZANGL1, DANIEL DAILL1,2, WOLFGANG GESSL1, THOMAS FRIEDRICH3, STEPHAN KOBLMÜLLER1

1Institute of Biology, University of Graz, Graz, Austria

2Consultants in Aquatic Ecology and Engineering –blattfisch e.U., Wels, Austria

3Institute of Hydrobiology and Aquatic Ecosystem Management, University of Natural Resources and Life Sciences Vienna, Vienna, Austria

ABSTRACT

Gudgeons of the genus Gobio are small Eurasian fishes whose systematics, taxonomy, and phylogenetic relationships have been the matter of a long‐standing debate. Two species, Gobio gobio and G. obtusirostris have been reported for Austria, with a potential hybrid zone in the upper Danube. Phylogenetic and phylogeographic analysis of mitochondrial cytochrome oxidase subunit I and control region sequences, as well as nuclear ribosomal protein S7 sequences, however, shows that the proposed hybrid zone is not restricted to the upper Danube, but spans large parts of the Austrian Danube system (upper Danube, Rába & Mur systems). Moreover, our data show that also a third lineage, closely related to species from the southern Balkan, contributed to the gene pool of Austrian Gobio. Patterns of intra‐lineage genetic diversity indicate that the distinct Gobio

lineages expanded their distribution recently (most likely post‐glacially) to come into secondary contact and hybridize in the Danube system.

INTRODUC TION

Gobio—which we treat as a member of the Gobionidae, a family in its own right according to Stout, Tan, Lemmon, Lemmon, and Armbruster (2016)—is a genus of small, mainly riverine Eurasian freshwater fishes distributed from the Iberian Peninsula in the west to China, Mongolia, and eastern Siberia in the east. Currently, the genus comprises 47 valid species (Fricke, Eschmeyer, & Fong, 2019). Some species have only very restricted distribution ranges, whereas others occur across several large drainage systems. Though the overall morphology appears to be pretty conserved throughout the genus, Gobio species display large intraspecific phenotypic variability (Banarescu, Soric, & Economidis, 1999) and are thus difficult to identify correctly based on morphological traits alone. This is even further complicated by sometimes overlapping distribution ranges and evidence of interspecific and even intergeneric hybridization (Kottelat & Freyhof, 2007; Mendel et al., 2008, 2012). Hence, the taxonomic status of European Gobio species has been (and still is) the matter of a long‐standing debate (Nowak, Košco, & Popek, 2008). With the increasing application of molecular methods, including DNA barcoding, it became clear that some species originally thought to be widespread are species complexes with several cryptic species. Molecular approaches have shed light on systematics, diversity, and phylogenetic relationships within the genus Gobio (Mendel et al., 2008; Takács et al., 2014), former sub‐species have been elevated to species rank and new species have been described (Doadrio & Madeira, 2004; Kottelat & Freyhof, 2007; Kottelat & Persat, 2005; Mousavi‐Sabet, Ganjbakhsh, Geiger & Freyhof, 2016; Naseka, Erkákan, & Kücük 2006; Turan, Ekmekçi, Lusková, & Mendel, 2012; Vasiléva, Vasilév, & Boltachev, 2005). Phylogenetic and phylogeographic studies resolved systematic uncertainties (Mendel et al., 2008) and clarified thus far erroneous or incomplete local distribution patterns (Lusk, Halacka, Lusková, & Horák, 2005; Takács et al., 2014), information not only of scientific interest but also important for field biologists, consultants, and conservational workers. Thus, a large amount of molecular data on Gobio have accumulated over the last few years, not least because of large past and

ongoing DNA barcoding initiatives (Geiger et al., 2014; Knebelsberger, Dunz, Neumann, & Geiger, 2015). Despite the wealth of molecular data available for Gobio, only very little is known about the genetic diversity of Gobio in Austria. In the Red List for Austria, only one species, Gobio gobio (Linnaeus, 1758), is listed (Zulka, 2007). In contrast, based on Kottelat and Freyhof (2007), Gobio obtusirostris Valenciennes, 1842 should be present in large parts of Austria, whereas G. gobio, which is distributed across large areas of western, central, northern, and northeast‐ ern Europe, occurs only in the upper Danube system, where it might form a hybrid zone with G. obtusirostris.

The Austrian Danube system can be divided into three main parts:

(a) the upper Danube which includes tributaries in northern and western Austria; (b) the Rába drainage in southeastern Austria, that merges with the Danube in northwestern Hungary; and (c) the Mur/Drava system in southern Austria, draining into the middle Danube in eastern Croatia. Thus, these three major parts of the Austrian Danube system constitute geographically well separated drainages. Considering phylogeographic data of other riverine fish species (e.g., brown trout, Salmo trutta L., 1758, Lerceteau‐Köhler, Schliewen, Kopun, & Weiss, 2013; Schenekar, Lerceteau‐Köhler, & Weiss, 2014; European grayling (L., 1758), Thymallus thymallus, Weiss, Persat, Eppe, Schlötterer, & Uiblein, 2002) a potential hybrid zone between G. gobio and G. obtusirostris in the upper Danube system (Kottelat & Freyhof, 2007) seems quite plausible. Indeed, increased levels of heterozygosity in allozyme data of Gobio from the German Danube system have been interpreted as evidence for secondary contact of previously isolated Gobio taxa (Schreiber, 2002).

Here, we use DNA sequences, two mitochondrial and one nuclear marker, of Gobio from the upper Danube, Rába, and Mur river systems and published sequences from other European regions to clarify phylogenetic and phylogeographic patterns of Gobio in Austria. Given the available literature on the genus, we predicted that two distinct lineages, corresponding to G. gobio and G. obtusirostris would be found in Austria, with G. gobio haplotypes confined to the upper Danube system and G. obtusirostris haplotypes present throughout Austria. We further predicted to find clear signatures of recent population expansion, consistent with re‐colonization of central Europe from glacial refugia and evidence for admixis among G. gobio and G. obtusirostris in the upper Danube system.

MATERIAL AND METHODS

Our data set includes sequences of samples collected in the field and sequences obtained from public sequence repositories (BOLD, GenBank) (Appendix 1). Field collections of 63 individuals of the genus Gobio and one specimen each of the four native Romanogobio species, R. carpathorossicus (Vladykov, 1925), R. skywalkeri (Friedrich et al., 2018), R. uranoscopus (Agassiz, 1828) and Romanogobio vladykovi (Fang, 1843) (Friedrich et al., 2018) were made (using electrofishing) at 23 locations in 13 rivers and streams across northern, central, southern, and eastern Austria (Figure 1). In addition, five G. gobio specimens from Germany were obtained from the aquarium trade. Fish were euthanized with an overdose of MS 222, fin clips (small parts of the right pectoral fin) were taken and stored in >95% ethanol at −24°C, and voucher specimens were deposited at the Natural History Museum Vienna (Appendix 1).

Total genomic DNA extraction followed a rapid Chelex protocol (Richlen & Barber, 2005). The first part of the mitochondrial cytochrome c oxidase subunit 1 (COI) gene (702 bp, the typical barcoding region), a large part of the mitochondrial control region (CR; 732 bp), and the nuclear ribosomal protein S7 (RPS7) gene (379–420 bp) were amplified and sequenced according to the protocols in Koblmüller et al. (2011) and Duftner, Koblmüller, and Sturmbauer (2005), respectively. The primers used for PCR and chain termination sequencing were VF2_t1 and FishR2_t1 (Ward, Zemlak, Innes, Last, & Hebert, 2005) for COI, CR159, and CR851 (Mendel et al., 2008) for CR, and S7univL and S7univP (Mendel et al., 2008) for RPS7. PCR primer annealing temperatures were 51, 50, and 49°C for COI, CR, and RPS7, respectively (see Table S1). Sequencing products were purified with SephadexTM G‐50 (Amersham Biosciences) and visualized on an ABI 3130xl capillary sequencer (Applied Biosystems). The PCR products were sequenced bidirectionally to ensure correct reads of every single site. Sequences were aligned using MUSCLE (Edgar, 2004), as implemented in Mega version 6 (Tamura, Stecher, Peterson, Filipski, & Kumar, 2013) and trimmed to unitize sequence lengths. Following the strategy of Mendel et al. (2008), heterozygous RPS7 sequences were excluded from further analyses, as presence/absence of certain RPS7 haplogroups in particular river systems should already become evident from homozygous sequences. The

final alignment sizes were 599, 693, and 395 bp for COI, CR, and RPS7, respectively (see alignments, S1–S3).

Alignments were collapsed into haplotypes using FaBox 1.41 (Villesen, 2007). Gaps in the RPS7 were coded using FastGap v1.2 (available at https://www.aubot.dk/FastGap_home.htm) and treated as a separate partition for phylogenetic analyses. Phylogenetic relationships were inferred separately for each gene by means of maximum‐likelihood (ML) and Bayesian inference (BI) in RaxML‐HPC v.8 (Stamakis, 2014) and MrBayes 3.2 (Ronquist & Huelsenbeck 2003), respectively. For ML tree search in RAxML, we employed the GTR + G model of molecular evolution for COI and CR and the GTRCAT for RPS7 using the BIN setting for recoded gap partitions, and conducted 10,000 fast bootstrap replicates to assess nodal support. For BI tree search in MrBayes, two simultaneous Markov Chain Monte Carlo (MCMC) searches were conducted for each gene (four chains for 40 million generations each; sampling frequency 1,000), employing the best fitting models of molecular evolution as inferred by the model testing module based on the Bayesian information criterion in Mega for the nucleotide partitions and the binary model for recoded gap partitions. Run convergence and stationarity of parameters were assessed in Tracer 1.6 (available at http://tree.bio. ed.ac.uk/software/tracer/). Effective samples sizes for all parameters exceeded 200, indicating that the parameter log file accurately reflected the posterior distribution (Kuhner, 2009). The first 25% of sampled trees were discarded as burn‐in prior to constructing a 50% majority rule consensus tree.

FIGURE 1 Sampling locations of Gobio sp. in Austrian rivers. The small inlay shows the entire Danube drainage, with the course of the Rába (R) and Mur/Dráva (MD) systems indicated. The occurrence of distinct mitochondrial (a) and nuclear (b) lineages is highlighted. Green, Gobio gobio lineage; red, Gobio obtusirostris lineage, blue, “Balkan” lineage; empty circles, sampling sites where outgroup taxa of the genus Romanogobio were collected. The Austrian parts of the upper Danube, Rába, and Mur drainages are indicated

Additionally, for distinct Gobio COI clades, statistical parsimony networks (Templeton, Crandall, & Sing, 1992) were constructed in PopART (Leigh & Bryant, 2015) using the TCS function (Clement, Posada, & Crandall, 2000) and COI net mean K2P (Kimura, 1980) distances—the standard model of evolution typically employed in DNA barcoding studies—between these lineages were calculated in Mega. To test for signatures of past population expansion in these mitochondrial lineages, we conducted two neutrality tests (Tajima's D, Tajima, 1989; Fu's Fs, Fu, 1997) and calculated mismatch distributions in Arlequin 3.5 (Excoffier, Laval, & Schneider, 2005). The fit of the observed mismatch distribution to the expectations based on growth parameter estimates was evaluated by the sum of squared differences and the raggedness index (rg). Past population size trajectories for these mitochondrial lineages were inferred by means of a Bayesian coalescent approach (Bayesian skyline plot [BSP] tree prior) as implemented in BEAST 1.8.4 (Drummond, Suchard, Xie, & Rambaut, 2012), employing the TN93 model as the best fitting model of molecular evolution and assuming a strict molecular clock. As there is no Gobionidae specific substitution rate available for COI, we assumed a general rate of 0.5%–2% per million years for the COI gene in fishes (Bermingham, McCafferty, & Martin, 1997; Bernal, Gaither, Simison, & Rocha, 2017; Brown, George, & Wilson, 1979; Lessios, 2008). Two independent MCMC runs of 15 million generations each were conducted, with a sampling frequency of 1,000 steps and a burn‐in of the first 10% of sampled generations. After assessing convergence and stationarity of model parameters, visualization of past population size changes was done in Tracer 1.6.

FIGURE 2 BI phylogram of the genus Gobio based on haplotypes of the mitochondrial COI gene. Node labels represent posterior probabilities (only PPs > 0.80 are shown). Numbers in parentheses indicate the total number of specimens and the number of Austrian samples per haplotype. * marks a questionable Gobio gobio haplotype from Slovenia, ** marks a G. gobio haplotype from the Czech Republic clustering within the outgroup

RESULTS AND DISCUSSION

Phylogenetic analysis of the COI gene provided evidence for the presence of three major mitochondrial lineages within the genus Gobio in Austria. Some individuals resulted within a lineage including French, Italian, German, Czech, and Swedish specimens identified as G. gobio. Others grouped with Czech specimens identified as G. 55

obtusirostris, and the third group of specimens clustered with southeastern European species such as Gobio balcanicus Dimovski & Grupche, 1977 (which is currently regarded a synonym of G. gobio; Fricke, Eschmeyer, & van der Laan, 2019), G. bulgaricus Drensky, 1926, and G. feraeensis Stephanidis, 1973, but represented a distinct lineage within this clade. Consequently, we termed these lineages G. gobio, G. obtusirostris, and Balkan lineage. This clustering was well supported by both BI (see Figure 2), and ML analysis (Figure S1) and was also corroborated by the analysis of the CR (Figures S2 and S3). A single previously published G. gobio from Slovenia clustered within G. balcanicus, G. bulgaricus, and G. feraeensis from Greece thus rendering the species assignment of this specimen questionable. One previously published G. gobio sequence from the Czech Republic clustered with R. vladykovi, indicating misidentification or intergeneric hybridization/introgression, which is known to occur among the two genera (Mendel et al., 2012). Previously regarded a sub‐species of G. gobio, G. obtusirostris has been, like several other previous sub‐species, elevated to species rank by Kottelat and Freyhof (2007) and is currently considered a valid species (Fricke, Eschmeyer, & Fong, 2019) with a presumed core distribution in the middle and lower Danube drainage. It is noteworthy, however, that the species was described based on just a handful of specimens from the Isar River in Munich, Germany (Upper Danube). Currently, no morphological characters are available that would allow to unambiguously identify specimens as G. obtusirostris or G. gobio; also, the putatively diagnostic characters given in Kottelat and Freyhof (2007) are partially overlapping and thus cannot be used to distinguish between the two species. Thus, whether the type specimens of G. obtusirostris from the Isar River belong to the G. gobio or G. obtusirostris lineage, or are of mixed ancestry with regard to different lineages (Mendel et al., 2008; Takács et al., 2014; this study), which is quite plausible considering the geographic distribution of the various Gobio lineages, still remains to be shown. Consequently, also the species status of G. obtusirostris still needs to be clarified. Nonetheless, for consistency with previous phylogenetic and phylogeographic studies on Gobio (Mendel et al., 2008; Takács et al., 2014), we decided to follow their terminology and use the term “G. obtusirostris lineage.”

Despite a generally poor resolution, analysis of the nuclear RPS7 gene (Figure 3, Figure S4) clustered the Austrian gudgeons into two very divergent lineages, a G. gobio lineage, which includes German, French, Slovakian, and Ukrainian specimens as well as some Austrian samples, and a lineage comprising G. obtusirostris, G. skadarensis Karaman,

1937 (from Albania and Montenegro), G. carpathicus Vladykov, 1925 (from Czech Republic, Slovakia, Ukraine and Turkey), G. ohridanus Karaman, 1924 (from Albania), and Austrian samples. Whether this lineage can be, similar to the COI data, subdivided into a G. obtusirostris clade and a Balkan lineage remains unclear, as no RPS7 data are available for the Balkan species G. balcanicus, G. bulgaricus, and G. feraeensis. Of the four samples with pure G. gobio lineage RPS7 DNA, three (two from the upper Danube and one from the Mur drainages, respectively) had G. obtusirostris mtDNA.

FIGURE 3 Bayesian inference phylogram of the genus Gobio based on the nuclear RPS7 gene, including indels as a separate partition. Node labels represent posterior probabilities (only PPs > 0.80 are shown). Numbers in parentheses indicate total number of specimens and number of Austrian samples. * The limited resolution of the S7 data and missing data from the Balkan species Gobio balcanicus, Gobio bulgaricus, and Gobio feraeensis preclude a distinction between Gobio obtusirostris and “Balkan lineage”

Mendel et al. (2008) suggested using indel patterns in the RPS7 gene as species‐specific markers. Based on these, Mendel et al. (2008) proposed the existence of additional Gobio species (G. sp.1, G. sp. 2, G. sp.3). Most of the indel patterns reported by Mendel et al. (2008), including those representing putative distinct species, were also present in our Austrian Gobio samples. In addition, we found a few new RPS7 haplotypes characterized by unique indel patterns (see Gobio_RPS7.fas alignment S3). However, assigning every unique RPS7 indel pattern to a distinct new species seems a bit far stretched and we refrain from doing so. Previously, Zulka (2007) listed G. gobio as the only Gobio species for Austria while Kottelat and Freyhof (2007) noted that there might be a hybrid zone between G. obtusirostris and G. gobio in the upper Danube River. Our phylogenetic analysis based on three loci (COI, CR, RPS7), however, revealed that the gudgeons from the Danube drainage in Austria represent a mixture of different mitochondrial and nuclear lineages, a situation much more complex than previously thought, with signatures of hybridization not just restricted to the upper Danube River (Kottelat & Freyhof, 2007; Zulka, 2007). The different main lineages are not equally distributed across Austria. Whereas in the upper Danube system, all three main lineages are present, only G. gobio and Balkan lineage mtDNA haplotypes and G. obtusirostris and Balkan lineage haplotypes were found in the Rába and Mur river systems, respectively (Figure 1a). At least in the Rába river system, the apparent absence of the third mitochondrial lineage might be due to a small sample size (N = 5), but our findings are consistent with Takács et al. (2014), who did not find Balkan lineage haplotypes in the Rába system either (our Balkan lineage corresponds to haplogroup “B” in Takács et al., 2014). Both main RPS7 lineages were found in the upper Danube and Mur systems (Figure 1b). Thus, the hybrid zone clearly spans across entire eastern Austria and all major Austrian river systems belonging to the Danube drainage. A recent DNA barcoding study on the German freshwater fishes (Knebelsberger et al., 2015) found, besides several individuals with haplotypes characteristic for G. gobio, one individual that had a deviating haplotype and was provisionally assigned to a Gobio sp. We included this Gobio sp. in our analyses and it clustered well within the G. obtusirostris lineage (haplotype 3 in the COI phylogenies, see Figure 2). Hence, G. obtusirostris lineage haplotypes are present also in the German Danube system, implying that the hybrid zone extends even into Germany, as is also indicated by increased levels of genetic diversity in allozymes (Schreiber, 2002). Furthermore, high levels of genetic diversity, potential cryptic species, and interspecific

hybridization, patterns not unlike those we observe in Austria, have also been reported for gudgeons from the middle Danubian hydrosystem in Hungary (Takács et al., 2014).

K2P net mean distances of COI among the three Gobio lineages present in Austria ranged from 1.3% to 2.2% (G. gobio—G. obtusirostris, 2.0%; G. gobio—Balkan lineage, 2.2%; G. obtusirostris—Balkan lineage, 1.3%). Assuming a general substitution rate of 0.5%– 2% per million years for the COI gene (Bermingham et al., 1997; Bernal et al., 2017; Brown et al., 1979; Lessios, 2008), the lineages diverged 0.65–1.2 to 2.6–4.8 million years ago. No clear phylogeographic structure became evident within the G. gobio and Balkan lineages, with haplotypes shared across river systems and different countries, especially in G. gobio. In the G. obtusirostris lineage, on the other hand, some clear phylogeographic structuring according to drainages became evident, even though the most common haplotype was shared among the upper Danube, Rába and Mur drainages (Figure 4). Star‐shaped haplogroups in the G. gobio and G. obtusirostris lineages are indicative of recent population expansion (Figure 4). No particularly common haplotypes were identified in the Balkan lineage. Fu's Fs was significantly negative for the G. gobio lineage (Fs = −4.92894, p < .001) and negative but non‐significant for the G. obtusirostris (Fs = −1.70286 p = .147) and the “Balkan” lineages (Fs = −2.52314, p = .071). Tajima's D was significantly negative for the G. gobio (D = −1.62680 p < .001) and G. obtusirostris lineages (D = −1.89496, p = .005) and negative but non‐significant for the “Balkan” lineage (D = −0.81513, p = .095). Mismatch distribution (Figure S5) and reconstruction of past population size trajectories by means of BSPs are consistent with recent population expansion in all three Gobio lineages (Figure 4), but population growth in the Balkan lineage started earlier than in the other two lineages. These observed patterns of deep inter‐lineage divergence, current admixis, and recent population expansion strongly argue for originally allopatric diversification in different glacial refugia and post‐glacial secondary contact.

FIGURE 4 Haplotype networks and Bayesian skyline plots (BSPs) of the mitochondrial (a) Gobio gobio lineage, (b) Gobio obtusirostris lineage and (c) ”Balkan” lineage based on the COI data. Dashes within the networks indicate the number of differences between haplotypes. BSPs of past population size trajectories assume minimum and maximum substitution rates of 0.5% and 2.0% per site per million years. Thick lines indicate median estimates; thin lines denote the 95% highest posterior density (HPD) intervals. The y‐axis shows the population size parameter (product of female effective population size, fNe, and substitution rate, µ)

Numerous phylogeographic studies showed that the current distributions of European freshwater fishes and their genetic diversity have been shaped by range shifts during Pleistocene glacial cycles, with the re‐colonization dynamics closely linked to the history of the river drainages (Bernatchez & Wilson, 1998; Leprieur et al., 2011; Reyjol et al., 2007). Notably, among European freshwater fish, there is no consistent pattern with respect to their phylogeographic structure and glacial refugia (Gum, Gross, & Kuehn, 2005; Hänfling, Dümpelmann, Bogutskaya, Brandl, & Brändle, 2009; Jeffries et al., 2016; Lerceteau‐Köhler et al., 2013; Nesbø, Fossheim, Vøllestad, & Jakobsen, 1999; Perdices, Doadrio, Economidis, Bohlen, & Banarescu, 2003; Salzburger et al., 2003; Seifertová, Bryja, Vyskočilová, Martínková, & Šimková, 2012; Skog, Vøllestad, Stenseth, Kasumyan, & Jakobsen, 2014; Weiss et al., 2002). Usually, watersheds represent strong barriers to dispersal, but ephemeral connections might provide opportunities for colonization of otherwise isolated hydrological systems during glacial melt periods

(Gibbard, Rose, & Bridgland, 1988). Despite the often-observed large differences in exact phylogeographic patterns and post‐glacial re‐colonization routes among European freshwater fish species, the Danube and the Balkan region appear to have been glacial refugia for many species. The present distribution of the three mitochondrial Gobio lineages found in Austria strongly argues for glacial refugia in the Danube, the Balkan and in addition somewhere in Western Europe. Thus, the pattern somewhat resembles the situation in perch, Perca fluviatilis L., 1758, for which the same refugia have been postulated (Nesbø et al., 1999). Even though admixture of different lineages in the upper and middle Danube system has been previously shown for other species too (Lerceteau‐ Köhler et al., 2013; Schenekar et al., 2014; Weiss et al., 2002), the extent of the hybrid zone in Gobio is outstanding. It involves three mitochondrial lineages, two of them considered to be good species in their respective core distribution areas, and spans a large part of the upper and middle Danube drainage. Whereas in fish species important for commercial and recreational fisheries, stocking with allochthonous lineages blurs the phylogeographic patterns (Baric et al., 2010; Duftner, Koblmüller, Weiss, Medgyesy, & Sturmbauer, 2005; Kohout, Jašková, Papoušek, Šedivá, & Šlechta, 2012), this should play only a marginal, if any, role in Gobio.

To conclude, our findings also indicate that, at least in gudgeons from the Danube drainage, DNA barcodes must be used with caution when assigning specimens to particular species. We have shown that Austrian gudgeons of the genus Gobio are a mixture of different, originally allopatric, lineages that came into secondary contact only fairly recently and now form a large hybrid zone that spans large parts of Austria. To fully understand the apparently highly complex dynamics of secondary contact and admixture in (central) European Gobio gudgeons and as the taxonomic and evolutionary species status of different glacial, lineages still remains unsettled; however, large scale nuclear multi‐locus or genomic data as well as detailed morphological analyses will be required.

ACKNOWLEDG EMENTS

We would like to thank Clemens Ratschan, Michael Schauer, Christian Witt, Klaus Berg, Paul Meulenbroek, Gerhard Woschitz, Albert Rechberger, Edgar Lorenz, Michael Jung, Günter Parthl, Josef Melcher, Peter Mehlmauer, and Harald Ellinger for help in fieldwork 61

and/or providing fish. Furthermore, we are grateful to Anja Palandacic and Ernst Mikschi for including the samples in the collection of the Natural History Museum Vienna and providing us with the museum IDs. Financial support was provided by the Austrian Federal Ministry of Science, Research and Economy in the frame of the ABOL (Austrian Barcode of Life; www. abol.ac.at) pilot project on vertebrates and an ABOL associated project within the framework of the “Hochschulraum‐Strukturmittel” Funds.

ORCID

Lukas Zangl ..http://orcid.org/0000‐0002‐1175‐564X

Thomas Friedrich ..https://orcid.org/0000‐0002‐9881‐5392

Stephan Koblmüller https://orcid.org/0000‐0002‐1024‐3220

REFERENCES

Banarescu, P., Soric, V., & Economidis, P. (1999) Gobio gobio (Agassiz, 1828). In P. Banarescu (Ed.), The Freshwater Fishes of Europe. Cyprinidae 2/1 (pp. 81–134). Wiesbaden, Germany: Aula. Baric, S., Riedl, A., Meraner, A., Medgyesy, N., Lackner, R., Pelster, B., & Dalla Via, J. (2010). Alpine headwater streams as reservoirs of remnant populations of the Danubian clade of brown trout. Freshwater Biology, 55, 866–880. https://doi.org/10.1111/j.1365‐2427.2009.02318.x Bermingham, E., McCafferty, B. B., & Martin, P. P. (1997). Fish biogeography and molecular clocks: Perspectives from the Panamanian Isthmus. In T. D. Kocher & C. A. Stepien (Eds.), Molecular systematics of fishes (pp. 113–128). San Diego, TX: Academic Press. Bernal, M. A., Gaither, M. R., Simison, W. B., & Rocha, L. A. (2017). Introgression and selection shaped the evolutionary history of sympatric sister‐species of coral reef fishes (genus: Haemulon). Molecular Ecology, 26, 639–652. Bernatchez, L., & Wilson, C. C. (1998). Comparative phylogeography of Nearctic and Palearctic fishes. Molecular Ecology, 7, 431–452. https:// doi.org/10.1046/j.1365‐294x.1998.00319.x Brown, W. M., George, M. Jr, & Wilson, A. C. (1979). Rapid evolution of animal mitochondrial DNA. Proceedings of the National Academy of Sciences, 76(4), 1967–1971. https://doi.org/10.1073/pnas.76.4.1967 Clement, M., Posada, D., & Crandall, K. A. (2000). TCS: A computer program to estimate gene genealogies. Molecular Ecology, 9, 1657–1659. https://doi.org/10.1046/j.1365‐294x.2000.01020.x Doadrio, I., & Madeira, M. J. (2004). A new species of the genus Gobio Cuvier, 1816 (Actinopterygii, Cyprinidae) from the Iberian Peninsula and southwestern France. Graellsia, 60, 107–116. Drummond, A. J., Suchard, M. A., Xie, D., & Rambaut, A. (2012). Bayesian phylogenetics with BEAUti and the BEAST 1.7. Molecular Biology and Evolution, 29, 1969–1973. https://doi.org/10.1093/molbev/mss075

Duftner, N., Koblmüller, S., & Sturmbauer, C. (2005). Evolutionary relationships of the Limnochromini, a tribe of benthic deepwater cichlid fish endemic to Lake Tanganyika, East Africa. Journal of Molecular Evolution, 60, 277–289. https://doi.org/10.1007/s00239‐004‐0017‐8 Duftner, N., Koblmüller, S., Weiss, S., Medgyesy, N., & Sturmbauer, C. (2005). The impact of stocking on the genetic structure of European grayling (Thymallus thymallus, Salmonidae) in two alpine rivers. Hydrobiologia, 542, 121–129. https://doi.org/10.1007/ s10750‐004‐4951‐ 7 Edgar, R. C. (2004). MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Research, 32, 1792–1797. https://doi.org/10.1093/nar/gkh340 Excoffier, L., Laval, G., & Schneider, S. (2005). Arlequin ver. 3.0: An integrated software package for population genetics data analysis. Evolutionary Bioinformatics Online, 1, 47–50. Fricke, R., Eschmeyer, W. N., & Fong, J. D. (2019). Eschmeyer’s catalogue of fishes: species by family/subfamily. Retrieved from http://researchar chive.calacademy.org/research/ichthyology/catalog/SpeciesByF amily.asp (electronic version accessed 21st May 2019). Fricke, R., Eschmeyer, W. N., & van der Laan, R. (2019). Eschmeyer’s catalogue of fishes: genera, species, references. Retrieved from http://resea rcharchive.calacademy.org/research/ichthyology/catalog/fishcat‐ main.asp (electronic version accessed 21st May 2019). Friedrich, T., Wiesner, C., Zangl, L., Daill, D., Freyhof, J., & Koblmüller, S. (2018). Romanogobio skywalkeri, a new gudgeon (Teleostei: Gobionidae) from the upper Mur River, Austria. Zootaxa, 4403, 336– 350. https://doi.org/10.11646/zootaxa.4403.2.6 Fu, Y. X. (1997). Statistical tests of neutrality of mutations against population growth, hitchhiking and background selection. Genetics, 147, 915–925. Geiger, M. F., Herder, F., Monaghan, M. T., Almada, V., Barbieri, R., Bariche, M., … Freyhof, J. (2014). Spatial heterogeneity in the Mediterranean Biodiversity Hotspot affects barcoding accuracy of its freshwater fishes. Molecular Ecology Resources, 14, 1210–1221. https://doi.org/10.1111/1755‐0998.12257 Gibbard, P. L., Rose, J., & Bridgland, D. R. (1988). The history of the great northwest European rivers furing the past three million years [and discussion]. Philosophical Transactions of the Royal Society London: Series B, Biological Sciences, 318, 559–702. Gum, B., Gross, R., & Kuehn, R. (2005). Mitochondrial and nuclear DNA phylogeography of European grayling (Thymallus thymallus): Evidence for secondary contact zones in central Europe. Molecular Ecology, 14, 1707–1725. https://doi.org/10.1111/j.1365‐294X.2005.02520.x Hänfling, B., Dümpelmann, C., Bogutskaya, N. G., Brandl, R., & Brändle, M. (2009). Shallow phylogeographic structuring of Vimba vimba across Europe suggests two distinct refugia during the last glaciation. Journal of Fish Biology, 75, 2269–2286. Jeffries, D. L., Copp, G. H., Handley, L. L., Olsén, K. H., Sayer, C. D., & Hänfling, B. (2016). Comparing RADseq and microsatellites to infer complex phylogeographic patterns, an empirical perspective in the Crucian carp, Carassius carassius, L. Molecular Ecology, 25, 2997–3018. Kimura, M. (1980). A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. Journal of Molecular Evolution, 16, 111–120. https://doi. org/10.1007/BF01731581 Knebelsberger, T., Dunz, A., Neumann, D., & Geiger, M. F. (2015). Molecular diversity of Germany’s freshwater fishes and lampreys assessed by DNA barcoding. Molecular Ecology Resources, 15, 562–572. https://doi.org/10.1111/1755‐0998.12322 Koblmüller, S., Salzburger, W., Obermüller, B., Eigner, E., Sturmbauer, C., & Sefc, K. M. (2011). Separated by sand, fused by dropping water: Habitat barriers and fluctuating water levels steer the evolution of rock‐dwelling cichlid populations. Molecular Ecology, 20, 2272–2290.

