Accepted Article

Received Date : 12-Mar-2014 Revised Date : 28-May-2014 Accepted Date : 30-May-2014 Article type

: Resource Article

Identifying the ichthyoplankton of a coral reef using DNA barcodes Nicolas HUBERT1, Benoit ESPIAU2,3, Christopher MEYER4, Serge PLANES2,3 1Institut

de Recherche pour le Développement (IRD), UMR226 ISE-M, Bât. 22 - CC065,

Place Eugène Bataillon, 34095 Montpellier cedex 5, France. 2USR

3278 CNRS-EPHE, CRIOBE – BP 1013 Papetoai, 98729 Moorea, French Polynesia.

3Laboratoire

d’Excellence CORAIL

4Department

of Invertebrate Zoology, National Museum of Natural History, Smithsonian

Institution, Washington, United States of America. Corresponding author: Serge PLANES, USR 3278 CNRS-EPHE, CRIOBE – BP 1013 Papetoai, 98729 Moorea, French Polynesia, Phone: 33 (0)6 03 02 09 30, e-mail: [email protected] Abstract Marine fishes exhibit spectacular phenotypic changes during their ontogeny and the identification of their early stages is challenging due to the paucity of diagnostic morphological characters at the species level. Meanwhile, the importance of early life stages in dispersal and connectivity has recently experienced an increasing interest in conservation programs for coral reef fishes. The present study aims at assessing the effectiveness of DNA barcoding for the automated identification of coral reef fish larvae through large-scale ecosystemic sampling. Fish larvae were mainly collected using bongo nets and light traps around Moorea between September 2008 and August 2010 in 10 sites distributed in open waters. Fish larvae ranged from 2mm to 100mm of total This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/1755-0998.12293 This article is protected by copyright. All rights reserved.

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length, with the most abundant individuals being less than 5mm. Among the 505 individuals DNA barcoded, 373 larvae (i.e. 75 percent) were identified to the species level. A total of 106 species were detected, among which 11 corresponded to pelagic and bathypelagic species, while 95 corresponded to species observed at the adult stage on neighbouring reefs. This study highlights the benefits and pitfalls of using standardized molecular systems for species identification and illustrates the new possibilities enabled by DNA Barcoding for future work on coral reef fish larval ecology. Introduction There are nearly 10,000 species of marine fishes in the Indo-Pacific, which represent 30 percent of the world ichthyofauna and of which half are observed tightly associated with coral reefs (Froese& Pauly 2011). Indo-Pacific coral reef fishes aggregate in some of the most diverse ecological communities and several thousands of species are frequently observed at a single island (Tittensor et al. 2010). From a regional perspective, this uneven distribution of species richness in the Indo-Pacific has attracted considerable attention over the last decade (Bellwood& Meyer 2009; Briggs 2000, 2003, 2005; Hubert et al. 2012; Read et al. 2006). Competing hypotheses have been proposed that differ in the importance they place on the contribution of dispersal in shaping large scale patterns of species richness (Briggs 2005; Mora et al. 2003). Most coral reef adult fish species are sedentary, therefore dispersal is enabled through the diffusion and transport of larvae in open waters (Sale 1998; Sale 1977; Sale& Dybdal 1978; Sale& Williams 1982). In this context, the role of larval dispersal in shaping community structure and spatial patterns of species richness is still poorly understood and recent studies have provided contrasting evidence for the dynamics of larval dispersal in relation to landscape ecological conditions and species life history traits (Ben-Tzvi et al. 2012; Berumen et al. 2012; Cowen et al. 2000; Dixson et al. 2008; Paris& Cowen 2004; Planes et al. 2009; Saenz-Adugelo et al. 2011, 2012; Siegel et al. 2008). However, the empirical study of larval ecology is currently limited by the effectiveness of accurately identifying larvae to the species level based on morphological characters. Given their high diversity and dramatic phenotypic changes during development, fish larvae identification is no easy task (Choat et al. 1993). The use of standardized molecular approaches for species identification (Kochzius et al. 2010) such as DNA barcoding, has recently proven to open up new perspectives in the

