, Volume 807, Issue 1, pp 37–51 | Cite as

Metabarcoding of lake benthic diatoms: from structure assemblages to ecological assessment

  • S. F. Rivera
  • V. Vasselon
  • S. Jacquet
  • A. Bouchez
  • D. Ariztegui
  • F. Rimet
Primary Research Paper


Benthic diatoms are relevant indicators of the ecological status of the littoral zone of lakes. Their use as bio-indicators is based on their morphological identification at species level using microscopy which is time consuming, requires taxonomic expertise, and is consequently expensive. To overcome these limitations, a molecular approach for diatom identification has been tested with success in rivers. DNA metabarcoding enables species identification from a standardized DNA barcode and high-throughput sequencing (HTS), using DNA reference library. The suitability of the morphological and molecular approaches to assess the diatom community structure and the ecological status of the littoral zone of the largest deep lake in France (Lake Bourget) was compared. 66 sites were sampled in August 2015 along the shoreline, all around the lake. The composition of diatom assemblages was similar with both morphological and molecular approaches, and diatom assemblages were structured by the same environmental factors. However, the ecological status of Lake Bourget differed significantly among approaches since floristic inventories to species level also differed significantly. The main source of this difference was the incompleteness of the DNA reference library. Nevertheless, in a near future, when this constraint will be solved, the use of DNA metabarcoding for biomonitoring purposes seems promising.


Algae Benthic biomonitoring Eutrophication High-throughput sequencing Lake Bourget Pollution 



The data presented herein is part of a master thesis in environmental sciences presented at the University of Geneva by the first author. The first author is in debt to the Simon I. Patiño Foundation for awarding the scholarship to undertake a Master in Environmental Sciences at the University of Geneva. We thank Lea Féret and Victor Frossard for the sample collection. We also thank the CISALB (Comité Intersyndical pour l’Assainissement du Lac du Bourget) for financing part of the study. The authors also acknowledge the European COST network DNAqua-Net (CA15219) as a fruitful scientific discussion space on molecular approaches for biomonitoring.

Supplementary material

10750_2017_3381_MOESM1_ESM.docx (13 kb)
Supplementary material 1 (DOCX 12 kb) Supplementary data 1. Results of the assessment of the ecological status of the littoral zone of Lake Bourget according to the three diatom indices: IPS, EPI-L and S
10750_2017_3381_MOESM2_ESM.docx (51 kb)
Supplementary material 2 (DOCX 50 kb) Supplementary data 2. Comparison between diatom taxa detected with the morphological (LM) and the molecular approach (Metabarcoding)


  1. Ács, É., 2007. Spatial and temporal change of epiphytic algae and their connection with the ecological condition of swallow Lake Velencei–To (Hungary). Acta Biologica Debrecina Oecologica Hungarica 17: 9–111.Google Scholar
  2. Afnor, 2004. NF EN 14407. Qualité de l’eau-Guide pour l’identification et le dénombrement des échantillons de diatomées benthiques de rivières, et leur interprétation. Afnor: 1–13.Google Scholar
  3. Afnor, 2003. NF EN 13946. Qualité de l’eau-Guide pour l’échantillonnage en routine et le prétraitement des diatomées benthiques de rivières. Afnor: 1–18.Google Scholar
  4. Apothéloz-Perret-Gentil, L., A. Cordonier, F. Straub, J. Iseli, P. Esling & J. Pawlowski, 2017. Taxonomy-free molecular diatom index for high-throughput eDNA biomonitoring. Molecular Ecology Resources. doi: 10.1111/1755-0998.12668.PubMedGoogle Scholar
