Journal of Fish Biology (2015)

doi:10.1111/jfb.12707, available online at wileyonlinelibrary.com

DNA barcoding and morphological identificationof neotropical ichthyoplankton from the Upper Paraná

and São Francisco

R. A. Becker, N. G. Sales, G. M. Santos, G. B. Santosand D. C. Carvalho*

Pontifícia Universidade Católica de Minas Gerais, Programa de Pós-graduação em Zoologiade Vertebrados, Laboratório de Genética da Conservação, Rua Dom José Gaspar, 500,

30535-901 Belo Horizonte, MG, Brazil

(Received 6 October 2014, Accepted 1 April 2015)

The identification of fish larvae from two neotropical hydrographic basins using traditional morpho-logical taxonomy and DNA barcoding revealed no conflicting results between the morphological andbarcode identification of larvae. A lower rate (25%) of correct morphological identification of eggsas belonging to migratory or non-migratory species was achieved. Accurate identification of ichthy-oplankton by DNA barcoding is an important tool for fish reproductive behaviour studies, correctestimation of biodiversity by detecting eggs from rare species, as well as defining environmental andmanagement strategies for fish conservation in the neotropics.

© 2015 The Fisheries Society of the British Isles

Key words: biodiversity; eggs; fishes; fresh water; larvae; molecular taxonomy.

INTRODUCTION

Unambiguous identification of fish eggs and larvae is an important tool for fish ecologyand conservation. For instance, it may allow the detection of spawning areas, the moni-toring of fish stocks affected by dams and improve fisheries management and conserva-tion policies (Baumgartner et al., 2004; Reynalte-Tataje et al., 2004; Agostinho et al.,2007; Moura et al., 2008; Valdez-Moreno et al., 2010). The ontogenetic morphologi-cal variation of larvae and the extreme biological diversity of neotropical ichthyofauna(around 3500 described species) (Reis et al., 2003) means that studies related to eggand larva identification are restricted to a few well-studied areas (Nakatani et al., 2001).As a consequence of these issues, the neotropical region has the lowest number ofstudies related to ichthyoplankton identification, despite its species diversity (Oliveiraet al., 2008; Hermes-Silva et al., 2009). Moreover, all published work to date regard-ing egg and larval identification has been based solely on morphological characteristicsand rarely reached identification to the species level (Nakatani et al., 2001; Graça &Pavanelli, 2007). In some cases, the studies analysed only abundance of ichthyoplank-ton, avoiding any tentative taxonomic identification of larvae (Gogola et al., 2010).

*Author to whom correspondence should be addressed. Tel.: +55 (31) 3319 4967; email: danielcarvalho@pucminas.br

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Therefore, a major obstacle for a broader use of fish larvae and egg surveys istheir unambiguous identification (Gleason & Burton, 2012). For instance, Ko et al.(2013) morphologically identified larvae from the Taiwan coast and reported that only13⋅5% were identified to the species level and 43% could not be identified due tothe lack of diagnostic morphological traits. On the other hand, using a DNA-basedtechnique (i.e. DNA barcoding), 69% of all larvae were identified to the species level(Ko et al., 2013). Reported morphological difficulties are normally due to sharedmorphological features and intraspecific morphological variation (Bialetzki et al.,1998, 2001, 2008). Additionally, it is only possible to differentiate fish eggs asbelonging to migratory or non-migratory species as the perivitellinic space is the onlydiagnostic characteristic available (Nakatani et al., 2001; Leite et al., 2007; Oliveira &Ferreira, 2008).

A broad range of molecular tools has been used to improve ichthyoplankton iden-tification accuracy, including species-specific fluorescent-labelled probes (Gleason &Burton, 2012) to a high-throughput robotic sample handling process (Richardson et al.,2007). Most studies make use of developed libraries for species identification throughDNA barcoding (650 bp of the mitochondrial gene coI), a technique which allowsthe identification of samples lacking diagnostic morphological characteristics, suchas processed fish products (e.g. fish fillets and caviar), stomach contents as well asfish larvae and eggs (Desalle & Amato, 2004; Carreon-Martinez et al., 2011; Car-valho et al., 2011a; Ko et al., 2013; Arroyave & Stiassny, 2014; Loh et al., 2014).For instance, Loh et al. (2014) developed and applied DNA barcoding to identify 14of the 16 species inhabiting the Brisbane River (Australia), including a quantitative(q)PCR assay for species-specific detection and quantification. For marine fish species,results using DNA barcoding have shown a high error rate of morphological identifi-cation to the species level of eggs and larvae (Ahlstrom & Moser, 1976; Shao et al.,2002). When considering Brazilian biodiversity, with over 2587 known species repre-senting around 25% of the described freshwater fish species (Buckup et al., 2007), how-ever, the accuracy of morphological identification of ichthyoplankton has not yet beeninvestigated.