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study of coral reef fish larval ecology (Hubert et al. 2010; Ko et al. 2013). Ko and colleagues (Ko et al. 2013), for example, have shown that the accuracy of specimen identification to the species level based on morphological characters was poor, with only 3 to 30% of species correctly identified compared to DNA barcoding. Likewise, Valdez-Moreno and colleagues (Valdez-Moreno et al. 2009) used DNA barcodes to link early life stages of marine fishes to their adult stage, resulting in the identification of previously unknown larval stages of several species from the Caribbean. In the Pacific, the Moorea Biocode project is attempting to create the first comprehensive inventory of all non-microbial life in a complex tropical ecosystem (http://mooreabiocode.org/). Extensive sampling of marine taxa in French Polynesia has been conducted over the last few years and several hundreds of coral-reef fish specimens have been collected. A comprehensive DNA barcode library has recently been published for Moorea which currently includes 829 DNA barcodes for 371 coral reef associated fish species (Hubert et al. 2012). Together with data available in BOLD, the identification of early ontogenetic stages of fish species is possible using readily available DNA barcodes. Here we present the results of fish larvae, comprehensively sampled at Moorea and identified to the species level using DNA barcodes. The accuracy of DNA barcoding-based identification, as well as the composition of larval assemblages in Moorea, are discussed. Material and Methods All the larvae analyzed here were sampled between September 2008 and August 2010 at 10 sites distributed in open waters in the vicinity of Moorea. A combination of Bongo Nets, light traps and reef nets was used at night (Fig. 1, Collection permits following a Permanent agreement, “Délégation à la Recherche”, French Polynesia). Light traps were deployed overnight during three consecutive nights at the new moon and checked every morning (LT points, Fig. 1). Alternatively, bongo nets were used during the new moons across six sites sampled clockwise around Moorea. Nets with a mesh size of 230μm loaded with three kilograms weights were immerged (BN points, Fig. 1). The Bongo nets were trawled at 2 knots during three consecutive sessions of 10 minutes, at depths of 50 and 25 meters aswell as the subsurface, along a transect parallel to the reef at 100 meters from the barrier reef. Some additional sampling was conducted using crest nets in order to sample in the vicinity of the reef outer-slop following previous protocols

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(Doherty et al. 2004). Total plankton was preserved in 95% ethanol during the sampling. In the lab, sorting consisted of first separating fish larvae from other plankton. Then, DNA sources for this study only included larvae in good condition, in other words we removed all larvae missing body parts essential for identification (e.g. gut, eyes). The remaining larvae, ranging from 1.2mm to 100mm in Total Length (TL), were then isolated, and for each specimen, detailed geographic information and photographs were collected, prior to processing for DNA analysis. Genomic DNA was extracted using the Biosprint 96 DNA Blood Kit (QIAGEN) according to manufacturer specifications and further used with no dilution for amplification and sequencing. A 650-bp segment from the 5’ region of the cytochrome oxidase

I

gene

(COI)

was

amplified

using

5’TCAACYAATCAYAAAGATATYGGCAC3’

the

and

primers

FishBCLFishBCH-

5’ACTTCYGGGTGRCCRAARAATCA3’ (Baldwin et al. 2009). PCR amplifications were performed in 10 μl including 6.3 μl of molecular grade water, 1.0 μl of 10X PCR buffer, 0.5 μl of MgCl2 (50 mM), 0.3 μl of each primer (10 mM), 0.5 μl of dNTPs (10 mM), 0.1 μl of Bioline Taq polymerase, and 1 μl of template DNA. The PCR conditions consisted of 95°C (5 min), 35 cycles of 95°C (30 sec), 52°C (30 sec), 72°C (45 sec) followed by a final extension at 72°C (5 min). PCR products were purified using the ExoSAP-IT protocol (Amersham Biosciences, Piscataway NY) and used as a template for the sequencing reaction using the BigDye Terminator (version 3.1) Cycle Sequencing Kit (Applied Biosystems, Inc., Foster City, Calif.) Sequencing products were cleaned before running them on the capillary sequencer using a Sephadex centrifugation protocol (Millipore MAHVN4550 plates). Sequence quality was estimated using Genious (Drummond et al. 2011) and three categories were considered for the contigs including low quality (i.e. 0 to 79.99 percents of concordance between forward and reverse reads), medium quality (i.e. 80 to 89.99 percents) and high quality (i.e. 90 to 100 percents). We opted for a conservative approach and only sequences with high quality contigs were considered in the present study. All sequences have been deposited in GenBank and accession numbers for the barcodes, specimens and collection data, sequences, trace files and primers details are available within the ‘French Polynesia Fish Larvae II’ project file (FPFLB) under the general container ‘Moorea Biocode – Fish’ in BOLD (http://www.barcodinglife.org). Identification was performed by running blast searches in BOLD. Both the best match

