ALGAE

The Korean Society of Phycology (한국조류학회(藻類))
권호 표지
DOI QR코드

DOI QR Code

Cortical structure of macroalgae influences epiphytic eukaryotic assemblages

  • Juhee Min (Department of Oceanography, College of Natural Sciences, Chonnam National University) ;
  • Kwang Young Kim (Department of Oceanography, College of Natural Sciences, Chonnam National University)
  • Received : 2025.05.30
  • Accepted : 2025.08.08
  • Published : 2025.09.15
Download PDF
⟨ Previous Next ⟩

Abstract

Macroalgae host diverse epiphytic eukaryotes that contribute to coastal biodiversity and ecosystem function. Yet how fine-scale host traits shape these communities remains unclear. Using small organelle-enriched metagenomics (SoEM), we profiled epiphytes on eight intertidal macroalgal species from Korea and tested whether host cortical cell layer thickness predicts community structure. Epiphytic composition separated strongly by cortical thickness (thick > 8 cells vs. thin ≤ 5 cells), independent of host phylum. Thick-layered hosts predominantly harbored macrofauna (e.g., Malacostraca, Hexapoda), whereas thin-layered hosts were dominated by microalgae (diatoms). Phylogenetic diversity and the net relatedness index (NRI) indicated phylogenetic clustering in most thick-layered hosts (suggesting habitat filtering), while thin-layered hosts tended toward near-random assembly. Our findings identify cortical cell layer thickness as a key morphological trait structuring epiphytic eukaryotic communities. This trait-based perspective clarifies host-epiphyte interactions and motivates replicated, multi-scale studies integrating morphological and functional traits with genomic data for coastal biodiversity management.

Keywords

Acknowledgement

This research was supported by a National Research Foundation (NRF) grant funded by the Korean government (MSIT) (NRF-2022M3I6A1085991) to KYK. Additional support was provided by the BK-21 FOUR program through National Research Foundation of Korea (NRF) under Ministry of Education to KYK.