In order to investigate the gain achieved by integrating DNA barcoding and neotrop-ical ichthyoplankton taxonomy, the accuracy of the morphological identification oflarvae conducted by two independent laboratories was investigated and compared withidentification provided by DNA barcodes. Secondly, the efficiency of morphologicaldiagnostic feature for egg identification (i.e. perivitellinic space) was evaluated in dif-ferentiating migratory from non-migratory freshwater fish species.

MATERIALS AND METHODS

S A M P L I N GIchthyoplankton samples were obtained from Nova Ponte reservoir, located on the Araguari

River (upper Paraná River basin; 19∘ 19′ 3⋅57′′ S; 46∘ 49′ 23⋅26′′ W) and the Pará River (SãoFrancisco Basin; 19∘ 45′ 46⋅10′′ S; 44∘ 53′ 57⋅58′′ W), south-eastern Brazil. The São Fran-cisco River and the upper Paraná River Basin encompass the most urbanized and exploited areaof Brazil, representing two major South American basins. Inventories of their freshwater fishfauna found at least 205 and 310 valid species in each of the rivers, respectively; however, manyputative species are yet to be described (Alves et al., 2007; Langeani et al., 2007). DNA barcode

© 2015 The Fisheries Society of the British Isles, Journal of Fish Biology 2015, doi:10.1111/jfb.12707

D NA BA R C O D I N G O F N E OT RO P I C A L I C H T H YO P L A N K T O N 3

libraries have already been developed for most species from both fish faunas (Carvalho et al.,2011b; Pereira et al., 2013).

A 500 μm conic net 1⋅45 m long and 38 cm in diameter was used for sampling. All ichthy-oplankton samples were fixed in ethanol (100%) and measured (total length, LT) using a stereo-scopic microscope with a micrometre ruler coupled to the ocular lens. Before extracting DNA,the same larvae were morphologically identified by two independent research laboratories. Asall eggs and larvae were macerated for DNA extraction, photographs were taken and kept asvouchers. Larvae and fish eggs are classified as zooplankton; therefore, no permit is needed fortheir collection in Brazil and no specific permission was required for collecting zooplanktonfrom the sample sites.

M O R P H O L O G I C A L I D E N T I F I C AT I O NEggs were identified as belonging to migratory species (eggs with a large perivitellinic space)

and non-migratory (reduced perivitellinic space) (Nakatani et al., 2001; Leite et al., 2007;Oliveira & Ferreira, 2008) according to Agostinho et al. (2003).

Larvae were identified to the lowest possible taxonomic level by two separate laboratories: theConservation Genetics Laboratory at the Pontifícia Universidade Católica de Minas Gerais (Lab-oratory LGC-PUC), Brazil and the Ichthyoplankton Laboratory from the Núcleo de Pesquisasem Limnologia e Aquicultura (Laboratory NUPELIA), State University of Maringá, Brazil.The larvae’s embryonic development was defined according to its ontogenetic development:larval yolk sac, preflexion, flexion and postflexion according to morphological traits suggestedby Ahlstrom & Moser (1976) and Nakatani et al. (2001).

Larvae belonging to the order Characiformes were identified by the absence of barbels, dermicplates, protractile mouth and the presence of an anal opening in the middle of the body. The orderGymnotiformes were characterized by the presence of the anal opening located on the anteriorhalf of the body, a falciform-shaped body and the absence of a caudal fin. The order Siluriformeswas differentiated by the presence of barbels. The Anostomidae has two small chromatophoreson the frontal head region, and the family Characidae was identified by excluding the other char-acteristics that define other families from the Characiformes order. The family Poecilidae hashighly developed eyes and a rounded caudal fin (Nakatani et al., 2001; Graça & Pavanelli, 2007).

D NA BA R C O D I N GDNA was extracted using a modified salting-out protocol (Sunnucks & Hales, 1996) or com-

mercial kits (Nucleo Spin kit and Nucleo Spin XS kit; Macherey-Nagel; www.mn-net.com),following the manufacturer’s instructions. Before DNA extraction, eggs and larvae were washedin ultrapure water and then macerated. Partial cytochrome c oxidase I (coI) gene sequences ofc. 650 bp were amplified by PCR using primers FishF1 and FishR1 (Ward et al., 2009). PCRconsisted of 1⋅0 μl of buffer, 0⋅2 μl of deoxynucleotide triphosphate (dNTP) (10 mM), 0⋅3 μlof MgCl2, 0⋅2 μl of each primer (10 μM), 0⋅1 μl of Taq polymerase, 7⋅0 μl of ultrapure waterand 1⋅0 μl of genomic DNA. PCR conditions comprised an initial step of 2 min at 95∘ C fol-lowed by 35 cycles of 30 s at 95∘ C, 30 s at 54∘ C and 60 s at 72∘ C, and one final step of10 min at 72∘ C. PCR products were visualized in 1% agarose gel, and successfully amplifiedsamples were selected for sequencing. DNA sequencing was conducted in both directions, andsequences were obtained using an automated DNA sequencing device 3500 (Life technologies;www.lifetechnologies.com).

