Free Access
| Issue |
Int. J. Lim.
Volume 61, 2025
|
|
|---|---|---|
| Article Number | 10 | |
| Number of page(s) | 14 | |
| DOI | https://doi.org/10.1051/limn/2025009 | |
| Published online | 25 November 2025 | |
- Alric B, Ter Braak CJ, Desdevises Y, Lebredonchel H, Dray S. 2020. Investigating microbial associations from sequencing survey data with co‐correspondence analysis. Mol Ecol Resour 20: 468–480. [Google Scholar]
- An SM, Choi DH, Lee H, Lee JH, Noh JH. 2018. Next-generation sequencing reveals the diversity of benthic diatoms in tidal flats. Algae 33: 167–180. [Google Scholar]
- Apothéloz‐Perret‐Gentil L, Cordonier A, Straub F, Iseli J, Esling P, Pawlowski J. 2017. Taxonomy‐free molecular diatom index for high‐throughput eDNA biomonitoring. Mol Ecol Resour 17: 1231–1242. [Google Scholar]
- Bailet B, Bouchez A, Franc A, Frigerio J-M., Keck F, Karjalainen S-M., Rimet F, Schneider S, Kahlert M. 2019. Molecular versus morphological data for benthic diatoms biomonitoring in Northern Europe freshwater and consequences for ecological status. Metabarcoding Metagenom 3. https://doi.org/10.3897/mbmg.3.34002. [Google Scholar]
- Ballesteros I, Castillejo P, Haro AP, Montes CC, Heinrich C, Lobo EA. 2020. Genetic barcoding of Ecuadorian epilithic diatom species suitable as water quality bioindicators. C R Biol 343: 41–52. [Google Scholar]
- Baricevic A, Chardon C, Kahlert M, Karjalainen SM, Pfannkuchen DM, Pfannkuchen M, Rimet F, Tankovic MS, Trobajo R, Vasselon V, Zimmermann J, Bouchez A. 2022. Recommendations for the preservation of environmental samples in diatom metabarcoding studies. Metabarcoding Metagenom 6:e85844. [Google Scholar]
- Berthon V, Bouchez A, Rimet F. 2011. Use of diatom life-forms and ecological guilds to assess pollution in rivers: case study of south-eastern French rivers. Hydrobiologia 673: 259–271. [Google Scholar]
- Blomberg SP, Garland T. 2002. Tempo and mode in evolution: phylogenetic inertia, adaptation and comparative methods. J Evol Biol 15: 899–910. [Google Scholar]
- Blomberg SP, Garland T, Ives AR, 2003. Testing for phylogenetic signal in comparative data: behavioral traits are more labile. Evolution 57: 717–745. [Google Scholar]
- Canino A, Bouchez A, Laplace-Treyture C, Domaizon I, Rimet F. 2021. Phytool, a ShinyApp to homogenise taxonomy of freshwater microalgae from DNA barcodes and microscopic observations. Metabarcoding Metagenom 5: e74096. [Google Scholar]
- CEN. 2014. EN 14407: Water quality − Guidance standard for the identification, enumeration and interpretation of benthic diatom samples from running waters. EN 14407:2014. Geneva: Comité European de Normalisation. [Google Scholar]
- CEN. 2018. Water Quality − CEN/TR 17244 − Technical Report for the Management of Diatom Barcodes. CEN Stand. [Google Scholar]
- CEN. 2025. EN 13946:2025: Water quality − Guidance standard for the routine sampling and preparation of benthic diatoms from rivers and lakes. CEN Stand. [Google Scholar]
- Crisp MD, Cook LG. 2012. Phylogenetic niche conservatism: what are the underlying evolutionary and ecological causes? New Phytol 196: 681–694. [Google Scholar]
- Cox E. 1996. Identification of Freshwater Diatoms from Live Material. London: Chapman and Hall, 1; 328 p. [Google Scholar]
- del Campo J, Kolisko M, Boscaro V, Santoferrara LF, Nenarokov S, Massana R, Guillou L, Simpson A, Berney C, de Vargas C. 2018. EukRef: phylogenetic curation of ribosomal RNA to enhance understanding of eukaryotic diversity and distribution. PLoS Biol 16: e2005849. [CrossRef] [PubMed] [Google Scholar]