Kohout, J., Jašková, I., Papoušek, I., Šedivá, A., & Šlechta, V. (2012). Effects of stocking on the genetic structure of brown trout, Salmo trutta, in Central Europe inferred from mitochondrial and nuclear markers. Fisheries Management and Ecology, 19, 252–263. Kottelat, M., & Freyhof, J. (2007). Handbook of European freshwater fishes. Cornol, Switzerland: Publications Kottelat. Kottelat, M., & Persat, H. (2005). The genus Gobio in France, with redescription of G. gobio and description of two new species. Cybium, 29, 211–234. Kuhner, M. K. (2009). Coalescent genealogy samplers: Windows into population history. Trends in Ecology and Evolution, 24, 86–93. https://doi.org/10.1016/j.tree.2008.09.007 Leigh, J. W., & Bryant, D. (2015). POPART: Full‐feature software for haplotype network construction. Methods in Ecology and Evolution, 6, 1110–1116. Leprieur, F., Tedesco, P. A., Hugueny, B., Beauchard, O., Dürr, H. H., Brosse, S., & Oberdorff, T. (2011). Partitioning global patterns of freshwater fish beta diversity reveals contrasting signatures of past climate changes. Ecology Letters, 14, 325–334. https://doi. org/10.1111/j.1461‐0248.2011.01589.x Lerceteau‐Köhler, E., Schliewen, U., Kopun, T., & Weiss, S. (2013). Genetic variation in brown trout Salmo trutta across the Danube, Rhine, and Elbe headwaters: A failure of the phylogeographic paradigm? BMC Evolutionary Biology, 13, 176. https://doi. org/10.1186/1471‐2148‐13‐176 Lessios, H. A. (2008). The Great American Schism: Divergence of marine organisms after the rise of the Central American Isthmus. Annual Review in Ecology and Systematics, 39, 63–91. https://doi. org/10.1146/annurev.ecolsys.38.091206.095815 Lusk, S., Halacka, K., Lusková, V., & Horák, V. (2005). Distribution of Gobio species in the Czech Republic. Folia Zoologica, 54, 56–64. Mendel, J., Lusk, S., Vasiléva, E. D., Vasilév, V. P., Luskova, V., Ekmekci, F. G., … Reshetnikov, S. I. (2008). Molecular phylogeny of the genus Gobio Curvier, 1816 (Teleostei: Cyprinidae) and its contribution to taxonomy. Molecular Phylogenetics and Evolution, 47, 1061–1075. Mendel, J., Papoušek, I., Marešová, E., Vetešník, E. L., Halačka, K., Nowak, M., & Čížková, D. (2012). Permanent genetic resources added to molecular ecology resources database 1 April 2012 ‐ 31 May 2012. Molecular Ecology Resources, 12(5), 972–974. https://doi. org/10.1111/j.1755‐0998.2012.03173.x Mousavi‐Sabet, H., Ganjbakhsh, B., Geiger, M. F., & Freyhof, J. (2016). Redescription of Gobio nigrescens from Hari River drainage (Teleostei: Cyprinidae). Zootaxa, 4114, 71–80. https://doi.org/10116 46/zootaxa4114.1.4 Naseka, A. M., Erkákan, F., & Kücük, F. (2006). A description of two new species of the genus Gobio from Central Anatolia (Turkey) (Teleostei: Cyprinidae). Zoosystematica Rossica, 15, 185–194. Nesbø, C. L., Fossheim, T., Vøllestad, L. A., & Jakobsen, K. S. (1999). Genetic divergence and phylogeographic relationships among European perch (Perca fluviatilis) populations reflect glacial refugia and postglacial colonization. Molecular Ecology, 8, 1387–1404. https://doi.org/10.1046/j.1365‐ 294x.1999.00699.x Nowak, M., Košco, J., & Popek, W. (2008). Review of the current status of systematics of gudgeons (Gobioninae, Cyprinidae) in Europe. AACL Bioflux, 1, 27–38. Perdices, A., Doadrio, I., Economidis, P. S., Bohlen, J., & Banarescu, P. (2003). Pleistocene effects on the European freshwater fish fauna: Double origin of the cobitid genus Sabanejewia in the Danube basin (Osteichthyes: Cobitidae). Molecular Phylogenetics and Evolution, 26, 289–299. https://doi.org/10.1016/S1055‐7903(02)00334‐2 Reyjol, Y., Hugueny, B., Pont, D., Bianco, P. G., Beier, U., Caiola, N., … Virbickas, T. (2007). Patterns in species richness and endemism of European freshwater fish. Global Ecology and Biogeography, 16, 65– 75. https://doi.org/10.1111/j.1466‐8238.2006.00264.x

Richlen, M. L., & Barber, P. H. (2005). A technique for the rapid extraction of microalgal DNA from single live and preserved cells. Molecular Ecology Notes, 5, 688–691. https://doi. org/10.1111/j.1471‐ 8286.2005.01032.x Ronquist, F., & Huelsenbeck, J. P. (2003). MRBAYES 3: Bayesian phylogenetic inference under mixed models. Bioinformatics, 19, 1572–1574. https://doi.org/10.1093/bioinformatics/btg180 Salzburger, W., Brandstätter, A., Gilles, A., Parson, W., Hempel, M., Sturmbauer, C., & Meyer, A. (2003). Phylogeography of the vairone (Leuciscus souffia, Risso 1826) in Central Europe. Molecular Ecology, 12, 2371–2386. https://doi.org/10.1046/j.1365‐294X.2003.01911.x Schenekar, T., Lerceteau‐Köhler, E., & Weiss, S. (2014). Fine‐scale phylogeographic contact zone in Austrian brown trout Salmo trutta reveals multiple waves of post‐glacial colonization and a pre‐dominance of natural versus anthropogenic admixture. Conservation Genetics, 15, 561–572. https://doi.org/10.1007/s10592‐013‐0561‐0 Schreiber, A. (2002). Differences in levels of heterozygosity in populations of the common gudgeon (Gobio gobio, Cyprinidae) among adjacent drainages in Central Europe: An effect of postglacial range dynamics? Heredity, 89, 163–170. https://doi.org/10.1038/ sj.hdy.6800109 Seifertová, M., Bryja, J., Vyskočilová, M., Martínková, N., & Šimková, A. (2012). Multiple Pleistocene refugia and post‐glacial colonization in the European chub (Squalius cephalus) revealed by combined use of nuclear and mitochondrial markers. Journal of Biogeography, 39, 1024–1040. https://doi.org/10.1111/j.1365‐2699.2011.02661.x Skog, A., Vøllestad, L. A., Stenseth, N. C., Kasumyan, A., & Jakobsen, K. S. (2014). Circumpolar phylogeography of the northern pike (Esox lucius) and its relationship to the Amur pike (E. reichertii). Frontiers in Zoology, 11, 67. https://doi.org/10.1186/s12983‐014‐0067‐8 Stamakis, A. (2014). RAxML version 8: A tool for phylogentic analysis and post‐analysis of large phylogenies. Bioinformatics, 30, 312–1313. Stout, C. C., Tan, M., Lemmon, A. R., Lemmon, E. M., & Armbruster, J. W. (2016). Resolving Cypriniformes relationships using an anchored enrichment approach. BMC Evolutionary Biology, 16(1), 244. https:// doi.org/10.1186/s12862‐016‐0819‐5 Tajima, F. (1989). Statistical method for testing the neutral mutations hypothesis by DNA polymorphism. Genetics, 123, 585–595. Takács, P., Bihari, P., Erős, T., Specziár, A., Szivák, I., Bíró, P., & Csoma, E. (2014). Genetic heterogeneity reveals on‐going speciation and cryptic taxonomic diversity of stream‐dwelling gudgeons (Teleostei, Cyprinidae) in the Middle Danubian hydrosystem (Hungary). PLoS ONE, 9, e97278. https://doi.org/10.1371/journal.pone.0097278 Tamura, K., Stecher, G., Peterson, D., Filipski, A., & Kumar, S. (2013). MEGA6: Molecular Evolutionary Genetics Analysis version 6.0. Molecular Biology and Evolution, 30, 2275–2279. https://doi. org/10.1093/molbev/mst197 Tang, K. L., Agnew, M. K., Chen, W.‐J., Hirt, M. V., Raley, M. E., Sado, T., Schneider, L. M., Yang, L., Bart, H. L., He, S., Liu, H., Miya, M., Saitoh, K., Simons, A. M., Wood, R. M., & Mayden, R. L. (2011). Phylogeny of the gudgeons (T eleostei: Cyprinidae: Gobioninae). Molecular Phylogenetics and Evolution, 61, 103–124. https://doi.org/10.1016/j. ympev.2011.05.022 Templeton, A. R., Crandall, K. A., & Sing, C. F. (1992). A cladistic analysis of phentotypic associations with haplotypes inferred from restriction endonuclease mapping and DNA sequence data. III. Cladogram estimation. Genetics, 132, 619–633. Triantafyllidis, A., Bobori, D., Koliamitra, C., Gbandi, E., Mpanti, M., Petriki, O., & Karaiskou, N. (2011). DNA barcoding analysis of fish species diversity in four north Greek lakes. Mitochondrial DNA, 22, 37– 42. https://doi.org/10.3109/19401736.2010.542242 Turan, D., Ekmekçi, G., Lusková, V., & Mendel, J. (2012). Description of a new species of genus Gobio from Turkey (Teleostei: Cyprinidae). Zootaxa, 3257, 56–65. https://doi.org/10.11646/zootaxa.3257.1.4

Vasiléva, E. D., Vasilév, V. P., & Boltachev, A. R. (2005). Taxonomic relationships of gudgeons of (Gobio, Gobioninae, Cyprinidae) in Crimea. Journal of Ichthyology, 4, 730–743. Villesen, P. (2007). FaBox: An online toolbox for fasta sequences. Molecular Ecology Notes, 7, 965–968. https://doi.org/10.1111/j.1471‐ 8286.2007.01821.x Ward, R. D., Zemlak, T. S., Innes, B. H., Last, P. R., & Hebert, P. D. N. (2005). DNA barcoding Australia's fish species. Philosophical Transactions of the Royal Society B‐Biological Sciences, 360, 1847–1857. https://doi. org/10.1098/rstb.2005.1716 Weiss, S., Persat, H., Eppe, R., Schlötterer, C., & Uiblein, F. (2002). Complex patterns of colonization and refugia revealed for European grayling Thymallus thymallus, based on complete sequencing of the mitochondrial DNA control region. Molecular Ecology, 11, 1393–1407. https://doi.org/10.1046/j.1365‐ 294X.2002.01544.x Zulka, K. P. (2007). Rote Liste gefährdeter Tiere Österreichs, Teil 2: Kriechtiere, Lurche, Fische, Nachtfalter, Weichtiere. Vienna, Austria: Böhlau.

APPENDIX

Appendix 1: The following table contains sample IDs of all newly sequenced Gobio samples. Furthermore, river and country of origin (A, Austria; D, Germany), and for both new and previously published Gobio sequences, the haplotype IDs for the three genes (COI, CR and RPS7) and the respective BOLD (for COI sequences generated in the present study) or GenBank accession numbers, as well as the reference to the original study (B, Bergsten et al. unpub.; F, Friedrich et al. 2018; G, Geiger et al. 2014; I, iBOL release 2011; K, Knebelsberger et al. 2015; M, Mendel et al. 2008; P, Perea et al. unpub.; T, Triantafyllidis et al. 2011; Ta, Tang et al. 2011; TS, this study) are listed.

Sample-ID River, country COI CR RPS7 BOLD-ID & GenBank Acc. Nos. Ref. of origin Gobio sp.1 Fish13 Lobenbach, A 2 1 49 BCAFL011-17; MN017069; MK972147; MK972207 TS Fish14 Lobenbach, A 3 2 48 BCAFL305-19; MN017083; MK972156; MK972219 TS Fish15 Lobenbach, A 3 3 40 BCAFL012-17; MG786165; MK975874; MK992900 TS Fish16 Lobenbach, A 4 4 40 BCAFL013-17; MN017043; MK972129; MK972184 TS Fish56 Naarn, A 3 5 35 BCAFL039-17; MN017053; MK972136; MK972192 TS Fish57 Naarn, A 3 5 36 BCAFL040-17; MN017078; MK972153; MK972215 TS Fish58 Naarn, A 5 6 40 BCAFL041-17; MN017060; MK972140; MK972198 TS Fish109 Naarn, A 6 1 40 BCAFL306-19; MN017051; MK972134; MK972190 TS Fish110 Naarn, A 7 7 40 BCAFL071-17; MN017091; MK972160; MK972226 TS Fish133 Naarn, A 1 9 33 BCAFL082-17; MG786150; MK975875; MK992901 TS Fish139 Teigitsch, A 3 2 41 BCAFL084-17; MN017076; MK972152; MK972214 TS Fish203 Schwarzaubach, A 8 2 41 BCAFL119-17; MN017067; MK972145; MK972205 TS Fish204 Schwarzaubach, A 9 10 41 BCAFL307-19; MN017075; MK972151; MK972213 TS Fish205 Schwarzaubach, A 8 2 47 BCAFL120-17; MN017061; MK972141; MK972199 TS Fish229 Mur, A 10 2 40 BCAFL126-17; MN017079; MK972154; MK972216 TS Fish239 March, A 3 5 40 BCAFL129-17; MN017073; MK972150; MK972211 TS Fish265 Mur, A 11 2 46 BCAFL146-17; MN017059; MK972139; MK972197 TS Fish267 Mur, A 12 11 41 BCAFL148-17; MN017049; MK972133; MK972188 TS Fish268 Mur, A 13 12 40 BCAFL149-17; MN017081; MK972155; MK972217 TS Fish269 Mur, A 14 13 40 BCAFL150-17; MN017048; MK972132; MK972187 TS Fish270 Mur, A 15 14 41 BCAFL151-17; MN017071; MK972148; MK972209 TS Fish278 Mur, A 16 2 40 BCAFL308-19; MN032616; MK975873; MK992902 TS Fish279 Mur, A 3 2 40 BCAFL153-17; MN017044; MK972130; MK972185 TS Fish344 Alterbach, A 17 2 40 BCAFL309-19; MN017055; MK972137; MK972194 TS 66

Fish353 Sulzbach/ 18 15 41 BCAFL166-17; MN017072; MK972149; MK972210 TS Trummerbach, A Fish354 Sulzbach/ 7 16 41 BCAFL167-17; MN017057; MK972138; MK972195 TS Trummerbach, A Fish355 Traun, A 3 17 37 BCAFL310-19; MN017088; MK972158; MK972223 TS Fish356 Traun, A 1 18 40 BCAFL311-19; MN017089; MK972159; MK972224 TS Fish359 Traun, A 3 6 34 BCAFL312-19; MN017064; MK972143; MK972202 TS Fish360 Traun, A 7 7 40 BCAFL313-19; MN017052; MK972135; MK972191 TS Fish361 Traun, A 3 17 40 BCAFL314-19; MN017063; MK972142; MK972201 TS Fish364 Traun, A 3 5 34 BCAFL315-19; MN017068; MK972146; MK972206 TS Fish365 Traun, A 3 5 40 BCAFL316-19; MN017066; MK972144; MK972204 TS Fish377 Mur, A 3 19 41 BCAFL317-19; MN017047; MK972131; MK972186 TS Fish385 Mur, A 19 20 39 BCAFL318-19; MN017087; MK972157; MK972222 TS Fish396 Kainach, A 7 - 45 BCAFL319-19; MN032617; MK992903 TS Fish397 Kainach, A 3 - 41 BCAFL320-19; MN032618; MK992904 TS Fish444 Traisen, A 3 - 42 BCAFL191-17; MN017065; MK972203 TS Fish445 Traisen, A 3 - - BCAFL192-17; MN017092 TS Fish446 Traisen, A 24 - 40 BCAFL193-17; MN017085; MK972220 TS Fish447 Traisen, A 24 - 40 BCAFL194-17; MN017062; MK972200 TS Fish448 Rába, A 3 - 40 BCAFL195-17; MN017086; MK972221 TS Fish450 Mur, A 7 - - BCAFL197-17; MN017080 TS Fish463 Mur, A 20 - - BCAFL204-17; MN017056 TS Fish464 Mur, A 3 - - BCAFL205-17; MN017046 TS Fish465 Mur, A 3 - 41 BCAFL206-17; MN017054; MK972193 TS Fish466 Mur, A 21 - 40 BCAFL207-17; MN017074; MK972212 TS Fish467 Mur, A 22 - 44 BCAFL208-17; MN017058; MK972196 TS Fish477 Mur, A 20 - - BCAFL215-17; MN017045 TS Fish488 Mur, A 20 - 41 BCAFL321-19; MN017090; MK972225 TS Fish489 Mur, A 25 - 43 BCAFL322-19; MN017082; MK972218 TS Fish495 Mur, A 19 - 40 BCAFL323-19; MN017070; MK972208 TS Fish499 Mur, A 3 - - BCAFL324-19; MN017084 TS Fish500 Mur, A 19 - 41 BCAFL325-19; MN017050; MK972189 TS Fish505 Mur, A 20 - - BCAFL326-19; MN017077 TS Ind9 Mur, A 20 21 41 MK962581; MK962596; MK962603 TS Ind10 Mur, A 20 21 38 MK962582; MK962597; MK962604 TS Ind11 Mur, A 7 22 40 MK962583; MK962598; MK962605 TS Ind12 Mur, A 20 21 37 MK962584; MK962599; MK962606 TS Ind13 Danube, A 23 - - MK962585 TS G. gobio G.gobio1 Fish farm, D 1 1 33 MK962586; MK962591; MK962600 TS G.gobio2 Fish farm, D 1 1 33 MK962587; MK962592; MK962601 TS G.gobio3 Fish farm, D 1 1 - MK962588; MK962593 TS G.gobio4 Fish farm, D 1 1 - MK962589; MK962594 TS G.gobio5 Fish farm, D 1 1 34 MK962590; MK962595; MK962602 TS

R. uranoscopu s Fish185 Mur, A 62 66 53 BCAFL103-17; MG786153; MK975876; MK992905 F; TS R. kesslerii Fish188 Mur, A 63 67 52 BCAFL106-17; MG786152; MK975877; MK992906 F; TS R. vladykovi Fish366 Danube, A 61 68 51 BCAFL304-18; MG786174; MK975878; MK992907 F; TS R. skywalkeri

Fish386 Mur, A 64 69 50 BCAFL299-18; MG786156; MK975879; MK992908 F; TS G. See reference 46; - - KJ553541; KJ553332; KJ553647 G balcanicus 47; 49 G. See reference 44; - - KJ553462; KJ553463; KJ553583; KJ553635 G battalgilae 44; 35; 35 G. See reference - - 28; 29 EU131611; EU131612 M brevicirris G. See reference 56 ; - - HQ600733; HQ600734; HQ600735 T bulgaricus 56 ; 56 G. See reference - 37; 7; 8; 9 EU131552; EU131559; EU131560; EU131561; EU131604; M carpathicus 38; EU131605; EU131606; 39; 40 G. See reference - 43; 14; 15; EU131584; EU131585; EU131586; EU131587; EU131615; M caucasicus 44; 16; 17 EU131616; EU131617; EU131618 45; 46 G. See reference 53 - - JN003367 Ta coriparoide s G. See reference 54 59 24 JN003364; EU131582; EU131608 Ta cynocephal (COI us ), M (CR, RPS 7) G. See reference 48; - - KJ553309; KJ553357; KJ553396; KJ553458; KJ553486; G feraeensis 50; KJ553489; KJ553371 48; 48; 48; 48; 48 G. gobio See reference 26; 1; 1; 1; 2; 3; HM560266; HQ960431; HQ960432; HQ960447; HQ960484; P 1; 58; 23; 4 HQ960485; HQ960486; HQ960487; HQ960537; HQ960600; (COI 1; 1; 24; HQ960607; HQ960683; HQ960690; HQ960691; HQ960692; ), I 1; 1; 25; HQ960693; HQ960829; HQ960830; HQ960831; HQ960832; (COI 1; 1; 26; HQ960833; HQ960834; HQ960950; HQ960951; HQ960996; ), B 59; 1; 27; HQ961007; HQ961008; HQ961009; KJ128498; KJ128499; (COI 1; 59; 28; KJ553347; KJ553349; KJ553353; KJ553373; KJ553387; ), G 1; 1; 29 KJ553429; KJ553502; KJ553507; KJ553535; KJ553546; (COI 1; 1; KJ553588; KJ553612; KJ553638; KJ553655; KM286653; ), K 1; 59; KM286654; KM286655; KM286656; KM286657; KM286658; (COI 1; 1; KM286659; KM286660; KM286661; KM286662; KM286663; ), M 1; 1; KM286664; KM286665; KM286666; KM286667; KM286668; (CR, 61; 1; KM286669; KM286670; KM286671; KM286672; KM286673; RPS 1; 1; KM286674; KM286675; KM373638; KM373643; KM373644; 7) 1; 1; KM373667; EU131542; EU131543; EU131544; EU131545; 1; 1; EU131546; EU131547; EU131548; EU131550; EU131589; 1; 1; EU131590; EU131591; EU131592; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1;

1; 55; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1; 1 G. See reference 33; - - KJ553380; KJ553475; KJ553516; KJ553534 G gymnosteth 33; us 33; 33 G. See reference 34; - - KJ553319; KJ553542; KJ553577; KJ553644 G hettitorum 35; 35; 34 G. See reference 43; 47; 18; 19; KJ553413; KJ553436; KJ553572; EU131574; EU131575; G insuyanus 43; 48; 20 EU131577; EU131576; EU131578; EU131579; EU131580; (COI 43; 49; EU131621; EU131622; EU131623 ), M 50; (CR, 51; RPS 52; 7) 53 G. See reference 32; - - KJ553334; KJ553431; KJ553432; KJ553473; G intermedius 32; 32; 32 G. See reference 45; - - KJ553320; KJ553366; KJ553415; KJ553446; KJ553515; G kovatschevi 45; KJ553621; KJ553645 45; 45; 45; 45; 45 G. See reference - 63 30 EU131549; EU131620 M krymensis G. lozanoi See reference 31; - - KJ553327; KJ553328; KJ553434; KJ553453 G 31; 31; 31 G. See reference 52; - - KJ553305; KJ553307; KJ553359; KJ553472 G meandricus 52; 52; 43 G. See reference 34; - - KJ553435; KJ553449; KJ553476; KJ553596; KJ553615; G microlepido 37; KJ553648; tus 36; 51; 35; 37 G. See reference 57; 3; 30; 5 HQ960430; HQ960912; HQ960913; HQ960928; HQ960938; I obtusirostri 3; 60; 30; EU131554; EU131555; EU131556; EU131557; EU131558; (COI s 57; 2; EU131607 ), M 31; (CR, 32 RPS 7) G. See reference 30; - - KJ553306; KJ553313; KJ553362; KJ553393; KJ553394; G occitaniae 27; KJ553399; KJ553474; KJ553526; KJ553553; KJ553554; 27; KJ553559; KJ553587; KJ553646; 27; 27; 27; 27; 27; 27;

37; 29; 27; 28 G. See reference 39; 55; 23 KJ553318; KJ553340; KJ553443; KJ553497; KJ553517; G ohridanus 39; 56; KJ553592; KJ553657; EU131570; EU131571; EU131572; (COI 39; 57; EU131573; EU131626 ), M 39; 58 (CR, 39; RPS 39; 7) 39; G. See reference 41; 60; 25; 26 KJ553360; KJ553383; KJ553440; KJ553496; KJ553571; G skadarensis 41; 61; KJ553593; KJ553601; EU131567; EU131568; EU131569; (COI 38; 62 EU131601; EU131602 ), M 38; (CR, 38; RPS 38; 7) 38; Gobio sp. See reference 42; - - KJ553421; KJ553569; KJ553575; KM286676 G, K 40; 40; 3 Gobio sp. 1 See reference - 36: 6 EU131562; EU131563; EU131564; EU131565; EU131603 M 33; 34; 35 Gobio sp. 2 See reference - 41 10; 11 EU131551; EU131593; EU131594 M Gobio sp. 3 See reference - 54 21; 22 EU131581; EU131624; EU131625 M G. tauricus See reference - - 27 EU131609 M G. See reference - 42 12; 13 EU131566; EU131613; EU131614 M volgensis Hybrid See reference - 64 - EU131583 M Hybrid See reference - 65 31 EU131553; EU131610 M Hybrid See reference - - 32 EU131619 M 1 For Austrian samples we did not distinguish between morphospecies as both nominal species and their hybrids are expected for the country.

SUPPORTING INFORMATION

Figure S1: ML tree based on the mitochondrial COI gene. Node labels represent bootstrap support values (only BS >80 are shown).

Figure S2: BI tree based on mitochondrial CR sequences. Node labels represent posterior probabilities (only PPs >0.80 are shown).

Figure S3: ML tree based on the CR. Node labels represent bootstrap support values (only BS >80 are shown).

Figure S4: ML tree based on the nuclear RPS7 gene. Node labels represent bootstrap support values (only BS >80 are shown).

Figure S5: Mismatch distribution calculated from segregating sites of the COI sequences of the three Gobio lineages. Black columns represent the observed frequency of pairwise differences; gray lines refer to the expected distribution under the sudden expansion model and the 95% confidence interval. A) G. gobio lineage, B) G. obtusirostris lineage and C) “Balkan” lineage. 75

Table S1: List of primers used in the present study, with their annealing temperatures (Ta), sequence and original publication.

Gene Ta Primer Sequence Reference COI PCR 51°C VF2_t1 TGT AAA ACG ACG GCC AGT CAA CCA ACC Ward et al., 2005 ACA AAG ACA TTG GCA C FishR2_t1 CAG GAA ACA GCT ATG ACA CTT CAG GGT Ward et al., 2005 GAC CGA AGA ATC AGA A Seq M13F TGT AAA ACG ACGGCC AGT Messing, 1983 M13R CAG GAA ACA GCT ATG AC Messing, 1983 CR PCR & Seq 50°C CR159 CCC AAA GCA AGT ACT AAC GTC Mendel et al., 2008 CR851 TGC GAT GGC TAA CTC ATA C Mendel et al., 2008 RPS7 PCR & Seq 49°C S7univL ACA ATT GTA AGT CGG AGA TG Mendel et al., 2008 S7univP CCC ACA AAA TAA GAT ATT AGG Mendel et al., 2008

Supplementary References:

Geiger, M. F., Herder, F., Monaghan, M. T., Almada, V., Barbieri, R., Bariche, M., Berrebi, P., Bohlen, J., Casal-Lopez, M., Delmastro, G. B., Denys, G. P. J., Dettai, A., Doadrio, I., Kalogianni, E., Kärst, H., Kottelat, M., Kovačić, M., Laporte, M., Lorenzoni, M., Marčić, Z., Özuluğ, M., Perdices, A., Perea, S., Persat, H., Porcelotti, S., Puzzi, C., Robalo, J., Šanda, R., Schneider, M., Šlechtová, V., Stoumboudi, M., Walter, S., & Freyhof, J. (2014). Spatial heterogeneity in the Mediterranean Biodiversity Hotspot affects barcoding accuracy of its freshwater fishes. Molecular Ecology Resources, 14, 1210–1221.

Knebelsberger, T., Dunz, A., Neumann, D., & Geiger, M. F. (2015) Molecular diversity of Germany’s freshwater fishes and lampreys assessed by DNA barcoding. Molecular Ecology Resources, 15, 562-572.

Mendel, J., Lusk, S., Vasiléva, E. D., Vasilév, V. P., Luskova, V., Ekmekci, F. G., Erkákan, F., Ruchin, A., Koščo, J., Vetešnik, L., Halačka, K., Šanda, R., Pashkov, A. N., & Reshetnikov, S. I. (2008). Molecular phylogeny of the genus Gobio Curvier, 1816 (Teleostei: Cyprinidae) and its contribution to taxonomy. Molecular Phylogenetics and Evolution, 47, 1061-1075.

Messing, J. (1983). New M13 vectors for cloning. Methods in Enzymology, 101, 20-78.