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and second interspecific best match in BOLD were retained and matches were scored as percents of sequence match. The second best match was used to assess the reliability of the identification performed. Blast searches in BOLD were first run by comparisons with published and publicly available DNA barcode reference libraries. In doing so, searches were performed on up-to-date libraries to buffer the impact of taxonomic uncertainties and misidentifications. Searches were enlarged to all the libraries in BOLD including early-released and private reference libraries whenever no match at more than 80 percent similarity was found (Appendix I). The reliability of the identifications was appraised using a threshold approach and blasts results were classified into three cases following the initial proposal of Hebert and colleagues (Hebert et al. 2004): - Case I “match to species”: the best match is below the threshold and the nearest neighbour best match is above the threshold. In that case, sequences match to species. - Case II “uncertain match”: both best match and nearest neighbour best match are below the threshold. The identification to the species level is uncertain and misidentification in the reference libraries is likely, incomplete lineage sorting or hybridization may occur. - Case III “unmatched”: both best match and nearest neighbour best match are above the threshold. Identification to the species level are impossible due to the incompleteness of the reference libraries in BOLD. The use of universal thresholds for either delineating species using molecular lineages or for assigning unknown sequences to species present major limitations due to the fact that universal divergence threshold associated to species boundaries are not observed in nature and marine fishes are no exception (Hubert et al. 2012; Jaafar et al. 2012; Puckridge et al. 2013). A threshold approach, however, is effective in describing match to species and identifying cases where matches are ambiguous. Along the same line, the effect of varying thresholds enables to explore the interval of divergence where ambiguous match occur. In this context, we examined the relative percentage of match to species (case I), ambiguous match (case II) and unmatched sequences (case III) based on a 1% and 2% divergence threshold for species delineation and used the associated 99% and 98% threshold of sequence similarities in the blast searches to identify cases

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of match to species. These estimations have been conducting for both specimens (i.e. considering the whole larvae pools without accounting for molecular lineages) and molecular lineages (i.e. considering only molecular lineages as a proxy of species following the species divergence threshold above mention). Results During the present sampling, 1379 larvae have been collected among which, 1264 were successfully amplified using the primers FishBCL and FishBCH (i.e. 92 percents). Only 505 contigs, however, have been assigned to high quality sequences according to Geneious and presented no ambiguities. As no priori identification to the species level were available when editing contigs, ambiguous base call cannot be fixed by comparisons with conspecific sequences and only the contigs belonging to the high quality sequence category were conserved and used in the following analyses. This conservative approach ensured that ambiguous assignment of unknown sequences to known species were due to the limits of the DNA barcodes reference libraries in BOLD and not due to low sequence quality. Only the results for the 505 sequenced larvae are presented here. DNA barcodes were obtained for 505 larvae and the attached data, photographs and sequences were deposited in BOLD (FPFLB project, Fig. 2). Most of the larvae analyzed were less than 15mm in Total Length (TL) with 31% belonging to the 1-5mm size class, 10% belonging to the 5-10mm size class and 17% belonging to the 10-15mm size class (Fig. 3A, Table 1). Altogether, 58% of the larvae were less than 15mm, while within the 42% remaining, the most abundant size classes were found between 1520mm and 50-55mm. The combined use of light traps and bongo nets provided a broader coverage of the larval size classes as TL ranged between 1.2 and 10.5 mm in bongo net collections while TL ranged between 4.9 and 100 mm in light trap collections. Although collections were carried out over a full year, the majority of larvae analyzed were collected between October 2009 and February 2010 (Fig. 3B, Table 1), as observed in previous work (Dufour& Galzin 1993). A match of 99-100 percent was found in 93% of the sequences (Fig. 4A). The matching results for the nearest neighbour were more scattered ranging from 99-100% of similarity for 20% of the sequences to 82-84% of similarity for 4 percent of the sequences. A total of 103 sequences exhibited percent of similarity with both the best