- Djemiel C, Plassard D, Terrat S, Crouzet O, Sauze J, Mondy S, Nowak V, Wingate L, Ogée G, Maron PA. 2020. µgreen-db: a reference database for the 23S rRNA gene of eukaryotic plastids and cyanobacteria. Sci Rep 10: 5915. [CrossRef] [PubMed] [Google Scholar]
- Gauvin P, Eme D, Domaizon I, Rimet F. 2025. An annotated reference library for supporting DNA metabarcoding analysis of aquatic macroinvertebrates in French freshwater environments. Metabarcoding Metagenom 9: e137772. [Google Scholar]
- Gibb RLA, Botha DK, Venkatachalam S, Bizani M, Bornman TG, Dorrington RA. 2024. DNA metabarcoding reveals distinct bacterial and phytoplankton assemblages in the Agulhas Current and the adjacent coastal shelf. Limnol Oceanogr 69: 2760–2774. [Google Scholar]
- Girard EB, Pratama AM, del Rio-Hortega L, Volkenandt S, Macher JN, Renema W. 2025. Coastal eutrophication transforms shallow micro-benthic reef communities. Sci Total Environ 961: 178252. [Google Scholar]
- Gottschalk S, Kahlert M. 2012. Shifts in taxonomical and guild composition of littoral diatom assemblages along environmental gradients. Hydrobiologia 694: 41–56. [Google Scholar]
- Guiry MD, Guiry GM. 2025. AlgaeBase. World-Wide Electronic Publication, University of Galway. https://www.algaebase.org [Google Scholar]
- Hamilton PB, Lefebvre KE, Bull RD. 2015. Single cell PCR amplification of diatoms using fresh and preserved samples. Front Microbiol 6: 1084. [Google Scholar]
- Hering D, Johnson RK, Kramm S, Schmutz S, Szoszkiewicz K, Verdonschot PFM. 2006. Assessment of European streams with diatoms, macrophytes, macroinvertebrates and fish: a comparative metric-based analysis of organism response to stress. Freshw Biol 51: 1757–1785. [Google Scholar]
- Irannia ZB, Chen T. 2016. TACO: Taxonomic prediction of unknown OTUs through OTU co-abundance networks. Quant Biol 4: 149–158. [Google Scholar]
- Keck F, Rimet F, Franc A, Bouchez A. 2016. Phylogenetic signal in diatom ecology: perspectives for aquatic ecosystems biomonitoring. Ecol Appl 26: 861–872. [Google Scholar]
- Keck F, Rimet F, Bouchez A, Franc A. 2016. phylosignal: an R package to measure, test, and explore the phylogenetic signal. Ecol Evol 6: 2774–2780. [Google Scholar]
- Keck F, Blackman RC, Bossart R, Brantschen J, Couton M, Hürlemann S, Altermatt F. 2022. Meta‐analysis shows both congruence and complementarity of DNA and eDNA metabarcoding to traditional methods for biological community assessment. Mol Ecol 31: 1820–1835. [Google Scholar]
- Keck F, Couton M, Altermatt F. 2023. Navigating the seven challenges of taxonomic reference databases in metabarcoding analyses. Mol Ecol Resour 23: 742–755. [Google Scholar]
- Keck F, Altermatt F. 2023. Management of DNA reference libraries for barcoding and metabarcoding studies with the R package refdb. Mol Ecol Resour 23: 511–518. [Google Scholar]
- Kelly M. 2013. Data rich, information poor? Phytobenthos assessment and the Water Framework Directive. Eur J Phycol 48: 437–450. [Google Scholar]
- Kelly M. 2019. Adapting the (fast-moving) world of molecular ecology to the (slow-moving) world of environmental regulation: lessons from the UK diatom metabarcoding exercise. Metabarcoding Metagenom 3:e39041. [Google Scholar]
- Kelly MG, Juggins S, Mann DG, Sato S, Glover R, Boonham N, Sapp M, Lewis E, Hany U, Kille P, Jones T, Walsh K. 2020. Development of a novel metric for evaluating diatom assemblages in rivers using DNA metabarcoding. Ecol Indic 118: 106725. [Google Scholar]
- Kermarrec L, Bouchez A, Rimet F, Humbert J-F. 2013. First evidence of the existence of semi-cryptic species and of a phylogeographic structure in the Gomphonema parvulum complex (Bacillariophyta). Protist 164: 686–705. [Google Scholar]