Tang, K.L., Agnew, M.K., Chen, W.-J., Hirt, M.V., Raley, M.E., Sado, T., Schneider, L.M., Yang, L., Bart, H.L., He, S., Liu, H., Miya, M., Saitoh, K., Simons, A.M., Wood, R.M., & Mayden, R.L. (2011). Phylogeny of the gudgeons (Teleostei: Cyprinidae: Gobioninae). Molecular Phylogenetics and Evolution, 61, 103- 124.

Takács, P., Bihari, P., Erős, T., Specziár, A., Szivák, I., Bíró, P., & Csoma, E. (2014). Genetic heterogeneity reveals on-going speciation and cryptic taxonomic diversity of stream-dwelling gudgeons (Teleostei, Cyprinidae) in the Middle Danubian hydrosystem (Hungary). PLoS ONE, 9, e97278.

Triantafyllidis, A., Bobori, D., Koliamitra, C., Gbandi, E., Mpanti, M., Petriki, O., & Karaiskou, N. (2011) DNA barcoding analysis of fish species diversity in four north Greek lakes. Mitochondrial DNA, 22(S1), 37-42.

Ward, R.D., Zemlak, T.S., Innes, B.H., Last, P.R., & Hebert, P.D.N. (2005). DNA barcoding Australia's fish species. Philosophical Transactions of the Royal Society B-Biological Sciences 360, 1847-1857.

How to cite this article: Zangl L, Daill D, Gessl W, Friedrich T, Koblmüller S. Austrian gudgeons of the genus Gobio (Teleostei: Gobionidae): A mixture of divergent lineages. J Zool Syst Evol Res. 2020;58:327–340. https://doi.org/10.1111/jzs.12340

Chapter 4

A reference DNA barcode library for Austrian amphibians and reptiles

Zangl L, Daill D, Schweiger S, Gassner G, Koblmüller S (2020) A reference DNA barcode library for Austrian amphibians and reptiles. PLoS ONE 15(3): e0229353. https://doi.org/10.1371/ journal.pone.0229353

LUKAS ZANGL1,2, DANIEL DAILL1,3, SILKE SCHWEIGER4, GEORG GASSNER4, STEPHAN KOBLMÜLLER1

1 Institute of Biology, University of Graz, Graz, Austria

2 Studienzentrum Naturkunde, Universalmuseum Joanneum, Graz, Austria

3 Consultants in Aquatic Ecology and Engineering—blattfisch e.U., Wels, Austria

4 First Zoological Department, Herpetological Collection, Museum of Natural History Vienna, Vienna, Austria

ABSTRACT

In the last few years, DNA barcoding became an established method for species identification in biodiversity inventories and monitoring studies. Such studies depend on the access to a comprehensive reference data base, covering all relevant taxa. Here we present a comprehensive DNA barcode inventory of all amphibian and reptile species native to Austria, except for the putatively extinct Vipera ursinii rakosiensis and Lissotriton helveticus, which has been only recently reported for the very western edge of Austria. A total of 194 DNA barcodes were generated in the framework of the Austrian Barcode of Life (ABOL) initiative. Species identification via DNA barcodes was successful for most species, except for the hybridogenetic species complex of water frogs (Pelophylax spp.) and the crested newts (Triturus spp.), in areas of sympatry. However,

DNA barcoding also proved powerful in detecting deep conspecific lineages, e.g. within Natrix natrix or the wall lizard (Podarcis muralis), resulting in more than one Barcode Index Number (BIN) per species. Moreover, DNA barcodes revealed the presence of Natrix helvetica, which has been elevated to species level only recently, and genetic signatures of the Italian water frog Pelophylax bergeri in Western Austria for the first time. Comparison to previously published DNA barcoding data of European amphibians and reptiles corroborated the results of the Austrian data but also revealed certain peculiarities, underlining the particular strengths and in the case of the genus Pelophylax also the limitations of DNA barcoding. Consequently, DNA barcoding is not only powerful for species identification of all life stages of most Austrian amphibian and reptile species, but also for the detection of new species, the monitoring of gene flow or the presence of alien populations and/or species. Thus, DNA barcoding and the data generated in this study may serve both scientific and national or even transnational conservation purposes.

INTRODUCTION

Amphibians and reptiles -at least across Europe- comprise rather species poor taxonomic groups compared to other classes of vertebrates [1]. However, despite their low species diversity, they are important indicators for biomonitoring and conservation management due to their sensitivity to environmental changes [1–7]. They show high vulnerability to changes in water regime, land use, pollution, habitat disruption, fragmentation and destruction and changes in interspecific competition accompanied by novel pathogens, like the chytrid fungus infesting amphibians or Ophidiomyces ophiodiicola, the snake fungal disease [4,5,8,9,10,11].

All of these factors have led to a decline in population and species numbers, not only on a local, but also on a global scale [5,12–16]. Generating and maintaining a comprehensive picture of the status of threatened species and in order to promote conservation efforts [12,17– 21], environmental monitoring is an undisputable necessity. Furthermore, as a member of the EU, Austria -as anchored in the EU Habitats Directive- is obliged to frequently report on the status of protected species and habitats [22]. Assessments of species composition, distribution and welfare frequently requires the species level identification of amphibians and reptiles in the field. While determination of adult or

fully-grown specimens is usually a routine exercise for experts, identification of leftovers from road kills, eggs or larvae of closely related species such as newts (Triturus spp.) and frogs (Rana spp., Pelophylax spp.) can pose a bigger challenge [7]. These challenges may often be overcome by DNA barcoding, a method that com- pares short, standardized gene sequences with a reference database [23]. This method has been shown to yield high accuracy and success rates for species identification, although certain exceptions and limitations remain [7]. Thus, in the recent past a large number of DNA barcoding sequences of various amphibian and reptile species accumulated across the globe [1,7,24– 28]. All of this data contributes to the global iBOL initiative [29] and can be used either for direct comparison or as the basis for environmental DNA (eDNA) approaches for studies on biodiversity, population dynamics, range shifts and anthropogenic translocation of species [7,30,31].

For Austria 20 species of amphibians and 14 species of reptiles are currently recognized, although Vipera ursinii is considered to be extinct [32,33]. Despite sporadic findings of palmate newts (Lissotriton helveticus) in Vorarlberg in 2008 and 2009 [34], this species does not appear in national species catalogues. Furthermore, the recently described Natrix helvetica, which was elevated to species level from N. n. helvetica in 2017 [35], can also be found in Austria, but is not yet listed as a distinct native faunal element. However, both L. helveticus and N. helvetica will be incorporated in the next red list of Austrian amphibians and reptiles (S. Schweiger, unpubl. data). Special conservational concern is attributed to a total of 76% or 16 species of amphibians and 10 species of reptiles, as they are mentioned in the appendices II and IV of the EU Habitats directive and all of these species are furthermore subject to national conservation laws as well [22]. The Austrian Barcode of Life initiative (ABOL, www.abol.ac.at) aims at contributing to the global genetic species inventory as well as providing a comprehensive overview of the national herpetofauna. With this data release we provide 194 DNA barcodes of all species native to Austria, except for the putatively extinct in Austria V. ursinii rakosiensis and the rarely encountered L. helveticus. In addition, we discuss the genetic diversity of Austria’s herpetofauna in a European context by comparing it to previously published molecular data from amphibians and reptiles from surrounding countries.

MATERIAL AND METHODS

Most samples were obtained from natural history museums. Additional samples were collected in the field, resorting only to freshly dead specimens to avoid sacrificing live animals (permit numbers ABT13-53S-7/1996-156 and ABT13-53W-50/2018-2, or passed on by the Museum of Natural History in Vienna, a CITES-registered federal institution, which is allowed to receive and store samples in its collections). Overall, 239 samples of Austrian amphibians and reptiles were obtained. Species of the water frog (Pelophylax) complex were determined morphologically using [36], crested newt species (Triturus) identification followed [37] and was linked to the geographic region the samples were acquired from. Tissue samples were stored in pure ethanol in a freezer at - 20˚C, and reptile and amphibian voucher specimens were fixed in 70% and 50% ethanol respectively and permanently stored in natural history museums. All information regarding specimen, collection and storage is available on BOLD (www.boldsystems. org, project code ‘BCAHF’) (also see S1 Table). DNA extraction followed two methods. As standard method, we employed a rapid Chelex protocol [38]. In addition, some difficult samples were extracted with the DNeasy Blood & Tissue Kit (Quiagen), following the manufacturer’s instructions. Polymerase chain reaction (PCR) for the first part of the mitochondrial cytochrome oxidase subunit 1 gene (COI), gel electrophoresis, enzymatic clean-up using Exo- SAP-IT and chain termination sequencing followed [39] and [40]. Primers used for PCR and cycle sequencing are listed in S2 Table, annealing temperatures ranged from 46–50˚C. DNA fragments were purified with SephadexTM G- 50 (Amersham Biosciences) and visualized on an ABI 3130xl capillary sequencer (Applied Biosystems). The sequences were edited manually and an alignment was manually created and trimmed in MEGA 6.06 [41]. For further analysis, the alignment was split into a reptilian and an amphibian dataset. Neighbor-joining (NJ) trees based on the Kimura 2-parameter (K2P) [42] distance model were generated on BOLD using the Taxon ID tree analysis tool for visualization of taxonomic clades. To put the genetic diversity of the Austrian herpetofauna into a European context, a second set of NJ trees was calculated with MEGA 6.06 after including sequences from other European countries [7,26,28,43–47], downloaded from the online repositories GenBank and BOLD. Maximum intraspecific genetic distances as well as the minimum interspecific distances were calculated under the K2P model using the “Barcode Gap Analysis” tool implemented on BOLD [48].

RESULTS

Out of 239 samples, we generated 194 DNA barcodes with a length of 584 to 658 bp, conforming to an 81% sequencing success rate. All sequences were deposited on GenBank (Accession Nos. MN993072—MN993264) and BOLD (dx.doi.org/10.5883/DS-BCAHF). Barcodes were obtained for all amphibian and reptile species native to Austria, except for the presumably extinct V. ursinii rakosiensis and the only rarely reported L. helveticus. Furthermore, COI sequence data proved the presence of N. helvetica, which has been elevated to species level only recently, and the first ever recovered genetic signatures of the Italian water frog (P. bergeri) in Austria. Overall, DNA barcodes of Austrian amphibians and reptiles contributed to 31 already existing BINs on BOLD and created seven new BINs (Iberolacerta horvathi, Natrix natrix, Zoo- toca vivipara (3), Vipera ammodytes and Pelophylax kl. esculentus). Most of the species (28 out of 34) were represented only by a single BIN and no cases of BIN sharing were detected, except for newts and water frogs, where hybrids are possible. In cases where species are represented by two or more BINs, this is due to single deviating sequences (Rana temporaria), or distinct intraspecific lineages (Podarcis muralis, Zootoca vivipara). Separate NJ trees for amphibians (Fig 1) and reptiles (Fig 2) were generated based on the COI sequences, allowing for unambiguous identification of all species except for the hybridogenic species complex of water frogs (Pelophylax spp.) and the crested newt complex (Triturus spp.), for which morphological species assignment was not reflected perfectly by the NJ tree.

Fig 1. NJ tree of Austrian amphibians based on K2P distances. The tree was inferred with the “Taxon ID Tree” tool implemented in BOLD and visualized in FigTree v1.4.2 (http://tree.bio.ed.ac.uk/software/figtree/). * indicates an Austrian water frog sample showing genetic signatures of the Italian water frog (P. bergeri). 1 indicates the T. dobrogicus clade, which contains one sample identified as T. carnifex. 2 marks the T. carnifex clade, which also holds one T. cristatus.

Austrian Pelophylax, determined based on their morphology, formed three clades of one (mitochondrial DNA of P. bergeri), eight (2 P. esculentus, 5 Pelophylax sp. and 1 P. lessonae) and three (2 P. ridibundus and 1 P. lessonae) sequences, respectively. The comparison of Austrian water frog COI sequences to already existing European water frog data corroborate this result (Fig 3). Although one clade (BOLD:AAN3045) was mainly composed of P. ridibundus sequences from Germany and Austria, it also included one German and one Austrian P. lessonae sample. P. ridibundus from Russia formed a distinct clade and was also represented by an individual BIN (BOLD:AAD6744). Two

sequences of Italian P. bergeri clustered together with one Western Austrian water frog sample in a distinct BIN (BOLD:ADH3024), indicating the presence of P. bergeri mtDNA in (western) Austrian water frogs.

Fig 2. NJ tree of Austrian reptiles based on K2P distances. The tree was inferred with the “Taxon ID Tree” tool implemented in BOLD and visualized in FigTree v1.4.2 (http://tree.bio.ed.ac.uk/software/figtree/).

The second major clade of pan-European water frog COI sequences included a mixture of all three species occurring in Central Europe. P. kl. esculentus, P. lessonae and P. ridibundus from Austria, Germany and Poland all contributed to the same BIN (BOLD:AAM0091).

Intraspecific genetic distances were well below 2% for most of the species (Table 1). In some species, haplotypes were very similar and differed by only a few substitutions despite a fairly large number of samples included in the analyses (e.g., Zamenis longissimus, 13 samples, 0.49% maximum intraspecific distance (Imax); Anguis fragilis, 14 samples, 0.46% Imax). Higher intraspecific genetic distances were observed for N. natrix (5.94%), V. berus (2.65%) P. muralis (3.6%), Z. vivipara (6.09%) within the reptiles and R. temporaria (4.01%), Triturus carnifex (8.00%) and Triturus cristatus (7.84%) within the amphibians (Table 1).

The large intraspecific distances in newts, however, are due to hybridization/introgression in areas of sympatry. Calculation of within (T. carnifex 0%, T. cristatus 0.03%, T. dobrogicus 0.02%) and between BIN distances (T. carnifex 7.5%, T. cristatus 7.8%, T. dobrogicus 7.5%), however, perfectly comply with the barcode gap hypothesis. Minimum interspecific distances within reptiles (10.76%) and amphibians (9.92%) exceeded intraspecific distances considerably. Contrasting the generally observed pattern of low intra- and higher interspecific genetic distances, the species complex of water frogs (Pelophylax spp.) showed an exactly reversed pattern when analyzed based on presumed species assignment. When resorting to BINs, genetic distances of conspecifics did not exceed one percent and the interspecific distance between BOLD:ADH3024 (new BIN, this study) and BOLD:AAM0091 (P. lessonae according to [7]) amounted to 3.85%.

DISCUSSION

General barcoding success and efficiency

In this study we present 194 barcodes for all extant species of the Austrian herpetofauna, except for the only recently documented and rarely observed palmate newt (L. helveticus) and the putatively extinct in Austria meadow viper V. ursinii rakosiensis. For all species, two or more barcodes were generated, except for the nose-horned viper (V. ammodytes), for which only a single sample could be obtained. Analysis of genetic barcoding data almost perfectly reflects the country’s species assemblage. Of the 11 families, 22 genera and 34 species of amphibians and reptiles occurring in Austria, only the hybridogenetic species group of water frogs (Pelophylax spp.) and the crested newt species (Triturus spp.), for which hybrids are known to exist in areas where two or more species occur in sympatry [49–51], could not be resolved properly by the COI tree. This result was also 85

reflected by the barcode gap analysis. Consequently, a species level determination based on DNA barcoding is possible for all species of the Austrian herpetofauna that form distinct barcode clusters. This, in principle, also includes the crested newts, but with the caveat that potential hybrids cannot be detected based on COI data alone.

The problem with Pelophylax

The only exception where reliable species identification was not possible with DNA barcodes is the genus Pelophylax. Even though the three species might be distinguished based on morphological and bioacoustical characters, mtDNA does not allow for species identification because of cross-breeding between the hybridogenetic P. kl. esculentus with its parent species [7]. This circumstance is shown by our taxon ID tree of Austrian Pelophylax COI sequences (Fig 1), as well as by the tree including also other European water frog COI data (Fig 3). Obviously, morphologically determined specimens of all three species do contribute to the same BIN on BOLD, thus blurring the significance of certain BINs. This also implies, that neither a BLAST search on GenBank or BOLD, nor the accumulation of further COI data of these species will result in an unambiguous identification, unless this data is supported and verified by additional analyses (e.g. PCR- RFLP [52]; microsatellite data [53–54]; PCR—sequence length differences [55]). On the other hand, DNA barcoding revealed the mitochondrial signature of the Italian water frog P. bergeri in one of our samples (Fig 3) collected in Vorarlberg in the far West of Austria for the first time. This again highlights one of the strengths of DNA barcoding, as it can be used to detect human-induced translocations or track natural migrations triggered by climate change, both possibly leading to a turnover in local species assemblages [56–58].

Table 1. Genetic (K2P) distances (in %) within and between species.

Species BIN N Imax Nearest neighbor DNN Anura Bombinatoridae Bombina bombina BOLD:AAD1964 3 0.15 Bombina variegata 10.09 Bombina variegata BOLD:AAD4416 5 0.17 Bombina bombina 10.09 Bufonidae Bufo bufo BOLD:AAC2139 8 1.41 Epidalea calamita 18.02 Epidalea calamita BOLD:AAI8496 2 0 Bufotes viridis 17.44 Bufotes viridis BOLD:AAJ8500 2 0 Epidalea calamita 17.44 Hylidae Hyla arborea BOLD:AAN9979 5 0.3 Bufo bufo 24.29 Pelobatidae Pelobates fuscus BOLD:AAL6663 6 0.46 Rana temporaria 25.75

Ranidae Pelophylax spp. BOLD:ADH3024 1 0� BOLD:AAM0091 3.85 BOLD:AAM0091 8 0.96 BOLD:ADH3024 3.85 � BOLD:AAN3045 3 0.15 BOLD:ADH3024 13.11 � Rana arvalis BOLD:AAL1420 8 1.54 Rana temporaria 9.92 Rana dalmatina BOLD:AAM0090 5 0.76 Rana temporaria 14.25 Rana temporaria BOLD:AAL6095 6 4.01 Rana arvalis 9.92 BOLD:ACH4056 1 Caudata Salamandridae Ichthyosaura alpestris BOLD:AAC5105 12 1.85 Triturus carnifex 19.74 Lissotriton vulgaris BOLD:AAL6213 7 0.66 Ichthyosaura alpestris 20.98 Salamandra atra BOLD:ACM1022 3 0.15 Salamandra salamandra 9.49 Salamandra salamandra BOLD:ACE6170 5 1.54 Salamandra atra 9.49 Triturus carnifex BOLD:ACE8564 9 8� Triturus dobrogicus 0.15 Triturus cristatus BOLD:AAC3031 2 7.84 Triturus carnifex 0.15 � Triturus dobrogicus BOLD:AAE0668 3 0� Triturus carnifex 0.15 Squamata Anguidae Anguis fragilis BOLD:AAK0900 14 0.46 Iberolacerta horvathi 24.73 Colubridae Coronella austriaca BOLD:AAL9606 7 0.64 Zamenis longissimus 12.75 Zamenis longissimus BOLD:AAL5946 13 0.49 Coronella austriaca 12.75 Natrix natrix BOLD:AAL6710 12 5.94 Natrix tessellata 10.76 � BOLD:ACM1720 2 BOLD:AAX3380 3 BOLD:ADH1094 1 Natrix tessellata BOLD:AAN4201 3 0.47 Natrix natrix 10.76 Viperidae Vipera ammodytes BOLD:ADH3451 1 0.00 Vipera berus 12.00 Vipera berus BOLD:AAW7158 2 2.65 Vipera ammodytes 12.00 BOLD:ACM2231 3 Lacertidae Iberolacerta horvathi BOLD:ADG8839 3 0.15 Lacerta agilis 16.70 Lacerta agilis BOLD:AAL6669 4 0.31 Lacerta viridis 13.60 Lacerta viridis BOLD:AAJ3146 5 1.88 Lacerta agilis 13.60 Podarcis muralis BOLD:AAH9270 3 3.60 Zootoca vivipara 17.16 BOLD:AAL6640 3 Zootoca vivipara BOLD:ADH1152 1 6.09 Podarcis muralis 17.16 BOLD:ADH1309 3 BOLD:AAL6569 2 BOLD:ADH1153 2 Testudines Emydidae Emys orbicularis BOLD:AAF8183 2 0.92 Lacerta viridis 25.15

K2P distances of COI sequences within and between species studied. BIN, “Barcode Index Number” assigned by BOLD; N, number of barcode sequences contributing to a certain BIN; Imax, maximum intraspecific distance; Nearest neighbor, most closely related species; DNN, genetic distance to the closest related species. � Indicates ambiguous cases where hybridization or multiple species blur genetic distances.

Signatures of postglacial recolonization

Most other species of both amphibians and reptiles are characterized by low intra- and higher interspecific genetic distances and represented by single BINs, which is in line with the findings of [7]. However, there are some exceptions like Bufo bufo (1.41% Imax), Rana arvalis (1.54% Imax), Salamandra salamandra (1.54% Imax), Ichthyosaura alpestris (1.85% Imax) or Lacerta viridis (1.88% Imax), where genetic distances are slightly higher but still contribute to only a single BIN, and others like V. berus (distance within clusters 2.65%), where the split into two separate lineages is also reflected by separate BINs. Similar to [7], divergent lineages in V. berus were also detected in Austria, allowing for a clear assignment of individuals to either an inner alpine area or to adjacent lowland regions (Fig 4). These lineages might be explained by different glacial refugia and post-glacial recolonization routes [59–60].

The genetic sub-structuring observed in the COI data of European populations of common toad (B. bufo), moor frog (R. arvalis), fire salamander (S. salmandra) and alpine newt (I. alpestris) has been attributed to different glacial refugial areas and explains the increased intraspecific genetic distance observed in Austrian samples [61–64]. In contrast to S. salamandra (Fig 5A), where our data is perfectly in line with [7], the alpine newt data generated in the present study deviates from [7] in that there is a clear separation into two conspecific lineages, comprising samples from north and from south(east) of the Alps, respectively (Fig 5B). This is in line with [64], who suggested two separate Pleistocene refugia north and south of the Alps.

However, all 12 Austrian samples of I. alpestris are included in the same BIN (BOLD: AAC5105) and cluster together with samples from Germany, Spain and the Ukraine, congruent with cytochrome b (cytb) and 16S data [64].

In the case of Rana temporaria, one divergent haplotype is causing the large intraspecific distance of 4.01%, which is also reflected by a new BIN (BOLD:ACH4056). Unlike the rest of the Austrian R. temporaria samples, which were obtained from the inner or southern region of the Austrian Alps, this specific sample was obtained from north of the Danube in Lower Austria. In comparison with other European common frog data (Fig 5D), this particular haplotype clusters together with samples from Sweden, Russia, the Ukraine and Germany. However, although a basic separation into an Eastern and Western

lineage of R. temporaria across mainland Europe was suggested by [66], we cautiously refrain from assigning divergent haplotypes/ BINs to one of these lineages.

Similar to V. berus, Z. vivipara shows deep conspecific lineages in the COI topology (Fig 2). Since they share similar ecological niches and inhabit the same habitats and biogeographical regions, it is not surprising that they also share similar postglacial recolonization patterns [58,60]. Nuclear and mitochondrial sequence data suggest up to 13 subclades and six main lineages with two areas of overlap, one being situated in Northern Italy, Austria and Northern Slovenia [58]. This could explain the high intraspecific divergence and consequently the split into four distinct BINs observed in Austrian Z. vivipara COI data (Fig 5F).

Fig 4. Subtree of the common European adder. COI sequences of V. berus allow for an assignment of origin from an inner alpine (blue) or adjacent lowland regions (red). Clades also include sequences from [7], only Austrian samples are displayed on the map.

Signatures of sympatric hybridization and introduction

Ambiguous results were obtained for the crested newt species (Triturus spp.) [67]. Genetic distances within and between BINs perfectly fit the barcode gap hypothesis and clearly separate sequence clusters and species. Based on morphological species assignment, though, the maximum within-clade distance exceeds the distance to the nearest neighbor by far (Table 1). This results from hybridization/introgression in areas of sympatry, which has been frequently reported for these three species [49–51,68]. The wall lizard (P. muralis) is known to occur throughout Europe in more than 100 populations originating from eight geographically distinct genetic lineages [65]. Furthermore, repeated introductions of allochthonous populations within and outside its native distribution range increased the overall distribution range and led to hybridization events between autochthonous and allochthonous subspecies [65,69–70]. Throughout Austria, at least three subspecies are known to occur, two of which, P. muralis muralis 89

and P. muralis maculiventris are autochthonous. Thus, finding different haplotypes was expected [70]. Similar to [7], DNA barcodes clustered in more than one clade and contributed to more than one BIN (Fig 5C). However, only one BIN (BOLD:AAL6640) was shared between German and Austrian samples, the rest of the Austrian samples was represented by a different BIN (BOLD:AAH9270), which might represent the Central Balkan clade according to [65]. This genetic lineage likely represents the subspecies P. m. muralis, which should be present across large parts of the species’ Austrian distribution range. Whether or not this distinct BIN is of autochthonous or allochthonous origin cannot be resolved and is outside the scope of the present study. Nonetheless, these genetic signatures may provide a geographic traceability and thus be of interest for conservation purposes.

Fig 5. Cases of ambiguity. A) The two recognized subspecies of S. salamandra form two distinct clades but contribute to the same BIN. B) I. alpestris is represented by only one BIN despite increased intraspecific distance and a subdivision into separate clades. C) Presumed subspecies of P. muralis. Austrian samples are found in the three clades recovered by [7], but also in the “Central Balkan clade” proposed by [65] and another Austria specific BIN. D) Conspecific lineages within R. temporaria represented by two distinct BINs. E) Discrepancies within N. natrix. Two separate BINs were recovered within the nominal form N. n. 91

natrix, as well as one new BIN from Austria. N. helvetica forms a distinct clade with an individual BIN. F) High genetic diversity within Z. vivipara. The separate clades and distinct BINs likely correspond to various genetic lineages proposed by [58].

Systematic and taxonomic implications

Similar to [7], our COI data also seems to pinpoint certain taxonomic cases where subspecies might be revealed. Systematic relationships of the genus Natrix have been repeatedly reevaluated, leading to the erection of new genera, the elevation of former subspecies to species level and the redefinition of distribution areas, but still rendering the exact number of subspecies and their validity open to debate [35,71]. Since 2017, however, N. helvetica is considered a valid species with its core distribution situated west of the river Rhine [35]. DNA barcoding data generated in this study as well as the definitive morphological determination of one of the samples, though, suggests that N. helvetica can also be found in Austria’s westernmost state Vorarlberg, as three of our samples clearly cluster with one N. n. helvetica from Germany (Fig 5E). Furthermore, three other distinct BINs were recovered, two within the nominal form N. n. natrix [72], possibly corresponding to the two main genetic lineages in Central Europe (“yellow” and “red”) found by [35]. Genetic distances between BINs ranged from 2.4 to 5.3%. However, we refrain from assigning BINs to certain subspecies, as [35] already found discrepancies between distribution ranges, genetics and morphology and highlighted the necessity of a comprehensive taxonomic revision.

Summary

In summary, DNA barcoding is a powerful tool for the identification of almost all species of amphibians and reptiles native to Austria. The only exceptions remaining are the species complex of water frogs (Pelophylax spp.) and syntopic hybrids of the crested newts (Triturus sp.), for which COI barcodes do not provide species level resolution. Furthermore, the species level identification of tissue remains, eggs and larval stages but also non-invasive sampling (cheek swaps, eDNA) will be possible based on a comprehensive DNA barcode reference library [7]. National -like this one- and large- scale data sets will also allow the determination of geographic origin to some extent [7]. In this respect, Austria has proven an important geographic area where various genetic lineages of several species from different refugial areas abut and overlap, and thus 92

valuable for the understanding of the distribution of European amphibians and reptiles. However, DNA barcoding also proved valuable in the detection of new/introduced/ potentially invasive species (N. helvetica, P. bergeri) and subspecies (N. natrix) and can pinpoint possible allochthonous haplotypes (P. muralis). Thus, DNA barcoding data can also serve conservation purposes in terms of monitoring native fauna and the early detection of human mediated introduced species/populations or natural (including potentially climate change induced) immigrations.

SUPPORTING INFORMATION

S1 Table. Table containing sampling and storage information. All necessary sampling and storage data as well as BOLD and BIN numbers are listed for all samples obtained and barcoded in the present study.