  5. Balvay, G., J.-C. Druart & S. Jacquet, 2012. Le lac du Bourget ses eaux et sa biologie. Versailles, Editions Quae: 150 pp.Google Scholar
  6. Bennion, H., M. G. Kelly, S. Juggins, M. L. Yallop, A. Burgess, J. Jamieson & J. Krokowski, 2014. Assessment of ecological status in UK lakes using benthic diatoms. Freshwater Science 33: 639–654.CrossRefGoogle Scholar
  7. Bere, T. & J. G. Tundisi, 2010. Biological monitoring of lotic ecosystems: the role of diatoms. Brazilian Journal of Biology 70: 493–502.CrossRefGoogle Scholar
  8. Besse-Lototskaya, A., P.F.M. Verdonschot & J.A. Sinkeldam, 2006. Uncertainty in diatom assessment: sampling, identification and counting variation. Hydrobiologia 566: 247–260.CrossRefGoogle Scholar
  9. Besse-Lototskaya, A., P. F. Verdonschot, M. Coste & B. Van de Vijver, 2011. Evaluation of European diatom trophic indices. Ecological Indicators 11: 456–467.CrossRefGoogle Scholar
  10. Bielczyńska, A., 2015. Bioindication on the basis of benthic diatoms: advantages and disadvantages of the Polish phytobenthos lake assessment method (IOJ–the Diatom Index for Lakes)/Bioindykacja na podstawie okrzemek bentosowych: Mocne i s\labe strony polskiej metody oceny jezior na podstawie fitobentosu (IOJ–Indeks Okrzemkowy Jezior). Ochrona Srodowiska i Zasobów Naturalnych 26: 48–55.Google Scholar
  11. Bigler, C., V. Gälman & I. Renberg, 2010. Numerical simulations suggest that counting sums and taxonomic resolution of diatom analyses to determine IPS pollution and ACID acidity indices can be reduced. Journal of Applied Phycology 22: 541–548.CrossRefGoogle Scholar
  12. Birk, S., W. Bonne, A. Borja, S. Brucet, A. Courrat, S. Poikane, A. Solimini, W. Van de Bund, N. Zampoukas & D. Hering, 2012. Three hundred ways to assess Europe’s surface waters: an almost complete overview of biological methods to implement the Water Framework Directive. Ecological Indicators 18: 31–41.CrossRefGoogle Scholar
  13. Blanco, S., L. Ector & E. Bécares, 2004. Epiphytic diatoms as water quality indicators in Spanish shallow lakes. Vie Milieu 54: 71–80.Google Scholar
  14. Bolla, B., G. Borics, K. Kiss, N. M. Reskóné, G. Várbíró & É. Ács, 2010. Recommendations for ecological status assessment of Lake Balaton (largest shallow lake of Central Europe), based on benthic diatom communities. Vie Milieu 60: 197–208.Google Scholar
  15. Brucet, S., S. Poikane, A. Lyche-Solheim & S. Birk, 2013. Biological assessment of European lakes: ecological rationale and human impacts. Freshwater Biology 58: 1106–1115.CrossRefGoogle Scholar
  16. Bruder, K. & L. K. Medlin, 2007. Molecular assessment of phylogenetic relationships in selected species/genera in the naviculoid diatoms (Bacillariophyta). I. The genus Placoneis. Nova Hedwig. 85: 331–352.CrossRefGoogle Scholar
  17. Bryhn, A. C., C. Girel, G. Paolini & S. Jacquet, 2010. Predicting future effects from nutrient abatement and climate change on phosphorus concentrations in Lake Bourget, France. Ecological Modelling 221: 1440–1450.CrossRefGoogle Scholar
  18. Cantonati, M. & R. L. Lowe, 2014. Lake benthic algae: toward an understanding of their ecology. Freshwater Science 33: 475–486.CrossRefGoogle Scholar
  19. Cellamare, M., S. Morin, M. Coste & J. Haury, 2012. Ecological assessment of French Atlantic lakes based on phytoplankton, phytobenthos and macrophytes. Environmental Monitoring and Assessment 184: 4685–4708.CrossRefPubMedGoogle Scholar
  20. CEN. 2015. Technical report for the routine sampling of benthic diatoms from rivers and lakes adapted for metabarcoding analyses. CEN/TC 230/WG 23 - Aquatic Macrophytes and Algae, 8pp.Google Scholar
