Search

Menu
Search
in Ecology

Environmental DNA reveals hidden eukaryotic diversity and fine-scale community patterns across seascape areas in the Northern Red Sea

199 Views


Abstract

Understanding how reef-associated biodiversity responds to seascape features is essential for monitoring and conserving coral reef ecosystems. Environmental DNA (eDNA) from seawater provides access to benthopelagic eukaryotic diversity but its relationship with benthic structure remains poorly understood. We conducted simultaneous assessment of benthopelagic eDNA derived from near-reef seawater and benthic photoquadrat surveys across 12 coral reef sites in the northern Red Sea, spanning three seascape regions: the Gulf of Aqaba, nearshore Northern Red Sea (NRS), and offshore NRS. We examined whether spatial patterns in benthopelagic eDNA communities were structured across regions and whether variation in benthic cover explained differences in eDNA-derived assemblages obtained from water samples. Benthopelagic eDNA revealed fine-scale spatial structuring across regions but showed non-significant whole-community correlation with benthic composition. When examined by major taxonomic groups, taxon-specific relationships emerged, with some taxa (i.e., Micromonas sp.) showing increasing relative abundances in reefs characterized by lower benthic complexity. While traditional photoquadrat surveys captured 72 benthic sessile taxa including dominant benthic groups (e.g. hard corals and algae) across four eukaryotic phyla, benthopelagic eDNA documented a broader range of eukaryotic diversity, including planktonic, cryptic, and low abundant taxa spanning 35 phyla. Notably, eDNA detected cryptic organisms overlooked by visual surveys, such the giant clam Tridacna sp., even where present but not recorded in photoquadrats. Our results demonstrate that benthopelagic eDNA and visual surveys provide complementary perspectives on reef biodiversity. Rather than serving as a direct proxy for benthic structure, benthopelagic eDNA captures spatial and taxonomic patterns that may be overlooked by visual transects, supporting its use in seascape-scale biodiversity assessments and conservation planning efforts in dynamic and understudied reef systems.

Data availability

Datasets and scripts used for data analysis have been deposited in GitHub [https://github.com/BEMlabKAUST/NEOM-2023-eDNA-COI](https:/www.google.com/url? q=https:/github.com/BEMlabKAUST/NEOM-2023-eDNA-COI&sa=D&source=docs&ust=1751464067758035&usg=AOvVaw2fbvpN29g_Big18AF25SNV)Reads have been deposited in NCBI SRA under BioProject accession PRJNA1283908, and can be accessed via https://www.ncbi.nlm.nih.gov/sra/?term=SRR34288405.

References

  1. Diaz, S. et al. Pervasive human-driven decline of life on Earth points to the need for transformative change. Science 366 https://doi.org/10.1126/science.aax3100 (2019).

  2. Exposito-Alonso, M. et al. Genetic diversity loss in the Anthropocene. Science 377, 1431–1435. https://doi.org/10.1126/science.abn5642 (2022).

    Google Scholar 

  3. Guan, Y., Hohn, S., Wild, C. & Merico, A. Vulnerability of global coral reef habitat suitability to ocean warming, acidification and eutrophication. Glob Change Biol. 26, 5646–5660. https://doi.org/10.1111/gcb.15293 (2020).

    Google Scholar 

  4. Burke, L., Reytar, K., Spalding, M. & Perry, A. Reefs at risk revisited (World Resources Institute (WRI), 2011).

  5. Hughes, T. P. et al. Coral reefs in the Anthropocene. Nature 546, 82–90 (2017).

    Google Scholar 

  6. Knowlton, N. et al. “Coral reef biodiversity” in Life world’s oceans: Divers. distribution abundance, 65–74, ed. McIntyre, A.D. (Blackwell Publishing Ltd) (2010). https://doi.org/10.1002/9781444325508

  7. Adey, W. H. Coral Reef Ecosystems and Human Health: Biodiversity Counts! Ecosyst. Health. 6, 227–236. https://doi.org/10.1046/j.1526-0992.2000.006004227.x (2000).