Sample Process ID Institution Genus Species State Region Exact Site ID Storing (Bold) (Bold) Herp1 BCAHF001- NHM Wien S. salamandra Tyrol Wilferertal Wilferertal 17 Herp4 BCAHF002- NHM Wien S. salamandra Upper St. Ulrich St. Ulrich 17 Austria Herp5 BCAHF003- NHM Wien S. atra Tyrol Ötztaler Alpen Zaunhof Richtung 17 Ludwigsbrunner Hütte Herp6 BCAHF004- NHM Wien S. atra Upper Reichraminger Sinnreitnerboden 17 Austria Hintergebirge Herp10 BCAHF005- NHM Wien L. vulgaris Styria Graz Graz Gösting 17 Herp11 BCAHF006- NHM Wien B. bombina Lower Horn Breitenteich bei 17 Austria Horn Herp12 BCAHF007- NHM Wien B. bombina Lower Wien Gr. Mühlhaufen 17 Austria bei Schwechat Herp13 BCAHF008- NHM Wien B. bombina Burgenland Andau Schottergrube 5 17 km nördlich von Andau Herp14 BCAHF009- NHM Wien B. variegata Lower Waldviertel Eisenbergeramt 17 Austria Herp15 BCAHF010- NHM Wien B. variegata Styria Mureck Mureck 17 Herp17 BCAHF011- NHM Wien B. variegata Carinthia Bodental Märchenwiese im 17 Bodental Herp19 BCAHF118- NHM Wien P. fuscus Lower Marchegg Köhlergrube- 17 Austria Tümpel im SE von Marchegg 93

Herp20 BCAHF012- NHM Wien B. calamita Lower Neu-Nagelberg Neu-Nagelberg 17 Austria Herp21 BCAHF013- NHM Wien B. calamita Lower Schrems Schrems 17 Austria Herp24 BCAHF119- NHM Wien B. viridis Burgenland Apetlon Apetlon 17 Herp27 BCAHF122- NHM Wien H. arborea Lower Neu-Nagelberg Neu-Nagelberg 19 Austria Herp28 BCAHF014- NHM Wien R. dalmatina Styria Graz Graz Andritz 17 Herp30 BCAHF015- NHM Wien P. ridibundus Burgenland Neusiedlersee Neusiedlersee 17 Herp31 BCAHF016- NHM Wien P. lessonae Burgenland Neusiedel Neusiedel am See 17 Herp32 BCAHF123- NHM Wien P. esculenta Tyrol St. Leonhard Naßwiese bei St. 19 Leonhard Herp33 BCAHF017- NHM Wien P. esculenta Carinthia Gailtal Webersee im 17 Gailtal Herp35 BCAHF124- NHM Wien E. orbicularis Lower Eckartsau Donauauen bei 19 Austria Eckartsau Herp36 BCAHF125- NHM Wien E. orbicularis Lower Lobau Lobau 19 Austria Herp37 BCAHF018- NHM Wien L. viridis Lower Kritzendorf Kritzendorf 17 Austria Herp39 BCAHF120- NHM Wien L. viridis Burgenland Eisenstadt-Umgebung Eisenstadt- 17 Umgebung Herp42 BCAHF019- NHM Wien C. austriaca Upper St. Ulrich St. Ulrich 17 Austria Herp43 BCAHF020- NHM Wien C. austriaca Burgenland Stadtschlaining Stadtschlaining 17 Herp45 BCAHF021- NHM Wien Z. longissimus Lower Hainburg Hainburg 17 Austria Herp46 BCAHF022- NHM Wien Z. longissimus Lower Hardegg Hardegg 17 Austria Herp47 BCAHF023- NHM Wien Z. longissimus Upper St. Ulrich St. Ulrich 17 Austria Herp48 BCAHF024- NHM Wien N. natrix Tyrol Sommeregg Sommeregg 17 Herp49 BCAHF126- NHM Wien N. natrix Lower St. Pölten St. Pölten, 19 Austria Spratzern Herp50 BCAHF025- NHM Wien N. natrix Burgenland Illmitz Illmitz 17 Herp51 BCAHF026- NHM Wien N. natrix Upper Mauthausen Mauthausen 17 Austria Hinterbergerstraße Herp52 BCAHF027- NHM Wien N. natrix Tyrol Lahntal Aufgelassener 17 Steinbruch, Lahntal Herp54 BCAHF028- NHM Wien N. tessellata Lower Hainburg Hainburg 17 Austria

Herp55 BCAHF029- NHM Wien N. tessellata Vienna Alberner Hafen Alberner Hafen 17 Herp57 BCAHF030- NHM Wien V. ammodytes Carinthia Griffen Griffen 17 Herp60 BCAHF127- NHM Wien B. bufo Tyrol Brennersee Brennersee 19 Herp61 BCAHF031- NHM Wien R. arvalis Vienna Wien Donauinsel 17 Herp62 BCAHF032- NHM Wien T. carnifex Lower Troppberg Troppberg 17 Austria Herp63 BCAHF033- NHM Wien T. carnifex Styria Kirchberg/Raab Kirchberg/Raab 17 Herp64 BCAHF034- NHM Wien T. carnifex Styria Stadl-Paura Stadl-Paura 17 Herp65 BCAHF035- NHM Wien T. cristatus Salzburg Anthering Anthering 17 Herp66 BCAHF036- NHM Wien I.. horvathii Carinthia Doberbachtal Doberbachtal 17 Herp67 BCAHF037- NHM Wien R. temporaria Lower Waldviertel Ullrichs 17 Austria Herp68 BCAHF038- NHM Wien R. arvalis Burgenland Weiden Weiden 17 Herp69 BCAHF039- NHM Wien Z. vivipara Carinthia Mallnitz Mallnitz 17 Herp70 BCAHF040- NHM Wien A. fragilis Tyrol Achensee Achensee 17 Herp71 BCAHF041- NHM Wien A. fragilis Styria Donnersbach Donnersbach 17 Herp72 BCAHF042- NHM Wien T. carnifex Styria St. Michael/Mur St. Michael/Mur 17 Herp73 BCAHF043- NHM Wien P. muralis Tyrol Kufstein Kufstein 17 Herp74 BCAHF044- NHM Wien B. bufo Tyrol Brennersee Brennersee 17 Herp75 BCAHF045- NHM Wien P. muralis Carinthia Lesachtal Lesachtal 17 Herp76 BCAHF046- NHM Wien T. cristatus Vorarlberg Lingenau Lingenau 17 Herp77 BCAHF121- NHM Wien T. dobrogicus Vienna Wien Donauinsel 17 Herp78 BCAHF128- NHM Wien T. dobrogicus Burgenland Illmitz Illmitz 19 Herp79 BCAHF129- NHM Wien P. fuscus Vienna Wien Donauinsel 19 Herp80 BCAHF047- NHM Wien I. alpestris Salzburg Obertrum Obertrum 17 Herp81 BCAHF130- NHM Wien I. alpestris Lower Gaaden Gaaden 19 Austria Herp82 BCAHF131- NHM Wien R. dalmatina 19

Herp83 BCAHF048- NHM Wien R. dalmatina Lower Gumpoldskirchen Gumpoldskirchen 17 Austria Herp84 BCAHF049- NHM Wien B. bufo Lower Gaaden Gaaden 17 Austria Herp85 BCAHF050- NHM Wien B. bufo Lower Waldviertel Litschau 17 Austria Herp86 BCAHF051- NHM Wien B. bufo Salzburg Obertrum Obertrum 17 Herp87 BCAHF132- NHM Wien R. arvalis Lower Heidenreichstein Brüneiteich, 19 Austria Thaures bei Heidenreichstein Herp88 BCAHF052- NHM Wien R. arvalis Carinthia Gösselsdorf Gösselsdorf 17 Herp89 BCAHF053- NHM Wien Z. vivipara Lower Heidenreichstein Thaures bei 17 Austria Heidenreichstein Herp90 BCAHF054- NHM Wien A. fragilis Vienna Weidlingau Weidlingau, 17 Wurzbachtal Herp91 BCAHF055- NHM Wien I. alpestris Styria Triebener Tauern Triebener Tauern 17 Herp92 BCAHF056- NHM Wien I. alpestris Carinthia Stranig Stranig 17 Herp93 BCAHF057- NHM Wien P. muralis Styria Rein Rein 17 Herp94 BCAHF058- NHM Wien L. agilis Carinthia Lavanttal Lavanttal 17 Herp95 BCAHF059- NHM Wien R. temporaria Carinthia Stranig Stranig 17 Herp96 BCAHF060- NHM Wien R. temporaria Styria Triebener Tauern Triebener Tauern 17 Herp98 BCAHF061- NHM Wien V. berus Carinthia Karnische Alpen Straniger Alm 17 Herp99 BCAHF062- NHM Wien A. fragilis Carinthia Rattendorf Rattendorf 17 Herp100 BCAHF063- NHM Wien R. temporaria Salzburg Stubachtal Stubachtal 17 Herp101 BCAHF064- NHM Wien Z. vivipara Carinthia Koralm Koralm 17 Herp102 BCAHF065- NHM Wien Z. vivipara Carinthia Karnische Alpen Straniger Alm 17 Herp103 BCAHF066- NHM Wien Z. vivipara Lower Schneeberg Schneeberg 17 Austria Herp104 BCAHF067- NHM Wien V. berus Lower Heidenreichstein Thaures, 17 Austria Brüneiteich Herp105 BCAHF068- NHM Wien R. temporaria Styria Wagna Sulmspitz 17 Herp106 BCAHF069- NHM Wien L. agilis Burgenland Illmitz Illmitz 17 Herp107 BCAHF070- NHM Wien P. muralis Lower Baden Baden 17 Austria

Herp108 BCAHF071- NHM Wien L. agilis Lower Lassingtal Lassingtal 17 Austria Herp109 BCAHF072- NHM Wien Z. vivipara Burgenland Neudegg Neudegg 17 Herp110 BCAHF073- NHM Wien R. arvalis Lower Heidenreichstein Brüneiteich, 17 Austria Thaures bei Heidenreichstein Herp111 BCAHF074- NHM Wien T. cristatus Upper Bad Zell Bad Zell 17 Austria Herp112 BCAHF075- NHM Wien P. muralis Lower Ötscher Ötscher 17 Austria Herp113 BCAHF076- NHM Wien A. fragilis Salzburg Wallersee Wallersee 17 Herp114 BCAHF077- NHM Wien Z. vivipara Upper Almsee Almsee 17 Austria Herp115 BCAHF078- NHM Wien L. agilis Upper Almsee Almsee 17 Austria Herp116 BCAHF079- NHM Wien A. fragilis Upper Almsee Almsee 17 Austria Herp117 BCAHF080- NHM Wien V. berus Salzburg Stubachtal Stubachtal 17 Herp118 BCAHF133- NHM Wien T. carnifex Styria Glanz/Weinstraße Glanz 74 19 Herp119 BCAHF134- NHM Wien R. arvalis Carinthia St. Veit St. Veit 19 Herp120 BCAHF135- NHM Wien A. fragilis Styria St. Josef St. Josef 19 Herp121 BCAHF081- NHM Wien A. fragilis Styria Graz Waltendorf 17 Herp122 BCAHF082- Biologiezentrum P. ridibundus Vienna Wien Zaubertal, 17 Linz Koppstraße 39 Herp124 BCAHF083- Biologiezentrum R. temporaria Upper Windischgarsten Dambach bei 17 Linz Austria Windischgarsten Herp126 BCAHF084- Biologiezentrum A. fragilis Upper Puchenau Am Steinbruch 24 17 Linz Austria Herp127 BCAHF085- Biologiezentrum V. berus Upper Liebenau Liebenau, Ruben 17 Linz Austria Herp128 BCAHF086- Biologiezentrum V. berus Upper Grünau/Almtal Almsee, 1 km SE 17 Linz Austria Jager Herp129 BCAHF087- Biologiezentrum N. natrix Upper Kleinraming Kleinkohlergraben 17 Linz Austria Herp130 BCAHF088- Biologiezentrum A. fragilis Upper Eberschwang Eberschwang 17 Linz Austria Herp131 BCAHF136- Biologiezentrum C. austriaca Upper Ranshofen Ranshofen, 19 Linz Austria Unterrothenbuch Herp132 BCAHF089- Biologiezentrum Z. longissimus Upper Eschelberg Eschelberg, 17 Linz Austria Rodltal Herp133 BCAHF090- Biologiezentrum N. natrix Upper Gutau Gutenbrunner 17 Linz Austria Leiten, Waldaisttal

Herp134 BCAHF091- Biologiezentrum S. salamandra Upper Windischgarsten Dambach bei 17 Linz Austria Windischgarsten Herp135 BCAHF137- NHM Wien A. fragilis Styria St. Josef St. Josef 19 Herp136 BCAHF092- NHM Wien Z. longissimus Burgenland Breitenbrunn Thenauriegel 17 Herp137 BCAHF138- NHM Wien N. natrix Styria St. Josef St. Josef 19 Herp138 BCAHF093- NHM Wien P. muralis Styria Wildon Buchberg 17 Herp139 BCAHF094- NHM Wien L. vulgaris Styria Graz Botanischer 17 Garten Graz Herp141 BCAHF095- Haus der Natur, Z. longissimus Tyrol Stumm Ortsgebiet Stumm Ortsgebiet 17 Salzburg Herp146 BCAHF139- Haus der Natur, A. fragilis Salzburg Haunsberg Nußdorf am 19 Salzburg Haunsberg Herp147 BCAHF096- Haus der Natur, Z. longissimus Salzburg Kuchl Kuchl, 17 Salzburg Georgenberg Herp148 BCAHF140- NHM Wien S. atra Styria Hochschwab Hochschwab 19 Herp149 BCAHF141- NHM Wien N. natrix Styria Gleinalm Gleinalm 19 Herp150 BCAHF097- NHM Wien N. natrix Styria Graz Graz 17 Herp151 BCAHF098- NHM Wien B. bufo Styria St. Josef St. Josef 17 Herp152 BCAHF099- NHM Wien P. esculenta Styria St. Josef St. Josef 17 Herp153 BCAHF100- NHM Wien P. esculenta Styria St. Josef St. Josef 17 Herp154 BCAHF142- NHM Wien P. esculenta Styria St. Josef St. Josef 19 Herp155 BCAHF101- NHM Wien B. variegata Styria St. Josef St. Josef 17 Herp157 BCAHF102- inatura, Dornbirn N. natrix Vorarlberg Bregenz Bregenz 17 Herp158 BCAHF103- inatura, Dornbirn N. natrix helvetica Vorarlberg Birken Birken 17 Herp159 BCAHF143- inatura, Dornbirn H. arborea Vorarlberg Bregenz Bregenz 19 Herp160 BCAHF104- inatura, Dornbirn P. esculenta Vorarlberg Bregenz Bregenz 17 Herp161 BCAHF105- inatura, Dornbirn I. alpestris Vorarlberg Dornbirn Dornbirn 17 Herp162 BCAHF106- NHM Wien N. natrix Styria Stainz Stainz 17 Herp163 BCAHF144- NHM Wien B. bufo Styria Glanz/Weinstraße Glanz an der 19 Weinstraße Herp164 BCAHF107- NHM Wien B. variegata Styria Glanz/Weinstraße Glanz an der 17 Weinstraße

Herp165 BCAHF145- NHM Wien S. salamandra Styria Graz Gösting 19 Herp166 BCAHF108- NHM Wien L. vulgaris Styria Kirchberg/Raab Kirchberg/Raab 17 Herp167 BCAHF109- NHM Wien L. vulgaris Styria Kirchberg/Raab Kirchberg/Raab 17 Herp168 BCAHF110- NHM Wien L. vulgaris Styria Kirchberg/Raab Kirchberg/Raab 17 Herp169 BCAHF111- NHM Wien T. carnifex Styria Grünau/Lassnitz Grünau/Lassnitz 17 Herp171 BCAHF112- NHM Wien R. dalmatina Styria Graz Gösting 17 Herp174 BCAHF113- NHM Wien N. natrix Styria Thal Thal 17 Herp175 BCAHF146- NHM Wien Z. longissimus Styria Thal Thal 19 Herp176 BCAHF114- NHM Wien N. tessellata Styria Gleinstätten/Sulm Gleinstätten an der 17 Sulm Herp177 BCAHF115- NHM Wien I. alpestris Styria Glanz/Weinstraße Glanz an der 17 Weinstraße Herp178 BCAHF116- NHM Wien I. alpestris Styria Glanz/Weinstraße Glanz an der 17 Weinstraße Herp179 BCAHF147- NHM Wien B. viridis Vienna Hirschstetten Badeteich 19 Hirschstetten Herp180 BCAHF148- NHM Wien P. fuscus Styria Kirchberg/Raab Kirchberg/Raab 19 Herp181 BCAHF117- inatura, Dornbirn N. natrix Vorarlberg Vorarlberg 17 Herp182 BCAHF149- inatura, Dornbirn I. alpestris Vorarlberg Vorarlberg 19 Herp183 BCAHF150- inatura, Dornbirn N. natrix Vorarlberg Vorarlberg 19 Herp185 BCAHF151- inatura, Dornbirn N. natrix Vorarlberg Vorarlberg 19 Herp186 BCAHF152- inatura, Dornbirn I. alpestris Vorarlberg Vorarlberg 19 Herp188 BCAHF153- Universalmuseum T. carnifex Styria Vorarlberg 19 Joanneum, Graz Herp189 BCAHF154- Universalmuseum T. carnifex Styria Vorarlberg 19 Joanneum, Graz Herp190 BCAHF155- Universalmuseum T. carnifex Styria Vorarlberg 19 Joanneum, Graz Herp191 BCAHF156- NHM Wien R. dalmatina Styria Graz Autal bei Graz 19 Herp192 BCAHF157- NHM Wien R. dalmatina/arbvalis Styria Bad Radkersburg Rabenhofteiche 19 Herp193 BCAHF158- NHM Wien H. arborea Styria Kirchberg/Raab Kirchberg/Raab 19 Herp194 BCAHF159- NHM Wien H. arborea Styria Kirchberg/Raab Kirchberg/Raab 19

Herp195 BCAHF160- NHM Wien S. salamandra Styria St. Josef 19 Herp196 BCAHF161- NHM Wien P. fuscus Styria Bad Radkersburg Rabenhofteiche 19 Herp197 BCAHF162- NHM Wien P. fuscus Styria Bad Radkersburg Rabenhofteiche 19 Herp198 BCAHF163- NHM Wien R. arvalis Styria Bad Radkersburg Rabenhofteiche 19 Herp199 BCAHF164- NHM Wien P. esculenta Styria Bad Radkersburg Rabenhofteiche 19 Herp200 BCAHF165- NHM Wien A. fragilis Styria Graz Weizbachweg 40 19 Herp202 BCAHF166- NHM Wien B. viridis Burgenland Illmitz 19 Herp203 BCAHF167- NHM Wien B. bufo Styria Leutschach/Weinstraße Remschnigg 28 19 Herp204 BCAHF168- NHM Wien Z. longissimus Styria Graz Baiernstraße 44 19 Herp205 BCAHF169- NHM Wien N. natrix Burgenland Illmitz Seebad 19 Herp206 BCAHF170- NHM Wien B. bufo Burgenland Bernstein Bienenhütte 19 Herp207 BCAHF171- NHM Wien P. fuscus Burgenland Illmitz Biologische 19 Station Herp208 BCAHF172- NHM Wien A. fragilis Lower Mödling Stadtwald 19 Austria Herp209 BCAHF173- NHM Wien R. temporaria Tyrol Ströden/Matrei Großbachalm 19 Herp210 BCAHF174- NHM Wien I. alpestris Styria Festenburg Festenburg 19 Herp211 BCAHF175- NHM Wien Z. vivipara Styria Festenburg Festenburg 19 Herp213 BCAHF176- NHM Wien Z. longissimus Lower Königstetten Peter Rosegger 19 Austria Straße Herp214 BCAHF177- NHM Wien Z. longissimus Lower Irenental Irenentalstraße 19 Austria Herp215 BCAHF178- NHM Wien L. horvathi Carinthia Doberbachtal 19 Herp216 BCAHF179- NHM Wien L. horvathi Tyrol Frauenbachtal Lavantergraben 19 Herp217 BCAHF180- NHM Wien L. viridis Carinthia Dellach/Drau Holztratten 28 19 Herp218 BCAHF181- NHM Wien P. Styria Neudau Neudauer Teiche 19 Herp221 BCAHF182- NHM Wien C. austriaca Lower Zwettl B36 nahe 19 Austria Ortsschild Herp222 BCAHF183- NHM Wien C. austriaca Burgenland Silberberg W-Straße, Oslip 19 Herp223 BCAHF184- NHM Wien C. austriaca Vienna Wien Alte Schanze 19

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Herp224 BCAHF185- NHM Wien H. arborea Styria Graz Rielteich 19 Herp225 BCAHF186- NHM Wien Z. longissimus Styria Glanz/Weinstraße Glanz 74 19 Herp226 BCAHF187- NHM Wien L. viridis Styria Glanz/Weinstraße Glanz 75 19 Herp227 BCAHF188- NHM Wien L. viridis Burgenland Breitenbrunn Thenauriegel 19 Herp228 BCAHF189- NHM Wien Z. longissimus Styria Bachsdorf Auenbachweg 21 19 Herp230 BCAHF190- NHM Wien N. natrix Styria Graz Graz 19 Herp234 BCAHF192- NHM Wien C. austriaca Styria Graz Schloßplatz 19 Gösting Herp235 BCAHF193- NHM Wien P. Styria Radkersburg Rabenhofteich, in 19 Kübelfalle Herp236 BCAHF194- NHM Wien I. alpestris Styria Dörfl an der Raab Dörfl 52, 19 Gartenteich Herp237 BCAHF195- NHM Wien I. alpestris Styria Dörfl an der Raab Dörfl 52, 19 Gartenteich Herp238 BCAHF196- NHM Wien L. vulgaris Styria Dörfl an der Raab Dörfl 52, 19 Gartenteich Herp239 BCAHF197- NHM Wien L. vulgaris Styria Dörfl an der Raab Dörfl 52, 19 Gartenteich

Supplementary table 2: Table containing all primer names, their nucleotide sequence and a reference to the original study used during the present research.

Primer name Sequence Source Chmf4 TYTCWACWAAYCAYAAAGAYATCGG Che et al. 2012 Chmr4 ACY TCR GGR TGR CCRAAR AAT CA Che et al. 2012 Rep-COI-F TNT TMT CAA CNA ACC ACA AAG A Nagy et al. 2012 Rep-COI-R ACT TCT GGR TGK CCA AAR AAT CA Nagy et al. 2012 dgLCO-1490 GGTCAACAAATCATAAAGAYATYGG Meyer 2003 dgHCO-2198 TAAACTTCAGGGTGACCAAARAAYCA Meyer 2003 COI-C01 TYTCWACWAAYCAYAAAGAYATTGG Che et al. 2012 COI-C02 AYTCAACAAATCATAAAGATATTGG Che et al. 2012 COI-C03 ACY TCY GGR TGA CCA AARAAY CA Che et al. 2012 COI-C04 ACY TCR GGR TGA CCA AAA AAT CA Che et al. 2012 C_VF1LFt1/ Ivanova C_VR1LRt1 et al. 2007

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LepF1_t1 GTAAAACGACGGCCAGTATTCAACCAATCATAAAGATATTGG Hebert et al. 2004 VF1_t1 GTAAAACGACGGCCAGTTCTCAACCAACCACAAAGACATTGG Ivanova et al. 2006 VF1d_t1 GTAAAACGACGGCCAGTTCTCAACCAACCACAARGAYATYGG Ivanova et al. 2006 VF1i_t1 GTAAAACGACGGCCAGTTCTCAACCAACCAIAAIGAIATIGG Ivanova et al. 2006 LepRI_t1 AGGAAACAGCTATGACTAAACTTCTGGATGTCCAAAAAATCA Hebert et al. 2004 VR1d_t1 CAGGAAACAGCTATGACTAGACTTCTGGGTGGCCRAARAAYCA Ivanova et al. 2006 VR1_t1 AGGAAACAGCTATGACTAGACTTCTGGGTGGCCAAAGAATCA Ward et al. 2005 VR1i_t1 AGGAAACAGCTATGACTAGACTTCTGGGTGICCIAAIAAICA Ivanova et al. 2006

References for Supplementary table 2:

Che J, Chen HM, Yang JX, Jin JQ, Jiang K, Yuan ZY, Murphy RW, Zhang YP. Universal COI primers for DNA barcoding amphibians. Mol. Ecol. Res. 2012;12(2): 247–258.

Hebert PDN, Penton EH, Burns JM, Janzen DH, Hallwachs W. Ten species in one: DNA barcoding reveals cryptic species in the neotropical skipper butterfly Astraptes fulgerator. Proc. Nati. Acad. Sci. U.S.A. 2004;101(41): 14812–14817.

Ivanova NV, Dewaard JR, Hebert PDN. An inexpensive, automation-friendly protocol for recovering high- quality DNA. Mol. Ecol. Notes. 2006;6(4): 998–1002.

Ivanova NV, Zemlak TS, Hanner RH, Hebert PDN. Universal primer cocktails for fish DNA barcoding. Mol. Ecol. Notes. 2007;7(4): 544–548.

Meyer CP. Molecular systematics of cowries (Gastropoda: Cypraeidae) and diversification patterns in the tropics. Biol. J. Linn. Soc. 2003;79(3): 401–459.

Nagy ZT, Sonet G, Glaw F, Vences M. First Large-Scale DNA Barcoding Assessment of Reptiles in the Biodiversity Hotspot of Madagascar, Based on Newly Designed COI Primers. PLoS ONE. 2012;7(3): e34506

Ward RD, Zemlak TS, Innes BH, Last PR, Hebert PDN. DNA barcoding Australia’s fish species. Phil. Trans. Royal Soc. B. 2005;360(1462): 1847–1857.

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ACKNOWLEDGEMENTS

We are very grateful to Werner Kammel, Werner Stangl, Frank Weihmann, Gernot Kunz, Johanna Gunczy, Christoph Hahn and Birgit Rotter and all staff of the Österreichische Bundesforste AG in Vienna and Lower Austria for their help collecting various samples. Furthermore, we like to thank Stefan Weigl from the Biozentrum Linz and Robert Lindner from the Haus der Natur in Salzburg as well as Georg Friebe and Christine Tschisner from INATURA Dornbirn for providing samples from their museum collections and Frank E. Zachos from the Natural History Museum in Vienna for countless coordinative efforts and revision of the manuscript. We kindly acknowledge Wolfgang Gessl (www.pisces.at) and Christoph Riegler for providing the pictures of Austrian amphibians and reptiles.

AUTHOR CONTRIBUTIONS

Conceptualization: Lukas Zangl, Silke Schweiger, Georg Gassner, Stephan Koblmüller.

Data curation: Lukas Zangl, Daniel Daill, Silke Schweiger, Georg Gassner, Stephan Koblmüller.

Formal analysis: Lukas Zangl, Silke Schweiger, Georg Gassner, Stephan Koblmüller.

Funding acquisition: Stephan Koblmüller.

Investigation: Lukas Zangl, Stephan Koblmüller.

Methodology: Lukas Zangl, Daniel Daill, Stephan Koblmüller.

Project administration: Lukas Zangl, Silke Schweiger, Stephan Koblmüller.

Supervision: Silke Schweiger, Stephan Koblmüller.

Validation: , Lukas Zangl, Georg Gassner, Stephan Koblmüller.

Visualization: Lukas Zangl.

Writing – original draft: Lukas Zangl, Daniel Daill.

Writing – review & editing: Lukas Zangl, Daniel Daill, Silke Schweiger, Georg Gassner, Stephan Koblmüller.

