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Animals, protists and bacteria share marine biogeographic patterns

Nature Ecology & Evolution volume 5, pages 738–746 (2021)Cite this article

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Abstract

Over millennia, ecological and evolutionary mechanisms have shaped macroecological patterns across the tree of life. Research describing these patterns at both regional and global scales has traditionally focused on the study of metazoan species. Consequently, there is a limited understanding of cross-phylum biogeographic structuring and an escalating need to understand the macroecology of both microscopic and macroscopic organisms. Here we used environmental DNA (eDNA) metabarcoding to explore the biodiversity of marine metazoans, protists and bacteria along an extensive and highly heterogeneous coastline. Our results showed remarkably consistent biogeographic structure across the kingdoms of life despite billions of years of evolution. Analyses investigating the drivers of these patterns for each taxonomic kingdom found that environmental conditions (such as temperature) and, to a lesser extent, anthropogenic stressors (such as fishing pressure and pollution) explained some of the observed variation. Additionally, metazoans displayed biogeographic patterns that suggested regional biotic homogenization. Against the backdrop of global pervasive anthropogenic environmental change, our work highlights the importance of considering multiple domains of life to understand the maintenance and drivers of biodiversity patterns across broad taxonomic, ecological and geographical scales.

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Fig. 1: Sampling sites, ASV taxonomic distribution and ASV richness.
Fig. 2: Patterns of β diversity.
Fig. 3: Plots showing distance between sites and community similarity measured using eDNA metabarcoding across South Africa.

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Data availability

The raw Illumina sequencing data are available from the European Nucleotide Archive under study accession number PRJEB38452; sample-specific accessions are provided in Supplementary Data 1. The associated metadata, R scripts and intermediate files are available at https://doi.org/10.5281/zenodo.4564075.

Code availability

All code used in the current study can be found at https://doi.org/10.5281/zenodo.4564075.

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Acknowledgements

L.E.H. acknowledges the assistance of M. Czachur and T. Grevesse during field surveys, S. von der Heyden for lab consumables and assistance with fieldwork logistics, and J. Hudson and I. Haigh for assistance with remote sensing data. L.E.H. acknowledges S. Parker-Nance and the Elwandle Node of the South African Environmental Observation Network for assistance and in-country logistics. We acknowledge all marina owners and operators for field site access. We acknowledge the Environmental Sequencing Facility at the National Oceanography Centre, Southampton, for advice and sequencing assistance. We thank the IRIDIS High Performance Computing Facility and associated support services at the University of Southampton. L.E.H. was supported by the Natural Environmental Research Council (grant no. NE/L002531/1). The UK Research and Innovation Newton Fund (grant no. ES/N013913/1) supported L.E.H.’s research stay in South Africa.

Author information

Authors and Affiliations

  1. School of Ocean and Earth Science, National Oceanography Centre Southampton, University of Southampton, Southampton, UK

    Luke E. Holman & Marc Rius

  2. School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia

    Mark de Bruyn

  3. Molecular Ecology and Fisheries Genetics Laboratory, School of Natural Sciences, Bangor University, Bangor, UK

    Mark de Bruyn, Simon Creer & Gary Carvalho

  4. Ocean Technology and Engineering Group, National Oceanography Centre Southampton, Southampton, UK

    Julie Robidart

  5. Centre for Ecological Genomics and Wildlife Conservation, Department of Zoology, University of Johannesburg, Johannesburg, South Africa

    Marc Rius

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Contributions

L.E.H. and M.R. designed the study. L.E.H. collected the samples, generated and analysed the data, prepared all figures and wrote the first draft of the paper. M.d.B., S.C., G.C., J.R. and M.R. supervised and advised the research. All authors substantially contributed to further manuscript drafts and provided final approval for publication.

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Correspondence to Luke E. Holman.

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The authors declare no competing interests.

Additional information

Peer review information Nature Ecology & Evolution thanks Simon Jarman, Ryan Kelly and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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

Extended data

Extended Data Fig. 1 Taxonomic identity of sequenced reads.

Bar charts indicating the proportion of reads assigned per phyla (metazoans/bacteria) or supergroup (protists) from environmental DNA metabarcoding of seawater collected from sites across South Africa. The three rows correspond with data from metazoans (top), protists (middle) and bacteria (bottom). Site name abbreviations as in Supplementary Table 9.

Extended Data Fig. 2 Beta diversity patterns of additional data subsets.

Observed patterns of β-diversity from environmental DNA metabarcoding of: a metazoans from the 18S dataset and b protists from the COI dataset; based on Jaccard dissimilarities between amplicon sequence variants along the coast of South Africa. The first column of plots shows non-metric multidimensional scaling (nMDS) ordinations. Coloured hulls show the spread of the data and lines indicate the spread around the centroid grouped by coast with the east, south and west coasts denoted by orange, green and blue respectively. Site name abbreviations as in Supplementary Table 9. Natural sites are denoted with triangles and artificial sites with filled circles. The second column of plots shows the same nMDS ordinations as the first column including the output of a generalised additive model with a 2D smoothed function for each of the significant environmental / impact variables overlaid; temperature – mean sea surface temperature (°C); impact – human marine impact score (unitless measurement, see details in main text) against the two nMDS axes. The Venn diagram charts indicate the percentage total of variance in community dissimilarity explained by each significant variable, derived using variance partitioning of a distance-based redundancy analysis.

Supplementary information

Supplementary Information

Supplementary Tables 1–9 and Notes 1–5.

Reporting Summary

Peer Review Information

Supplementary Data 1

Sample identifiers and raw sequence accession numbers.

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Holman, L.E., de Bruyn, M., Creer, S. et al. Animals, protists and bacteria share marine biogeographic patterns. Nat Ecol Evol 5, 738–746 (2021). https://doi.org/10.1038/s41559-021-01439-7

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