  21. Cemagref, 1997. Qualité biologique des eaux du Rhône et essai d’estimation d’effets toxiques sur les communautés de diatomées récoltées à l’aide de substrats artificiels. Agence Eau Rhône-Méditerranée-Corse: 78.Google Scholar
  22. Cemagref, 1982. Etude des méthodes biologiques quantitatives d’appréciation de la qualité des eaux. Rapport Division Qualité des Eaux Lyon. Agence financiè de Bassin Rhone-Méditerarée Corse^ ePierre-Bénite Pierre-Bénite.Google Scholar
  23. Chonova, T., F. Keck, J. Labanowski, B. Montuelle, F. Rimet & A. Bouchez, 2016. Separate treatment of hospital and urban wastewaters: a real scale comparison of effluents and their effect on microbial communities. Science of the Total Environment 542: 965–975.CrossRefPubMedGoogle Scholar
  24. Deiner, K., J.-C. Walser, E. Mächler & F. Altermatt, 2015. Choice of capture and extraction methods affect detection of freshwater biodiversity from environmental DNA. Biological Conservation 183: 53–63.CrossRefGoogle Scholar
  25. DeNicola, D. M., E. de Eyto, A. Wemaere & K. Irvine, 2004. Using epilithic algal communities to asses trophic status in Irish Lakes. Journal of Phycology 40: 481–495.CrossRefGoogle Scholar
  26. Dokulil, M. T., 2003. Algae as ecological bio-indicators. Trace Metals and Other Contaminants in the Environment 6: 285–327.CrossRefGoogle Scholar
  27. Elbrecht, V. & F. Leese, 2015. Can DNA-based ecosystem assessments quantify species abundance? Testing primer bias and biomass—sequence relationships with an innovative metabarcoding protocol. PLoS ONE 10: e0130324.CrossRefPubMedPubMedCentralGoogle Scholar
  28. Hebert, P. D., A. Cywinska, S. L. Ball, et al., 2003. Biological identifications through DNA barcodes. Proceedings of the Royal Society of London. Series B: Biological Sciences 270: 313–321.CrossRefPubMedPubMedCentralGoogle Scholar
  29. Hofmann, G., 1994. Aufwuchs-diatomeen in Seen und ihre Eignung als Indikatoren der Trophie. Bibliotheca Diatomologica 30, Cramer, Berlin: 241 pp.Google Scholar
  30. Hofmann, G., M. Werum & H. Lange-Bertalot, 2011. Diatomeen im Sü\s swasser-Benthos von Mitteleuropa: Bestimmungsflora Kieselalgen für die ökologische Praxis: über 700 der häufigsten Arten und ihre Ökologie. ARG Gantner.Google Scholar
  31. Jacquet, S., O. Anneville & I. Domaizon, 2012. Evolution de paramètres clés indicateurs de la qualité des eaux et du fonctionnement écologique des grands lacs péri-alpins (Léman, Annecy, Bourget): étude comparative de trajectoire de restauration post-eutrophisation. Archives des Sciences 65: 191–208.Google Scholar
  32. Jacquet, S., I. Domaizon & O. Anneville, 2014. The need for ecological monitoring of freshwaters in a changing world: a case study of Lakes Annecy, Bourget, and Geneva. Environmental Monitoring and Assessment 186: 3455–3476.CrossRefPubMedGoogle Scholar
  33. Jacquet, S., D. Barbet, C. Barbier, S. Cachera, M. Colon, L. Espinat, J. Guillard, V. Hamelet, J.-C. Hustache, D. Lacroix, L. Laine, B. Leberre, J. Neasta, G. Paolini, M.-E. Perga, P. Perney & F. Rimet, 2016. Suivi environnemental des eaux du lac du Bourget pour l’année 2015. Rapport INRA-CISALB-CALB.Google Scholar
  34. Kahlert, M., R.-L. Albert, E.-L. Anttila, R. Bengtsson, C. Bigler, T. Eskola, V. Gälman, S. Gottschalk, E. Herlitz, A. Jarlman, et al., 2009. Harmonization is more important than experience—results of the first Nordic-Baltic diatom intercalibration exercise 2007 (stream monitoring). Journal of Applied Phycology 21: 471–482.CrossRefGoogle Scholar
  35. Kebschull, J. M. & A. M. Zador, 2015. Sources of PCR-induced distortions in high-throughput sequencing data sets. Nucleic Acids Research 43: e143–e143.CrossRefPubMedPubMedCentralGoogle Scholar