- Khan-Bureau DA, Morales EA, Ector L, Beauchene MS, Lewis LA. 2016. Characterization of a new species in the genus Didymosphenia and of Cymbella janischii (Bacillariophyta) from Connecticut, USA. Eur J Phycol 51: 203–216. [Google Scholar]
- Krammer K, Lange-Bertalot H. 1986. Bacillariophyceae, Teil 1: Naviculaceae, 876 pp. [Google Scholar]
- Krammer K, Lange-Bertalot H. 1988. Bacillariophyceae, Teil 2: Bacillariaceae, Epithemiaceae, Surirellaceae, 596 pp. [Google Scholar]
- Krammer K, Lange-Bertalot H. 1991a. Bacillariophyceae, Teil 3: Centrales, Fragilariaceae, Eunotiaceae, 576 pp. [Google Scholar]
- Krammer K, Lange-Bertalot H. 1991b. Bacillariophyceae, Teil 4: Achnanthaceae. Kritische Ergänzungen zu Navicula (Lineolatae) und Gomphonema. Gesamtliteraturverzeichnis Teil 14, 437 pp. [Google Scholar]
- Kruk C, Huszar VL, Peeters ET, Bonilla S, Costa L, Lürling M, Scheffer M. 2010. A morphological classification capturing functional variation in phytoplankton. Freshw Biol 55: 614–627. [Google Scholar]
- Laamanen T, Norros V, Vihervaara P, Jerney J, Kortelainen P, Kujala K, Lambert S, Mäyrä J, Nikula L, Palmroos I, Tolkkinen M, Vuorio K, Meissner K. 2025. Technology readiness level of biodiversity monitoring with molecular methods − where are we on the road to routine implementation? Metabarcoding Metagenom 9: e130834. [Google Scholar]
- Leese F, Altermatt F, Bouchez A, Ekrem T, Hering D, Meissner K, Mergen P, Pawlowski J, Piggott J, Rimet F, Steinke D, Taberlet P, Weigand A, Abarenkov K, Beja P, Bervoets L, Björnsdóttir S, Boets P, Boggero A, Bones A, Borja Á, Bruce K, Bursić V, Carlsson J, Čiampor F, Čiamporová-Zatovičová Z, Coissac E, Costa F, Costache M, Creer S, Csabai Z, Deiner K, DelValls Á, Drakare S, Duarte S, Eleršek T, Fazi S, Fišer C, Flot J-F., Fonseca V, Fontaneto D, Grabowski M, Graf W, GuÐbrandsson J, Hellström M, Hershkovitz Y, Hollingsworth P, Japoshvili B, Jones J, Kahlert M, Stroil BK, Kasapidis P, Kelly M, Kelly-Quinn M, Keskin E, Kõljalg U, Ljubešić Z, Maček I, Mächler E, Mahon A, Marečková M, Mejdandzic M, Mircheva G, Montagna M, Moritz C, Mulk V, Naumoski A, Navodaru I, Padisák J, Pálsson S, Panksep K, Penev L, Petrusek A, Pfannkuchen M, Primmer C, Rinkevich B, Rotter A, Schmidt-Kloiber A, Segurado P, Speksnijder A, Stoev P, Strand M, Šulčius S, Sundberg P, Traugott M, Tsigenopoulos C, Turon X, Valentini A, van der Hoorn F B, Várbíró G, Hadjilyra VM, Viguri J, Vitonytė I, Vogler A, Vrålstad T, Wägele W, Wenne R, Winding A, Woodward G, Zegura B, Zimmermann J. 2016. DNAqua-Net: Developing new genetic tools for bioassessment and monitoring of aquatic ecosystems in Europe. Res Ideas Outcomes 2:e11321. [Google Scholar]
- Li F, Zhang Y, Altermatt F, Zhang X, Cai Y, Yang Z. 2022. Gap analysis for DNA-based biomonitoring of aquatic ecosystems in China. Ecol Indic 137: 108732. [Google Scholar]
- Liu M, Zhao Y, Sun Y, Wu P, Zhou S, Ren L. 2020. Diatom DNA barcodes for forensic discrimination of drowning incidents. FEMS Microbiol Lett 367: fnaa 145. [Google Scholar]
- Marques V, Milhau T, Albouy C, Dejean T, Manel S, Mouillot D, Juhel JB. 2021. GAPeDNA: Assessing and mapping global species gaps in genetic databases for eDNA metabarcoding. Divers Distrib 27: 1880–1892. [CrossRef] [Google Scholar]
- Medlin LK. 2011. A review of the evolution of the diatoms from the origin of the lineage to their populations. In: Seckbach J. Kociolek J.P. (eds.), The Diatom World, Springer Science + Business Media B. V. pp. 93–118. [Google Scholar]
- MIGALE. 2020. Migale bioinformatics facility. INRAE. https://doi.org/10.15454/1.5572390655343293 E12. [Google Scholar]
- Murali A, Bhargava A, Wright ES. 2018. IDTAXA: A novel approach for accurate taxonomic classification of microbiome sequences. Microbiome 6: 140. [Google Scholar]