    Google Scholar 

  8. Woodhead, A. J., Hicks, C. C., Norström, A. V. & Williams, G. J. Graham, N. A. Coral reef ecosystem services in the Anthropocene. Funct. Ecol. 33, 1023–1034 (2019).

    Google Scholar 

  9. Beger, M., Jones, G. P. & Munday, P. L. Conservation of coral reef biodiversity: a comparison of reserve selection procedures for corals and fishes. Biol. Conserv. 111, 53–62 (2003).

    Google Scholar 

  10. Miloslavich, P. et al. Essential ocean variables for global sustained observations of biodiversity and ecosystem changes. Glob Chang. Biol. 24, 2416–2433 (2018).

    Google Scholar 

  11. Pereira, P. H. et al. Reef fishes biodiversity and conservation at the largest Brazilian coastal Marine Protected Area (MPA Costa dos Corais). Neotrop. Ichthyol. 19, e210071 (2021).

    Google Scholar 

  12. Heenan, A. & Williams, I. D. Monitoring herbivorous fishes as indicators of coral reef resilience in American Samoa. PLoS One. 8, e79604 (2013).

    Google Scholar 

  13. Smith, J. E. et al. Re-evaluating the health of coral reef communities: baselines and evidence for human impacts across the central Pacific. Proc. R Soc. Lond. B Biol. Sci. 283, 20151985 (2016).

    Google Scholar 

  14. Fisher, R. et al. Species richness on coral reefs and the pursuit of convergent global estimates. Curr. Biol. 25, 500–505 (2015).

    Google Scholar 

  15. Carvalho, S. et al. Beyond the visual: using metabarcoding to characterize the hidden reef cryptobiome. Proc. R Soc. Lond. B Biol. Sci. 286, 20182697 (2019).

    Google Scholar 

  16. Stella, J. S. et al. Functional and phylogenetic responses of motile cryptofauna to habitat degradation. J. Anim. Ecol. 91, 2203–2219 (2022).

    Google Scholar 

  17. Wolfe, K., Kenyon, T. M. & Mumby, P. J. The biology and ecology of coral rubble and implications for the future of coral reefs. Coral Reefs. 40, 1769–1806 (2021).

    Google Scholar 

  18. Aylagas, E., Borja, Á. & Muxika, I. Rodríguez-Ezpeleta, N. Adapting metabarcoding-based benthic biomonitoring into routine marine ecological status assessment networks. Ecol. Indic. 95, 194–202. https://doi.org/10.1016/j.ecolind.2018.07.044 (2018).

    Google Scholar 

  19. DiBattista, J. D. et al. Environmental DNA can act as a biodiversity barometer of anthropogenic pressures in coastal ecosystems. Sci. Rep. 10 https://doi.org/10.1038/s41598-020-64858-9 (2020).

  20. Ruiz-Abierno, A. & Armenteros, M. Coral reef habitats strongly influence the diversity of macro-and meiobenthos in the Caribbean. Mar. Biodivers. 47, 101–111 (2017).

    Google Scholar 

  21. Fraser, K. et al. Production of mobile invertebrate communities on shallow reefs from temperate to tropical seas. Proc. R Soc. Lond. B Biol. Sci. 287, 20201798 (2020).

    Google Scholar 

  22. Armenteros, M. et al. Cryptofaunal communities are influenced by benthic cover and fish abundance in a large Caribbean coral reef system. Coral Reefs. 43, 1731–1748 (2024).

    Google Scholar 

  23. Villalobos, R. et al. Responses of the coral reef cryptobiome to environmental gradients in the Red Sea. PLoS One. 19, e0301837. https://doi.org/10.1371/journal.pone.0301837 (2024).

    Google Scholar 

  24. Marzo-Pérez, D., Pérez-García, J. A., Apprill, A. & Armenteros, M. Diversity of Cryptofaunal Nematode Assemblages along the Jardines de La Reina Coral Reef, Southern Cuba. Diversity 16, 264 (2024).

    Google Scholar 

  25. Deiner, K. et al. Environmental DNA metabarcoding: Transforming how we survey animal and plant communities. Mol. Ecol. 26, 5872–5895 (2017).