DATA A NA LY S I SThe consensus DNA sequence was obtained, checked visually using the DNA Baser

software (www.dnabaser.com) and ambiguous ends were removed. All sequences were com-pared with the existing Barcode of Life Data (BOLD; www.boldsystems.org) and GenBank(www.ncbi.nlm.nih.gov/genbank) databases for sample identification using the BOLD Iden-tification tool and basic local-alignment search tool (BLAST), respectively. DNA sequences,images and geographic location of all ichthyoplankton were deposited in BOLD under accessionnumbers LARVA00114–LARVA09714.

© 2015 The Fisheries Society of the British Isles, Journal of Fish Biology 2015, doi:10.1111/jfb.12707

4 R . A . B E C K E R E T A L.

(a)

Morphology

DNA barcode P. maculatus(M)

P. maculatus(M)

P. maculatus(M)

L. octofasciatus(N-M)

L. octofasciatus(N-M)

P. maculatus(M)

Migratory Migratory ? Non-migratory Non-migratory Non-migratory

(b) (c) (d) (e) (f)

Fig. 1. Morphological and DNA barcode identification of neotropical fish eggs. (a, b), Eggs were identified asmigratory fish species due to the reduced perivitellinic space. (d, e, f) Eggs presenting developed periv-itellinic space were classified as non-migratory species. The visualization of perivitellinic space of egg (c)was hampered due to the presence of collated organic matter. Eggs identified through DNA barcoding asmigratory species Pimelodus maculatus (a, b, c, f) varied widely in their perivitellinic space, similar toeggs of the non-migratory species Leporinus octofasciatus (d, e). Migratory and non-migratory species areindicated as M and N-M, respectively.

RESULTS

M O R P H O L O G I C A L I D E N T I F I C AT I O N

A total of 97 ichthyoplankton samples, consisting of 40 eggs and 57 larvae, from theupper Paraná River and the São Francisco River were analysed. Eggs varied in size(mean± s.e. = 1⋅00± 0⋅13 mm), colour, shape and integrity state (Fig. 1). Morpholog-ical identification according to the perivitellinic space resulted in the classification of16% as belonging to migratory species as they showed a large perivitellinic space, and84% as non-migratory due to a reduced perivitellinic space (Table I).

Larvae had mean± s.d. LT of 4⋅75± 0⋅27 mm and varied greatly in their ontoge-netic stage, colour and integrity state (Fig. 2). Classification of the larvae’s ontogeneticstage consisted of 9% having embryonic larval yolk-sac development, 65% were atpreflexion stage (disappearance of yolk and no notochord flexion), 14% were at flex-ion stage (showing initial notochord flexion and initial caudal fin rays) and 12% wereat postflexion (complete notochord flexion and dorsal-fin rays).

None of the larvae were identified to the species level, 3⋅5% were identified to thegenus level (Hoplias sp.), 8⋅8% to the family and 75⋅4% to the order level. Detailedtaxonomic identification from LGC-PUC laboratory revealed that 77⋅2% of all larvae

Table I. Rates of morphological and DNA barcode identification of 40 fish eggs belonging tomigratory or non-migratory species

Morphology DNA barcode

% n % n

Migratory 16 5 67⋅5 27Non-migratory 84 35 32⋅5 13Total 100 40 100 40

© 2015 The Fisheries Society of the British Isles, Journal of Fish Biology 2015, doi:10.1111/jfb.12707

D NA BA R C O D I N G O F N E OT RO P I C A L I C H T H YO P L A N K T O N 5

(a)

Ontogeneticstage

Larval yolk sac Characidae K. moenkausii

S. brandtiiSerrasalmus sp.Preflexion

Flexion Apareiodon sp. A. affinis

A. affinisApareiodon sp.Postflexion

Preflexion ? A. affinis

Morphology DNA barcode

(b)

(c)

(d)

(e)

Fig. 2. Morphological and DNA barcode identification of neotropical fish larvae. Distinct ontogenetic larvalstages: (a) larval yolk sac, (b) preflexion, (c) flexion, (d) postflexion and their identification based on mor-phology and DNA barcoding are shown. Larva (e) is an example of a damaged sample lacking any usefultaxonomic characteristic.

belonged to the order Characiformes, 1⋅7% to the order Cyprinodontiformes, 3⋅5% tothe order Gymnotiformes and 5⋅3% to the order Siluriformes. The family Anostomidaewas represented by 1⋅7%, Characidae by 5⋅3% and Poecilidae by 1⋅7% of all larvalsamples. Due to morphological damage, 12⋅3% of all larvae were not considered foridentification.