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REFERENCES

1. Murphy RW, Crawford AJ, Bauer AM, Che J, Donnellan SC, Fritz U, et al. Cold Code: the global initiative to DNA barcode amphibians and nonavian reptiles. Mol. Ecol. Res. 2013; 13(2): 161–167. 2. Chovanec A, Grillitsch B. Gefährdeter Lebensraum » Kleingewässer « - Amphibien als Bioindikatoren. Österreichs Fischerei. 1994; 47: 289–292. 3. Reichholf JH. Frösche als Bioindikatoren. Stapfia 47, zugleich Kataloge des O.Ö¨ Landesmuseum N.F. 1996; 107: 177–188. 4. Araújo MB. The coincidence of people and biodiversity in Europe. Glob Ecol. Biogeogr. 2003; 12: 5–12. 5. Beebee TJC, Griffiths RA. The amphibian decline crisis: A watershed for conservation biology? Biol. Conserv. 2005; 125: 271–285. 6. Schlaepfer MA, Hoover C, Dodd CK. Challenges in evaluating the impact of the trade in amphibians and reptiles on wild populations. BioScience. 2005; 55: 256–264. 7. Hawlitschek O, Morinière J, Dunz A, Franzen M, Rödder D, Glaw F, et al. Comprehensive DNA barcoding of the herpetofauna of Germany. Mol. Ecol. Res. 2015; 16: 242–253. 8. Heym A, Deichsel G, Hochkirch A, Veith M, Schulte U. Do introduced wall lizards (Podarcis muralis) cause niche shifts in a native sand lizard (Lacerta agilis) population? A case study from south-western Germany. Salamandra. 2013; 49: 97–104. 9. Hajibabaei M, Shokralla S, Zhou X, Singer GAC, Baird DJ. Environmental barcoding: a next- generation sequencing approach for biomonitoring applications using river benthos. PLoS ONE. 2011; 6: e17497. https://doi.org/10.1371/journal.pone.0017497 PMID: 21533287 10. Thomsen PF, Kielgast J, Iversen LL, Wiuf C, Rasmussen M, Gilbert MTP, et al. Monitoring endangered freshwater biodiversity using environmental DNA. Mol. Ecol. 2012; 21: 2565–2573. https://doi.org/10. 1111/j.1365-294X.2011.05418.x PMID: 22151771 11. Franklinos LH, Lorch JM, Bohuski E, Fernandez JRR, Wright ON, Fitzpatrick L, et al. Emerging fungal pathogen Ophidiomyces ophiodiicola in wild European snakes. Sci. Rep. 2017; 7(1): 3844. https://doi. org/10.1038/s41598-017-03352-1 PMID: 28630406 12. Stuart SN, Chanson JS, Cox NA, Young BE, Rodrigues ASL, Fischman DL, et al. Status and trends of amphibian declines and extinctions worldwide. Science (New York, N.Y.). 2004; 306(5702): 1783– 1786. 13. Vitt LJ, Caldwell JP. Herpetology: An Introductory Biology of Amphibians and Reptiles. San Diego: Academic Press; 2014. pp. 757. 14. Araújo MB, Thuiller W, Pearson RG. Climate warming and the decline of amphibians and reptiles in Europe. J. Biogeogr. 2005; 33: 1712–1728. 15. Köhler J, Vieites DR, Bonett RM, García FH, Glaw F, Steinke D, et al. New amphibians and global conservation: a boost in species discoveries in a highly endangered vertebrate group. BioScience. 2005; 55(8): 693–696. 16. Ceballos G, Ehrlich PR, Dirzo R. Biological annihilation via the ongoing sixth mass extinction signaled by vertebrate population losses and declines. Proc. Nati. Acad. Sci. 2017; 114(30): https://doi.org/10. 1073/pnas.1704949114 17. Cox NA, Temple HJ. European Red List of Reptiles. Luxembourg: Office for Official Publications of the European Communities. 2009. 18. Martel A, Blooi M, Adriaensen C, Van Rooij P, Beukema W, Fisher MC, et al. Recent introduction of a chytrid fungus endangers Western Palearctic salamanders. Science. 2014; 346: 630–631. https://doi. org/10.1126/science.1258268 PMID: 25359973 19. Wake SD, Vredenurg VT. Are we in the midst of the sixth mass extinction? A view from the amphibians. Proc. Nat. Acad. Sci. U.S.A. 2008; 105: 11466–11473. 104

20. Sinervo B, Mendez-De-La-Cruz F, Miles DB, Heulin B, Bastiaans E, Villagrán-Santa Cruz M, et al. Erosion of lizard diversity by climate change and altered thermal niches. Science. 2010; 328(5980): 894– 899. https://doi.org/10.1126/science.1184695 PMID: 20466932 21. Böhm M, Collen B, Baillie JE, Bowles P, Chanson J, Cox N, et al. The conservation status of the world’s reptiles. Biol. Conserv. 2013; 157: 372–385. 22. The Council of the European Communities (1992) Council Directive 92/43/EEC of 21 May 1992 on the conservation of natural habitats and of wild fauna and flora (http://eur-lex.europa.eu/legal- content/EN/ TXT/?uri=CELEX:31992L0043). 23. Hebert PDN, Cywinska A, Ball SL, deWaard JR. Biological identifications through DNA barcodes. Proc. Royal Soc. B. 2004; 270: 313–321. 24. Perl RB, Nagy ZT, Sonet G, Glaw F, Wollenberg KC, Vences M. DNA barcoding Madagascar’s amphibian fauna. Amphibia-Reptilia. 2014; 35(2): 197–206. 25. Vences M, Nagy ZT, Sonet G, Verheyen E. DNA barcoding amphibians and reptiles. DNA Barcodes. Humana Press, Totowa, NJ. 2012: 79–107. 26. Smith MA, Poyarkov NA Jr, Hebert PD. DNA barcoding: CO1 DNA barcoding amphibians: take the chance, meet the challenge. Mol. Ecol. Res. 2008; 8(2): 235–246. 27. Vasconcelos R, Montero-Mendieta S, Simó-Riudalbas M, Sindaco R, Santos X, Fasola M, et al. Unex- pectedly high levels of cryptic diversity uncovered by a complete DNA barcoding of reptiles of the Socotra Archipelago. PLoS One. 2016; 11(3): https://doi.org/10.1371/journal.pone.0149985 PMID: 26930572 28. Chambers EA, Hebert PD. Assessing DNA barcodes for species identification in North American reptiles and amphibians in natural history collections. Plos One. 2016; 11(4): https://doi.org/10.1371/ journal.pone.0154363 PMID: 27116180 29. Ratnasingham S, Hebert PDN. BOLD: The Barcode of Life Data System (www.barcodinglife.org). Mol. Ecol. Notes. 2007; 7: 355–364. https://doi.org/10.1111/j.1471-8286.2007.01678.x PMID: 18784790 30. Dejean T, Valentini A, Miquel C, Taberlet P, Bellemain E, Miaud C. Improved detection of an alien invasive species through environmental DNA barcoding: the example of the American bullfrog Lithobates catesbeianus. J. Appl. Ecol. 2012; 49(4): 953–959. 31. Hawlitschek O, Nagy ZT, Berger J, Glaw F. Reliable DNA barcoding performance proved for species and island populations of Comoran squamate reptiles. PLoS One. 2013; 8(9): e73368. https://doi.org/ 10.1371/journal.pone.0073368 PMID: 24069192 32. Cabela A, Grillitsch H, Tiedemann F. Atlas zur Verbreitung und Ökologie der Amphibien und Reptilien in Österreich: Auswertung der Herpetofaunistischen Datenbank der Herpetologischen Sammlung des Naturhistorischen Museums in Wien. 2001: 1–880. 33. Gollmann G. Rote Liste der in Österreich gefährdeten Lurche (Amphibia) und Kriechtiere (Reptilia). In: BUNDESMINISTERIUM FU¨ R LAND- UND FORSTWIRTSCHAFT (Hrsg.): Rote Listen gefährdeter Tiere Österreichs, Teil 2: Kriechtiere, Lurche, Fische, Nachtfalter, Weichtiere. Böhlau Verlag, Wien- Köln-Weimar; 2007. P. 515. 34. Grabher M, Niederer W. Der Fadenmolch Lissotriton helveticus (Razoumowsky, 1789), eine neue Amphibienart für Österreich. UMG Berichte 7. 2011. Retrieved from http://www.umg.at/umgberichte/ UMGberichte7_Fadenmolch_2011.pdf 35. Kindler C, Chèvre M, Ursenbacher S, Böhme W, Hille A, Jablonski D, et al. Hybridization patterns in two contact zones of grass snakes reveal a new Central European snake species. Sci. Rep. 2017; 7(1): 7378. https://doi.org/10.1038/s41598-017-07847-9 PMID: 28785033 36. Plötner J. Möglichkeiten und Grenzen morphologischer Methoden zur Artbestimmung bei europäischen Wasserfröschen (Pelophylax esculentus-Komplex). Zeitschrift für Feldherpetologie. 2010; 17: 129– 146.

105

37. Speybroeck J, Beukema W, Bok B, Van Der Voort J. Field Guide to the Amphibians & Reptiles of Britain and Europe. Bloomsbury Natural History. 2016. pp. 432. 38. Richlen ML, Barber PH. A technique for the rapid extraction of microalgal DNA from single live and preserved cells. Mol. Ecol. Notes. 2005; 5: 688–691. 39. Koblmüller S, Salzburger W, Obermüller B, Eigner E, Sturmbauer C, Sefc KM. Separated by sand, fused by dropping water: habitat barriers and fluctuating water levels steer the evolution of rock- dwelling cichlid populations. Mol. Ecol. 2011; 20: 2272–2290. https://doi.org/10.1111/j.1365- 294X.2011.05088.x PMID: 21518059 40. Duftner N, Koblmüller S & Sturmbauer C. Evolutionary relationships of the Limnochromini, a tribe of benthic deepwater cichlid fish endemic to Lake Tanganyika, East Africa. J. Mol. Evol. 2005; 60: 277– 289. https://doi.org/10.1007/s00239-004-0017-8 PMID: 15871039 41. Tamura K, Stecher G, Peterson D, Filipski A, Kumar S. MEGA6: Molecular Evolutionary Genetics Anal- ysis version 6.0. Mol. Biol. Evol. 2013; 30: 2275–2279. 42. 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. https://doi.org/10.1007/bf01731581 PMID: 7463489 43. Bergsten J, Englund M, Erricson P. A DNA key to all Swedish vertebrates. Forthcoming. 44. Cesaroni D, De Felici S, Riccarducci G, Ciambotta M, Ventura A, Bianchi E. Sbordoni V. DNA- Barcodes of the animal species occurring in Italy under the European ’Habitats Directive’ (92/43/EEC): a database for the Italian National Biodiversity Network. Forthcoming. 45. Prusak B, Grzybowski G. National Network of DNA Bank of Plants, Fungi and Animals. Forthcoming. 46. Stefani F, Gentilli A, Sacchi R and Galli P. Multiple refugia within the Italian peninsula for the common frog Rana temporaria (Anura, Ranidae). Forthcoming. 47. Hofman S, Pabijan M, Dziewulska-Szwajkowska D, Szymura JM. Mitochondrial genome organization and divergence in hybridizing central European waterfrogs of the Pelophylax esculentus complex (Anura, Ranidae). Gene. 2012; 491(1): 71–80. https://doi.org/10.1016/j.gene.2011.08.004 PMID: 21951340 48. Puillandre N, Lambert A, Brouillet S, Achaz G. ABGD, Automatic Barcode Gap Discovery for primary species delimitation. Mol. Ecol. 2012; 21: 1864–1877. https://doi.org/10.1111/j.1365- 294X.2011.05239. x PMID: 21883587 49. Maletzky A, Mikulíček P, Franzen M, Goldschmid A, Gruber HJ, Horák A, et al. Hybridization and introgression between two species of crested newts (Triturus cristatus and T. carnifex) along contact zones in Germany and Austria: morphological and molecular data. Herpetol. J. 2008; 18(1): 1–15. 50. Mikulicek P, Kautman J, Zavadil V, Pialek J. Natural hybridization and limited introgression between the crested newts Triturus cristatus and T. dobrogicus (Caudata: Salamandridae) in Slovakia. Biologia (Suppl. 15). 2004; 59: 211–218. 51. Meilink WR, Arntzen JW, van Delft JJ, Wielstra B. Genetic pollution of a threatened native crested newt species through hybridization with an invasive congener in the Netherlands. Biol. Conserv. 2015; 184: 145–153. 52. Patrelle C, Ohst T, Picard D, Pagano A, Sourice S, Dallay MG, et al. A new PCR-RFLP-based method for an easier systematic affiliation of European water frogs. Mol. Ecol. Res. 2011; 11(1): 200–205. 53. Dufresnes C, Di Santo L, Leuenberger J, Schuerch J, Mazepa G, Grandjean N, et al. Cryptic invasion of Italian pool frogs (Pelophylax bergeri) across Western Europe unraveled by multilocus phylogeography. Biol. Invasions. 2017; 19(5): 1407–1420. 54. Dubey S, Leuenberger J, Perrin N. Multiple origins of invasive and ‘native’water frogs (Pelophylax spp.) in Switzerland. Biol. J. Linn. Soc. 2014; 112(3): 442–449.

106

55. Hauswaldt JS, Ho¨ er M, Ogielska M, Christiansen DG, Dziewulska-Szwajkowska D, Czernicka E, et al. A simplified molecular method for distinguishing among species and ploidy levels in European water frogs (Pelophylax). Mol. Ecol. Res. 2012; 12(5): 797–805. 56. Armstrong KF, Ball SL. DNA barcodes for biosecurity: invasive species identification. Philos. Trans. Royal Soc. B. 2005; 360(1462): 1813–1823. 57. Bálint M, Domisch S, Engelhardt CHM, Haase P, Lehrian S, Sauer J, et al. Cryptic biodiversity loss linked to global climate change. Nat. Clim. Change. 2011; 1(6), 313. 58. Horreo JL, Pelaez ML, Suárez T, Breedveld MC, Heulin B, Surget-Groba Y, et al. Phylogeography, evolutionary history and effects of glaciations in a species (Zootoca vivipara) inhabiting multiple biogeographic regions. J. Biogeogr. 2018; 45(7): 1616–1627. 59. Kalyabina-Hauf S, Schweiger S, Joger U, Mayer W, Orlov N, Wink M. Phylogeny and systematics of adders (Vipera berus complex). Mertensiella, Rheinbach; 2004; 15: 7–16. 60. Ursenbacher S, Carlsson M, Helfer V, Tegelstrom H, Fumagalli L. Phylogeography and Pleistocene refugia of the adder (Vipera berus) as inferred from mitochondrial DNA sequence data. Mol. Ecol. 2006; 15: 3425–3437. https://doi.org/10.1111/j.1365-294X.2006.03031.x PMID: 16968280 61. Garcia-Porta J, Litvinchuk SN, Crochet PA, Romano A, Geniez PH, Lo-Valvo M, et al. Molecular phylogenetics and historical biogeography of the west-palearctic common toads (Bufo bufo species complex). Mol. Phylogenet. Evol. 2012; 63(1): 113–130. https://doi.org/10.1016/j.ympev.2011.12.019 PMID: 22214922 62. Babik W, Branicki W, Sandera M, Litvinchuk S, Borkin LJ, Irwin JT, et al. Mitochondrial phylogeography of the moor frog, Rana arvalis. Mol. Ecol. 2004; 13(6): 1469–1480. https://doi.org/10.1111/j.1365-294X. 2004.02157.x PMID: 15140091 63. Steinfartz S, Veith M, Tautz D. Mitochondrial sequence analysis of Salamandra taxa suggests old splits of major lineages and postglacial recolonizations of Central Europe from distinct source populations of Salamandra salamandra. Mol. Ecol. 2000; 9: 397–410. https://doi.org/10.1046/j.1365- 294x.2000. 00870.x PMID: 10736043 64. Sotiropoulos K, Eleftherakos K, Dzˇukić G, Kalezić ML, Legakis A, Polymeni RM. Phylogeny and biogeography of the alpine newt Mesotriton alpestris (Salamandridae, Caudata), inferred from mtDNA sequences. Mol. Phylogenet. Evol. 2007; 45(1): 211–226. https://doi.org/10.1016/j.ympev.2007.03.012 PMID: 17467298 65. Schulte U, Veith M, Hochkirch A. Rapid genetic assimilation of native wall lizard populations (Podarcis muralis) through extensive hybridization with introduced lineages. Mol. Ecol. 2012; 21(17): 4313–4326. https://doi.org/10.1111/j.1365-294X.2012.05693.x PMID: 22765844 66. Teacher AGF, Garner TWJ, Nichols RA. European phylogeography of the common frog (Rana temporaria): routes of postglacial colonization into the British Isles, and evidence for an Irish glacial refugium. Heredity. 2009; 102(5): 490. https://doi.org/10.1038/hdy.2008.133 PMID: 19156165 67. Macgregor H, Sessions SK, Arntzen JW. An integrative analysis of phylogenetic relationships among newts of the genus Triturus (family Salamandridae), using comparative biochemistry, cytogenetics and reproductive interactions. J. Evol. Biol. 1990; 3: 329–373. 68. Mikul´ıček P, Hora´k A, Zavadil V, Kautman J, Piálek J. Hybridization between three crested newt species (Triturus cristatus superspecies) in the Czech Republic and Slovakia: comparison of nuclear markers and mitochondrial DNA. Folia Zoologica. 2012; 61(3–4): 202–219. 69. Maletzky A, Hattinger A, Moosbrugger K, Schweiger S. The Common Wall Lizard Podarcis muralis (LAURENTI, 1786), new to the province of Salzburg (Austria). Origin of a paraneozoon. Herpetozoa. 2011; 23: 88–90. 70. Schweiger S, Grillitsch H, Hill J, Mayer W. Die Mauereidechse, Podarcis muralis (LAURENTI, 1768) in Österreich: Phylogeographie, Verbreitung, Lebensräume und Schutz. - In: Laufer H, Schulte U. (2015): Verbreitung, Biologie und Schutz der Mauereidechse Podarcis muralis (LAURENTI, 1768). Mertensiella, Mannheim. 2015; 22: 44–55.

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71. Guicking D, Lawson R, Joger U, Wink M. Evolution and phylogeny of the genus Natrix (Serpentes: Colubridae). Biol. J. Linn. Soc. 2006; 87(1): 127–143. 72. Glaw F, Franzen M, Oefele M et al. Genetischer Erstnachweis, Verbreitung und südalpine Herkunft der Barrenringelnatter (Natrix helvetica spp.) in Bayern.–Zeitschrift für Feldherpetologie.2019; 26(1):1–20.

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Chapter 5

Oriental or not: First record of an alien weatherfish (Misgurnus) species in Austria verified by molecular data

Zangl L, Jung M, Gessl W, Koblmüller S, Ratschan C (2020) Oriental or not: First record of an alien weatherfish (Misgurnus) species in Austria verified by molecular data. BioInvasions Records 9(2): 375–383, https://doi.org/10.3391/bir.2020.9.2.23

LUKAS ZANGL1,2, MICHAEL JUNG3, WOLFGANG GESSL1, STEPHAN KOBLMÜLLER1, CLEMENS RATSCHAN3

1University of Graz, Institute of Biology, Universitätsplatz 2, 8010 Graz, Austria

2Universalmuseum Joanneum, Studienzentrum Naturkunde, Weinzöttlstraße 16, 8045 Graz, Austria

3ezb–TB Zauner GmbH, Marktstraße 35, 4090 Engelhartszell, Austria

ABSTRACT

Weatherfishes of the genus Misgurnus are natively distributed across large parts of Eurasia. Since the end of the 20th century, two alien weatherfish species, the oriental weatherfish, Misgurnus anguillicaudatus, and the large-scaled loach, Paramisgurnus dabryanus, have been reported from Europe. Here, we provide a first record of alien Misgurnus for Austria (Inn river). Based on morphology and DNA barcoding in combination with sequences of the nuclear RAG1 gene we found that this alien Austrian weatherfish is neither M. anguillicaudatus nor P. dabryanus, but Misgurnus bipartitus, the northern weatherfish. Fish from further upstream the Inn in Germany, previously identified as M. anguillicaudatus, share their COI haplotype with the Austrian samples and other M. bipartitus, suggesting a misidentification of these German fishes and raising

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alarm that alien Misgurnus might be already present across large parts of the middle and lower Inn drainage.

KEY WORDS: DNA barcoding, invasive species, COI, RAG1, Misgurnus anguillicaudatus, Misgurnus bipartitus

INTRODUCTION

Throughout the world, there is an increasing number of alien species, sometimes with negative effects on indigenous taxa (Seebens et al. 2017). This is also true for weatherfishes of the family Cobitidae. Eschmeyer’s catalogue of fishes lists seven species of Misgurnus and one species of Paramisgurnus, mostly known from East Asia (Table 1; Fricke et al. 2019). Misgurnus fossilis (Linnaeus, 1758) is the only weatherfish native to Europe. It is a species of special national and European conservation concern (Council of the European Union 1992, listed in Annex II of the European Habitat Directive) and mainly threatened by the loss of suitable habitats (Belle et al. 2017). Negative impacts on European weatherfish populations may further arise by the spread of allochthonous weatherfish due to potential interspecific competition, but also by potential hybridization. Hybridization has at least been documented in natural populations of P. dabryanus and M. anguillicaudatus (Stoeckle et al. 2019 and authors therein).

Table 1. List of species in the genera Misgurnus and Paramisgurnus and their distribution ranges.

Species Distribution Misgurnus anguillicaudatus Widely distributed in the middle and lower reaches of the Yangtze river Basin, East Asia M. mohoity Amur River Basin in northeast China, Mongolia and the M. bipartitus north of the Yellow River in China M. buphoensis Korea M. fossilis Europe and Eastern Asia M. multimaculatus Vietnam M. nikolskyi East Asia (Amur River drainage) M. tonkinensis Vietnam Paramisgurnus dabryanus China (Tijanjin

Hence, identifying potentially invasive alien weatherfishes and taking actions against their further spread might be crucial to the long-term survival of the indigenous species. 110

Initially farmed for the food industry in Asia (Belle et al. 2017; Yi et al. 2017b), the aquarium trade of ornamental pond fishes fueled the global spread and concordantly reports of alien weatherfish have been ever increasing (van Kessel et al. 2013). Today, populations of Asian weatherfishes are known from Australia, North America, South America and Asia outside of their natural range (Belle et al. 2017). From Europe, Misgurnus anguillicaudatus, the oriental weatherfish has been reported from Italy (Razzetti et al. 2001), Spain (Franch et al. 2008), Germany (Freyhof and Korte 2005; Belle et al. 2017) and the Netherlands (van Kessel et al. 2013). Furthermore, Marchesi (2010) and Stoeckle et al. (2019) have confirmed Paramisgurnus dabryanus, from Switzerland and Germany, respectively.

In this study we report the first record of an alien Misgurnus species in Austria. Based on morphology, DNA barcodes (part of the mitochondrial COI gene) and sequences of the nuclear RAG1 gene we aim to identify it to the species level and relate it to recent findings of alien weatherfish species in Germany. Furthermore, we discuss difficulties in the correct species identification of alien weatherfish species, even when DNA sequence data are available, as systematics and taxonomy, especially of the genera Misgurnus and Paramisgurnus, are still not fully resolved.

MATERIAL AND METHODS

On October 18th 2018 two strange cobitid individuals (both with a total length of 125 mm, Figure 1A, B) were caught in the central area of the impoundment of the Egglfing- Obernberg power plant (48.301614°N; 13.282020°E, Upper Austria, Figure 1C) at the river Inn during an electrofishing survey. Specimens from the river Inn were determined morphologically following identification keys published by Kottelat and Freyhof (2007) and Vasil’eva (2001, and a short Chinese key therein), sampled (finclips put in 99% EtOH), fixed in formalin and deposited at the Biologiezentrum Linz (Museum IDs 2019/166-167). Extraction of genomic DNA employed a rapid Chelex protocol (Richlen and Barber 2005) and PCR and sequencing followed Koblmüller et al. (2011) and Duftner et al. (2005), respectively, using the primer cocktail C_FishF1t1 and C_FishR1t1 (Ivanova et al. 2007) for COI and RAG1-2533F (Lopez et al. 2004) and RAG1-3261 (Li and Ortí 2007) for RAG1. Sequences were visualized on a 3130xl capillary sequencer (Applied Biosystems). Sequences were edited and aligned by eye in MEGA 6.06 (Tamura

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et al. 2013). All newly generated sequences are available on GenBank under the accession numbers MT108218–MT108221. Additional COI sequences (the same set as compiled by Belle et al. 2017, as well as sequences of M. mohoity, the Amur weatherfish and M. bipartitus from Yi et al. 2016) and RAG1 sequences were downloaded from GenBank (Table 2). Minimum inter- as well as maximum intraspecific genetic distances were calculated using SPIDER (Brown et al. 2012). Maximum likelihood (ML) and Bayesian Inference (BI) analyses were performed for both COI and RAG1 data using PhyML 3.0 (Guindon et al. 2010) and MrBayes 3.2 (Ronquist and Huelsenbeck 2003), respectively, employing the best fitting models of evolution as suggested by the Smart Model Selection tool in PhyML (Lefort et al. 2017).

Figure 1. A + B) Pictures of the two Misgurnus bipartitus caught in the Inn impoundment lake close to the German border. C) Bird’s eye view picture of the impoundment lake at the Egglfing-Obernberg power plant and a map of Central Europe showing the sampling site close to the German border.

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Table 2. Accession numbers of previously published sequences downloaded from GenBank and included in this study. * denote M. bipartitus sequences labelled as M. anguillicaudatus.

Sequence ID, Reference Species COI RAG1 KX865083*, KX865084*, KX865082* M. (Belle et al. 2017); KX224173.1; KM610758.1 EF056344.1 (Šlechtová et al. anguillicaudatus (Chen et al. 2015); 2007) KJ553886.1 (Geiger et al. 2014) KX505271, KX505247, KX505245, KX505243, KX505240, KX505225, KX505236, KX505235, M. bipartitus - KX505220 (Yi et al. 2016) KM286765.1, KM286763.1, EF056339.1 (Šlechtová et al. M. fossilis KM286764.1 (Knebelsberger et al. 2007) 2015) JN858807.1, JN858809.1, KX505204, KX505198, KX505176, KX505175, JN858808.1, JN858810.1 KX505180, KX505191, KX505171, KX505170, M. mohoity (Perdices et al. 2012); KX505200 (Yi EF056392.1 (Šlechtová et al. et al. 2016) 2007) EF508660.1 (Šlechtová et al. Misgurnus sp. 2 - 2008) KM286530.1 (Knebelsberger et al. 2015); C. taenia - KJ128459.1, KJ128460.1 Danio rerio NC_002333.2 (Broughton et al. 2001) - EF508670.1 (Šlechtová et al. Pangio pangia KX355473.1 2008) JN177188.1 (Liu et al. 2012); KM610791.1, KM610790.1, KM610792.1 (Chen EF508675.1, EF508676.1 P. dabryanus et al. 2015) (Šlechtová et al. 2008); HQ454347.1

RESULTS

Based on characters given in the key by Vasil’eva (2001 and the translated Chinese key therein) (caudal peduncle depth 2.4–2.5 times in caudal peduncle length vs. 1.3–1.8 times in M. anguillicaudatus, maximum body depth 8.2–8.6 times in SL vs. < 7.5 times in M. anguillicaudatus) our specimens from the Inn were identified as M. bipartitus. Phylogenetic analysis of 612 bp of the COI gene (Figure 2A; Supplementary material Figure S1) also grouped the alien Austrian Misgurnus with M. bipartitus. Interestingly, the Austrian fish and M. bipartitus share their haplotype with German fish previously identified as M. anguillicaudatus (KX865082, KX865083, KX865084; Belle et al. 2017) collected 145 km further upstream in an oxbow of the Inn in Germany. Consistent with previous studies (Perdices et al. 2012; Yi et al. 2016), the genus Misgurnus resulted as paraphyletic. Phylogenetic relationships based on 658 bp of the nuclear RAG1 gene (Figure 2B, Figure S2) mirrored the results of the mitochondrial COI data, although node

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support was generally lower in the nuclear trees. In the RAG1 tree, the Austrian fishes grouped with a Misgurnus sp. 2 from Korea and a single M. mohoity from Russia. All other M. mohoity from their native range form a distinct clade, sister to that including the Austrian samples, albeit with limited bootstrap support. It is noteworthy though, that no RAG1 sequences of alleged M. bipartitus (see below) were available to be included in our analysis. The maximum intraspecific genetic distance, based on uncorrected p- distances of the COI gene, varied from 0% within M. bipartitus to 3.6% within M. mohoity. The minimum interspecific distance was 9% between M. anguillicaudatus and M. bipartitus.

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Figure 2. Maximum Likelihood (ML) phylograms based on (A) 612 bp of the mitochondrial COI gene and (B) 658 bp of the nuclear RAG1 gene. Node labels indicate bootstrap support values (1000 bootstrap replicates; only values > 85 are shown). Samples in bold were obtained and sequenced in this study. Numbers in parentheses represent GenBank accession numbers.

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DISCUSSION

In this study we present the first record of an alien Misgurnus species for Austria. Phylogenetic analysis of the COI gene clearly clustered the two specimens caught in the Inn impoundment with other previously published COI sequences of M. bipartitus (Yi et al. 2016, 2017a). This particular clade also contains three sequences of specimens likely misidentified as M. anguillicaudatus from further upstream the Inn in Germany (Belle et al. 2017), which share the exact same haplotype with the Austrian samples and all M. bipartitus included in our dataset. In theory, ancient hybridization could explain this finding, as hybridization is known to occur between Misgurnus species as well as between Misgurnus and Paramisgurnus (van Kessel et al. 2013). On the other hand, though, Belle et al. (2017) did not include any sequence of M. mohoity and M. bipartitus. Unfortunately, the systematic background of the genera Misgurnus and Paramisgurnus is still not fully resolved. Perdices et al. (2012), for example, suggested synonymy of M. bipartitus and M. mohoity based on DNA sequence data of the mitochondrial cytochrome b (cyt b) and the nuclear recombination activating gene 1 (RAG1) genes, a view concordant with Vasil’eva’s (2001) morphological study. Yi et al. (2016, 2017a, b) and Li et al. (2010), on the other hand, granted species level to M. bipartitus as well, based on clear divergence in DNA sequence data of the mitochondrial cytochrome oxidase subunit 1 (COI) gene and morphology. Here, we follow Yi et al. (2016) and treat M. bipartitus as a valid and distinct species. Thus, based on our data we strongly argue that the three specimens found in the German stretches of the Inn river (Belle et al. 2017) and the two specimens found on the Austrian side do belong to Misgurnus bipartitus, the northern weatherfish and so might several other findings of alien loaches in Germany determined as M. anguillicaudatus down to 46 km upstream of the recent finding (unpublished reports) be as well. These findings are also corroborated by nuclear RAG1 data, which group the Austrian samples not with M. anguillicaudatus, but with a distinct lineage within M. mohoity (but note, no RAG1 data are available for morphologically identified M. bipartitus).

The close genetic relationship of German and Austrian alien Misgurnus from the Inn, however, further indicates a downstream range expansion of at least 145 km, which is also supported by several more recent catches of alien Misgurnus along the German stretch of the Inn downstream the site of first record by Belle et al. (2017). Thus, alien Misgurnus seem to use the main stem of the Alpine river Inn with low water temperatures 116

and high turbidity at least as a dispersal corridor. Systematic uncertainties as well as scarce available ecological data on these species further complicate the prediction of the invasive potential, prime habitats and possible conflicts with native biota. Despite the above-mentioned challenges, we agree with Belle et al. (2017) that DNA barcoding, and even more so eDNA metabarcoding or the application of diagnostic primers for detecting alien species in eDNA samples (e.g., Rees et al. 2014; Thalinger et al. 2019) helps to detect and identify non-native Misgurnus/Paramisgurnus species, which might be a threat to the autochthonous Misgurnus species (Franch et al. 2008). Confronted with a new alien species, facing potential interspecific competition and/or genetic dilution through hybridization (Stoeckle et al. 2019), protection and conservation of M. fossilis should be enforced. Furthermore, appropriate regulations on the trade of ornamental fish should be considered in order to reduce the risk of unintentional spread of alien species that could become invasive and threaten the native biodiversity (Franch et al. 2008).

ACKNOWLEDGEMENTS

We thank the “Verbund” for commissioning the fish census survey of the impoundment lake of the Inn power plant. Our gratitude also goes to Franz Seiler for sharing information and pictures of the specimens from Rosenheim, as well as to Michael Effenberger, Johannes Öhm, Josef Wanzenböck, Jörg Freyhof and Ekaterina Vasil’eva for sharing information and pictures and providing critical comments. Furthermore, we are grateful to the reviewers for their constructive comments and suggestions.