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match and the nearest neighbour ranging from 99 to 100%, meaning that 20% of the sequences led to ambiguous species assignments (Fig. 4B). Overall, 80% of the sequences analyzed showed more than a 1% difference between the best match and the nearest neighbour. The comparison of the percent of similarity of the best match and the nearest neighbour provided a more detailed insight into the BLAST outputs (Fig. 5). Using a conservative 99% of similarity threshold (i.e. a 1% divergence threshold for species boundaries), we found that 366 sequences belonged to case I “match to species” (i.e. 73% of the cases), 103 sequences belonged to case II “ambiguous match” (i.e. 20% of the cases) and 36 sequences belonged to case III “unmatched” (i.e. 7% of the cases). Using a canonical 2% of divergence among species (April et al. 2011; Hebert et al. 2003; Hebert et al. 2004) and a 98% of similarity threshold, led to very similar results as only 7 (out of 36) sequences belonging to Case III “unmatched” with the 99% threshold were transferred to Case I “match to species” (Appendix I). Using the canonical 98% threshold, 373 sequences matching to species were identified to the species level, that is 75% of the 505 larvae analyzed (Appendix II). Following differential thresholds for setting species boundaries, 151 mitochondrial lineages (i.e. proxy to species in the larvae pool) were delineating at the 1% threshold and 141 lineages at the 2% threshold. Considering the 106 lineages assigned to case I “match to species”, that is 70% and 75% of the mitochondrial lineages that were matching to species using a 99% and 98% similarity threshold (i.e. following a 1% threshold for species boundaries), respectively. From the 373 larvae sequences matching species, the families Pomacentridae (15 species, 87 individuals), Blenniidae (9 species, 64 specimens), Apogonidae (13 species, 43 specimens), Holocentridae (6 species, 37 specimens) and Acanthuridae (8 species, 34 specimens) were the most abundant (Appendix II). Among the 106 species detected in the larval pools, 83 were previously sampled from the adjacent reefs at the adult stage and DNA barcoded (Hubert et al. 2012). In the remaining 23 species, 12 correspond to species that were previously observed on the Moorea reef but not previously sampled for DNA barcoding, one corresponds to a species found in the deep reefs above 200m (Parapriacanthus ransonneti), five correspond to bathypelagic species from the families Melanocetidae, Myctophidae and Nomeidae, and five correspond to pelagic species.

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Finally, apart from the 103 case with ambiguous matching (i.e. case II) which were mainly due to misidentification in the reference libraries (e.g. 100% of match with both the best match and the nearest neighbour best match), the 29 cases of unmatched sequences (case III) detected here highlight that nearly 6% of the larvae sampled and analyzed do not match anything with 98% percent of similarity ranging from 97.9% in one case, 92.6% in another case but less than 90% in the 27 remaining unmatched sequences (case III). Discussion Blast analyses were conducted on October 2013 and reflect up-to-date state of the art in the assembly of the DNA barcode reference libraries for Indo-Pacific coral reef fishes at that time. Considering a total of 505 larvae sampled and analyzed, DNA barcodes assigned to species 75% of the larvae using a 98% similarity threshold and 75% of the mitochondrial lineages delineated following a 2% threshold for species boundaries. These results readily illustrate the benefit of DNA barcode based identifications in our understanding of the dynamics at play in coral reef ecological communities. In the large majority of the species identified in larval pools, results were consistent with a local contribution from the adult pools in the neighbouring reefs. Of the 106 species identified, 83 were previously sampled for DNA barcoding in Moorea’s reefs and among the 23 species previously not DNA barcoded, 12 correspond to species observed in the coral reefs of the area. Interestingly, the 11 remaining species correspond to pelagic (5 species) and bathypelagic (6 species) species that happen to have pelagic larvae found close to reef and close to the surface. The detection of bathypelagic species in larval pools was surprising since the present individuals have been sampled at 50m depth using bongo nets or at the surface at night using light traps. A single larva of a bathypelagic species, however, was captured using light traps suggesting that occasionally they can even enter into the lagoon. All the bathypelagic species identified correspond to widely distributed species. The present results highlight that misidentifications are still limiting the accuracy of species identification using BOLD in 20% of the sequences, 100% of similarity to sequences attributed to two different species were found (i.e. Case II “ambiguous match”; Appendix I). Lineage sorting and hybridization could explain these cases (Birky 1989; Birky et al. 1983; Meyer& Paulay 2005; Pamilo 1988). Recent studies