Larval identification conducted by NUPELIA laboratory allowed the identificationof 24⋅5% to the genus level, 57⋅9% to family level and 5⋅3% to order level (Table II).Larvae identified to the genus level consisted of 3⋅5% Astyanax sp., 8⋅8% Apareiodonsp., 5⋅3% Serrasalmus sp., 3⋅5% Hoplias sp. and 3⋅5% Eigenmannia sp. Identificationto family level found 1⋅7% Anostomidae, 1⋅7% Poecilidae and 54⋅4% Characidae, and5⋅3% of larvae were identified to the order Siluriformes. Due to damaged larvae, 12⋅3%were not considered for identification.

Higher taxonomic morphological identification of larvae was strongly correlatedto ontogenetic development (Table II). For instance, when considering PUC-LGC’sresults, no larvae at yolk-sac stage were identified to the genus level, but identified20% to the family and 80% to order level. At the preflexion stage, 81% of larvae couldbe identified to order level and 19% were too damaged to be classified. Consideringthe flexion ontogenetic stage, 12⋅5% of the larvae could be identified to the genus,12⋅5% to the family and 75% to the order level. Taxonomical identification resultsobtained by NUPELIA identified 60% to order and 40% to family level of larvaeat yolk-sac stage. Furthermore, 68% of larvae at preflexion stage were identified tofamily, 13% to genus level and 19% were not identified due to morphological damage.At flexion ontogenetic stage, 12% of larvae were identified to family and 88% to the

© 2015 The Fisheries Society of the British Isles, Journal of Fish Biology 2015, doi:10.1111/jfb.12707

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Table II. Percentage accuracies of ichthyoplankton identification to each taxonomic level bymorphology (Laboratory LGC-PUC and Laboratory NUPELIA) and DNA barcoding

Taxonomic level Yolk sac Preflexion Flexion Postflexion

LGC-PUC Species 0 0 0 0Genus 0 0 12⋅5 14Family 20 0 12⋅5 43Order 80 81* 75 43

NUPELIA Species 0 0 0 0Genus 0 13 88 43Family 40 68* 12 57Order 60 0 0 0

DNA barcode Species 100 100 100 100

*Some larvae were damaged and therefore not included. LGC-PUC, Conservation Genetics Laboratory,Pontifícia Universidade Católica de Minas Gerais, Brazil; NUPELIA, Ichthyoplankton Laboratory, Núcleode Pesquisas em Limnologia e Aquicultura, State University of Maringá, Brazil.

genus level. At the postflexion stage, 57% of larvae were identified to family and 43%to the genus level (Table II).

M O L E C U L A R I D E N T I F I C AT I O N (D NA BA R C O D I N G )

Barcode sequences (684 bp on average) for all 40 eggs and 57 larvae were success-fully obtained. Barcodes obtained from eggs and larvae were compared against theGenBank and BOLD databases. For all barcodes, DNA sequence similarities were>99% (Tables SI and SII, Supporting Information).

Unexpectedly, only nine eggs were similarly designated to migratory or non-migratory species using morphological features when compared with DNA barcodingidentification, resulting in an accuracy rate of 22⋅5%. DNA barcoding results showedthat 67⋅5% of all eggs belonged to a single migratory species: Pimelodus maculatusLacépède 1803 and 32⋅5% belonged to four non-migratory species: Galeocharaxknerii (Steindachner 1879) (12⋅5%), Leporinus octofasciatus Steindachner 1915(10%), Leporinus paranensis Garavello & Britski 1987 (2⋅5%) and Pimelodella meekiEigenmann 1910 (7⋅5%) (Table SI, Supporting Information).