FUNDING DECLARATION

Financial support was provided by the Austrian Federal Ministry of Science, Research and Economy in the frame of an ABOL associated project within the framework of the “Hochschulraum-Strukturmittel” Funds. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

REFERENCES

Belle CC, Stoeckle BC, Cerwenka AF, Kuehn R, Mueller M, Pander J, Geist J (2017) Genetic species identification in weatherfish and first molecular confirmation of Oriental Weatherfish Misgurnus 117

anguillicaudatus (Cantor, 1842) in Central Europe. Knowledge and Management of Aquatic Ecosystems 418: 31, https://doi.org/10.1051/kmae/2017025 Broughton RE, Milam JE, Roe BA (2001) The complete sequence of the zebrafish (Danio rerio) mitochondrial genome and evolutionary patterns in vertebrate mitochondrial DNA. Genome Research 11: 1958–1967, https://doi.org/10.1101/gr.156801 Brown SDJ, Collins RA, Boyer S, Lefort MC, Malumbres-Olarte J, Vink CJ, Cruickshank RH (2012) SPIDER: an R package for the analysis of species identity and evolution, with particular reference to DNA barcoding. Molecular Ecology Resources 12: 562–565, https://doi.org/10.1111/j.1755-0998.2011.03108.x Chen W, Ma X, Shen Y, Mao Y, He S (2015) The fish diversity in the upper reaches of the Salween River, Nujiang River, revealed by DNA barcoding. Scientific Reports 5: 17437, https://doi.org/10.1038/srep17437 Council of the European Union (1992) Directive 92/43/ EEC of the European Parliament and the Council of 21st May 1992 on the conservation of natural habitats and of wild fauna and flora. Official Journal of the European Communities L206, 750 pp Duftner N, Koblmüller S, Sturmbauer C (2005) Evolutionary relationships of the Limnochromini, a tribe of benthic deepwater cichlid fish endemic to Lake Tanganyika, East Africa. Journal of Molecular Evolution 60: 277–289, https://doi.org/10.1007/s00239-004-0017-8 Franch N, Clavero M, Garrido M, Gaya N, López V, Pou-Rovira Q, Queral JM (2008) On the establishment and range expansion of oriental weatherfish (Misgurnus anguillicaudatus) in NE Iberian Peninsula. Biological Invasions 10: 1327–1331, https://doi.org/10.1007/s10530- 007-9207-9 Freyhof J, Korte E (2005) The first record of Misgurnus anguillicaudatus in Germany. Journal of Fish Biology 66: 568–571, https://doi.org/10.1111/j.0022-1112.2005.00606.x Fricke R, Eschmeyer WN, van der Laan R (eds) (2019) Eschmeyer’s catalog of fishes: genera, species, references. http://researcharchive.calacademy.org/research/ichthyology/catalog/fishcatmain.asp (accessed 02 July 2019) Geiger MF, Herder F, Monaghan MT, Almada V, Barbieri R, Bariche M, Berrebi P, Bohlen J, Casal‐Lopez M, Delmastro GB, Denys GPJ, Dettai A, Doadrio I, Kalogianni E, Kärst H, Kottelat M, Kovačić M, Laporte M, Lorenzoni M, Marčić Z, Özuluğ M, Perdices A, Perea S, Persat H, Porcelotti S, Puzzi C, Robalo J, Šanda R, Schneider M, Šlechtová V, Stoumboudi M, Walter S, Freyhof J (2014) Spatial heterogeneity in the Mediterranean Biodiversity Hotspot affects barcoding accuracy of its freshwater fishes. Molecular Ecology Resources 14: 1210–1221, https://doi.org/10.1111/1755-0998.12257 Guindon S, Dufayard JF, Lefort V, Anisimova M, Hordijk W, Gascuel O (2010) New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0. Systematic Biology 59: 307–321, https://doi.org/10.1093/sysbio/syq010 Ivanova NV, Zemlak TS, Hanner RH, Hebert PD (2007) Universal primer cocktails for fish DNA barcoding. Molecular Ecology Notes 7: 544–548, https://doi.org/10.1111/j.1471-8286.2007.01748.x Knebelsberger T, Dunz AR, Neumann D, Geiger MF (2015) Molecular diversity of Germany’s freshwater fishes and lampreys assessed by DNA barcoding. Molecular Ecology Resources 15: 562–572, https://doi.org/10.1111/1755-0998.12322 Koblmüller S, Salzburger W, Obermüller B, Eigner E, Sturmbauer C, Sefc KM (2011) Separated by sand, fused by dropping water: habitat barriers and fluctuating water levels steer the evolution of rock-dwelling cichlid populations. Molecular Ecology 20: 2272–2290, https://doi.org/10.1111/j.1365-294X.2011.05088.x Kottelat M, Freyhof J (2007) Handbook of European freshwater fishes. Publications Kottelat, Cornol, 319 pp Lefort V, Longueville J-E, Gascuel O (2017) SMS: Smart Model Selection in PhyML. Molecular Biology and Evolution 34: 2422–2424, https://doi.org/10.1093/molbev/msx149 Li C, Ortí G (2007) Molecular phylogeny of Clupeiformes (Actinopterygii) inferred from nuclear and mitochondrial DNA sequences. Molecular Phylogenetics and Evolution 44: 386–398, https://doi.org/10.1016/j.ympev.2006.10.030

118

Li YJ, Zhang MZ, Yu Z, Pang YM, Qian C, Arai K (2010) Morphological variations in Amur weatherfish Misgurnus mohoity, northern weatherfish Misgurnus bipartitus and oriental weatherfish Misgurnus anguillicaudatus in China. Journal of Dalian Ocean University 25: 397–401 Liu SQ, Mayden RL, Zhang JB, Yu D, Tang QY, Deng X, Liu HZ (2012) Phylogenetic relationships of the Cobitoidea (Teleostei: Cypriniformes) inferred from mitochondrial and nuclear genes with analyses of gene evolution. Gene 508: 60–72, https://doi.org/10.1016/ j.gene.2012.07.040 Lopez AJ, Chen WJ, Orti G (2004) Esociform phylogeny. Copeia 2004: 449–464, https://doi.org/ 10.1643/CG-03-087R1 Marchesi P (2010) Histoires de loches et notes sur d’autres poissons non indigènes introduits en Valais. Bulletin de la Murithienne 128: 73–77 Perdices A, Vasil’ev V, Vasil’eva E (2012) Molecular phylogeny and intraspecific structure of loaches (genera Cobitis and Misgurnus) from the Far East region of Russia and some conclusions on their systematics. Ichthyology Resources 59: 113–123, https://doi.org/10.1007/ s10228-011-0259-6 Razzetti E, Nardi PA, Strosselli S, Bernini F (2001) Prima segnalazione di Misgurnus anguillicaudatus (Cantor, 1842) in acque interne italiane. Annali del Museo Civico di Storia Naturale di Genova 93: 559– 563 Rees HC, Maddison BC, Middleditch DJ, Patmore JRM, Gough KC (2014) The detection of aquatic animal species using environmental DNA - a review of eDNA as a survey tool in ecology. Journal of Applied Ecology 51: 1450–1459, https://doi.org/10.1111/1365-2664.12306 Richlen ML, Barber PH (2005) A technique for the rapid extraction of microalgal DNA from single live and preserved cells. Molecular Ecology Notes 5: 688–691, https://doi.org/10.1111/j. 1471- 8286.2005.01032.x Ronquist F, Huelsenbeck JP (2003) MRBAYES 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19: 1572–1574, https://doi.org/10.1093/bioinformatics/btg180 Seebens H, Blackburn TM, Dyer EE, Genovesi P, Hulme PE, Jeschke JM, Pagad S, Pyšek P, Winter M, Arianoutsou M, Bacher S, Blasius B, Brundu G, Capinha C, Celesti-Grapow L, Dawson W, Dullinger S, Fuentes N, Jäger H, Kartesz J, Kenis M, Kreft H, Kühn I, Lenzner B, Liebhold A, Mosena A, Moser D, Nishino M, Pearman D, Pergl J, Rabitsch W, Rojas- Sandoval J, Roques A, Rorke S, Rossinelli S, Roy HE, Scalera R, Schindler S, Štajerová K, Tokarska-Guzik B, Van Kleunen M, Walker K, Weigelt P, Yamanaka T, Essl F (2017) No saturation in the accumulation of alien species worldwide. Nature Communications 8: 14435, https://doi.org/10.1038/ncomms14435 Šlechtová V, Bohlen J, Tan HH (2007) Families of Cobitoidea (Teleostei; Cypriniformes) as revealed from nuclear genetic data and the position of the mysterious genera Barbucca, Psilorhynchus, Serpenticobitis and Vaillantella. Molecular Phylogenetics and Evolution 44: 1358–1365, https://doi.org/10.1016/j.ympev.2007.02.019 Šlechtová V, Bohlen J, Perdices A (2008) Molecular phylogeny of the freshwater fish family Cobitidae (Cypriniformes: Teleostei): delimitation of genera, mitochondrial introgression and evolution of sexual dimorphism. Molecular Phylogenetics and Evolution 47: 812–831, https://doi.org/10.1016/j.ympev.2007.12.018 Stoeckle BC, Belle CC, Geist J, Oehm J, Effenberger M, Heiss M, Seifert K, Kuehn R (2019) Molecular confirmation of the large-scale loach Paramisgurnus dabryanus Dabry de Thiersant, 1872 (Cypriniformes, Cobitidae) in Europe. Bioinvasions Records 8: 419–426, https://doi.org/10.3391/bir.2019.8.2.24 Tamura K, Stecher G, Peterson D, Filipski A, Kumar S (2013) MEGA6: Molecular Evolutionary Genetics Analysis version 6.0. Molecular Biology and Evolution 30: 2725–2729, https://doi. org/10.1093/molbev/mst197 Thalinger B, Wolf E, Traugott M, Wanzenböck J (2019) Monitoring spawning migrations of potamodromous fish species via eDNA. Scientific Reports 9: 15388, https://doi.org/10.1038/ s41598-019- 51398-0

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van Kessel N, Dorenbosch M, Crombaghs B, Niemeijer B, Binnendijk E (2013) First record of Asian weather loach Misgurnus anguillicaudatus (Cantor, 1842) in the River Meuse basin. Bioinvasions Records 2: 167–171, https://doi.org/10.3391/bir.2013.2.2.14 Vasil’eva ED (2001) Loaches (genus Misgurnus, Cobitidae) of Russian Asia. I. the species composition in waters of Russia (with a description of a new species) & some nomenclature and taxonomic problems of related forms from adjacent countries. Journal of Ichthyology 41: 553–563 Yi S, Zhong J, Wang S, Huang S, Wang W (2016) Mitochondrial DNA reveals evolutionary status and population genetics of two closely related fish (Misgurnus bipartitus and Misgurnus mohoity) in northeast China. Biochemical Systematics and Ecology 68: 192–199, https://doi.org/10.1016/j.bse.2016.07.018 Yi S, Zhong J, Huang S, Wang S, Wang W (2017a) Morphological comparison and DNA barcoding of four closely related species in the genera Misgurnus and Paramisgurnus (Cypriniformes: Cobitidae). Biochemical Systematics and Ecology 70: 50–59, https://doi.org/ 10.1016/j.bse.2016.10.019 Yi S, Li Y, Wang W (2017b) Selection shapes the patterns of codon usage in three closely related species of genus Misgurnus. Genomics 110: 134–142, https://doi.org/10.1016/j.ygeno. 2017.09.004

SUPPLEMENTARY MATERIAL

Suppl. Fig. 1: Bayesian Inference (BI) phylogram of 612 bp COI sequences. Node labels indicate posterior probabilities of the 50 % majority rule consensus tree of all trees sampled during 40 million generations. Bold lettering indicates all samples obtained and sequenced in the present study. Numbers in brackets represent GenBank accession numbers.

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Suppl. Fig. 2: Bayesian Inference (BI) phylogram of 658 bp RAG1 sequences. Node labels indicate posterior probabilities of the 50 % majority rule consensus tree of all trees sampled during 40 million generations. Bold lettering indicates all samples obtained and sequenced in the present study. Numbers in brackets represent GenBank accession numbers.

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Chapter 6 Molecular Biology Reports https://doi.org/10.1007/s11033-020-05786-9

Discriminating larvae of two syntopic Cychramus species (Coleoptera, Nitidulidae) by means of bar‑HRM analysis

Zangl, L., Oberreiter, H., Huss, H., Stabentheiner, E., Sturmbauer, C., Koblmüller, S. (2020). Discriminating larvae of two syntopic Cychramus species (Coleoptera, Nitidulidae) by means of bar-HRM analysis. Molecular Biology Reports, 47, 8251-8257.

LUKAS ZANGL1,2,3, HANNES OBERREITER1, HERBERT HUSS4, EDITH STABENTHEINER5, CHRISTIAN STURMBAUER1, STEPHAN KOBLMÜLLER1

1 Institute of Biology, University of Graz, Universitätsplatz 2, 8010 Graz, Austria

2 Universalmuseum Joanneum, Studienzentrum Naturkunde, Weinzöttlstraße 16, 8045 Graz, Austria

3 ÖKOTEAM - Institute for Animal Ecology and Landscape Planning, Bergmanngasse 22, 8010 Graz, Austria

4 Present Address: 4651 Stadl-Paura, Austria

5 Institute of Biology, University of Graz, Schubertstraße 51, 8010 Graz, Austria

ABSTRACT

Molecular genetic methods are increasingly used to supplement or substitute classical morphology-based species identification. Here, we employ a COI mini-barcode coupled high-resolution melting analysis to quickly, cost-efficiently and reliably determine larvae of two closely related Cychramus (Coleoptera, Nitidulidae) species. Euclidean distance comparison (p < 0.01) and a Welch t-test of the melting point temperatures (p < 0.01) provide highly significant statistical evidence for species specific differences in melting and fluorescence curves, thus allowing the assignment of larvae to either of the two 122

species. This protocol serves as a fast, low-cost and low-tech method to discriminate between pairs or groups of closely related species and can be adapted and applied to various ecological research questions.

KEYWORDS Coleoptera · DNA-barcoding · High-resolution melting analysis · Larvae · Mini-barcodes · Sap beetles

INTRODUCTION

Many key questions asked today in basic and applied biological research require precise species identifications. Traditionally, species identification is based on morphological characters and depends on the organisms’ internal and/or external structures. However, taxonomic identification based only on morphology can be difficult to virtually impossible or very time consuming when two or more species are morphologically highly similar. Indeed, there is increasing evidence that the diversity of recognized morphospecies does by far not reflect the true species diversity, especially in inconspicuous and small taxa [1, 2]. In addition, certain life stages (i.e., eggs and larvae) or sexes are often morphologically indistinguishable among species [3], complicating inferences about species richness and ecological interactions.

In the last two decades, DNA sequence-based methods facilitated species determination in taxa where due to a shortage of reliable characters, morphological identification is difficult. Especially DNA-barcoding [4], which relies on DNA sequence variation of a short and standardized section of a specific gene or set of genes, has become a widely used tool among biologists. Indeed, this approach proved to be a powerful and invaluable method for discriminating a broad range of organisms [5]. Often even shorter fragments, so-called mini-barcodes, are sufficient for discriminating between closely related species and they are typically used for analyzing samples containing degraded DNA and in metabarcoding approaches to efficiently characterize entire communities [6, 7]. In addition, mini-barcodes can be combined with high resolution melting analysis (bar- HRM), which provides a time- and cost-effective way to discriminate DNA sequences with small, even single, nucleotide differences, thus avoiding the need of sequencing, 123

which is the costliest step in standard DNA barcoding. The method is particularly suited for fast discrimination of a limited number of species [8]. Briefly, following a real-time PCR, the products are denatured by increased temperature and the changes in fluorescence caused by the release of an intercalating dye from the DNA duplex are measured [9]. By comparing the melting curves of unknown samples, i.e. the change in intensity of the fluorescence signal with increasing temperature, with profiles of reliably identified samples, they can be assigned to known species [10, 11].

The sap beetle (Nitidulidae) genus Cychramus comprises six valid species, two of which, C. luteus and C. variegatus, are widely distributed across Eurasia and the only Cychra- mus species reported from Europe. Whereas the beetles are regular flower visitors feeding on pollen [12], with C. luteus even reported from bee hives [13], the larvae are found on various fleshy fungi, and are particularly common on representatives of the honey fungus species complex, Armillaria spp. [14–16]. Unlike the beetles, which are easy to identify, the larvae are almost indistinguishable based on morphological characteristics, especially at younger stages [17]. Due to a lack of reliable species identification, little is known about the larval presence and population dynamics of each of these two species, or the interaction among them. Because honey fungi are among the most important fungal pathogens of temperate and boreal forests, it is of substantial interest to gain better knowledge which of the mushroom-consuming species is prevalent under certain ecological conditions. To this end we developed a robust bar-HRM assay to rapidly identify larvae of C. luteus and C. variegatus that will facilitate studying ecological interactions between these two species at the larval stage and fungus-beetle (larvae) interactions, and might be easily adapted to other study systems.

MATERIAL AND METEHODS

Sampling, species determination and standard COI barcode generation

In total, 38 specimens (25 adult beetles, 13 larvae, Table 1) of the two closely related species C. luteus and C. variegatus were collected from two localities in Austria. Adult specimens were morphologically identified to species level. Standard-length DNA barcodes (658 bp) were generated for some of these specimens. Initial morphological

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identification of younger larval stages was omitted due to the scarcity of distinguishing characters. Total genomic DNA was extracted using the DNeasy blood and tissue kit (QIAGEN) following the manufacturer’s instructions. Polymerase chain reaction, enzymatic cleanup and cycle sequencing using C_LepFolF and C_LepFolR [18] followed [19] and [20]. Sequencing products were visualized on a 3130xl capillary sequencer (Applied Biosystems). Sequence editing and alignment was done in MEGA 6.06 [21].

Primer design for mini‑barcodes and validation

Additional sequences were downloaded from GenBank (Table 1) to account for geographic genetic variation. A 153 bp fragment spanning from nucleotide position 51 to 204 of the standard barcode fragment containing sufficient nucleotide differences for species discrimination was selected for HRM analysis (Fig. 1). Primers Cyc-HRM-F 5′- TGAGAATCTTAATTCGGACTGAATT and Cyc-HRM-R 5′ GGAACAAGTCAATTTCCAAATCC were designed and their properties (annealing temperature, hairpins, etc.) checked with Primer-BLAST (https://www.ncbi. nlm.nih.gov/tools/primer-blast/). Successful amplification and genetic species determination (including the larvae) by these mini-barcodes was confirmed. Protocols for PCR and cycle sequencing applied as mentioned above, only the PCR annealing temperature (49 °C) differed.

qPCR and high‑resolution melting analysis of COI mini‑barcodes

Quantitative real time PCR and subsequent HRM analyses were conducted in a Rotor- Gene 3000 thermal cycler (Corbett Research, Mortlake, New South Wales, Australia). PCR reactions using the Real Time 2 × PCR Master Mix EvaGreen (A & A Biotechnology, Gdynia, Poland) and cycling conditions followed [8], only altering the annealing temperature to 49 °C. Optical measurements at 510 nm were recorded during each extension step. The final extension phase immediately initialized the heating process. Changes in fluorescence were detected during the increase of 0.1 °C increments per second between 60 and 95 °C. qPCR was repeated to obtain a technical replicate. The resulting fluorescence data was visualized using the Rotor-Gene 6.0.27 software.

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Statistical analysis of melting and fluorescence curves

Statistical analyses were conducted with R version 3.6.3. For reproducibility a docker container was created with Rocker:Tidyverse image 3.6.3 [22, 23]. The R-code and raw relative fluorescence data is publicly available on GitHub and an automatically generated Docker image can be downloaded from Dockerhub. Raw data were normalized at 75 and 85 °C after visual examination of the relative fluorescence decline over time (Fig. 2a). The negative first derivative values (-d(RFU/dT)) from a geometric spline function were used for statistical analysis in the qpcR package. The threshold to identify the melting point (Tm) was set to 0.2, which resulted in a single peak area for all samples.

Table 1 Information on specimens analyzed in the present study as well as sequences downloaded from online repositories are given

Species Life stage ID Locality Sampling site BOLD ID; Acc. No

C. luteus Larva Cyc1 UA, Gunskirchen 48.1144 N; 13.9433 E MT881657 Larva Cyc2 UA, Gunskirchen 48.1144 N; 13.9433 E MT881658 Larva Cyc3 UA, Gunskirchen 48.1144 N; 13.9433 E MT881659 Larva Cyc4 UA, Gunskirchen 48.1144 N; 13.9433 E MT881660 Larva Cyc5 UA, Gunskirchen 48.1144 N; 13.9433 E MT881661 Larva Cyc6 UA, Gunskirchen 48.1144 N; 13.9433 E MT881662 Larva Cyc7 UA, Gunskirchen 48.1144 N; 13.9433 E MT881663 Larva Cyc8 UA, Gunskirchen 48.1144 N; 13.9433 E MT881664 Beetle Cyc18 UA, Gunskirchen 48.1144 N; 13.9433 E ANIT002-20; MT890466 Beetle Cyc24 UA, Gunskirchen 48.1144 N; 13.9433 E ANIT008-20; MT890467 Beetle Cyc25 UA, Gunskirchen 48.1144 N; 13.9433 E ANIT009-20; MT890468 Beetle Cyc26 UA, Gunskirchen 48.1144 N; 13.9433 E ANIT010-20; MT890469 Beetle Cyc27 UA, Gunskirchen 48.1144 N; 13.9433 E ANIT011-20; MT890470 Beetle Cyc28 UA, Gunskirchen 48.1144 N; 13.9433 E ANIT012-20; MT884449 Beetle Cyc29 UA, Gunskirchen 48.1144 N; 13.9433 E ANIT013-20; MT884448 Beetle Cyc30 UA, Gunskirchen 48.1144 N; 13.9433 E ANIT014-20; MT884447 Beetle Cyc31 UA, Gunskirchen 48.1144 N; 13.9433 E ANIT015-20; MT890471 Beetle Cyc37 ST, Graz 47.0863 N; 15.4616 E ANIT021-20; MT890472 Beetle Cyc38 ST, Graz 47.0863 N; 15.4616 E ANIT022-20; MT884446 Beetle Cyc39 ST, Graz 47.0863 N; 15.4616 E ANIT023-20; MT890473 Beetle Cyc40 ST, Graz 47.0863 N; 15.4616 E ANIT024-20; MT890474 Beetle Cyc41 ST, Graz 47.0863 N; 15.4616 E ANIT025-20; MT890475 Additional sequences KJ962607; KJ965813; KJ966832; KJ962410; KJ964017; KJ962846; KM448028; KM446407; KM451876; KM448866; KM448805; KM449494; KM449753; KM452505; KM445184; KM442734; KM446278; KU908905; KU910131; KU916564; KU915694; KU914876; KU910893; KM286278 C. variegatus Larva Cyc9 UA, Gunskirchen 48.1144 N; 13.9433 E MT881665 Larva Cyc1 UA, Gunskirchen 48.1144 N; 13.9433 E MT881666 0 126

Larva Cyc1 UA, Gunskirchen 48.1144 N; 13.9433 E MT881667 4 Beetle Cyc1 UA, Gunskirchen 48.1144 N; 13.9433 E ANIT001-20; MT884455 5 Larva Cyc1 UA, Gunskirchen 48.1144 N; 13.9433 E MT881668 6 Larva Cyc1 UA, Gunskirchen 48.1144 N; 13.9433 E MT881669 7 Beetle Cyc1 UA, Gunskirchen 48.1144 N; 13.9433 E ANIT003-20; MT884454 9 Beetle Cyc2 UA, Gunskirchen 48.1144 N; 13.9433 E ANIT004-20; MT884451 0 Beetle Cyc2 UA, Gunskirchen 48.1144 N; 13.9433 E ANIT005-20; MT884450 1 Beetle Cyc2 UA, Gunskirchen 48.1144 N; 13.9433 E ANIT006-20; MT890476 2 Beetle Cyc2 UA, Gunskirchen 48.1144 N; 13.9433 E ANIT007-20; MT890477 3 Beetle Cyc3 ST, Graz 47.0863 N; 15.4616 E ANIT016-20; MT884453 2 Beetle Cyc3 ST, Graz 47.0863 N; 15.4616 E ANIT017-20; MT884452 3 Beetle Cyc3 ST, Graz 47.0863 N; 15.4616 E ANIT018-20; MT890478 4 Beetle Cyc3 ST, Graz 47.0863 N; 15.4616 E ANIT019-20; MT890479 5 Beetle Cyc3 ST, Graz 47.0863 N; 15.4616 E ANIT020-20; MT890480 6 Additional sequences KM286238; KJ965586 Acronyms UA and ST denote Upper Austria and Styria respectively

Distribution analysis was done visually with a Q-Q-plot. The Tm from all samples grouped by taxa were compared with a two-sided Welch t-test using a 95% confidence interval and10,000 bootstrap replicates. Euclidean distance comparison of melt curves followed [24]. p-values below 0.05 were considered significant.

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Fig. 1 COI sequence alignment of mini-barcode fragments of the two Cychramus species. Primer regions are marked in green. (Color figure online)

RESULTS AND DISCUSSION

The distinction between pairs or groups of sometimes strikingly similar species is often a key element when tackling biological, ecological or conservational research questions [24]. In the recent past, molecular biological methods have increasingly been used to aid in species assignment, albeit often requiring a substantial amount of infrastructure. Although standard genetic methods constantly aim for a reduction in hands-on time and financial efforts, few approaches actually decrease the necessary infrastructure. Here we present a fast, efficient and adaptable way to discriminate morphologically highly similar larvae of two closely related species of sap- feeding beetles of the family Nitidulidae, that will aid in investigating the population dynamics between these two sympatric species, but also the interactions of beetles, fungi and trees [25]. In the present study, we generated 10 new full-length DNA barcodes (MT884446-MT884455) and used them, together with previously published data, as a basis to create primers for a short mini-barcode fragment. High-resolution melting analysis of the mini-barcodes resulted in two clearly separated clusters of melting curves (see Fig. 2b). Subsequent statistical analyses of Euclidean distances (PERMANOVA, df = 1, pseudo-F = 29.6, p < 0.01, 10,000 permutations) and a two-sided Welch t-test (95% CI, df = 24.257, p < 0.01) of the melting point temperatures yielded significant differences in melting and fluorescence curves for C. luteus and C. variegatus (Fig. 2c), thus allowing for the assignment of the 13 larvae to either of the two species. The significant outcome of these tests indicates that shape, amplitude and melting

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peak do not just vary by chance [24]. The sensitivity of this method is known to account for single nucleotide differences [8]. The observed consistent differences in melting and fluorescence curves allow for the discrimination of species based on their melting profiles by eye. These results were corroborated by sequencing the short fragments and aligning them to the full-length barcodes. Thus, we conclude that HRM analyses of mini-barcode fragments present an adequate means to reliably differentiate morphologically similar specimens of these closely related species. Our workflow can be easily adapted for many applied and basic research questions whenever time and cost-efficient discrimination of a large number of samples of a limited number of species is necessary. Furthermore, our publicly available R-code can be used for any HRM study to provide statistical corroboration of visual results. Consequently, when short-fragment primers are established, only a qPCR machine and adequate software for visualization is required to facilitate high-sensitivity species discrimination.

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Fig. 2 Relative fluorescence curve (a), identified melting point comparison (b) and melting rate curve (c). Species are indicated by blue (C. variegatus) and red (C. lutues) colors. Colored lines in (a) represent means, grey areas cover standard deviations. Colored dots in (b) mark the distribution of resulting melting points, black dots and error bars represent the means and 95% confidence intervals (bootstrap, BCa 10,000) respectively. (Color figure online)

ACKNOWLEDGEMENTS

We kindly appreciate Anna Dünser’s help with the statistical analysis.

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Author contributions

CS, SK and LZ contributed to the study conception and design. Material preparation, data collection and analysis were performed by HH, ES, HO and LZ. The first draft of the manuscript was written by SK and LZ and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Funding acquisition and resources were provided by CS and SK.

Funding

Open access funding provided by University of Graz. Financial support for the laboratory work was provided by the Austrian Federal Ministry of Science, Research and Economy in the frame of an ABOL associated project within the framework of the “Hochschulraum-Strukturmittel” funds.

Data availability

DNA-barcoding data was stored on BOLD, BOLD- IDs and GenBank accession numbers are provided.

Code availability

All code for the statistical analyses was deposited on GitHub (https://github.com/HannesOberreiter/melt_graz) and archived on zenodo (https://doi.org/10.5281/zenodo.38628482) and is publicly available on Dockerhub (https://hub.docker.com/r/hannesoberreiter/ melt_graz).

Compliance with ethical standards

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Conflict of interest

The authors declare that they have no conflict of interest.