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of spatial patterns of speciation, however, frequently detected a signature of geographic isolation and allopatric speciation in numerous cases (Hubert et al. 2012; Hubert et al. 2011; Leray et al. 2010; McCafferty et al. 2002; Quenouille et al. 2011). Some exceptions to this general pattern were found (Hodge et al. 2013), however, the increasing body of evidence supporting geographic isolation as a common process suggests that hybridization is probably not common enough at the Indo-Pacific scale to account for all cases of ambiguous matches with multi-specific best match, but some noticeable examples of incomplete lineage sorting have been recently described (DiBattista et al. 2012; Gaither et al. 2014; Horne& Van Herwerden 2013). It is worth mentioning, the cases of ambiguous match (case II) detected here were frequently associated with unpublished data still under process and about 60 percent of these cases were observed in the families Apogonidae and Holocentridae, two diverse families showing closely related and morphologically similar species, difficult to identify and subject to present day revision. In addition, most of these cases involved sequences identified based on specimens collected in different countries and likely result from misidentification as a consequence of multiple independent identifications. As such, most cases of ambiguous matches highlight the need for curation of the BOLD reference libraries for those families rather than a limit of DNA barcoding per se. In these families with numerous and closely related species, we can also question the fact that local isolation and subsequent genetic differentiation may limit identification. In this case, it should be emphasized to include the same species from several geographical locations. The taxonomic incompleteness of the DNA barcode reference libraries in BOLD for Indo-Pacific fishes limits the broad use of those libraries for automated identification, as in nearly 5% of the sequences, poor matches were obtained (less than 90% of similarity for some sequences belonging to Case III). Sequence quality is unlikely to account for these discrepancies since all the sequences involved in the present study were bi-directionally sequenced and 95% of the trace files were scored as high quality data in BOLD. The present case study benefited from extensive barcoding sampling carried out 2 years prior to fish larval collection in this study, but even in this context and in a context of an increasing amount of data for coral reef fishes being available in BOLD, this result highlights that some marine biotas in the Indo-Pacific are still poorly known and will deserve more attention in the future. The assembly of the DNA barcode reference libraries for Indo-Pacific coral reef fishes is a work in progress and given the

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spatial scales and the number of countries and researchers involved, this effort will remain in progress for at least the next decade. Recent studies suggest that the task might be even more intricate than initially expected since cryptic diversity seems to be a general trend for Indo-Pacific fishes (Hubert et al. 2012; Jaafar et al. 2012; Leray et al. 2010; McCafferty et al. 2002; Ward et al. 2009; Ward et al. 2005). Despite these shortcomings due to the incompleteness of the DNA barcode reference libraries, the unambiguous identification of species were obtained for more than 75 percent of both the sequences and mitochondrial lineages anlyzed, illustrating that the BOLD reference libraries readily enable the identification of early stages of fish to the species level using DNA barcodes. As a result, the present study provides a photographic library of fish larvae identified to the species level, a task not previously considered possible using morphological characters. Several alternative methods to delineate species or assign unknown sequences to known species have been recently proposed based on coalescent models (David et al. 2012), phylogenetic models (Munch et al. 2008a; Munch et al. 2008b), mixed phylogenetic-coalescent models (Pons et al. 2006), mutational models (Brown et al. 2012) or distance-based models (Puillandre et al. 2012). These models, however, require that either phylogenetic diversity or intra-specific genealogies are well sampled in order to provide accurate parameter estimates (Ratnasingham& Hebert 2013). Unfortunately, this is still not the case for most lineages of Indo-Pacific fishes even if some progress has been made during the last decade (Cooper et al. 2009; Fessler& Westneat 2007; Hubert et al. 2011; Quenouille et al. 2004; Smith et al. 2008; Westneat& Alfaro 2005). Providing that the use of model-based approaches for species identification is pending more comprehensive DNA barcode reference libraries, we opted for a straightforward threshold approach in order to explore the potential limits of DNA barcode-based identifications. The two similarity thresholds based on one and two percent species boundaries thresholds provided very similar outputs and suggest that species level divergence only scarcely overlap that of intra-specific divergence when a single place is considered. Hubert and colleagues (Hubert et al. 2012) have shown that when accounting for cryptic diversity in species with a distribution in the Indo-Pacific range, the remaining widespread species showing no evidence of interoceanic divergence exhibit maximum intra-specific divergence of less than 2 percent. By contrast, most of the cryptic lineages detected exhibited mitochondrial divergence