When considering larval molecular identification, 14 species were recovered:Astyanax altiparanae Garutti & Britski 2000 (3⋅5%), Bryconamericus stramineusEigenmann 1908 (1⋅8%), Knodus moenkhausii (Eigenmann & Kennedy 1903)(36⋅7%), Piabina argentea Reinhardt 1867 (7%), Apareiodon affinis (Steindachner1879) (15⋅8%), Myleus micans (Lütken 1875) (10⋅5%), Serrasalmus brandtii Lütken1875 (7%), Leporinus obtusidens (Valenciennes 1837) (1⋅8%), Hoplias malabaricus(Bloch 1794) (3⋅5%), Bergiaria westermanni (Lütken 1874) (3⋅5%), Iheringichthyslabrosus (Lütken 1874) (1⋅8%), Pimelodus fur (Lütken 1874) (1⋅8%), Eigenmanniavirescens (Valenciennes 1836) (3⋅5%) and Poecilia reticulata Peters 1859 (1⋅8%)(Table SII, Supporting Information). No discrepancy between DNA barcoding andmorphologically identified larvae was observed. The morphologically identified lar-vae, however, were resolved to the family or genus level (Laboratory LGC-PUC 3⋅5%and Laboratory NUPELIA 24⋅6%); by using barcodes, all were identified to specieswith high sequence similarity (99–100%).

© 2015 The Fisheries Society of the British Isles, Journal of Fish Biology 2015, doi:10.1111/jfb.12707

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DISCUSSION

Identification through DNA barcoding overcame the lack of morphological charac-teristics and ontogenetic variation, allowing the identification of all sampled ichthy-oplankton. DNA barcoding reached a greater taxonomic resolution complementingtraditional morphological taxonomy. Due to difficulties in ichthyoplankton identifi-cation, DNA barcoding provides an important taxonomic tool for regions that alreadyhave barcode libraries available, such as the two river basins analysed in this study(Carvalho et al., 2011b; Pereira et al., 2013).

The low accuracy rate (25%) observed using morphological techniques when identi-fying eggs as belonging to migratory or non-migratory species (Table I) clearly demon-strates that the large perivitellinic space for migratory species and reduced perivitellinicspace for non-migratory species (Fig. 1) are not informative morphological character-istics. For instance, eggs from the non-migratory species L. octofasciatus, identified byDNA barcoding, showed a developed perivitellinic space [Fig. 1(d)] while the migra-tory species P. maculatus showed a reduced perivitellinic space [Fig. 1(a)]. Migratoryand non-migratory eggs also showed similar shape, colour, size and perivitellinic space(Fig. 1). Moreover, great intraspecific morphological variations were observed for theeggs of P. maculatus [Fig. 1(a), (b), (c), (f)]. In some cases, the presence of collatedorganic matter [Fig. 1(c)] and damaged morphological characteristics made any mor-phological taxonomic inference impossible [Fig. 1(c)]. Shao et al. (2002) reported thatmorphological characteristics were less informative when compared with molecularidentification even when more refined morphological techniques for identifying fisheggs were applied (i.e. light microscopy and scanning electron microscopy).

Due to the low accuracy rates reported for morphological marine larvae identifica-tion when compared with DNA barcoding (Ko et al., 2013), a similar or lower accuracywhen dealing with the megadiverse neotropical fish fauna was expected. Despite differ-ent levels of taxonomic resolution, disagreement when comparing morphological andDNA barcoding identification was not observed. Larval identification using DNA bar-coding, however, resulted in a better taxonomic resolution when compared with tradi-tional morphological taxonomy from both laboratories, especially for the early embry-onic phase (i.e. larval yolk-sac stage), as well as allowing damaged sample identifica-tion (Table II). For instance, no larvae at larval yolk-sac stage could be identified to thegenus level, but when considering the last developmental ontogenetic stage of postflex-ion, 43% of larvae were correctly identified to the genus level (Table II). Larvae in theyolk-sac ontogenetic stage show very few taxonomically useful morphological char-acteristics, making their identification to genus level speculative (Fig. 2). In this onto-genetic phase, characteristics are similar between different species, including speciesbelonging to different families (Snyder, 1981; Bialetzki et al., 1998). Specimens thatpresented damaged morphological characteristics, such as sample larvae (Fig. 2), weresuccessfully identified as A. affinis by DNA barcoding only, which illustrates a recur-rent problem when identifying ichthyoplankton solely based on morphological traits.

Interestingly, through the use of DNA barcoding, eggs from species not yet registeredfor this section of the upper Paraná River were detected, such as: K. moenkhausii,L. paranensis and P. meeki, all showed high DNA sequence similarity (99–100%)(Table SI, Supporting Information). Species assessments conducted in the upper ParanáBasin (Nova Ponte Reservoir) have not detected these fishes (unpubl. data). As theseare native species already described in the lower parts of the Paraná Basin, they may

© 2015 The Fisheries Society of the British Isles, Journal of Fish Biology 2015, doi:10.1111/jfb.12707

8 R . A . B E C K E R E T A L.

occur in the upper region but have not yet been collected by traditional survey meth-ods. Therefore, this is the first record of those species in this region, based solely onmolecular data from ichthyoplankton.