References

  1. Arendsee, Z., Li, J., Singh, U., Seetharam, A., Dorman, K. & Wurtele, E. S. 2019. phylostratr: a framework for phylostratigraphy. Bioinformatics 35:3617–3627. doi.org/10.1093/bioinformatics/btz171
  2. Bjorbækmo, M. F. M., Brodie, J., Krabberød, A. K., et al. 2023. 18S rDNA gene metabarcoding of microeukaryotes and epi-endophytes in the holobiome of seven species of large brown algae. J. Phycol. 59:859–878. doi.org/10.1111/jpy.13377
  3. Bolger, A. M., Lohse, M. & Usadel, B. 2014. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120. doi.org/10.1093/bioinformatics/btu170
  4. Bringloe, T. T. 2023. Unraveling brown seaweed eukaryomes through metabarcoding. J. Phycol. 59:856–858. doi.org/10.1111/jpy.13383
  5. Burfeid-Castellanos, A. M., Martín-Martín, R. P., Kloster, M., Angulo-Preckler, C., Avila, C. & Beszteri, B. 2021. Epiphytic diatom community structure and richness is determined by macroalgal host and location in the South Shetland Islands (Antarctica). PLoS ONE 16:e0250629. doi.org/10.1371/journal.pone.0250629
  6. Cappelatti, L., Mauffrey, A. R. L. & Griffin, J. N. 2020. Functional diversity of habitat formers declines scale-dependently across an environmental stress gradient. Oecologia 194:135–149. doi.org/10.1007/s00442-020-04746-1
  7. Chamberlain, S. & Vanhoorne, B. 2023. worrms: World Register of Marine Species (WoRMS) Client. R package version 0.4.3. Available from: https://cran.r-project.org/package=worrms. Accessed Sep 20, 2024.
  8. Chemello, R. & Milazzo, M. 2002. Effect of algal architecture on associated fauna: some evidence from phytal molluscs. Mar. Biol. 140:981–990. doi.org/10.1007/s00227-002-0777-x
  9. Chen, Y.-Y., Edgar, G. J. & Fox, R. J. 2021. The nature and ecological significance of epifaunal communities within marine ecosystems. In Hawkins, S. J., Lemasson, A. J., Allcock, A. L., et al. (Eds.) Oceanography and Marine Biology: and Annual Review. CRC Press, Boca Raton, FL, pp. 585–720.
  10. El-Khaled, Y. C., Daraghmeh, N., Tilstra, A., et al. 2022. Fleshy red algae mats act as temporary reservoirs for sessile invertebrate biodiversity. Commun. Biol. 5:579. doi.org/10.1038/s42003-022-03523-5
  11. Florez, J. Z., Camus, C., Hengst, M. B. & Buschmann, A. H. 2017. A functional perspective analysis of macroalgae and epiphytic bacterial community interaction. Front. Microbiol. 8:2561. doi.org/10.3389/fmicb.2017.02561
  12. Fong, C. R., Ryznar, E. R., Smith, L. L. & Fong, P. 2023. Towards a trait-based framework for marine macroalgae: using categorical data to explore the nature of emergent functional groups. J. Ecol. 111:1848–1865. doi.org/10.1111/1365-2745.14144
  13. Gallardo, D., Oliva, F. & Ballesteros, M. 2021. Marine invertebrate epibionts on photophilic seaweeds: importance of algal architecture. Mar. Biodivers. 51:16. doi.org/10.1007/s12526-020-01151-y
  14. Gibbons, E. G. & Quijón, P. A. 2023. Macroalgal features and their influence on associated biodiversity: implications for conservation and restoration. Front. Mar. Sci. 10:1304000. doi.org/10.3389/fmars.2023.1304000
  15. Hwang, E. K., Choi, H. G. & Kim, J. K. 2020. Seaweed resources of Korea. Bot. Mar. 63:395–405. doi.org/10.1515/bot-2020-0007
  16. Jin, S., Lee, H.-G., Park, C. & Kim, K. Y. 2023. Small-organelle-enriched metagenomics: an improved method for environmental DNA-based identification of marine plankton. Limnol. Oceanogr. Methods 21:178–191. doi.org/10.1002/lom3.10538
  17. Jo, J., Lee, H. G., Kim, K. Y. & Park, C. 2019. SoEM: a novel PCR-free biodiversity assessment method based on small-organelles enriched metagenomics. Algae 34:57–70. doi.org/10.4490/algae.2019.34.2.26
  18. Keith, S. A., Kerswell, A. P. & Connolly, S. R. 2014. Global diversity of marine macroalgae: environmental conditions explain less variation in the tropics. Glob. Ecol. Biogeogr. 23:517–529. doi.org/10.1111/geb.12132
  19. Kembel, S. W., Cowan, P. D., Helmus, M. R., et al. 2010. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26:1463–1464. doi.org/10.1093/bioinformatics/btq166
  20. Kim, H. M., Jo, J., Park, C., Choi, B.-J., Lee, H.-G. & Kim, K. Y. 2019. Epibionts associated with floating Sargassum horneri in the Korea Strait. Algae 34:303–313. doi.org/10.4490/algae.2019.34.12.10
  21. Kim, S. Y., Boo, S. M., Yoon, H. S. & Kim, M. S. 2023. Insight into the species identification and distribution of Grateloupiaceae (Halymeniales, Rhodophyta) having Grateloupia filicina-like morphology in the Northwest Pacific. Algae 38:23–38. doi.org/10.4490/algae.2023.38.3.14
  22. Koehl, M. A. R. & Daniel, T. L. 2022. Hydrodynamic interactions between macroalgae and their epibionts. Front. Mar. Sci. 9:872960. doi.org/10.3389/fmars.2022.872960
  23. Lachnit, T., Meske, D., Wahl, M., Harder, T. & Schmitz, R. 2011. Epibacterial community patterns on marine macroalgae are host-specific but temporally variable. Environ. Microbiol. 13:655–665. doi.org/10.1111/j.1462-2920.2010.02371.x
  24. Lenzo, D., Colangelo, M. A., Pasteris, A., Rindi, F., Pistocchi, R. & Pezzolesi, L. 2023. Understanding the role of macroalgal complexity and allelochemicals production in invasive and non-invasive macroalgae in the north-western Adriatic Sea: effect on the associated communities. Water 15:1697. doi.org/10.3390/w15091697
  25. Littler, M. M. & Littler, D. S. 1984. Relationships between macroalgal functional form groups and substrata stability in a subtropical rocky-intertidal system. J. Exp. Mar. Biol. Ecol. 74:13–34. doi.org/10.1016/0022-0981(84)90035-2
  26. Liu, J., Meng, Z., Liu, X. & Zhang, X.-H. 2019. Microbial assembly, interaction, functioning, activity and diversification: a review derived from community compositional data. Mar. Life Sci. Technol. 1:112–128. doi.org/10.1007/s42995-019-00004-3