  36. Kermarrec, L., A. Franc, F. Rimet, P. Chaumeil, J.-F. Humbert & A. Bouchez, 2013. Next-generation sequencing to inventory taxonomic diversity in eukaryotic communities: a test for freshwater diatoms. Molecular Ecology Resources 13: 607–619.CrossRefPubMedGoogle Scholar
  37. Kermarrec, L., A. Franc, F. Rimet, P. Chaumeil, J.-M. Frigerio, J.-F. Humbert & A. Bouchez, 2014. A next-generation sequencing approach to river biomonitoring using benthic diatoms. Freshwater Science 33: 349–363.CrossRefGoogle Scholar
  38. King, L., G. Clarke, H. Bennion, M. Kelly & M. Yallop, 2006. Recommendations for sampling littoral diatoms in lakes for ecological status assessments. Journal of Applied Phycology 18: 15–25.CrossRefGoogle Scholar
  39. Krammer, K. & H. Lange-Bertalot, 1986. Bacillariophyceae. 1. Teil: Naviculaceae. Süswasserflora Von Mitteleuropa. Gustav Fischer Verlag, Sttuttgart edn: 610 pp.Google Scholar
  40. Krammer, K. & H. Lange-Bertalot, 1988. Süsswasserflora von Mitteleuropa. Bacillariophyceae. 2. Teil: Epithemiaceae, Bacillariaceae, Surirellaceae, vol 2/2. Gustav Fischer Verlag, Stuttgart edn: 610 pp.Google Scholar
  41. Krammer, K. & H. Lange-Bertalot, 1991. Susswasserflora von Mitteleuropa. Bacillariophyceae 3. Teil: Centrales, Fragilariaceae, Eunotiaceae. Süs Swasserflora Von Mitteleuropa. Gustav Fischer Verlag, Sttuttgart edn: 598 pp.Google Scholar
  42. Lange-Bertalot, H., 2001. Navicula sensu stricto 10 genera separated from Navicula sensu lato Frustulia. Diatoms of Europe: Diatoms of the European Inland Waters and Comparable Habitats 2: 526.Google Scholar
  43. Lecointe, C., M. Coste & J. Prygiel, 1993. “Omnidia”: software for taxonomy, calculation of diatom indices and inventories management. Hydrobiologia 269: 509–513.CrossRefGoogle Scholar
  44. Lee, P. Y., J. Costumbrado, C.-Y. Hsu & Y. H. Kim, 2012. Agarose gel electrophoresis for the separation of DNA fragments. JoVE Journal of Visualized Experiments 62: e3923.Google Scholar
  45. Lejzerowicz, F., P. Esling, L. Pillet, T. A. Wilding, K. D. Black & J. Pawlowski, 2015. High-throughput sequencing and morphology perform equally well for benthic monitoring of marine ecosystems. Scientific Reports 5: 13932.CrossRefPubMedPubMedCentralGoogle Scholar
  46. Mann, D. G. & P. Vanormelingen, 2013. An inordinate fondness? The number, distributions, and origins of diatom species. Journal of Eukaryotic Microbiology 60: 414–420.CrossRefPubMedGoogle Scholar
  47. Mann, D. G., S. Sato, R. Trobajo, P. Vanormelingen & C. Souffreau, 2010. DNA barcoding for species identification and discovery in diatoms. Cryptogamie Algologie 31: 557–577.Google Scholar
  48. Marchetto, A., Agostinelli, C., Alber, R., Beghi, A., Balsamo, S., Bracchi, S., Buzzi, F., Carena, E., Cavalieri, S., Cimoli, F., et al., 2013. Indice per valutazione della qualità delle acque lacustri italiane a partire dalle diatomee epifitiche ed epilitiche (EPI-L). Rep. CNR-ISE 2: 75–92.Google Scholar
  49. Maruyama, A., K. Shinohara, M. Sakurai, T. Ohtsuka & B. Rusuwa, 2015. Microhabitat variations in diatom composition and stable isotope ratios of the epilithic algae in Lake Malawi. Hydrobiologia 748: 161–169.CrossRefGoogle Scholar
  50. McCune, B., J.B. Grace & D.L. Urban, 2002. Analysis of ecological communities. MjM software design Gleneden Beach, OR: 300 pp.Google Scholar
  51. Meunier, A. & S. Jacquet, 2015. Do phages impact microbial dynamics, prokaryotic community structure and nutrient dynamics in Lake Bourget? Biology Open 4: 1528–1537.CrossRefPubMedPubMedCentralGoogle Scholar
  52. Oliveros, J.C., 2007. Venny. An interactive tool for comparing lists with Venn’s diagrams (WWW Document). Venny Interactions Tool Comparing Lists with Venns Diagram [available on internet at].