In conclusion, the ichthyoplankton identification to the species level through DNAbarcoding is an efficient tool for the neotropical megadiverse realm, complementingand enhancing traditional morphological taxonomy. The upper Paraná and São Fran-cisco River basins have a large barcode data set available, due to barcode libraries beingalready available for their ichthyofauna (Carvalho et al., 2011b; Pereira et al., 2013),which explains the great rate of identification of eggs and larvae in the present work tothe species level (100% of identification with 99–100% sequences similarities). Withthe unfolding of the Brazilian Barcode of Life Project (BrBol; http://brbol.org/pt-br/),ichthyoplankton identification by DNA barcoding may be applicable to all river basinsin Brazil providing unprecedented information on fish reproduction effects due todamming, detection of species-specific reproduction sites, recovery of hidden fishbiodiversity as well as benefiting environmental and fish management conservationin the neotropics. Moreover, the developing of non-destructive DNA extraction fromlarvae (Alvarado Bremer et al., 2014) will allow the preservation of larvae vouchersand the performance of re-evaluation of diagnostic morphological or meristic charac-teristics, helping integrate morphological and molecular ichthyoplankton taxonomy.The accuracy of species identification via DNA barcoding, however, is ultimatelydependent on the accuracy of morphology-based taxonomic assessment of voucherspecimens whose barcodes are available in databases such as GenBank and BOLD.

We are grateful to A. Bialetzki and her team for larvae identification performed at NUPELIA;B. Sanches, I. Penido, L. Carvalho, G. N. Salvador, M. L. Pugedo and V. Borges from Genéticada Conservação Lab (PUC Minas) for their assistance and helping with sample collection.We thank BrBol/CNPq (564953/2010-5), FAPEMIG, CEMIG (Projeto Peixe Vivo) andCAPES – PRO-EQUIPAMENTOS (783380/2013) for financial support.

Supporting Information

Supporting Information may be found in the online version of this paper:Table SI. Summary of morphological and DNA barcode identification of eggs. Accu-racy rate between morphological and barcoding identification is summarized at the endof the tableTable SII. Summary of morphological and DNA barcode identification of larvaeobtained from the upper Paraná River basin (UP) and the São Francisco River basin(SF). Due to damaged samples, some larvae were not considered for morphologicalidentification (−). Accuracy rate between morphological and barcoding identificationis summarized at the end of the table

ReferencesAgostinho, A. A., Gomes, L. C., Suzuki, H. I. & Júlio, H. F. Jr. (2003). Migratory fishes of

the upper Paraná River basin, Brazil. In Migratory Fishes of South America: Biology,Fisheries and Conservation Status (Carolsfeld, J., Harvey, B., Ross, C. & Baer, A., eds),pp. 19–98. Victoria, BC: World Fisheries Trust.

Agostinho, A. A., Marques, E. E., Agostinho, C. S., Almeida, D. D., Oliveira, R. D. & Melo,J. D. (2007). Fish ladder of Lajeado Dam: migrations on one-way routes? NeotropicalIchthyology 5, 121–130. doi: 10.1590/S1679-62252007000200005

© 2015 The Fisheries Society of the British Isles, Journal of Fish Biology 2015, doi:10.1111/jfb.12707

D NA BA R C O D I N G O F N E OT RO P I C A L I C H T H YO P L A N K T O N 9

Ahlstrom, E. H. & Moser, H. G. (1976). Eggs and larvae of fishes and their role in systematicinvestigations and in fisheries. Revue des Travaux de l’Institut des Peches Maritimes 40,379–398.

Alvarado Bremer, J. R., Smith, B. L., Moulton, D. L., Lu, C. P., & Cornic, M. (2014). Shakeand stew: a non-destructive PCR–ready DNA isolation method from a single preservedfish larva. Journal of Fish Biology 84, 267–272. doi: 10.1111/jfb.12280.

Alves, C. B. M., Vieira, F. & Pompeu, P. S. (2007). Programa Zoneamento Ecológico –Econômico. In Caderno Temático: Biodiversidade (Vizentin, R. R., ed.), pp. 110–130.Brasília: MMA/SEDR/SBF.