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greater than two percent and emphasized that there is no need to opt for a conservative one percent threshold. Concretely, shifting from one to two percent divergence threshold (i.e. 99 to 98% similarity threshold) only led to a slight increase in the number of match to species (case I) as only 7 unmatched sequences using the 99 percent similarity threshold were matching to species using the 98 threshold (Appendix II). The validity of the present patterns of divergence and their impact on the effectiveness of DNA barcode-based identification, however, are based on a single site and still need to be explored at wider spatial scales. The present results, however, show great promise. Conclusion The identification of fish larvae to the species level is ambiguous for 20% of the larvae analyzed due to the misidentification in the DNA barcode reference libraries, either published, early-released or private. As frustrating as this result is, and bearing in mind the massive effort required to advance the establishment of comprehensive DNA barcode reference libraries for Indo-Pacific fishes, the present study highlights that DNA barcode data, even at an early stage of their assembly, can already be used to identify almost 80% of the specimens randomly collected in plankton samples. It is worth mentioning, that the identification of 106 species opened a new window to understanding the dynamics at play in coral reef fish ecological communities. A greater spatial and taxonomic coverage of DNA barcode data for Indo-Pacific fishes will, without a doubt, improve the accuracy of DNA barcode based identification. The present study, however, already stresses the benefit of using automated and standardized approaches to species identification for the study of coral reef fish ecology. With the development of molecular tools and the decrease in costs, the approach can already be considered in future plankton sampling programs. Acknowledgments We thank Moorea BIOCODE project, founded by the Moore foundation, for support and funding. Sampling was conducted according to a Permanent agreement form “Délégation à la Recherche” French Polynesia. The authors thank Frank Lerouvreur, Martin Desmalades, David Lecchini and René Galzin from the USR 3278 - CRIOBE (Moorea) for their help during the field sampling and larval identification in French

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Polynesia. Sampling was processed with the help of the Gump station facilities and the help of Frank Murphy and Neil Davis. This publication has number ISEM 2014-XX.

Figure 1. Map of the sampling sites including specimen numbers. Figure 2. Photographs of specimens encompassing the total size range observed in the present survey. A, Acanthurus guttatus, FLMOO1370, 1.7mm TL; B, Abudefduf sexfasciatus, FLMOO1115, 1.7mm TL; C, Cirripectes quagga, FLMOO1014, 1.9mm TL; D, Apogon doryssa, FLMOO1274, 11mm TL; E, Thalassoma amblycephalum, FLMOO1281, 14mm TL; F, Chromis atripectoralis, FLMOO675, 12mm TL; G, Sufflamen bursa, FLMOO1337, 40mm TL; H, Sargocentron spiniferum, FLMOO481, 52mm TL; I, Saurida gracilis, FLMOO346, 50mm TL. Figure 3. Size classes and number of captures. A. Number of specimens sampled by size classes of 5 mm. B. Number of specimens sampled per month during the present survey. Figure 4. Distribution of matching percentages. A, Numbers of match are given per classes of one percent for both best match and nearest neighbour best match. B, Distribution of percent difference between the best match and the nearest neighbour best match. Figure 5. Best match compared to nearest neighbour (similarity percent) for each specimen. Dotted lines correspond to two percent divergence threshold for species boundaries.