    Google Scholar 

  26. Bakker, J. et al. Biodiversity assessment of tropical shelf eukaryotic communities via pelagic eDNA metabarcoding. Ecol. Evol. 9, 14341–14355. https://doi.org/10.1002/ece3.5871 (2019).

    Google Scholar 

  27. Madduppa, H. et al. eDNA metabarcoding illuminates species diversity and composition of three phyla (chordata, mollusca and echinodermata) across Indonesian coral reefs. Biodivers. Conserv. 30, 3087–3114. https://doi.org/10.1007/s10531-021-02237-0 (2021).

    Google Scholar 

  28. DiBattista, J. D., Fowler, A. M., Shalders, T. C., Williams, R. J. & Wilkinson, S. Tree of life metabarcoding can serve as a biotic benchmark for shifting baselines in urbanized estuaries. Environ. Res. 258, 119454 (2024).

    Google Scholar 

  29. Taberlet, P., Bonin, A., Zinger, L. & Coissac, E. Environmental DNA: For biodiversity research and monitoring (Oxford University Press, 2018).

  30. West, K. M. et al. eDNA metabarcoding survey reveals fine-scale coral reef community variation across a remote, tropical island ecosystem. Mol. Ecol. 29, 1069–1086 (2020).

    Google Scholar 

  31. Dugal, L. et al. Coral monitoring in northwest Australia with environmental DNA metabarcoding using a curated reference database for optimized detection. Environ. DNA. 4, 63–76 (2022).

    Google Scholar 

  32. Jeunen, G. J. et al. Environmental DNA (eDNA) metabarcoding reveals strong discrimination among diverse marine habitats connected by water movement. Mol. Ecol. Resour. 19, 426–438. https://doi.org/10.1111/1755-0998.12982 (2019).

    Google Scholar 

  33. Allan, E. A., Dibenedetto, M. H., Lavery, A. C., Govindarajan, A. F. & Zhang, W. G. Modeling characterization of the vertical and temporal variability of environmental DNA in the mesopelagic ocean. Sci. Rep. 11 https://doi.org/10.1038/s41598-021-00288-5 (2021).

  34. Sempere-Valverde, J. et al. First assessment of biofouling assemblages in the northern Red Sea, an important region for marine non-indigenous species transfer. Front. Mar. Sci. 12 https://doi.org/10.3389/fmars.2025.1522723 (2025).

  35. Alexander, J. B. et al. Development of a multi-assay approach for monitoring coral diversity using eDNA metabarcoding. Coral Reefs. 39, 159–171 (2020).

    Google Scholar 

  36. Muenzel, D. et al. Combining environmental DNA and visual surveys can inform conservation planning for coral reefs. Proc. Natl. Acad. Sci. USA. 121, e2307214121 (2024).

  37. Nichols, P. K. & Marko, P. B. Rapid assessment of coral cover from environmental DNA in Hawai’i. Environ. DNA. 1, 40–53. https://doi.org/10.1002/edn3.8 (2019).

    Google Scholar 

  38. Nguyen, B. N. et al. Environmental DNA survey captures patterns of fish and invertebrate diversity across a tropical seascape. Sci. Rep. 10 https://doi.org/10.1038/s41598-020-63565-9 (2020).

  39. Mittal, H. V. R., Hammoud, M. A. E. R., Carrasco, A. K., Hoteit, I. & Knio, O. M. Oil spill risk analysis for the NEOM shoreline. Sci. Rep. 14, 6623. https://doi.org/10.1038/s41598-024-57048-4 (2024).

    Google Scholar 

  40. Dugal, L. et al. Distinct coral reef habitat communities characterized by environmental DNA metabarcoding. Coral Reefs. 42, 17–30 (2023).

    Google Scholar 

  41. Hill, J. & Wilkinson, C. Methods For Ecological Monitoring Of Coral Reefs A Resource For Managers Australian Institute Of Marine Science. Townsville Australia, 117 pp (2004).