Arroyave, J. & Stiassny, M. L. (2014). DNA barcoding reveals novel insights into pterygophagyand prey selection in distichodontid fishes (Characiformes: Distichodontidae). Ecologyand Evolution 4, 4534–4542. doi: 10.1002/ece3.1321

Baumgartner, G., Nakatani, K., Gomes, L. C., Bialetzki, A. & Sanches, P. V. (2004). Identifica-tion of spawning sites and natural nurseries of fishes in the upper Paraná River, Brazil.Environmental Biology of Fishes 71, 115–125. doi: 10.1007/s10641-003-0098-z

Bialetzki, A., Sanches, P. V., Baumgartner, G. & Nakatani, K. (1998). Caracterização mor-fológica e distribuição temporal de larvas e juvenis de Apareiodon affinis (Steindachner)(Osteichthyes, Parodontidae) no alto rio Paraná, Paraná. Revista Brasileira de Zoologia15, 1037–1047. doi: 10.1590/S0101-81751998000400021

Bialetzki, A., Baumgartner, G., Sanches, P. V., Galuch, A. V., Luvisto, M. A., Nakatani, K.,Makrakis, M. C. & Borges, M. E. E. (2001). Caracterização do desenvolvimento inicialde Auchenipterus osteomystax (Osteichthyes, Auchenipteridae) da bacia do rio Paraná,Brasil. Acta Scientiarum Biological Sciences 23, 377–382. doi: 10.4025/actascibi-olsci.v23i0.2692

Bialetzki, A., Sanches, P. V., Baumgartner, G., Makrakis, M. C. & Taguti, T. L. (2008).Desenvolvimento inicial de Hoplias aff. malabaricus (Bloch, 1794) (Osteichthyes,Erythrinidae) da planície alagável do alto rio Paraná, Brasil. Acta Scientiarum BiologicalSciences 30, 141–149. doi: 10.4025/actascibiolsci.v30i2.3608

Buckup, P. A., Menezes, A. & Ghazzi, N. A. (2007). Catálogo das espécies de peixes de águadoce do Brasil, Vol. 1. Rio de Janeiro: Museu Nacional.

Carreon-Martinez, L., Johnson, T. B., Ludsin, S. A. & Heath, D. D. (2011). Utilization of stom-ach content DNA to determine diet diversity in piscivorous fishes. Journal of Fish Biology78, 1170–1182. doi: 10.1111/j.1095-8649.2011.02925.x

Carvalho, D. C., Neto, D. A., Brasil, B. S. & Oliveira, D. A. (2011a). DNA barcoding unveils ahigh rate of mislabeling in a commercial freshwater catfish from Brazil. MitochondrialDNA 22, 97–105. doi: 10.3109/19401736.2011.588219

Carvalho, D. C., Oliveira, D. A., Pompeu, S., Leal, C. G., Oliveira, C. & Hanner, R. (2011b).Deep barcode divergence in Brazilian freshwater fishes: the case of the São FranciscoRiver basin. Mitochondrial DNA 22, 80–86. 10.3109/19401736.2011.588214

DeSalle, R. & Amato, G. (2004). The expansion of conservation genetics. Nature ReviewsGenetics 5, 702–712. doi: 10.1038/nrg1425

Gleason, L. U. & Burton, R. S. (2012). High throughput molecular identification of fish eggsusing multiplex suspension bead arrays. Molecular Ecology Resources 12, 57–66. doi:10.1111/j.1755-0998.2011.03059.x

Gogola, T. M., Daga, V. S., da Silva, P. R., Sanches, P. V., Gubiani, E. A., Baumgartner, G. &Delariva, R. L. (2010). Spatial and temporal distribution patterns of ichthyoplankton in aregion affected by water regulation by dams. Neotropical Ichthyology 8, 341–349. doi:10.1111/eff.12007

Graça, W. J. & Pavanelli, C. S. (2007). Peixes da planície de inundação do alto rio Paraná eáreas adjacentes. Maringá: Editora da Universidade Estadual de Maringá.

Hermes-Silva, S., Reynalte-Tataje, D. & Zaniboni-Filho, E. (2009). Spatial and temporal dis-tribution of ichthyoplankton in the upper Uruguay River, Brazil. Brazilian Archives ofBiology and Technology 52, 933–944. 10.1590/S1516-89132009000400017

Ko, H. L., Wang, Y. T., Chiu, T. S., Lee, M. A., Leu, M. Y., Chang, K. Z. & Shao, K. T. (2013).Evaluating the accuracy of morphological identification of larval fishes by applying DNAbarcoding. PLoS One 8, e53451. doi: 10.1371/journal.pone.0053451

© 2015 The Fisheries Society of the British Isles, Journal of Fish Biology 2015, doi:10.1111/jfb.12707

10 R . A . B E C K E R E T A L.

Langeani, F., Castro, R. M. C., Oyakawa, O. T., Shibatta, A. O., Pavanelli, C. S. & Casatti, L.(2007). Diversidade da ictiofauna do Alto Rio Paraná: composição atual e perspectivasfuturas. Biota Neotropica 7, 181–197.