Open Access

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REFERENCES

1. Schäffer S, Kerschbaumer M, Koblmüller S (2019) Multiple new species: cryptic diversity in the widespread mite species Cymbaeremaeus cymba (Oribatida, Cymbaeremaeidae). Mol Phylogenet Evol 135:185–192. https://doi.org/10.1016/j.ympev.2019.03.008 2. Young MR, Proctor HC, deWaard JR, Hebert PDN (2019) DNA barcodes expose unexpected diversity in Canadian mites. Mol Ecol 28:5347–5359. https://doi.org/10.1111/mec.15292 3. Janzen DH, Hajibabaei M, Burns JM, Hallwachs W, Remigio E, Hebert PD (2005) Wedding biodiversity inventory of a large and complex Lepidoptera fauna with DNA barcoding. Phil Trans R Soc B 360(1462):1835–1845 4. Hebert PDN, Cywinska A, Ball SL, DeWaard JR (2003) Biological identifications through DNA barcodes. Proc R Soc Lond B Biol Sci 270:313–321. https://doi.org/10.1098/rspb.2002.2218 5. Kress WJ, García-Robledo C, Uriarte M, Erickson DL (2014) DNA barcodes for ecology, evolution, and conservation. Trends Ecol Evol 30:25–35. https://doi.org/10.1016/j.tree.2014.10.008 6. Hajibabaei M, Smith MA, Janzen DH, Rodriguez JJ, Whitfield JB, Hebert PDN (2006) A minimalist barcode can identify a specimen whose DNA is degraded. Mol Ecol Notes 6:959–964. https://doi. org/10.1111/j.1471-8286.2006.01470.x 7. Elbrecht V, Leese F (2017) Validation and development of COI metabarcoding primers for freshwater macroinvertebrate bioassessment. Front Environ Sci 5:11. https://doi.org/10.3389/fenvs.2017.00011 8. Behrens-Chapuis S, Malewski T, Suchecka E, Geiger MF, Herder F, Bogdanowicz W (2018) Discriminating European cyprinid specimens by barcode high-resolution melting analysis (Bar-HRM)—a cost efficient and faster way for specimen assignment? Fish Res 2014:61–73. https://doi.org/10.1016/j.fishr es.2018.02.007 132

9. Wittwer CT (2009) High-resolution DNA melting analysis: advancements and limitations. Hum Mutat 30:857–859. https:// doi.org/10.1002/humu.20951 10. Song M, Li J, Xiong C, Liu H, Liang J (2016) Applying high-resolution melting (HRM) technology to identify five commonly used Artemisia species. Sci Rep 6:34133. https://doi.org/10.1038/ srep34133 11. Fernandes TJR, Costa J, Okiveira MBPP, Mafra I (2018) COI barcode-HRM as a novel approach for the discrimination of hake species. Fish Res 197:50–59. https://doi.org/10.1016/j.fishr es.2017.09.014 12. Kirejtshuk AG (1997) On the evolution of anthophilous Nitidulidae (Coleoptera) in tropical and subtropical regions. Bonn Zool Beitr 46:11–134 13. Neumann P, Ritter W (2004) A scientific note on the association of Cychramus luteus (Coleoptera: Nitidulidae) with honeybee (Apis mellifera) colonies. Apidologie 35:665–666. https://doi. org/10.1051/apido:2004051 14. Rimšaitė J (2000) Contribution to the knowledge of insects humifactors of fungi in Lithuania. Acta Zool Litu 10:95–99 15. De Oude J (2007) Het voorkomen van glanskevers van de genera Cychramus, Pocadius en Thalycra in Nederland (Coleoptera: Nitidulidae). Nederl Faun Med 26:51–64 16. Schigel DS (2007) Fleshy fungi of the genera Armillaria, Pleurotes, and Grifola as habitats of Coleoptera. Karstenia 47:37–48 17. Hayashi N (1978) A contribution to the knowledge of the larvae of Nitidulidae occurring in Japan (Coleoptera: Cucujoidea). Insecta Matsum (N S) 14:1–97 18. Hernández-Triana LM, Prosser SW, Rodríguez-Perez MA, Chaverri LG, Hebert PDN, Ryan Gregory T (2014) Recovery of DNA barcodes from blackfly museum specimens (Diptera: Simuliidae) using primer sets that target a variety of sequence lengths. Mol Ecol Res 14(3):508–518. https://doi. org/10.1111/1755-0998.12208 19. Duftner N, Koblmüller S, Sturmbauer C (2005) Evolutionary relationships of the Limnochromini, a tribe of benthic deepwater cichlid fish endemic to Lake Tanganyika, East Africa. J Mol Evol 60:277–289. https://doi.org/10.1007/s00239-004-0017-8 20. Koblmüller S, Salzburger W, Obermüller B, Eigner E, Sturmbauer C, Sefc KM (2011) Separated by sand, fused by dropping water: habitat barriers and fluctuating water levels steer the evolution of rock- dwelling cichlid populations. Mol Ecol 20:2272–2290 21. Tamura K, Stecher G, Peterson D, Filipski A, Kumar S (2013) MEGA6: molecular evolutionary genetics analysis version 6.0. Mol Biol Evol 30:2725–2729. https://doi.org/10.1093/molbev/ mst197 22. R Core Team. 2020. R: A language and environment for statistical computing. Vienna, Austria. https://www.R-project.org/. 23. Wickham H, Averick M, Bryan J, Chang W, McGowan L, François R, Kuhn M (2019) Welcome to the Tidyverse. J Open Source Softw 4(43):1686 24. Everman S, Wang SY (2019) Distinguishing Anuran species by high-resolution melting analysis of the COI barcode (COI-HRM). Ecol Evol 9(23):13515–13520 25. Lachat T, Wermelinger B, Gossner MM, Bussler H, Isacsson G, Müller J (2012) Saproxylic beetles as indicator species for dead-wood amount and temperature in European beech forests. Ecol Indic 23:323– 331

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Chapter 7 Manuscript

First insights into the genetic diversity of Austrian snow scorpionflies (genus Boreus)

Lukas Zangl1,2*, Elisabeth Glatzhofer1, Raphael Schmid1, Susanne Randolf3, Stephan Koblmüller1

1 Institute of Biology, University of Graz, Universitätsplatz 2, 8010 Graz, Austria

2 Universalmuseum Joanneum, Studienzentrum Naturkunde, Weinzöttlstraße 16, 8045 Graz, Austria

3 Natural History Museum Vienna, Burgring 7, 1010 Vienna, Austria

*Corresponding author: [email protected] (LZ)

ABSTRACT

Snow scorpionflies (genus Boreus) belong to a family of Mecoptera that is vastly neglected by entomological research due to their shift in seasonality to the winter months. Their activity during this time is regarded as predator avoidance and regular sightings on snow cover are assumed to facilitate easier dispersal. Besides these and few other known facts about their biology, several other aspects about snow scorpionflies like systematics, taxonomy, distribution of species, phylogenetics and phylogeography remained fairly unexplored until the present day. In this study, we fill some of these gaps concerning the Boreids across Austria and present a genetic reference database for Austrian snow scorpionflies and consequently for European Boreus in general for the first time. Initial inspection of 67 mitochondrial cytochrome c oxidase subunit 1 (COI) DNA barcodes revealed deep intraspecific splits, seven different BINs and the paraphyly of Boreus

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westwoodi in Austria. Furthermore, species delimitation analyses and the inspection of morphological characters previously reported as suitable for the distinction of species yielded inconclusive results. Hence, genomic data for five specimens was generated and phylogenetic relationships based on whole mitochondrial genomes were inferred, mirroring the results of the DNA barcoding analysis. These results suggest cryptic diversity in Austrian snow scorpionflies which probably also extends to other national populations of Boreidae across Central Europe.

Key words: Biodiversity, Boreus hyemalis, Boreus westwoodi, COI, DNA barcoding, high-throughput sequencing, insects, winter scorpionflies

INTRODUCTION

The holometabolous insect genus Boreus (Insecta: Boreidae), commonly known as snow scorpionflies or winter scorpionflies (Ibrahimi et al. 2018) is assumed to have a Holarctic distribution and is most famous for its cold tolerance and activity on snow (Hågvar & Østbye 2011). They occur from about October to March/April (Finch 1997, Hågvar 2001), a temporal niche, which, among other hypotheses, is attributed to predator avoidance and improved dispersal (Hågvar 2010). Snow scorpionflies predominantly feed on mosses, but are also known to process decaying insects (Finch 1997). Despite a basic understanding of their general biology (Finch 1997, Hågvar 2001, Hågvar 2010), gaps in the knowledge concerning their distribution and species richness are yet to be overcome (e. g. Willmann 1978, Hågvar & Østbye 2011, Ibrahimi et al. 2018). However, most of the existing literature unanimously reports Boreus hyemalis (Linnaeus, 1767) and Boreus westwoodi Hagen 1866 from Southwest Europe to Northeast Scandinavia (Willmann 1978, Devetak 1988, Finch 1997, Kreithner 2001, Raemakers & Kleukers 1999, Hågvar & Østbye 2011, Tillier et al. 2011, Ibrahimi et al. 2018), even though field studies suggest similar ecological preferences for these two species (Hagvar 2010 and references therein). Other species like Boreus lokayi (Romania, Slovakia), Boreus aktijari (Crimea) or Boreus kratochvili (Czech Republic) are only scarcely mentioned (Penny 1977, Willmann 1978, Kreithner 2001, Ibrahimi et al. 2018) and the latter one is even regarded a synonym of B. hyemalis (Kreithner 2001). Boreus gigas poses another ambiguous example, which is also considered a synonym of B. hyemalis and in this case even lacks a formal species 135

description at all (Willmann 1978). In the past, descriptions of species have exclusively been based on morphological characters (Brauer 1876; Mayer 1938, Blades 2002), the similarity, plasticity and overlapping ranges of which, though, have issued continuous discussions about the validity (Willmann 1978 and authors therein; Kreithner 2001) and consequently the distribution of distinct species across Europe in general (Willmann 1978; Finch 1997; Kreithner 2001) but also for Austria in particular (Gepp 1982; Kreithner 2001; Gruppe and Aistleitner 2011). A detailed morphological investigation of material from the Alps (Austria, Switzerland, Slovenia, Italy and France) was compared to specimens from Croatia and Sweden by Kreithner (2001), also providing a set of morphological characters for species discrimination spanning some of the intraspecific and geographic morphological plasticity. However, no relevant genetic information of European Boreus species was available so far. Since DNA barcoding was introduced as a method for biological species discrimination (Hebert et al. 2003), several studies have shown that its delimiting powers also apply to various insect groups (Raupach et al. 2016, Huemer et al. 2019, Zangl et al. 2019, Galimberti et al. 2020, Paill et al. (in prep.), Geiger et al. (in press)). However, DNA barcoding also shows well known limitations with respect to recently diverged species and hybridization/introgression (e.g., van Velzen et al. 2012, Zangl et al. 2020, Ermakov et al. 2015, Cong et al. 2017). In some cases, though, these uncertainties may be overcome by the additional investigation of genomic data (e.g., Baack & Rieseberg 2007, Kehlmaier et al. 2019, Taylor et al. 2019, Alexander et al. 2017). In the framework of the Austrian Barcode of Life initiative (ABOL, www.abol.ac.at) this study was aiming at i) contributing DNA barcodes of Austrian Boreus species to the Barcode of Life database (BOLD), ii) investigating their genetic diversity, iii) validating the two proposed Central European species with mitogenomic data and iv) to test whether genetic results mirror the morphological variability displayed by both Boreus hyemalis and Boreus westwoodi.

MATERIAL AND METHODS

All fresh specimens investigated in the present study were collected in concordance with state conservation laws and under according permits where needed (ABT13-53W- 50/2018-2, 08-NATP-845/1-2019(007/2019O, N-2018-326688/8-Pin)). From 2017 to 2020, 67 individuals from 18 localities from Central and Eastern Austria were caught by

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hand and stored in 2 ml Eppendorf tubes at -20°C (species determinations, collection and storage information are deposited on BOLD, see supplementary table 1). Morphological species discrimination followed Kreithner (2001). Primarily, the shape of tergal apophyses (TA), epiandrum (EA) and hypandrum (HA) of males were used to assign specimens to species. Further morphological investigation included the properties of the caput, the number of antennal segments and the number of bristles on the front wing. Due to the lack of reliably discriminating morphological characters, females were determined based on male individuals from the same geographic location. A Keyence digital microscope was used to assess TA, EA and HA in males and to capture the general appearance of all specimens. For DNA analyses, total genomic DNA was extracted from three legs using the DNAesy XS KIT (QIAGEN) following the manufacturer’s instructions. All extracts were initially used for DNA barcoding and some of the extracts were later sent to Novogene (https://en.novogene.com/) for low-coverage high- throughput whole-genome sequencing and were processed on an Illumina Novaseq 6000. PCR amplification, purification and chain termination sequencing using the primer combinations C_LepFolF and C_LepFolR (Hernández‐Triana et al. 2014) followed Koblmüller et al. (2011) and Duftner et al. (2005). Sequences were visualized on an 3500xl capillary sequencer (ABI) and aligned using MEGA 6.06 (Tamura et al. 2013). Clustering analysis was performed using the “Taxon ID Tree” tool implemented on BOLD. Genetic distances within and between species were calculated using the “Barcode Gap Analysis” tool, also provided on BOLD. Additional Sequences of Boreus borealis (KU874461.1, KU874462 (Sikes et al. 2017)) and Boreus elegans (HQ696579.1 (Beckenbach 2011)) were downloaded as outgroups. For species delimitation, BIN assignment on BOLD, the Automatic Barcode Gap Discovery (ABGD) (Puillandre et al. 2011), Generalized Mixed Yule Coalescent (GMYC) (Zhang et al. 2013), the Bayesian Poisson Tree Processes (bPTP) model (Zhang et al. 2013), and the Bayesian GMYC (bGMYC) were used. ABGD was performed via the web version (https://bioinfo.mnhn.fr/abi/public/abgd/abgdweb.html) using default settings and the Kimura (K80) TS/TV distance model. For the GMYC analysis, BEAST v.2.6.3 including BEAUTi 2 and TreeAnnotator v2.6.3 was used to create an ultrametric tree, ESS values (all > 200) were checked with Tracer v1.6. GMYC was run from the web server (https://species.h-its.org/gmyc/) with the single threshold option. For the bPTP analysis PhyML 3.0 (http://www.atgc-montpellier.fr/phyml/) was used to create a tree file as input for the web server (https://species.h-its.org/ptp/) using the default settings and a burn-in 137

value of 25 %. For the bGMYC analysis the package ‘ape’ was downloaded and run in R v3.6.0 (MCMC = 50,000; burnin = 40,000; thinning = 100) on 668 trees (501 after burn- in cropping) according to Reid and Carstens (2012).

Genomic data of five giga bases were generated for each of five selected specimens corresponding to the main clusters retrieved from the DNA barcode analysis. Raw reads were stored on the high-performance cluster at the University of Graz. For quality filtering and trimming a snakemake pipeline including Trim Galore v0.6.0 (https://github.com/chrishah/prepro) was used. Mitochondrial genomes were extracted using a custom-made snakemake pipeline (https://github.com/luksnza). The pipeline was iterated over different mitochondrial genomes (one species each from the families Panorpidae, Boreidae and Bittacidae) as well as DNA barcodes from species of Panorpidae and Boreidae as starting molecules to rule out seed-based errors or biases in mitogenome recovery. In addition, the locations and number of recovered genes were verified by submitting filtered reads to MITOS (http://mitos.bioinf.uni- leipzig.de/index.py) (Bernt et al. 2013) and comparing the results of annotation and gene predictions. Mitochondrial genomes were aligned using Clustal Omega from a predesigned Docker container (https://github.com/chrishah/clustalo-docker) and used for phylogenomic inference running an IQ-TREE analysis (including best-fit model selection and 1000 bootstrap replicates).

RESULTS

Morphological determination resulted in one alleged B. hyemalis and 28 alleged B. westwoodi males and one B. hyemalis and 37 B. westwoodi females based on the co- occurrence of males in the same geographic area (see table 1).

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Table 1: The following table lists the results of the comparison of morphological characters from this study to the different types and data recovered by Kreithner (2001). Numbers in Field ID correspond with supplementary table 1. Tergal apophyses (TA), epiandrum (EA), gonostylus (GS). Numbers in GS correspond to figures in Kreithner (2001). Forms of TA correspond with figure 1.

Field Caput No. of TA No. of bristles on EA GS

ID antennal front wing

segments (external/internal)

200 Corrugated 24 Form 7 9/34 n.a. 41

208 Corrugated 25 Form 1 4/34 Lateral lobes shorter 41

than septum,

septum broad

triangular

209 Corrugated 24 Form 2 9/0 Lateral lobes same 41

length as septum,

septum broad

triangular

210 25 Form 4 9/0 Lateral lobes shorter 41

than septum,

septum broad

triangular

211 Corrugated 23 Form 7 9/0 n.a. n.a.

212 Corrugated 24 Form 7 10/0 Lateral lobes shorter 41

than septum

214 Smooth 23 Form 3 9/0 Lateral lobes shorter 41

than septum,

septum broad

triangular

215 Corrugated 23 Form 7 9/23 n.a. 41

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216 Smooth, pilose 16 Form 5 0/29 Lateral lobes shorter 41

than septum

265 Corrugated 25 Form 8 11/0 n.a. 41

266 Smooth, pilose Form 8 8/0 Lateral lobes shorter 41

than septum,

septum broad

triangular

267 Corrugated 23 Form 8 7/0 Lateral lobes shorter 41

than septum,

septum broad

triangular

268 Smooth, pilose 25 Form 8 12/0 n.a. 41

269 23 Form 8 8/0 n.a. 41

274 Corrugated 25 Form n.a. Lateral lobes shorter 41 10 than septum,

septum broad

triangular

275 Smooth, pilose 24 Form 8 9/0 Lateral lobes longer 41

than septum,

septum pointed

276 Smooth, pilose 23 Form 8 12/0 n.a. 41

277 Corrugated 24 Form 5 11/0 Lateral lobes longer Individu al shape than septum,

septum pointed

278 Smooth, pilose 23 Form 9 8/0 Lateral lobes longer 41

than septum,

septum pointed

280 Smooth, pilose 24 Form 5/0 n.a. 41 10 282 Smooth, pilose 24 Form 5 10/0 n.a. 41

284 Smooth, pilose 24 Form 10/0 n.a. 41 12 140

285 Smooth, pilose n.a. Form 7/0 n.a. 41 12 287 n.a. n.a. Form n.a. Lateral lobes flat 41 12 290 Smooth, pilose n.a. Form 7/0 Lateral lobes shorter 41 11 than septum,

septum broad

triangular

291 Smooth, pilose 24 Form 8/0 Lateral lobes longer Individu 11 al shape than septum,

septum pointed

292 Smooth, pilose n.a. Form 4 5/0 n.a. 41

294 Corrugated 23 Form 2 1/0 Lateral lobes longer 45

Many on hind wings than septum,

septum pointed

296 Smooth, pilose 23 Form 8 11/0 septum broad 41

triangular

297 Smooth, pilose 23 Form 8 12/0 Lateral lobes shorter 41

than septum,

septum broad

triangular

299 Smooth, pilose 24 Form 7 8/0 n.a. 41

301 Smooth, pilose 25 Form 5 11/0 Lateral lobes shorter 41

than septum,

septum broad

triangular

303 Smooth, pilose 24 Form 14/0 Lateral lobes shorter 41 10 than septum

307 Smooth, pilose 24 Form 11/0 Lateral lobes shorter 41 10 than septum,

septum broad

triangular

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308 Smooth, pilose 24 Form 9 12/0 n.a. 41

312 Corrugated, 25 Form 6 7/0 Lateral lobes shorter n.a.

pilose than septum,

septum broad

triangular

314 Smooth, pilose 25 Form 9 n.a. n.a. n.a.

318 Smooth, pilose 24 Form n.a. Lateral lobes shorter 41 10 than septum,

septum broad

triangular

Figure 1: Schematic drawings and images of the tergal apophyses (TA) and genital segments (GS) with the epiandrum. Types of TA of Boreus westwoodi (forms 25-32) from across Europe (a) and Austria (d). Digital microscopy images of the anvil-shaped TA of B. westwoodi (b) and pointed TA of B. hyemalis from Austria. Main shapes of GS (e-f, see table 1). Drawings of TA (a) and GS (e-f) retrieved and edited from Kreithner (2001).

DNA barcodes of the partial COI gene ranging from 649 to 657 bp in length were generated for 67 specimens (sequences are available on BOLD (DOI will be provided upon acceptance) and GenBank (Acc.No. will be provided upon acceptance). Analysis of the COI sequences based on sequence similarity resulted in six distinct clusters and one singleton. These clusters almost perfectly correspond to the seven BINs assigned by

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BOLD (see figure 2). Based on the results of the DNA barcoding, Boreus westwoodi turned out to be paraphyletic with respect to B. hyemalis.

Figure 2: Maximum likelihood phylogeny based on the partial mitochondrial COI gene. Colored branches indicate initial morphological species assignment. Numbers indicate statistical node support (posterior probabilities).

K2P distances based on morphological species assignment yielded low intraspecific genetic distances within B. hyemalis, but high conspecific distances within B. westwoodi. Consequently, interspecific distances exceeded intraspecific distances by far for B. hyemalis, whereas the opposite was true for B. westwoodi. The same results were also obtained when excluding those B. westwoodi specimens that clustered together with B. hyemalis in the NJ tree (not shown) from the analysis.

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Table 2: Maximum intraspecific K2P distances (Imax) and distances (DNN – distance to nearest neighbor) to nearest neighbor (NN) are listed. * indicates distance values when excluding B. westwoodi samples which cluster together with B. hyemalis.

Species Imax DNN NN

Boreus hyemalis 0.15; 0.15* 2.53, 4.3* Boreus westwoodi Boreus westwoodi 7.21; 7.21* 2.53, 4.3* Boreus hyemalis

Species delimitation analyses results varied considerably between the four methods. While ABGD inferred four species in the recursive approach including the outgroup (three species in the initial approach) and GMYC suggested six species, bPTP estimated 19 to 44 (mean 28) and bGMYC resulted in 30 species (Figure 2).

Analysis of all 13 protein coding genes of the mitochondrial genome mirrored the topology recovered from the single barcoding marker. Similar to the results described above, B. westwoodi again appeared paraphyletic with respect to B. hyemalis.

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Figure 3: Maximum likelihood phylogeny of Austrian Boreidae based on whole mitochondrial genomes. Numbers indicate statistical node support based on 1000 bootstrap replicates.

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DISCUSSION

In this study, we provide 67 new DNA barcodes and five fully recovered mitochondrial genomes representing the first genetic insights into the snow scorpionfly diversity of the genus Boreus from Austria and consequently from all of Europe. This apparent lack of genetic information may be attributed to a certain characteristic of Boreids’ biology. Due to their shift in seasonality of the imaginal stage to the winter months, few entomologists ever collect them as bycatch from passive stationary traps, led alone actively pursue them (Hågvar and Østbye 2011). Consequently, contemporary literature about Boreidae almost exclusively only covers new records (Ibrahimi et al. 2018, Tillier et al. 2011), re-evaluates national distribution of species (Devetak 1988, Tillier et al. 2011, Hågvar & Østbye 2011, Raemakers & Kleukers 1999, Finch 1997) and conducts the morphological comparison of already available material (Kreithner 2001). However, phenotypic plasticity has been found to be extensive both within species and across larger geographic distances and has fueled debates about the validity and exact distribution of extant species (Willmann 1978, Kreithner 2001). Nonetheless, certain morphological traits have been reported to hold sufficient discriminative power and suggested the presence of Boreus hyemalis and Boreus westwoodi throughout Central Europe (Kreithner 2001, Ibrahimi et al. 2018, Hågvar & Østbye 2011). However, examination of these characters of material from Austria also recovered a high degree of morphological variation at least within B. westwoodi (see figure 1 and table 1). Comparison of the Austrian material to results reported by Kreithner (2001) showed, that some of the different morphotypes are very similar between the Austrian and the European samples, indicating a large diversity even within Austria. Since only one single male could clearly be assigned to B. hyemalis based on synoptic inspection of all morphological characters, phenotypic plasticity cannot be evaluated here. However, the shape of TA recovered for Panorpa294 matches form 34 of Kreithner (2001) almost perfectly and for the first time links this particular morphotype with a DNA barcode and a particular BIN (BOLD:ACT2769). Furthermore, the results of the DNA barcoding and species delimitation analyses suggest, that there could be more than two species present in Austria alone (see figure 2). Genetic K2P distances show a clear barcoding gap for B. hyemalis with interspecific distances exceeding distances between conspecifics more than tenfold (see table 2). In B. westwoodi on the other hand, maximum intraspecific distances are significantly higher than the distance to their nearest neighbor (see table 2), which has also been reported for ground beetles, butterflies and

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aphids (Raupach et al. 2016, Janzen et al. 2017, Lee et al. 2017) and may be an indication for cryptic diversity. Furthermore, interspecific distances of two to three percent separating good species have previously been found in aphids and mosquitos (Lee et al. 2017, Wang et al. 2012). While distance-based species delimitation methods like ABGD are prone to lump many species together (Dellicour & Flot 2018, Galimberti et al. 2020, da Silva et al. 2017) and Dellicour and Flot (2015) even reported ABGD and GMYC as unable to correctly delimit species in scenarios involving only one or two species, ABGD suggested one additional species for Austrian Boreids. Tree-based methods on the other hand are reported to oversplit both in cases with few and many species (Dellicour and Flot 2018), which would explain the suggested 30 to 40 species by bGMYC and bPTP in our case. However, despite a general incongruence and a large range in the number of potentially recovered species between the different methods (see figure 2), they all concur in resulting in more than the two previously reported species.

Limitations for species delimitation inferences based on a single gene are obvious and well discussed in literature but still can pinpoint ambiguous cases (da Silva et al. 2017, Galimberti et al 2020). However, in this case, the patterns observed from DNA barcoding and species delimitation analyses are mirrored by the phylogeny inferred from whole mitochondrial genomes (see figure 3), indicating actual cryptic diversity.

In conclusion, this study presents the first genetic information on the genus Boreus in Austria and consequently in all of Europe. Furthermore, it also provides several new localities from which Boreids have not been reported so far within Austria and thus augments their known distribution range in Austria. DNA barcodes linked to different morphotypes prove the presence of Boreus westwoodi and Boreus hyemalis in Austria but also indicate the potential presence of further cryptic species. The phenotypic plasticity previously reported for these two species is matched by the genetic diversity and represented by seven distinct BINs recovered by BOLD. This potential cryptic diversity probably also extends to other European populations of Boreus but disentangling the exact number of species, possible hybridization/introgression and the precise distribution of those species will require further (nuclear) genomic as well as morphological investigations and a pan-European sampling of Boreids in the future.

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ACKNOWLEDGEMENTS

We are grateful to Lukas Strohmaier, Thomas Bernhart, Barbara Bernhart and Christian Komposch for their help in sample collection. Furthermore, we acknowledge Christoph Hahn, Philipp Resl, Maximilian Wagner and Samuel Leeming for their help with bioinformatics and the Austrian Federal Ministry of Science, Research and Economy for funding this research in the frame of an ABOL associated project within the framework of the “Hochschulraum-Strukturmittel” Funds.

REFERENCES

Alexander, A. M., Su, Y. C., Oliveros, C. H., Olson, K. V., Travers, S. L., & Brown, R. M. (2017). Genomic data reveals potential for hybridization, introgression, and incomplete lineage sorting to confound phylogenetic relationships in an adaptive radiation of narrow‐mouth frogs. Evolution, 71(2), 475-488.

Baack, E. J., & Rieseberg, L. H. (2007). A genomic view of introgression and hybrid speciation. Current opinion in genetics & development, 17(6), 513-518.

Beckenbach, A. T. (2011). Mitochondrial genome sequences of representatives of three families of scorpionflies (Order Mecoptera) and evolution in a major duplication of coding sequence. Genome, 54(5), 368-376.

Bernt M, A. Donath, F. Jühling, F. Externbrink, C. Florentz, G. Fritzsch, J. Pütz, M. Middendorf, P. F. Stadler. (2013). MITOS: Improved de novo Metazoan Mitochondrial Genome Annotation Molecular Phylogenetics and Evolution, 69(2):313-319

Blades, D. C. (2002). A new species of Boreus (Mecoptera: Boreidae) from Vancouver Island, British Columbia. Journal of the Entomological Society of British Columbia, 99, 133-140.

Brauer, F. (1876): Die Neuropteren Europas und insbesondere Österreichs. — Festschr. k. k. zool.-bot. Ges.: 263 — 300. — Wien

Cong, Q., Shen, J., Borek, D., Robbins, R. K., Opler, P. A., Otwinowski, Z., & Grishin, N. V. (2017). When COI barcodes deceive: complete genomes reveal introgression in hairstreaks. Proceedings of the Royal Society B: Biological Sciences, 284(1848), 20161735. da Silva, R., Peloso, P. L., Sturaro, M. J., Veneza, I., Sampaio, I., Schneider, H., & Gomes, G. (2018). Comparative analyses of species delimitation methods with molecular data in snappers (Perciformes: Lutjaninae). Mitochondrial DNA Part A, 29(7), 1108-1114.

148

Dellicour, S., & Flot, J. F. (2015). Delimiting species-poor data sets using single molecular markers: a study of barcode gaps, haplowebs and GMYC. Systematic Biology, 64(6), 900-908.

Dellicour, S., & Flot, J. F. (2018). The hitchhiker's guide to single‐locus species delimitation. Molecular Ecology Resources, 18(6), 1234-1246.

Devetak, D. (1988). The distribution of scorpionflies (Mecoptera, Insecta) in Slovenia= Razširjenost kljunavcev (Mecoptera, Insecta) v Sloveniji. BV, 36(2), 1-12.

Duftner N, Koblmüller S, Sturmbauer C (2005) Evolutionary relationships of the Limnochromini, a tribe of benthic deepwater cichlid fish endemic to Lake Tanganyika, East Africa. Journal of Molecular Evolution 60: 277-289. DOI https://doi.org/10.1007/s00239-004-0017-8

Ermakov, O. A., Simonov, E., Surin, V. L., Titov, S. V., Brandler, O. V., Ivanova, N. V., & Borisenko, A. V. (2015). Implications of hybridization, NUMTs, and overlooked diversity for DNA barcoding of Eurasian ground squirrels. PLoS One, 10(1), e0117201.

Finch, O. D. (1997) Zum Vorkommen des Winterhaftes Boreus hiemalis L (Insecta: Mecoptera) im nordwestlichen Niedersachsen. Drosera (2): 113-116.

Galimberti, A., Assandri, G., Maggioni, D., Ramazzotti, F., Baroni, D., Bazzi, G., ... & Ilahiane, L. (2020). Italian Odonates in the Pandora's Box: A Comprehensive DNA Barcoding Inventory Shows Taxonomic Warnings at the Holarctic Scale. bioRxiv.

Geiger, M., Koblmüller, S., Koch, S., Assandri, G., Chovanec, … & Morinère, J. (2021). Coverage and quality of DNA barcode references for Central and Northern European Odonata. PeerJ, (in press).

Gepp J (1982) Die Mecopteren Kärntens mit Bemerkungen über Lautäußerungen von Bittacus italicus (MÜLLER). Carinthia II 172(92): 341-350

Gruppe, A., & Aistleitner, U. (2011). Beitrag zur Kenntnis der Arteninventare und ökologischen Ansprüche der Netzflügler (Neuropterida) und Skorpionsfliegen (Mecoptera) in Vorarlberg, Austria occ. inatura – Forschung online. 1:1-8

Hågvar, S. (2001). Occurrence and migration on snow, and phenology of egg-laying in the winter-active insect Boreus sp. (Mecoptera). Norwegian Journal of Entomology, 48, 51-60.

Hågvar, S. (2010). A review of Fennoscandian arthropods living on and in snow. European Journal of Entomology, 107(3), 281.

Hågvar, S., & Østbye, E. (2011). Distribution of Boreus westwoodi Hagen, 1866 and Boreus hyemalis (L., 1767) (Mecoptera) in Norway. Norwegian Journal of Entomology, 58, 73-80.