  42. Bruno, J. F. & Selig, E. R. Regional decline of coral cover in the Indo-Pacific: timing, extent, and subregional comparisons. PLoS One. 2, e711 (2007).

    Google Scholar 

  43. Williams, I. D. et al. Leveraging automated image analysis tools to transform our capacity to assess status and trends of coral reefs. Front. Mar. Sci. 6, 222 (2019).

    Google Scholar 

  44. Pearman, J. K., Anlauf, H., Irigoien, X. & Carvalho, S. Please mind the gap – Visual census and cryptic biodiversity assessment at central Red Sea coral reefs. Mar. Environ. Res. 118, 20–30. https://doi.org/10.1016/j.marenvres.2016.04.011 (2016).

    Google Scholar 

  45. Stat, M. et al. Ecosystem biomonitoring with eDNA: metabarcoding across the tree of life in a tropical marine environment. Sci. Rep. 7 https://doi.org/10.1038/s41598-017-12501-5 (2017).

  46. Pernice, M. et al. Down to the bone: the role of overlooked endolithic microbiomes in reef coral health. ISME J. 14, 325–334. https://doi.org/10.1038/s41396-019-0548-z (2019).

    Google Scholar 

  47. Singer, D. et al. Protist taxonomic and functional diversity in soil, freshwater and marine ecosystems. Environ. Int. 146, 106262. https://doi.org/10.1016/j.envint.2020.106262 (2021).

    Google Scholar 

  48. Govindarajan, A. F. et al. Exploring the use of environmental DNA (eDNA) to detect animal taxa in the mesopelagic zone. Front. Ecol. Evol. 9, 574877 (2021).

    Google Scholar 

  49. Collins, R. A. et al. Persistence of environmental DNA in marine systems. Commun. Biology. 1, 185. https://doi.org/10.1038/s42003-018-0192-6 (2018).

    Google Scholar 

  50. Wu, Y. et al. Integrating Dam-Induced Effects into a Bayesian eDNA-Hydrodynamic Model to Improve Fish Monitoring in Regulated Rivers. Environ. Sci. Technol. 59, 21670–21681 (2025).

    Google Scholar 

  51. Hoban, M. L., Bunce, M. & Bowen, B. W. Plumbing the depths with environmental DNA (eDNA): Metabarcoding reveals biodiversity zonation at 45–60 m on mesophotic coral reefs. Mol. Ecol. 32, 5590–5608 (2023).

    Google Scholar 

  52. Villalobos, R. et al. Biodiversity patterns of the coral reef cryptobiota around the Arabian Peninsula. Sci. Rep. 14 https://doi.org/10.1038/s41598-024-60336-8 (2024).

  53. Levy, N. et al. Evaluating biodiversity for coral reef reformation and monitoring on complex 3D structures using environmental DNA (eDNA) metabarcoding. Sci. Total Environ. 856, 159051. https://doi.org/10.1016/j.scitotenv.2022.159051 (2023).

    Google Scholar 

  54. Pearman, J. K. et al. Pan-regional marine benthic cryptobiome biodiversity patterns revealed by metabarcoding Autonomous Reef Monitoring Structures. Mol. Ecol. 29, 4882–4897. https://doi.org/10.1111/mec.15692 (2020).

    Google Scholar 

  55. Ma, H. et al. Multiplex species-specific PCR identification of native giant clams in the South China Sea: A useful tool for application in giant clam stock management and forensic identification. Aquac 531, 735991. https://doi.org/10.1016/j.aquaculture.2020.735991 (2021).

    Google Scholar 

  56. Koziol, A. et al. Environmental DNA metabarcoding studies are critically affected by substrate selection. Mol. Ecol. Resour. 19, 366–376 (2019).

    Google Scholar 

  57. Gösser, F., Schweinsberg, M., Mittelbach, P., Schoenig, E. & Tollrian, R. An environmental DNA metabarcoding approach versus a visual survey for reefs of Koh Pha-ngan in Thailand. Environ. DNA. 5, 297–311. https://doi.org/10.1002/edn3.378 (2023).