  53. Pan, Y., A. Herlihy, P. Kaufmann, J. Wigington, J. Van Sickle & T. Moser, 2004. Linkages among land-use, water quality, physical habitat conditions and lotic diatom assemblages: a multi-spatial scale assessment. Hydrobiologia 515: 59–73.CrossRefGoogle Scholar
  54. Pawlowski, J., F. Lejzerowicz, L. Apotheloz-Perret-Gentil, J. Visco & P. Esling, 2016. Protist metabarcoding and environmental biomonitoring: time for change. European Journal of Protistology 55: 12–25.CrossRefPubMedGoogle Scholar
  55. Potapova, M. & D. F. Charles, 2003. Distribution of benthic diatoms in US rivers in relation to conductivity and ionic composition. Freshwater Biology 48: 1311–1328.CrossRefGoogle Scholar
  56. Prygiel, J. & M. Coste, 1993. The assessment of water quality in the Artois-Picardie water basin (France) by the use of diatom indices. Hydrobiologia 269/270 (Dev. Hydrobiologia 90): 343–349.Google Scholar
  57. Quail, M. A., M. Smith, P. Coupland, T. D. Otto, S. R. Harris, T. R. Connor, A. Bertoni, H. P. Swerdlow & Y. Gu, 2012. A tale of three next generation sequencing platforms: comparison of Ion Torrent, Pacific Biosciences and Illumina MiSeq sequencers. BMC Genomics 13: 341.CrossRefPubMedPubMedCentralGoogle Scholar
  58. Reichardt, E., 1997. Taxonomische revision des artenkomplexes um Gomphonema pumilum (Bacillariophyceae). Nova Hedwigia 65: 99–130.Google Scholar
  59. Rimet, F., 2012. Recent views on river pollution and diatoms. Hydrobiologia 683: 1–24.CrossRefGoogle Scholar
  60. Rimet, F., H.-M. Cauchie, L. Hoffmann & L. Ector, 2005. Response of diatom indices to simulated water quality improvements in a river. Journal of Applied Phycology 17: 119–128.CrossRefGoogle Scholar
  61. Rimet, F., A. Bouchez & K. Tapolczai, 2016a. Spatial heterogeneity of littoral benthic diatoms in a large lake: monitoring implications. Hydrobiologia 771: 179–193.CrossRefGoogle Scholar
  62. Rimet, F., Chaumeil, P., Keck, F., Kermarrec, L., Vasselon, V., Kahlert, M., Franc, A. & Bouchez, A., 2016b. R-Syst:: diatom: an open-access and curated barcode database for diatoms and freshwater monitoring. Database 2016: baw016.Google Scholar
  63. Round, F. E., R. M. Crawford & D. G. Mann, 1990. Diatoms: Biology and Morphology of the Genera. Cambridge University Press, Cambridge.Google Scholar
  64. Schloss, P. D., S. L. Westcott, T. Ryabin, J. R. Hall, M. Hartmann, E. B. Hollister, R. A. Lesniewski, B. B. Oakley, D. H. Parks, C. J. Robinson, et al., 2009. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and Environment Microbiology 75: 7537–7541.CrossRefGoogle Scholar
  65. Schmidt, T. S., J. F. Matias Rodrigues & C. Mering, 2015. Limits to robustness and reproducibility in the demarcation of operational taxonomic units. Environmental Microbiology 17: 1689–1706.CrossRefPubMedGoogle Scholar
  66. Schmidt-Kloiber, A. & D. Hering, 2015. www. freshwaterecology. info—an online tool that unifies, standardises and codifies more than 20,000 European freshwater organisms and their ecological preferences. Ecological Indicators 53: 271–282.CrossRefGoogle Scholar
  67. Sgro, G. V., E. D. Reavie, J. C. Kingston, A. R. Kireta, M. J. Ferguson, N. P. Danz & J. R. Johansen, 2007. A diatom quality index from a diatom-based total phosphorus inference model. Environmental Bioindicators 2: 15–34.CrossRefGoogle Scholar
  68. Smol, J. P. & E. F. Stoermer, 2010. The Diatoms: Applications for the Environmental and Earth Sciences. Cambridge University Press, Cambridge.CrossRefGoogle Scholar
  69. Spitale, D., A. Scalfi & M. Cantonati, 2014. Urbanization effects on shoreline phytobenthos: a multiscale approach at lake extent. Aquatic Sciences 76: 17–28.CrossRefGoogle Scholar
  70. Stenger-Kovács, C., K. Buczko, E. Hajnal & J. Padisák, 2007. Epiphytic, littoral diatoms as bioindicators of shallow lake trophic status: Trophic Diatom Index for Lakes (TDIL) developed in Hungary. Hydrobiologia 589: 141–154.CrossRefGoogle Scholar
  71. Stevenson, R. J., 1998. Diatom indicators of stream and wetland stressors in a risk management framework. Environmental Monitoring and Assessment 51: 107–118.CrossRefGoogle Scholar