- Passy SI. 2007. Diatom ecological guilds display distinct and predictable behavior along nutrient and disturbance gradients in running waters. Aquat Bot 86: 171–178. [Google Scholar]
- Pérez-Burillo J, Trobajo R, Vasselon V, Rimet F, Bouchez A, Mann DG. 2020. Evaluation and sensitivity analysis of diatom DNA metabarcoding for WFD bioassessment of Mediterranean rivers. Sci Total Environ 727: 138445. [Google Scholar]
- Pérez-Burillo J, Valoti G, Witkowski A, Prado P, Mann DG, Trobajo R. 2022a. Assessment of marine benthic diatom communities: insights from a combined morphological-metabarcoding approach in Mediterranean shallow coastal waters. Mar Pollut Bull 174: 113183. [Google Scholar]
- Pérez-Burillo J, Mann DG, Trobajo R. 2022b. Evaluation of two short and similar rbcL markers for diatom metabarcoding of environmental samples: effects on biomonitoring assessment and species resolution. Chemosphere 307: 135933. [Google Scholar]
- RCore Team. 2019. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. [Google Scholar]
- Rimet F. 2012. Recent views on river pollution and diatoms. Hydrobiologia 683: 1–24. [Google Scholar]
- Rimet F, Bouchez A. 2012. Life-forms, cell-sizes and ecological guilds of diatoms in European rivers. Knowl Manag Aquat Ecosyst 406: 1–14. [Google Scholar]
- Rimet F, Bouchez A, Montuelle B. 2015. Benthic diatoms and phytoplankton to assess nutrients in a large lake: Complementarity of their use in Lake Geneva (France-Switzerland). Ecol Indic 53: 231–239. [Google Scholar]
- Rimet F, Abarca N, Bouchez A, Kusber WH, Jahn R, Kahlert M, et al. 2018. The potential of high-throughput sequencing (HTS) of natural samples as a source of primary taxonomic information for reference libraries of diatom barcodes. Fottea 18. [Google Scholar]
- Rimet F, Gusev E, Kahlert M, Kelly M, Kulikovskiy M, Maltsev Y, Mann D, Pfannkuchen M, Trobajo R, Vasselon V, Zimmermann J, Bouchez A. 2019. Diat.barcode, an open-access curated barcode library for diatoms. Sci Rep 9: 15116. [Google Scholar]
- Rivera SF, Vasselon V, Bouchez A, Rimet F. 2020. Diatom metabarcoding applied to large scale monitoring networks: Optimization of bioinformatics strategies using Mothur software. Ecological indicators 109: 105775. [Google Scholar]
- Round FE, Crawford RM, Mann DG. 1990. The Diatoms: Biology and Morphology of the Genera. Cambridge University Press, Vol. 747. [Google Scholar]
- Salmaso N, Padisák J. 2007. Morpho-functional groups and phytoplankton development in two deep lakes (Lake Garda, Italy and Lake Stechlin, Germany). Hydrobiologia 578: 97–112. [Google Scholar]
- Salmaso N, Naselli-Flores L, Padisák J. 2015. Functional classifications and their application in phytoplankton ecology. Freshw Biol 60: 603–619. [Google Scholar]
- Sayers EW, Cavanaugh M, Clark K, Ostell J, Pruitt KD, Karsch-Mizrachi I 2020. GenBank. Nucleic Acids Res 48: D84– D86. [Google Scholar]
- Simpson GL. 2009. Cocorresp: Co-correspondence analysis ordination methods. (R package version 0.4-0). Retrieved from http://cran.r-project.org/package=cocorresp [Google Scholar]
- Silvestro D, Michalak I. 2012. raxmlGUI: a graphical front-end for RAxML. Org Divers Evol 12: 335–337. [Google Scholar]
- Smucker NJ, Pilgrim EM, Nietch CT, Gains-Germain L, Carpenter C, Darling JA, Yuan LL, Mitchell RM, Pollard AI. 2024. Using DNA metabarcoding to characterize national scale diatom-environment relationships and to develop indicators in streams and rivers of the United States. Sci Total Environ 939: 173502. [Google Scholar]