    Google Scholar 

  58. Nishitsuji, K. et al. An environmental DNA metabarcoding survey reveals generic-level occurrence of scleractinian corals at reef slopes of Okinawa Island. Proc. R Soc. Lond. B Biol. Sci. 290, 20230026 (2023).

    Google Scholar 

  59. Reimer, J. D. & Gösser, F. Can environmental DNA unlock the mysteries of biodiversity on coral reefs? Proc. R Soc. Lond. B Biol. Sci. 290, 20230605. https://doi.org/10.1098/rspb.2023.0605 (2023).

    Google Scholar 

  60. McCartin, L. et al. Nuclear eDNA metabarcoding primers for anthozoan coral biodiversity assessment. PeerJ 12, e18607. https://doi.org/10.7717/peerj.18607 (2024).

    Google Scholar 

  61. Wangensteen, O. S., Palacín, C., Guardiola, M. & Turon, X. DNA metabarcoding of littoral hard-bottom communities: high diversity and database gaps revealed by two molecular markers. PeerJ 6, e4705 (2018).

    Google Scholar 

  62. Apprill, A. et al. Toward a New Era of Coral Reef Monitoring. Environ. Sci. Technol. 57, 5117–5124. https://doi.org/10.1021/acs.est.2c05369 (2023).

    Google Scholar 

  63. Darling, E. S. et al. Relationships between structural complexity, coral traits, and reef fish assemblages. Coral Reefs. 36, 561–575 (2017).

    Google Scholar 

  64. Counsell, C. W. W., Donahue, M. J., Edwards, K. F., Franklin, E. C. & Hixon, M. A. Variation in coral-associated cryptofaunal communities across spatial scales and environmental gradients. Coral Reefs. 37, 827–840. https://doi.org/10.1007/s00338-018-1709-7 (2018).

    Google Scholar 

  65. Enochs, I. C. & Manzello, D. P. Species richness of motile cryptofauna across a gradient of reef framework erosion. Coral Reefs. 31, 653–661. https://doi.org/10.1007/s00338-012-0886-z (2012).

    Google Scholar 

  66. Furlan, E. M., Gleeson, D., Hardy, C. M. & Duncan R. P. A framework for estimating the sensitivity of eDNA surveys. Mol. Ecol. Resour. 16, 641–654 (2016).

    Google Scholar 

  67. Zanovello, L. et al. DNA metabarcoding analysis of stomach flushing contents reveals the exceptionally diverse diet of the golden alpine salamander. Sci. Rep. 15, 1–12 (2025).

    Google Scholar 

  68. Guo, X., Pang, M., Zheng, X. & Huang, L. Micromonas, a small pigmented flagellate, predominates the nanoflagellate and photosynthetic picoeukaryote communities in the northern South China Sea. Environ. Microbiol. Rep. 16, e13244. https://doi.org/10.1111/1758-2229.13244 (2024).

    Google Scholar 

  69. Ip, Y. C. A. et al. Seeking life in sedimented waters: Environmental DNA from diverse habitat types reveals ecologically significant species in a tropical marine environment. Environ. DNA. 3, 654–668. https://doi.org/10.1002/edn3.162 (2021).

    Google Scholar 

  70. Girard, E. B. et al. Coastal eutrophication transforms shallow micro-benthic reef communities. Sci. Total Environ. 961, 178252. https://doi.org/10.1016/j.scitotenv.2024.178252 (2025).

    Google Scholar 

  71. Glasl, B., Webster, N. S. & Bourne, D. G. Microbial indicators as a diagnostic tool for assessing water quality and climate stress in coral reef ecosystems. Mar. Biol. 164 https://doi.org/10.1007/s00227-017-3097-x (2017).

  72. Terzin, M. et al. The road forward to incorporate seawater microbes in predictive reef monitoring. Environ. microbiome. 19 https://doi.org/10.1186/s40793-023-00543-4 (2024).

  73. Beijbom, O. et al. Towards automated annotation of benthic survey images: Variability of human experts and operational modes of automation. PLoS One. 10, e0130312 (2015).