Leite, R. G., Cañas, C., Forsberg, B., Barthem, R. & Goulding, M. (2007). Larvas dos grandesbagres migradores. Manaus: Instituto Nacional de Pesquisas da Amazônia/Asociaciónpara La Conservación de la Cuenca Amazónica.

Loh, W. K. W., Bond, P., Ashton, K. J., Roberts, D. T. & Tibbetts, I. R. (2014). DNA bar-coding of freshwater fishes and the development of a quantitative qPCR assay for thespecies-specific detection and quantification of fish larvae from plankton samples. Jour-nal of Fish Biology 85, 307–328. doi: 10.1111/jfb.12422

Moura, T., Silva, M. C., Figueiredo, I., Neves, A., Muñoz, P. D., Coelho, M. M. & Gordo, L. S.(2008). Molecular barcoding of north-east Atlantic deep-water sharks: species identifica-tion and application to fisheries management and conservation. Marine and FreshwaterResearch 59, 214–223. doi: 10.1071/mf07192

Nakatani, K., Agostinho, A. A., Baumgartner, G., Bialetzki, A., Sanches, P. V., Makrakis, M.C. & Pavanelli, C. S. (2001). Ovos e larvas de peixes de água doce: desenvolvimento emanual de identificação, 1st edn. Maringá: Editora da Universidade Estadual de MaringáEDUEM.

Oliveira, E. C. & Ferreira, E. J. G. (2008). Spawning areas, dispersion and microhabitats offish larvae in the Anavilhanas Ecological Station, Rio Negro, Amazonas State, Brazil.Neotropical Ichthyology 6, 559–566. doi: 10.1590/S1679-62252008000400003

Oliveira, E. C., Bialetzki, A. & Assakawa, L. F. (2008). Morphological development of Hypoph-thalmus fimbriatus and H. marginatus post-yolk-sac larvae (Siluriformes: Pimelodidae).Zootaxa 1707, 37–48.

Pereira, L. H., Hanner, R., Foresti, F. & Oliveira, C. (2013). Can DNA barcoding accuratelydiscriminate megadiverse Neotropical freshwater fish fauna? BMC Genetics 14, 20. doi:10.1186/1471-2156-14-20

Reis, R. E., Kullander, S. O. & Ferraris, C. J. (2003). CLOFFSCA-Check List of the Freshwa-ter Fishes of South and Central America, 1st edn. Porto Alegre: Editora da PontifíciaUniversidade do Rio Grande do Sul (EDIPUCRS).

Reynalte-Tataje, D., Zaniboni-Filho, E. & Esquivel, J. R. (2004). Embryonic and larvae devel-opment of piracanjuba, Brycon orbignyanus Valenciennes, 1849 (Pisces, Characidae).Acta Scientiarum Biological Sciences 26, 67–71.

Richardson, D. E., Vanwye, J. D., Exum, A. M., Cowen, R. K. & Crawford, D. L. (2007). Highthroughput species identification: from DNA isolation to bioinformatics. Molecular Ecol-ogy Notes 7, 199–207. doi: 10.1111/j.1471-8286.2006.01620.x

Shao, K. T., Chen, K. C. & Wu, J. H. (2002). Identification of marine fish eggs in Taiwanusing light microscopy, scanning electric microscopy and mtDNA sequencing. Marineand Freshwater Research 53, 355–365. doi: 10.1071/MF01141

Snyder, D. E. (1981). Contributions to a Guide to the Cypriniform Fish Larvae of the Upper Col-orado Rover System in Colorado. Denver, CO: Colorado State Office of the US Bureauof Land Management and Non-game Section of the Colorado Division of Wildlife.

Sunnucks, P. & Hales, D. F. (1996). Numerous transposed sequences of mitochondrialcytochrome oxidase I-II in aphids of the genus Sitobion (Hemiptera: Aphididae).Molecular Biology and Evolution 13, 510–524.

Valdez-Moreno, M., Vásquez-Yeomans, L., Elías-Gutiérrez, M., Ivanova, N. V. & Hebert, P. D.(2010). Using DNA barcodes to connect adults and early life stages of marine fishes fromthe Yucatan Peninsula, Mexico: potential in fisheries management. Marine and Freshwa-ter Research 61, 655–671. doi: 10.1071/MF09222

Ward, R. D., Hanner, R. & Hebert, P. D. (2009). The campaign to DNA barcode all fishes,FISH-BOL. Journal of Fish Biology 74, 329–356. doi: 10.1111/j.1095-8649.2008.02080.x

© 2015 The Fisheries Society of the British Isles, Journal of Fish Biology 2015, doi:10.1111/jfb.12707