Hamilton, C. A., Hendrixson, B. E., Brewer, M. S., & Bond, J. E. (2014). An evaluation of sampling effects on multiple DNA barcoding methods leads to an integrative approach for delimiting species: a case study of the North American tarantula genus Aphonopelma (Araneae, Mygalomorphae, Theraphosidae). Molecular Phylogenetics and Evolution, 71, 79-93.

149

Hebert, P. D., Ratnasingham, S., & De Waard, J. R. (2003). Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species. Proceedings of the Royal Society of London. Series B: Biological Sciences, 270(suppl_1), S96-S99.

Hernández‐Triana, L. M., Prosser, S. W., Rodríguez‐Perez, M. A., Chaverri, L. G., Hebert, P. D. N., & Ryan Gregory, T. (2014). Recovery of DNA barcodes from blackfly museum specimens (Diptera: Simuliidae) using primer sets that target a variety of sequence lengths. Molecular Ecology Resources, 14(3), 508-518.

Huemer, P., Wieser, C., Stark, W., Hebert, P. D., & Wiesmair, B. (2019). DNA barcode library of megadiverse Austrian Noctuoidea (Lepidoptera)–a nearly perfect match of Linnean taxonomy. Biodiversity Data Journal, 7.

Ibrahimi, H., Devetak, D., Pizzigalli, C., & Hoxha, L. (2018). First record of the genus Boreus Latreille, 1816 from the Republic of Kosovo. Spixiana 41(1): 12

Janzen, D. H., Burns, J. M., Cong, Q., Hallwachs, W., Dapkey, T., Manjunath, R., ... & Grishin, N. V. (2017). Nuclear genomes distinguish cryptic species suggested by their DNA barcodes and ecology. Proceedings of the National Academy of Sciences, 114(31), 8313-8318.

Kehlmaier, C., Zhang, X., Georges, A., Campbell, P. D., Thomson, S., & Fritz, U. (2019). Mitogenomics of historical type specimens of Australasian turtles: clarification of taxonomic confusion and old mitochondrial introgression. Scientific reports, 9(1), 1-12.

Koblmüller S, Salzburger W, Obermüller B, Eigner E, Sturmbauer C, Sefc KM (2011) Separated by sand, fused by dropping water: habitat barriers and fluctuating water levels steer the evolution of rock-dwelling cichlid populations. Molecular Ecology 20: 2272-2290. https://doi.org/10.1111/j.1365-294X.2011.05088.x

Kreithner, A. (2001). Über Boreus-Arten aus den Alpen: Taxonomische Charakterisierung und Verbreitung (Insecta, Mecoptera, Boreidae). Ber. nat.-med. Verein Innsbruck, 88, 213-236.

Lee, Y., Lee, W., Kanturski, M., Foottit, R. G., Akimoto, S. I., & Lee, S. (2017). Cryptic diversity of the subfamily Calaphidinae (Hemiptera: Aphididae) revealed by comprehensive DNA barcoding. Plos one, 12(4), e0176582.

Mayer, K. (1938): Boreus in der Cechoslovakei. — Ent. listy, 2: 129-140

Paill, W., Koblmüller, S., Frieß, T., Gereben-Krenn, B.-A., Mairhuber, C., … & Zangl, L. (2021). Relicts from glacial times: The ground beetle Pterostichus adstrictus Eschscholtz, 1823 (Coleoptera: Carabidae) in the Austrian Alps. Insects, (in review)

Penny, N. 1977. A systematic study of the family Boreidae (Mecoptera). The University of Kansas Science Bulletin, Vol 51, No. 5: 141-217.

Puillandre N, A Lambert, S Brouillet and G Achaz ABGD, Automatic Barcode Gap Discovery for primary species delimitation, Mol Ecol. 2011.

150

Raemakers, I., & Kleukers, R. M. J. C. (1999). De sneeuwspringer Boreus hyemalis in Nederland (Mecoptera: Boreidae). Nederlandse Faunistische Mededelingen, 8: 1-10

Raupach, M. J., Hannig, K., Moriniere, J., & Hendrich, L. (2016). A DNA barcode library for ground beetles (Insecta, Coleoptera, Carabidae) of Germany: The genus Bembidion Latreille, 1802 and allied taxa. ZooKeys, (592), 121.

Reid, N. M., & Carstens, B. C. (2012). Phylogenetic estimation error can decrease the accuracy of species delimitation: a Bayesian implementation of the general mixed Yule-coalescent model. BMC evolutionary biology, 12(1), 196.

Rossini, B. C., Oliveira, C. A. M., Melo, F. A. G. D., Bertaco, V. D. A., Astarloa, J. M. D. D., Rosso, J. J., ... & Oliveira, C. (2016). Highlighting Astyanax species diversity through DNA barcoding. PLoS One, 11(12), e0167203.

Sikes, D. S., Bowser, M., Morton, J. M., Bickford, C., Meierotto, S., & Hildebrandt, K. (2017). Building a DNA barcode library of Alaska’s non-marine arthropods. Genome, 60(3), 248-259.

Tamura K, Stecher G, Peterson D, Filipski A, Kumar S (2013) MEGA6: Molecular Evolutionary Genetics Analysis version 6.0. Molecular Biology and Evolution 30: 2725-2729. https://doi.org/10.1093/molbev/mst197

Taylor, S. A., & Larson, E. L. (2019). Insights from genomes into the evolutionary importance and prevalence of hybridization in nature. Nature ecology & evolution, 3(2), 170-177.

Tillier, P., Callot, H., & Ragué, J. C. (2011). Contribution à la connaissance de Boreus hyemalis L., 1767 en France (Neomecoptera Boreidae). L’Entomologiste, 67(5), 251-255. van Velzen, R., Weitschek, E., Felici, G., & Bakker, F. T. (2012). DNA barcoding of recently diverged species: relative performance of matching methods. PloS one, 7(1), e30490.

Wang, G., Li, C., Guo, X., Xing, D., Dong, Y., Wang, Z., ... & Zhu, X. (2012). Identifying the main mosquito species in China based on DNA barcoding. PLoS One, 7(10), e47051.

Willmann, R. (1978). Redeskription von Boreus gigas Brauer (Boreidae, Mecoptera), zugleich ein Beitrag zur Variabilität von B. hyemalis (L.). Annalen des Naturhistorischen Museums in Wien, 525-532.

Zangl, L., Kunz, G., Berg, C., & Koblmüller, S. (2019). First records of the parthenogenetic Surinam cockroach Pycnoscelus surinamensis (Insecta: Blattodea: Blaberidae) for Central Europe. Journal of Applied Entomology, 143(3), 308-313.

Zangl, L., Daill, D., Schweiger, S., Gassner, G., & Koblmüller, S. (2020). A reference DNA barcode library for Austrian amphibians and reptiles. PloS one, 15(3), e0229353.

Zhang, J., Kapli, P., Pavlidis, P., & Stamatakis, A. (2013). A general species delimitation method with applications to phylogenetic placements. Bioinformatics, 29(22), 2869-2876.

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Discussion

DNA barcoding was proclaimed to be a revolutionary tool for taxonomic discovery, species discrimination and specimen idendification (Hebert et al. 2003, DeSalle & Goldstein 2019). The initial idea was based on the explicit difference between intraspecific variability and interspecific divergence of genetic distances, henceforth known as the ‘barcoding gap’ (Hebert et al. 2003, Jinbo et al. 2011, Coissac et al. 2016). As a consequence, many national barcoding initiatives were created (FinBOL, NorBOL, GBOL, Barcoding Fauna Bavarica, SwissBOL, …) generating national reference species inventories of various taxonomic groups (e.g., Ward et al. 2005, Raupach et al. 2010, Hausmann et al. 2011, Lakra et al. 2011, Knebelsberger et al. 2015, Blagoev et al. 2016, Hawlitschek et al. 2016, Hawlitschek et al. 2017, Galimberti et al. 2020). In addition, this led to the description of several species new to science (e.g., Huemer et al. 2014, Nguyen et al. 2014, Packer & Ruz 2017) as well as to the detection of various cases of cryptic diversity (e.g., Clare et al. 2007, Hubert et al. 2012, Vasconcelos et al. 2016, Zangl et al. 2020a). On the applied side, DNA barcoding was, among others, used for the authentification of food products (Galimberti et al. 2013, Khaksar et al. 2015, Hellberg et al. 2017) as well as for the detection of pest species (Germain et al. 2014, Madden et al. 2019).

Similarly, the ‘Austrian Barcode of Life’ initiative was founded, targeting the same goals as other national initiatives (Haring et al. 2015). So far, DNA barcoding was used for creating national reference databases for e.g., Lepidoptera (Huemer et al. 2014), amphibians and reptiles (Zangl et al. 2020b) as well as fish (in prep.) and snow scorpionflies (Zangl et al. manuscript), and many more are currently in the progress of being completed. In the course of creating the species inventory of the Austrian fish fauna, the recovered barcoding data suggested the presence of a new, previously unknown species, which, as a consequence was then described based on morphological and genetic data (Friedrich et al. 2018). In this context, separating DNA barcodes as well as the differences in intra- and interspecific genetic distances could be used for the discrimination of species, which is in line with previous works (e.g., Hebert et al. 2003, Briski et al. 2011, Nguyen et al. 2014). The strengths of this method in pointing out taxonomic groups based on sequence similarity were also used to prove the presence of

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alien species of cockroaches (Zangl et al. 2019) and fish (Zangl et al. 2020c) and were suitable for the distinction of two closely related species of beetles with highly similar larval phenotypes (Zangl et al. 2020d).

However, the alledged strenghts but especially also the obvious weaknesses of DNA barcoding have triggered ample discussions about the significance, interpretation and applicability of this method (Jinbo et al. 2011, Krishna Krishnamurthy & Francis 2012, Coissac et al. 2016 and references therein, DeSalle & Goldstein 2019). Many authors explicitly state the urgent need for comprehensive reference databases in order to reliably determine query specimens’ identifications (Kress & Erickson 2008, Briski et al. 2011, Jinbo et al. 2011, Krishna Krishnamurthy & Francis 2012, DeSalle & Goldstein 2019). The qualitative prerequisites for these reference specimens are a broad coverage of the geographical and genetic range in order to ensure high certainty for the identification of conspecifics but also reliable distinction from other closely related species (Jinbo et al. 2011). This emphasizes the value and necessity of (national) species inventories, which might be laborious and costly to set up, but, once set up, provide an up-to-date picture of the national diversity of a specific taxonomic group (e.g., Knebelsberger et al. 2015, Hawlitschek et al. 2016, Zangl et al. 2020b). For example, building up the reference database for Austrian amphibians and reptiles revealed the presence of the only recently described Natrix helvetica in Austria and provided first evidence for the occurrence of the Italian waterfrog (Pelophylax bergeri), or at least its mitochondrial DNA, in Austria (Zangl et al. 2020b). The investigation of gudgeons in Austria proved the presence of two species/lineages, but also resulted in a third, previously unknown mitochondrial lineage (Zangl et al. 2020a). However, this case also represents a prime example of the pivotal importance of taxonomic expertise as well as the quality of reference databases, as specimens of the different mitochondrial lineages could not be distinguished based on morphological characters. Thus, attributing the resulting DNA barcodes to a certain species should be conducted with caution or even omitted in some cases.

The ambiguity of these examples highlights the need for further in-depth research and inevitably stresses the insufficiency of DNA barcoding data alone to describe new species (Jinbo et al. 2011, Zinger & Philippe 2016, DeSalle & Golstein 2019). Genomic data might provide the necessary resolution in some of these cases and has also already been proposed as a suitable means for the barcoding of e.g., plants, where previous single locus approaches failed (Kress & Erickson 2008, Coissac et al. 2016). However, additional data 153

is indispensable, like for example in the case of the description of Romanogobio skywalkeri (Friedrich et al. 2018) or the investigation of Austrian snow scorpionflies (Zangl et al. manuscript). In the latter case, even additional morphological and mitogenomic data only allowed for the prediction of cryptic diversity but not to undoubtedly give rise to new species. The reason therefore could be a rather rapid phylogenetic divergence with (ancient) incomplete lineage sorting, or ancient introgression/hybridization events, which poses another well discussed weakness of DNA barcoding. Many authors report the obvious inability of this method to distinguish between recently diverged species due to the lack of accumulated mutational differences. Additionally, the resolution is blurred by introgressive or hybridization events and ancient mitochondrial capture (Jinbo et al. 2011, Krishna Krishnamurthy & Francis 2012, Zinger & Philippe 2016). This becomes obvious at the hybridogenic species complex of green frogs (Pelophylax spp.) where different species combinations of parental specimens determine the species of the offspring. They can still be identified down to species level, with some difficulties though, based on morphology and bioacoustics. However, a species assignment based on DNA barcodes cannot be conducted reliably (Hawlitschek et al. 2016, Zangl et al. 2020b). Furthermore, some authors also complain about the semantic erosion of phylogenetic terms used in the barcoding context and critizise the interpretation and shallow phylogentic depth of barcoding data and their use for phylogenetic deductions (Jinbo et al. 2011, DeSalle & Goldstein 2019). This could be observed in the case of allochthonous Misgurnus species that were newly reported from Germany (Belle et al. 2017) and Austria (Zangl et al. 2020c). Due to varying depths of analyses, the barcoding data were interpreted differently and consequently, specimens most likely belonging to the same species (Misgurnus bipartitus) were assigned to different species in the two studies (Belle et al. 2017, Zangl et al. 2020c). Again, the inclusion of additional nuclear genetic data provided further support for the barcoding results.

In the case of the Austrian gudgeons, phylogentic inferences solely based on the barcoding data would have also been unsound and required additional sources of data. Furthermore, the systematic and taxonomic uncertainties regarding the species, and their respective distributions, that are present in the Austrian Danube system and the rest of Europe (Kottelat & Freyhof, 2007) complicated the interpretation. Hence, a complete re- evaluation of this family would be necessary in order to accurately assign DNA barcodes of the mitochondrial lineages to certain species.

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I refrain from providing a comprehensive technical explaination as to why DNA barcoding data in its current form and with the regularly applied standard substitution models and distance calculations is regarded as unsuitable for phylogentic inferences here, simply because it would by far exceed the frame of this discussion and the whole thesis. In addition, this was no declared aim of this thesis in the first place and this exact issue has already been discussed in length by various other authors (e.g., Jinbo et al. 2011, Zinger & Philippe 2016, DeSalle & Goldstein 2019).

However, I would like to restate that, based on the literature reviewed and on the basis of my own research presented in this thesis, DNA barcoding, when used in the way following current standards and conventions, provides only limited phylogenetic inferences which has to be considered for the interpretation as well as the semantic description of data. Furthermore, DNA barcoding data alone has to be regarded as insufficient to initiate taxonomic/systematic changes or to describe species new to science. Nonetheless, this method has proven effective for the distinction of species across a broad taxonomic range and showed its value and ease of use in detecting alien/invasive species and thus far unknown taxonomic units as well as cryptic diversity. Consequently, the content of this thesis confirms the proposed strengths but also the known weaknesses of DNA barcoding and the reference inventories provided to the scientific community as well as to the general public will aid in future basic and applied research depending on the exact identification of species.

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References

Abd-Rabou, S., Shalaby, H., Germain, J. F., Ris, N., Kreiter, P., & Malausa, T. (2012). Identification of mealybug pest species (Hemiptera: Pseudococcidae) in Egypt and France, using a DNA barcoding approach. Bulletin of Entomological Research, 102(5), 515–523. doi: 10.1017/S0007485312000041 Alberdi, A., Garin, I., Aizpurua, O., & Aihartza, J. (2012). The foraging ecology of the Mountain Long-eared bat Plecotus macrobullaris revealed with DNA mini- barcodes. PLoS ONE, 7(4). doi: 10.1371/journal.pone.0035692 Ardura, A., & Planes, S. (2017). Rapid assessment of non-indigenous species in the era of the eDNA barcoding: A Mediterranean case study. Estuarine, Coastal and Shelf Science, 188, 81–87. doi: 10.1016/j.ecss.2017.02.004 Baudrin, G., Roy, V., Gigon, A., & Dupont, L. (2020). Bar-HRM for identification of cryptic earthworm species. Pedobiologia, 80. doi: 10.1016/j.pedobi.2020.150634 Belle, C. C., Stoeckle, B. C., Cerwenka, A. F., Kuehn, R., Mueller, M., Pander, J., & Geist, J. (2017). Genetic species identification in weatherfish and first molecular confirmation of Oriental Weatherfish Misgurnus anguillicaudatus (Cantor, 1842) in Central Europe. Knowledge and Management of Aquatic Ecosystems, (418). doi: 10.1051/kmae/2017025 Blagoev, G. A., deWaard, J. R., Ratnasingham, S., deWaard, S. L., Lu, L., Robertson, J., … Hebert, P. D. N. (2016). Untangling taxonomy: A DNA barcode reference library for Canadian spiders. Molecular Ecology Resources, 16(1), 325–341. doi: 10.1111/1755-0998.12444 Briski, E., Cristescu, M. E., Bailey, S. A., & MacIsaac, H. J. (2011). Use of DNA barcoding to detect invertebrate invasive species from diapausing eggs. Biological Invasions, 13(6), 1325–1340. doi: 10.1007/s10530-010-9892-7 Caley, M. J., Fisher, R., & Mengersen, K. (2014). Global species richness estimates have not converged. Trends in Ecology and Evolution, Vol. 29, pp. 187–188. doi: 10.1016/j.tree.2014.02.002 Clare, E. L., Lim, B. K., Engstrom, M. D., Eger, J. L., & Hebert, P. D. N. (2007). DNA barcoding of Neotropical bats: Species identification and discovery within Guyana: Barcoding. Molecular Ecology Notes, 7(2), 184–190. doi: 10.1111/j.1471- 8286.2006.01657.x Coissac, E., Hollingsworth, P. M., Lavergne, S., & Taberlet, P. (2016). From barcodes to genomes: Extending the concept of DNA barcoding. Molecular Ecology, 25(7), 1423–1428. doi: 10.1111/mec.13549 Dejean, T., Valentini, A., Miquel, C., Taberlet, P., Bellemain, E., & Miaud, C. (2012). Improved detection of an alien invasive species through environmental DNA barcoding: The example of the American bullfrog Lithobates catesbeianus. Journal of Applied Ecology, 49(4), 953–959. doi: 10.1111/j.1365-2664.2012.02171.x

156

DeSalle, R., & Goldstein, P. (2019). Review and Interpretation of Trends in DNA Barcoding. Frontiers in Ecology and Evolution, 7(September), 1–11. doi: 10.3389/fevo.2019.00302 Doña, J., Diaz-Real, J., Mironov, S., Bazaga, P., Serrano, D., & Jovani, R. (2015). DNA barcoding and minibarcoding as a powerful tool for feather mite studies. Molecular Ecology Resources, 15(5), 1216–1225. doi: 10.1111/1755-0998.12384 Friedrich, T., Wiesner, C., Zangl, L., Daill, D., Freyhof, J., & Koblmüller, S. (2018). Romanogobio skywalkeri, a new gudgeon (Teleostei: Gobionidae) from the upper Mur River, Austria. Zootaxa, 4403(2). doi: 10.11646/zootaxa.4403.2.6 Galimberti, A., Assandri, G., Maggioni, D., Ramazzotti, F., Bazzi, G., Chiandetti, I., … Surdo, S. (n.d.). Italian Odonates in the Pandora’s Box: A Comprehensive DNA Barcoding Inventory Shows Taxonomic Warnings at the Holarctic Scale. Molecular Ecology Ressources, 21(1), 183-200. Galimberti, A., De Mattia, F., Losa, A., Bruni, I., Federici, S., Casiraghi, M., … Labra, M. (2013). DNA barcoding as a new tool for food traceability. Food Research International, Vol. 50, pp. 55–63. doi: 10.1016/j.foodres.2012.09.036 Geiser, E. (2018). How Many Animal Species are there in Austria? Update after 20 Years. In Acta ZooBot Austria (Vol. 155). Haring, E., Sattmann, H., & Szucsich, N. U. (2015). ABOL als Biodiversitätsnetzwerk- Struktur und Ziele taxonspezifischer Cluster. In Acta ZooBot Austria (Vol. 152). Hausmann, A., Haszprunar, G., & Hebert, P. D. N. (2011). Dna barcoding the geometrid fauna of bavaria (lepidoptera): Successes, surprises, and questions. PLoS ONE, 6(2). doi: 10.1371/journal.pone.0017134 Hawlitschek, O., Morinière, J., Dunz, A., Franzen, M., Rödder, D., Glaw, F., & Haszprunar, G. (2016). Comprehensive DNA barcoding of the herpetofauna of Germany. Molecular Ecology Resources, 16(1), 242–253. doi: 10.1111/1755- 0998.12416 Hawlitschek, O., Morinière, J., Lehmann, G. U. C., Lehmann, A. W., Kropf, M., Dunz, A., … Haszprunar, G. (2017). DNA barcoding of crickets, katydids and grasshoppers (Orthoptera) from Central Europe with focus on Austria, Germany and Switzerland. Molecular Ecology Resources, 17(5), 1037–1053. doi: 10.1111/1755-0998.12638 Hebert, P. D. N. P. D. N., Ratnasingham, S., Jeremy, R., DeWaard, J. R., & de Waard, J. R. (2003). Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species. Proceedings of the Royal Society of London. Series B: Biological Sciences, 270(Suppl 1), S96. doi: 10.1098/rsbl.2003.0025 Hellberg, R. S., Hernandez, B. C., & Hernandez, E. L. (2017). Identification of meat and poultry species in food products using DNA barcoding. Food Control, 80, 23– 28. doi: 10.1016/j.foodcont.2017.04.025 Hubert, N., Meyer, C. P., Bruggemann, H. J., Guérin, F., Komeno, R. J. L., Espiau, B., … Planes, S. (2012). Cryptic diversity in indo-pacific coral-reef fishes revealed by DNA-barcoding provides new support to the centre-of-overlap hypothesis. PLoS ONE, 7(3). doi: 10.1371/journal.pone.0028987

157

Huemer, P., Karsholt, O., & Mutanen, M. (2014). DNA barcoding as a screening tool for cryptic diversity: An example from Caryocolum, with description of a new species (Lepidoptera, Gelechiidae). ZooKeys, 404, 91–111. doi: 10.3897/zookeys.404.7234 Huemer, P., Wieser, C., Stark, W., Hebert, P. D. N., & Wiesmair, B. (2019). DNA barcode library of megadiverse Austrian Noctuoidea (Lepidoptera) - A nearly perfect match of Linnean taxonomy. Biodiversity Data Journal, 7. doi: 10.3897/BDJ.7.e37734 Jinbo, U., Kato, T., & Ito, M. (2011). Current progress in DNA barcoding and future implications for entomology. Entomological Science, 14(2), 107–124. doi: 10.1111/j.1479-8298.2011.00449.x Kassas, M. (2002). Biodiversity: Gaps in knowledge. Environmentalist, 22(1), 43–49. doi: 10.1023/A:1014520024945 Khaksar, R., Carlson, T., Schaffner, D. W., Ghorashi, M., Best, D., Jandhyala, S., … Amini, S. (2015). Unmasking seafood mislabeling in U.S. markets: DNA barcoding as a unique technology for food authentication and quality control. Food Control, 56, 71–76. doi: 10.1016/j.foodcont.2015.03.007 Knebelsberger, T., Dunz, A. R., Neumann, D., & Geiger, M. F. (2015). Molecular diversity of Germany’s freshwater fishes and lampreys assessed by DNA barcoding. Molecular Ecology Resources, 15(3), 562–572. doi: 10.1111/1755- 0998.12322 Kottelat, M., & Freyhof, J. (2007). Handbook of European freshwater fishes. Copeia, Vol. 2008, p. 646. Retrieved from http://agris.fao.org/agris- search/search.do?recordID=US201300126031 Kress, W. J., & Erickson, D. L. (2008). DNA barcodes: Genes, genomics, and bioinformatics. PNAS, 105(8), 2761–2762. Krishna Krishnamurthy, P., & Francis, R. A. (2012). A critical review on the utility of DNA barcoding in biodiversity conservation. Biodiversity and Conservation, 21(8), 1901–1919. doi: 10.1007/s10531-012-0306-2 Kundu, S., Kumar, V., Tyagi, K., & Chandra, K. (2018). Environmental DNA (eDNA) testing for detection of freshwater turtles in a temple pond. Herpetology Notes, Vol. 11, pp. 369–371. Lakra, W. S., Verma, M. S., Goswami, M., Lal, K. K., Mohindra, V., Punia, P., … Hebert, P. (2011). DNA barcoding Indian marine fishes. Molecular Ecology Resources, 11(1), 60–71. doi: 10.1111/j.1755-0998.2010.02894.x Madden, M. J. L., Young, R. G., Brown, J. W., Miller, S. E., Frewin, A. J., & Hanner, R. H. (2019). Using DNA barcoding to improve invasive pest identification at U.S. Ports-of-entry. PLoS ONE, 14(9). doi: 10.1371/journal.pone.0222291 Nguyen, S. N., Yang, J. X., Le, T. N. T., Nguyen, L. T., Orlov, N. L., Van Hoang, C., … Zhang, Y. P. (2014). DNA barcoding of Vietnamese bent-toed geckos (Squamata: Gekkonidae: Cyrtodactylus) and the description of a new species. Zootaxa, Vol. 3784, pp. 48–66. doi: 10.11646/zootaxa.3784.1.2

158

Packer, L., & Ruz, L. (2017). DNA barcoding the bees (Hymenoptera: Apoidea) of Chile: Species discovery in a reasonably well known bee fauna with the description of a new species of Lonchopria (Colletidae). Genome, 60(5), 414–430. doi: 10.1139/gen-2016-0071 Rabitsch, W., & Essl, F. (2009). Endemiten – Kostbarkeiten in Österreichs Pflanzen- und Tierwelt. (W. Rabitsch & F. Essl, Eds.). Klagenfurt und Wien: Naturwissenschaftlicher Verein für Kärnten und Umweltbundesamt GmbH. Rach, J., DeSalle, R., Sarkar, I. N., Schierwater, B., & Hadrys, H. (2008). Character- based DNA barcoding allows discrimination of genera, species and populations in Odonata. Proceedings of the Royal Society B: Biological Sciences, 275(1632), 237–247. doi: 10.1098/rspb.2007.1290 Raupach, M. J., Astrin, J. J., Hannig, K., Peters, M. K., Stoeckle, M. Y., & Wägele, J. W. (2010). Molecular species identification of Central European ground beetles (Coleoptera: Carabidae) using nuclear rDNA expansion segments and DNA barcodes. Frontiers in Zoology, 7. doi: 10.1186/1742-9994-7-26 Reid, B. N., Le, M., Mccord, W. P., Iverson, J. B., Georges, A., Bergmann, T., … Naro- Maciel, E. (2011). Comparing and combining distance-based and character-based approaches for barcoding turtles. Molecular Ecology Resources, 11(6), 956–967. doi: 10.1111/j.1755-0998.2011.03032.x Rodrigues, N. T., Saranholi, B. H., Angeloni, T. A., Pasqualotto, N., Chiarello, A. G., & Galetti, P. M. (2020). DNA mini-barcoding of leporids using noninvasive fecal DNA samples and its significance for monitoring an invasive species. Ecology and Evolution, 10(12), 5219–5225. doi: 10.1002/ece3.5863 Vasconcelos, R., Montero-Mendieta, S., Simó-Riudalbas, M., Sindaco, R., Santos, X., Fasola, M., … Carranza, S. (2016). Unexpectedly high levels of cryptic diversity uncovered by a complete DNA barcoding of reptiles of the socotra archipelago. PLoS ONE, 11(3). doi: 10.1371/journal.pone.0149985 Ward, R. D., Zemlak, T. S., Innes, B. H., Last, P. R., & Hebert, P. D. N. (2005). DNA barcoding Australia’s fish species. Philosophical Transactions of the Royal Society B: Biological Sciences, 360(1462), 1847–1857. doi: 10.1098/rstb.2005.1716 Yanqing, C., Bo, W., Ping, W., Bisheng, H., Hegang, L., Chao, X., … Shilin, C. (2019). Rapid identification of common medicinal snakes and their adulterants using the Bar-HRM analysis method. Mitochondrial DNA Part A: DNA Mapping, Sequencing, and Analysis, 30(2), 367–374. doi: 10.1080/24701394.2018.1532417 Zangl, Lukas, Kunz, G., Berg, C., & Koblmüller, S. (2019). First records of the parthenogenetic Surinam cockroach Pycnoscelus surinamensis (Insecta: Blattodea: Blaberidae) for Central Europe. Journal of Applied Entomology, 143(3), 308–313. doi: 10.1111/jen.12587 Zangl, Lukas, Daill, D., Gessl, W., Friedrich, T., & Koblmüller, S. (2020a). Austrian gudgeons of the genus Gobio (Teleostei: Gobionidae): A mixture of divergent lineages. Journal of Zoological Systematics and Evolutionary Research, 58(1), 327–340. doi: 10.1111/jzs.12340

159

Zangl, L., Daill, D., Schweiger, S., Gassner, G., & Koblmüller, S. (2020b). A reference DNA barcode library for Austrian amphibians and reptiles. PLoS ONE, 15(3). doi: 10.1371/journal.pone.0229353 Zangl, Lukas, Jung, M., Gessl, W., Koblmüller, S., & Ratschan, C. (2020c). Oriental or not: First record of an Alien Weatherfish (Misgurnus) species in Austria verified by molecular data. BioInvasions Records, 9(2), 375–383. doi: 10.3391/bir.2020.9.2.23 Zangl, Lukas, Oberreiter, H., Huss, H., Stabentheiner, E., Sturmbauer, C., & Koblmüller, S. (2020d). Discriminating larvae of two syntopic Cychramus species (Coleoptera, Nitidulidae) by means of bar-HRM analysis. Molecular Biology Reports, 47, 8251-8257. doi: 10.1007/s11033-020-05786-9 Zinger, L., & Philippe, H. (2016). Coalescing molecular evolution and DNA barcoding. Molecular Ecology, 25(9), 1908–1910. doi: 10.1111/mec.13639

160