    Google Scholar 

  74. Gonzalez, K. et al. Differential spatio-temporal responses of Red Sea coral reef benthic communities to a mass bleaching event. Sci. Rep. 14, 24229 (2024).

    Google Scholar 

  75. DiBattista, J. D. et al. Assessing the utility of eDNA as a tool to survey reef-fish communities in the Red Sea. Coral Reefs. 36, 1245–1252 (2017).

    Google Scholar 

  76. Leray, M. et al. A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: application for characterizing coral reef fish gut contents. Front. Zool. 10, 1–14 (2013).

    Google Scholar 

  77. Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, 10–12 (2011).

    Google Scholar 

  78. Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods. 13, 581–583 (2016).

    Google Scholar 

  79. Schultz, J. A. & Hebert, P. D. N. Do pseudogenes pose a problem for metabarcoding marine animal communities? Mol. Ecol. Resour. 22, 2897–2914. https://doi.org/10.1111/1755-0998.13667 (2022).

    Google Scholar 

  80. Buchner, D. & Leese, F. BOLDigger–a Python package to identify and organise sequences with the Barcode of Life Data systems. MBMG 4, e53535 (2020).

    Google Scholar 

  81. Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).

    Google Scholar 

  82. Ratnasingham, S., Hebert, P. D. & BOLD The Barcode of Life Data System. Mol. Ecol. Notes. 7, 355–364 (2007). http://www.barcodinglife.org.

    Google Scholar 

  83. Teixeira, M. A., Aylagas, E., Pearman, J. K. & Carvalho, S. Gaps and Data Ambiguities in DNA Reference Libraries: A Limiting Factor for Molecular-Based Biodiversity Assessments Using Annelids as a Case Study. Ecol. Evol. 15, e71544 (2025).

    Google Scholar 

  84. Antich, A., Palacin, C., Wangensteen, O. S. & Turon, X. To denoise or to cluster, that is not the question: optimizing pipelines for COI metabarcoding and metaphylogeography. BMC Bioinform. 22, 177 (2021).

    Google Scholar 

  85. Antich, A., Palacín, C., Zarcero, J., Wangensteen, O. S. & Turon, X. Metabarcoding reveals high-resolution biogeographical and metaphylogeographical patterns through marine barriers. J. Biogeogr. 50, 515–527 (2023).

    Google Scholar 

  86. Giebner, H. et al. Comparing diversity levels in environmental samples: DNA sequence capture and metabarcoding approaches using 18S and COI genes. Mol. Ecol. Resour. 20, 1333–1345 (2020).

    Google Scholar 

  87. Rognes, T., Flouri, T., Nichols, B., Quince, C. & Mahé, F. VSEARCH: a versatile open source tool for metagenomics. PeerJ 4, e2584. https://doi.org/10.7717/peerj.2584 (2016).

    Google Scholar 

  88. Oksanen, J. et al. vegan: Community Ecology Package. 2.3-2 edn, (2015).

  89. Legendre, P. & Gallagher, E. D. Ecologically Meaningful Transformations for Ordination of Species Data. Oecologia 129, 271–280 (2001).

    Google Scholar 

  90. Acker, J. et al. Remotely-sensed chlorophyll a observations of the northern Red Sea indicate seasonal variability and influence of coastal reefs. J. Mar. Syst. 69 (3–4), 191–204. https://doi.org/10.1016/j.jmarsys.2005.12.006 (2008).

    Google Scholar 

Download references

Acknowledgements

We would like to express our special thanks to Chakkiath Paul Antony for his support during raw sequencing data processing and to Carolina Bocanegra and Doaa Baker from their assistance in sample preparation.

Funding

This study was funded by the Ocean Science and Solutions Applied Research Institute (OSSARI), NEOM (RGC/3/5209-01-01) and the baseline funding from KAUST (BAS/1/1109-01-01).