  72. Stevenson, R. J. & Y. Pan, 1999. Assessing environmental conditions in rivers and streams with diatoms. The Diatoms: Applications for the Environmental and Earth Sciences 1: 4.Google Scholar
  73. Stevenson, R. J., J. T. Zalack & J. Wolin, 2013. A multimetric index of lake diatom condition based on surface-sediment assemblages. Freshwater science 32(3): 1005–1025.CrossRefGoogle Scholar
  74. Stoof-Leichsenring, K. R., L. S. Epp, M. H. Trauth & R. Tiedemann, 2012. Hidden diversity in diatoms of Kenyan Lake Naivasha: a genetic approach detects temporal variation. Molecular Ecology 21: 1918–1930.CrossRefPubMedGoogle Scholar
  75. Taberlet, P., E. Coissac, F. Pompanon, C. Brochmann & E. Willerslev, 2012. Towards next-generation biodiversity assessment using DNA metabarcoding. Molecular Ecology 21: 2045–2050.CrossRefPubMedGoogle Scholar
  76. Thomas, A. C., B. E. Deagle, J. P. Eveson, C. H. Harsch & A. W. Trites, 2016. Quantitative DNA metabarcoding: improved estimates of species proportional biomass using correction factors derived from control material. Molecular Ecology Resources 16: 714–726.CrossRefPubMedGoogle Scholar
  77. Tornés, E., J. Cambra, J. Gomà, M. Leira, R. Ortiz & S. Sabater, 2007. Indicator taxa of benthic diatom communities: a case study in Mediterranean streams. Annales de Limnologie-International Journal of Limnology. EDP Sciences 43: 1–11.CrossRefGoogle Scholar
  78. Vadeboncoeur, Y., M. J. Vander Zanden & D. M. Lodge, 2002. Putting the Lake Back Together: reintegrating Benthic Pathways into Lake Food Web Models: lake ecologists tend to focus their research on pelagic energy pathways, but, from algae to fish, benthic organisms form an integral part of lake food webs. BioScience 52: 44–54.CrossRefGoogle Scholar
  79. Valentini, A., P. Taberlet, C. Miaud, R. Civade, J. Herder, P. F. Thomsen, E. Bellemain, A. Besnard, E. Coissac, F. Boyer, et al., 2016. Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding. Molecular Ecology 25: 929–942.CrossRefPubMedGoogle Scholar
  80. Van Dam, H., A. Mertens & J. Sinkeldam, 1994. A coded checklist and ecological indicator values of freshwater diatoms from the Netherlands. Aquatic Ecology 28: 117–133.CrossRefGoogle Scholar
  81. Vasselon, V., I. Domaizon, F. Rimet, M. Kahlert & A. Bouchez, 2017a. Application of high-throughput sequencing (HTS) metabarcoding to diatom biomonitoring: do DNA extraction methods matter? Freshwater Science 36: 162–177.CrossRefGoogle Scholar
  82. Vasselon, V., I. Domaizon, F. Rimet, K. Tapolczai & A. Bouchez, 2017b. Optimization of Diatom DNA Metabarcoding for Freshwater Biomonitoring: Application to Mayotte Streams Monitoring Network. University of Essen, Germany.Google Scholar
  83. Vilmi, A., S. M. Karjalainen, S. Hellsten & J. Heino, 2016. Bioassessment in a metacommunity context: are diatom communities structured solely by species sorting? Ecological Indicators 62: 86–94.CrossRefGoogle Scholar
  84. Visco, J. A., L. Apothéloz-Perret-Gentil, A. Cordonier, P. Esling, L. Pillet & J. Pawlowski, 2015. Environmental monitoring: inferring the diatom index from next-generation sequencing data. Environmental Science and Technology 49: 7597–7605.CrossRefPubMedGoogle Scholar
  85. Wang, Q., G. M. Garrity, J. M. Tiedje & J. R. Cole, 2007. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and Environment Microbiology 73: 5261–5267.CrossRefGoogle Scholar
  86. Zimmermann, J., G. Glöckner, R. Jahn, N. Enke & B. Gemeinholzer, 2015. Metabarcoding vs. morphological identification to assess diatom diversity in environmental studies. Molecular Ecology Resources 15: 526–542.CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • S. F. Rivera
    • 1
  • V. Vasselon
    • 2
  • S. Jacquet
    • 2
  • A. Bouchez
    • 2
  • D. Ariztegui
    • 3
  • F. Rimet
    • 2
  1. 1.Institute for Environmental SciencesUniversity of GenevaGenevaSwitzerland
  2. 2.CARRTEL, INRAUniversité de Savoie Mont BlancThonon les bains CedexFrance
  3. 3.Section of Earth & Environmental SciencesUniversity of GenevaGenevaSwitzerland

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