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Table I. Summary statistics of sampling including numbers of specimens, minimum and maximum Total Length (TL). BN, Bongo Net; LT, Light Trap; CN, Crest Net. Latitude -17,47833

Longitude -149,92189

BN2

-17,5255

-149,93281

BN3

-17,61303

-149,82161

BN4

-17,55633

-149,76886

BN5

-17,48339

-149,75075

BN6

-17,47258

-149,83117

LT1

-17,48333

-149,86972

LT2

-17,4825

-149,87278

BN1

Site

Date 30/09/2008 29/10/2008 28/11/2008 20/10/2009 21/01/2010 17/02/2010 19/05/2010 01/07/2010 19/08/2010 Total 29/10/2008 28/11/2008 20/10/2009 21/01/2010 17/02/2010 19/03/2010 01/07/2010 19/08/2010 Total 29/09/2008 28/11/2008 21/01/2010 24/03/2010 01/07/2010 19/08/2010 Total 30/09/2008 28/11/2008 21/01/2010 17/02/2010 24/03/2010 01/07/2010 19/08/2010 Total 29/10/2008 28/11/2008 21/01/2010 17/02/2010 24/03/2010 19/05/2010 Total 29/10/2008 17/12/2009 21/01/2010 17/02/2010 24/03/2010 01/07/2010 19/08/2010 Total 28/11/2008 23/12/2008 24/12/2008 28/01/2009 26/02/2009 27/02/2009 26/05/2009 20/10/2009 21/01/2010 17/03/2010 19/03/2010 16/04/2010 12/07/2010 Total 29/10/2008 28/11/2008 23/12/2008 24/12/2008 26/02/2009 27/02/2009 27/03/2009 26/05/2009 27/05/2009

This article is protected by copyright. All rights reserved.

N 1 4 5 4 2 1 8 8 6 39 2 3 10 11 6 3 4 3 42 7 4 1 14 5 2 33 3 3 1 2 3 2 2 16 4 1 2 6 2 15 30 1 3 4 7 13 4 4 36 12 8 9 18 14 11 10 6 4 9 9 1 2 113 3 4 13 9 18 10 2 3 2

Min 2.6 2.8 1.9 3.2 2.2 1.7 2.3 1.8 1.7 2 2.7 1.4 1.9 1.9 1.8 1.8 2.3 1.4 1.8 1.8 4.7 1.4 3.4 2.9 1.4 4.5 2.4 10.5 1.8 1.7 2.9 1.4 1.4 1.8 3.7 5.3 1.9 1.7 1.9 1.7 2.8 2.6 1.7 1.2 1.7 2.2 4.6 1.2 3.7 11 4.9 10 17 11 8 11 30 22 8 23 31 4.9 11 22 11 11 10 33 41 21 14

TL (mm)

Max 3.4 8.3 8.2 6.4 2.2 6.3 4.7 2.3 8.3 3.4 4.8 5.1 9.7 3.4 6 5.8 2.8 9.7 5.5 7.5 4.7 6.3 6.7 3 7.5 9 4.1 10.5 2.2 4.2 7.2 1.7 10.5 6.8 3.7 6.1 3.6 6.3 7.1 7.1 2.8 3.9 9.6 3.7 7.1 5.1 6.1 9.6 22 54 52 65 70 68 64 22 42 64 56 23 52 70 11 42 50 54 73 74 100 23 17

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LT3

-17,48222

-149,87389

CN

-17.518717 Total

-149.922469

19/10/2009 20/10/2009 17/12/2009 18/01/2010 19/03/2010 Total 28/11/2008 29/11/2008 23/12/2008 24/12/2008 26/02/2009 27/02/2009 26/05/2009 27/05/2009 19/10/2009 17/12/2009 18/01/2010 17/03/2010 18/03/2010 16/04/2010 12/07/2010 Total 20/01/09

5 13 6 1 2 91 6 1 8 3 9 7 8 4 18 26 2 2 3 1 1 99 6 505

13 12 7 9 15 7 10 11 12 11 10 12 11 12 12 8 57 21 17 40 49 8 1.2

30 21 17 9 22 100 23 11 50 12 73 53 48 21 22 35 57 40 56 40 49 73 100

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Data Accessibility All sequences have been deposited in GenBank and accession numbers for the barcodes, specimens and collection data, sequences, trace files and primers details are available within the ‘French Polynesia Fish Larvae II’ project file (FPFLB) under the general container ‘Moorea Biocode – Fish’ in BOLD (http://www.barcodinglife.org).

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Accepted Article This article is protected by copyright. All rights reserved.

Accepted Article This article is protected by copyright. All rights reserved.

Accepted Article This article is protected by copyright. All rights reserved.