Author information

Authors and Affiliations

  1. Biological and Environmental Sciences and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia

    Eva Aylagas, Karla Gonzalez, Warren R. Francis, Basmah Alabdulaziz, Joao Gabriel Rosado, Gloria Gil-Ramos, Matthew David Tietbohl Talas, Morgan Bennett-Smith, Viktor N. Peinemann, Michael L. Berumen, Maggie D. Johnson & Susana Carvalho

  2. Applied Genomic Technologies Institute, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia

    Basmah Alabdulaziz

  3. Department of Biology, Boston University, 5 Cummington Mall, Boston, MA, 02215, USA

    Morgan Bennett-Smith

  4. Education, Research, and Innovation Foundation, Ocean Science and Solutions Applied Research Institute (OSSARI), NEOM Base Camp, Building Number, 4758, NEOM, 49643, Saudi Arabia

    Flor Torres

  5. Rosenstiel School of Marine and Atmospheric Sciences, University of Miami, Coral Gables, USA

    Ameer A. Eweida

  6. Marine Biodiversity, Ecosystems, and Conservation, NEOM, 49643, Saudi Arabia

    Ameer A. Eweida

Authors

  1. Eva Aylagas
    View author publications

    Search author on:PubMed Google Scholar

  2. Karla Gonzalez
    View author publications

    Search author on:PubMed Google Scholar

  3. Warren R. Francis
    View author publications

    Search author on:PubMed Google Scholar

  4. Basmah Alabdulaziz
    View author publications

    Search author on:PubMed Google Scholar

  5. Joao Gabriel Rosado
    View author publications

    Search author on:PubMed Google Scholar

  6. Gloria Gil-Ramos
    View author publications

    Search author on:PubMed Google Scholar

  7. Matthew David Tietbohl Talas
    View author publications

    Search author on:PubMed Google Scholar

  8. Morgan Bennett-Smith
    View author publications

    Search author on:PubMed Google Scholar

  9. Viktor N. Peinemann
    View author publications

    Search author on:PubMed Google Scholar

  10. Flor Torres
    View author publications

    Search author on:PubMed Google Scholar

  11. Ameer A. Eweida
    View author publications

    Search author on:PubMed Google Scholar

  12. Michael L. Berumen
    View author publications

    Search author on:PubMed Google Scholar

  13. Maggie D. Johnson
    View author publications

    Search author on:PubMed Google Scholar

  14. Susana Carvalho
    View author publications

    Search author on:PubMed Google Scholar

Contributions

S.C., E.A., F.T., and A.E. funded the project and contributed to study design. M.D.T.T., M.B.S., V.N.P., B.A., J.G.R., G.G.R. contributed to sample acquisition and laboratory processing. E.A., K.G., and W.R.F. analyzed the data and produced the figures. E.A., K.G., W.R.F, and S.C. wrote the manuscript. M.D.J., M.L.B., S.C., and E.A. supervised students contributing to this manuscript. All authors revised and contributed to the final version manuscript.

Corresponding authors

Correspondence to
Eva Aylagas or Susana Carvalho.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethical approval and permits

Field sampling was conducted in compliance with institutional biosafety and bioethics regulations. The study was approved by the KAUST Institutional Animal Care and Use Committee under the reference #24IACUC020 and seawater samples were collected under the permits issued by NEOM.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1 (download DOCX )

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Cite this article

Aylagas, E., Gonzalez, K., Francis, W.R. et al. Environmental DNA reveals hidden eukaryotic diversity and fine-scale community patterns across seascape areas in the Northern Red Sea.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-47093-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41598-026-47093-6

Keywords

  • coral reef monitoring
  • environmental DNA (eDNA)
  • seascape ecology
  • eukaryotic communities
  • benthic structure

Source: Ecology - nature.com

Ranking water-scarcity management strategies using the TOPSIS method

Associations between soil microbiomes and carbon stabilization under long-term no-till farming systems in the Argentine Pampas

This portal is not a newspaper as it is updated without periodicity. It cannot be considered an editorial product pursuant to law n. 62 of 7.03.2001. The author of the portal is not responsible for the content of comments to posts, the content of the linked sites. Some texts or images included in this portal are taken from the internet and, therefore, considered to be in the public domain; if their publication is violated, the copyright will be promptly communicated via e-mail. They will be immediately removed.

Back to Top
Close