  27. Logares, R., Deutschmann, I. M., Junger, P. C., et al. 2020. Disentangling the mechanisms shaping the surface ocean microbiota. Microbiome 8:55. doi.org/10.1186/s40168-020-00827-8
  28. Machado, J. P. G. & Oliveira, V. P. 2024. The distribution of seaweed forms and foundational assumptions in seaweed biology. Sci. Rep. 14:22407. doi.org/10.1038/s41598-024-73857-z
  29. Magoč, T. & Salzberg, S. L. 2011. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27:2957–2963. doi.org/10.1093/bioinformatics/btr507
  30. Malik, S. A. A., Bedoux, G., Garcia Maldonado, J. Q., Freile-Pelegrín, Y., Robledo, D. & Bourgougnon, N. 2020. Defence on surface: macroalgae and their surface-associated microbiome. In Bourgougnon, N. (Ed.) Advances in Botanical Research. Vol. 95. Seaweeds around the World: State of Art and Perspectives. Elsevier, Amsterdam, pp. 327–368. doi.org/10.1016/bs.abr.2019.11.009
  31. Manca, F., Benedetti-Cecchi, L., Bradshaw, C. J. A., et al. 2024. Projected loss of brown macroalgae and seagrasses with global environmental change. Nat. Commun. 15:5344. doi.org/10.1038/s41467-024-48273-6
  32. Menaa, F., Wijesinghe, P. A. U. I., Thiripuranathar, G., et al. 2020. Ecological and industrial implications of dynamic seaweed-associated microbiota interactions. Mar. Drugs 18:641. doi.org/10.3390/md18120641
  33. Milke, F., Wagner-Doebler, I., Wienhausen, G. & Simon, M. 2022. Selection, drift and community interactions shape microbial biogeographic patterns in the Pacific Ocean. ISME J. 16:2653–2665. doi.org/10.1038/s41396-022-01318-4
  34. Miller, R. J., Reed, D. C. & Brzezinski, M. A. 2011. Partitioning of primary production among giant kelp (Macrocystis pyrifera), understory macroalgae, and phytoplankton on a temperate reef. Limnol. Oceanogr. 56:119–132. doi.org/10.4319/lo.2011.56.1.0119
  35. Min, J. & Kim, K. Y. 2023. Diversity and assembly of planktonic protist communities in the Jeju Strait, Korea. Front. Mar. Sci. 10:1225640. doi.org/10.3389/fmars.2023.1225640
  36. Oksanen, J., Simpson, G. L., Blanchet, F. G., et al. 2025. vegan: Community Ecology Package. R package version 2.6-10. Available from: https://CRAN.R-project.org/package=vegan. Accessed Sep 20, 2024.
  37. Paine, E. R., Schmid, M., Boyd, P. W., Diaz-Pulido, G. & Hurd, C. L. 2021. Rate and fate of dissolved organic carbon release by seaweeds: a missing link in the coastal ocean carbon cycle. J. Phycol. 57:1375–1391. doi.org/10.1111/jpy.13198
  38. Paradis, E. & Schliep, K. 2019. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35:526–528. doi.org/10.1093/bioinformatics/bty633
  39. Pearman, W. S., Duffy, G. A., Liu, X. P., Gemmell, N. J., Morales, S. E. & Fraser, C. I. 2023. Macroalgal microbiome biogeography is shaped by environmental drivers rather than geographical distance. Ann. Bot. 133:169–182. doi.org/10.1093/aob/mcad151
  40. R Core Team. 2024. R: A Language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available from: https://www.R-project.org/. Accessed Sep 20, 2024.
  41. Ryznar, E. R., Fong, P. & Fong, C. R. 2021. When form does not predict function: empirical evidence violates functional form hypotheses for marine macroalgae. J. Ecol. 109:833–846. doi.org/10.1111/1365-2745.13509
  42. Saarinen, A., Salovius-Laurén, S. & Mattila, J. 2018. Epifaunal community composition in five macroalgal species: what are the consequences if some algal species are lost? Estuar. Coast. Shelf Sci. 207:402–413. doi.org/10.1016/j.ecss.2017.08.009
  43. Saha, M., Dittami, S. M., Chan, C. X., et al. 2024. Progress and future directions for seaweed holobiont research. New Phytol. 244:364–376. doi.org/10.1111/nph.20018
  44. Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. 2012. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9:671–675. doi.org/10.1038/nmeth.2089
  45. Smith, L. L., Grier, S. R. & Fong, P. 2025. Selecting functional traits that capture trade-offs for intertidal macroalgae provides a roadmap for future studies. J. Phycol. 61:792–804. doi.org/10.1111/jpy.70027
  46. Vass, M., Székely, A. J., Lindström, E. S. & Langenheder, S. 2020. Using null models to compare bacterial and microeukaryotic metacommunity assembly under shifting environmental conditions. Sci. Rep. 10:2455. doi.org/10.1038/s41598-020-59182-1
  47. Vranken, S., Robuchon, M., Dekeyzer, S., et al. 2023. Algae-Traits: a trait database for (European) seaweeds. Earth Syst. Sci. Data 15:2711–2754. doi.org/10.5194/essd-15-2711-2023
  48. Wahl, M. 2008. Ecological lever and interface ecology: epibiosis modulates the interactions between host and environment. Biofouling 24:427–438. doi.org/10.1080/08927010802339772
  49. Wahl, M., Goecke, F., Labes, A., Dobretsov, S. & Weinberger, F. 2012. The second skin: ecological role of epibiotic biofilms on marine organisms. Front. Microbiol. 3:292. doi.org/10.3389/fmicb.2012.00292
  50. Whitaker, D. & Christman, M. 2014. clustsig: Significant Cluster Analysis. R package version 1.1. Available from: https://github.com/cran/clustsig. Accessed Sep 20, 2024.
  51. Xie, X., He, Z., Hu, X., Wang, Q. & Yang, Y. 2023. The composition, function and assembly mechanism of epiphytic microbial communities on Gracilariopsis lemaneiformis. J. Exp. Mar. Biol. Ecol. 564:151909. doi.org/10.1016/j.jembe.2023.151909
  52. Zuccarello, G. C., Gachon, C. M. M., Badis, Y., Murúa, P., Garvetto, A. & Kim, G. H. 2024. Holocarpic oomycete parasites of red algae are not Olpidiopsis, but neither are they all Pontisma or Sirolpidium (Oomycota). Algae 39:43–50. doi.org/10.4490/algae.2024.39.3.8