- Spaulding SA 2021. Diatoms.org: supporting taxonomists, connecting communities. Diatom Res 36: 291–304. [CrossRef] [Google Scholar]
- Stamatakis A. 2014. RAxML Version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30: 1312–1313. [CrossRef] [PubMed] [Google Scholar]
- Stenger-Kovács C, Körmendi K, Lengyel E, Abonyi A, Hajnal É, Szabó B, Padisák J. 2018. Expanding the trait-based concept of benthic diatoms: development of trait- and species-based indices for conductivity as the master variable of ecological status in continental saline lakes. Ecol Indic 95: 63–74. [Google Scholar]
- Stoof‐Leichsenring KR, Epp LS, Trauth MH, Tiedemann R. 2012. Hidden diversity in diatoms of Kenyan Lake Naivasha: a genetic approach detects temporal variation. Mol Ecol 21: 1918–1930. [Google Scholar]
- Stoof-Leichsenring KR, Dulias K, Biskaborn BK, Pestryakova LA, Herzschuh U. 2020. Lake-depth related pattern of genetic and morphological diatom diversity in boreal Lake Bolshoe Toko, Eastern Siberia. PLoS One 15:e0230284. [Google Scholar]
- Soininen J, Jamoneau A, Rosebery J, Passy S I. 2016. Global patterns and drivers of species and trait composition in diatoms. Global ecology and biogeography 25: 940–950. [Google Scholar]
- Tapolczai K, Bouchez A, Stenger-Kovács C, Padisák J, Rimet F. 2016. Trait-based ecological classifications for benthic algae: review and perspectives. Hydrobiologia 776: 1–17. [Google Scholar]
- Tapolczai K, Bouchez A, Stenger-Kovács C, Padisák J, Rimet F. 2017. Taxonomy-or trait-based ecological assessment for tropical rivers? Case study on benthic diatoms in Mayotte island (France, Indian Ocean). Sci Total Environ 607: 1293–1303. [Google Scholar]
- Tapolczai K, Keck F, Bouchez A, Rimet F, Kahlert M, Vasselon V. 2019. Diatom DNA metabarcoding for biomonitoring: strategies to avoid major taxonomical and bioinformatical biases limiting molecular indices capacities. Front Ecol Evol 7: 1–15. [CrossRef] [Google Scholar]
- Tapolczai K, Rimet F, Ćirić M, Ballot A, Laplace-Treyture C, Alric B. 2025. A novel framework for phytoplankton biomonitoring: Trait assignment of 23S rRNA sequences. Ecol Indic 173: 113361. [Google Scholar]
- Vasselon V, Rimet F, Tapolczai K, Bouchez A. 2017. Assessing ecological status with diatoms DNA metabarcoding: Scaling-up on a WFD monitoring network (Mayotte island, France). Ecol Indic 82: 1–12. [Google Scholar]
- Vasselon V, Bouchez A, Rimet F, Jacquet S, Trobajo R, Corniquel M, et al. 2018. Avoiding quantification bias in metabarcoding: application of a cell biovolume correction factor in diatom molecular biomonitoring. Methods Ecol Evol 9: 1060–1069. [Google Scholar]
- Vasselon V, Rivera SF, Ács É, Almeida SB, Andree KB, Apothéloz-Perret-Gentil L, Bailet B, Baričević A, Beentjes KK, Bettig J, Paix B. 2025. Proficiency testing and cross-laboratory method comparison to support standardisation of diatom DNA metabarcoding for freshwater biomonitoring. Metabarcoding Metagenom 9: e133264. [Google Scholar]
- Weigand H, Beermann AJ, Čiampor F, Costa FO, Csabai Z, Duarte S, Ekrem T. 2019. DNA barcode reference libraries for the monitoring of aquatic biota in Europe: gap-analysis and recommendations for future work. Sci Total Environ 678: 499–524. [CrossRef] [PubMed] [Google Scholar]
- Wolf DI, Vis ML. 2020. Stream algal biofilm community diversity along an acid mine drainage recovery gradient using multimarker metabarcoding. J Phycol 56: 11–22. [Google Scholar]
- Zorzal-Almeida S, Soininen J, Bini LM, Bicudo DC. 2017. Local environment and connectivity are the main drivers of diatom species composition and trait variation in a set of tropical reservoirs. Freshw Biol 62: 1551–1563. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.
