Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Contrasting processes drive ophiuroid phylodiversity across shallow and deep seafloors


Our knowledge of the distribution and evolution of deep-sea life is limited, impeding our ability to identify priority areas for conservation1. Here we analyse large integrated phylogenomic and distributional datasets of seafloor fauna from the sea surface to the abyss and from equator to pole of the Southern Hemisphere for an entire class of invertebrates (Ophiuroidea). We find that latitudinal diversity gradients are assembled through contrasting evolutionary processes for shallow (0–200 m) and deep (>200 m) seas. The shallow-water tropical–temperate realm broadly reflects a tropical diversification-driven process that shows exchange of lineages in both directions. Diversification rates are reversed for the realm that contains the deep sea and Antarctica; the diversification rates are highest at polar and lowest at tropical latitudes, and net exchange occurs from high to low latitudes. The tropical upper bathyal (200–700 m deep), with its rich ancient phylodiversity, is characterized by relatively low diversification and moderate immigration rates. Conversely, the young, specialized Antarctic fauna is inferred to be rebounding from regional extinctions that are associated with the rapid cooling of polar waters during the mid-Cenozoic era.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Get just this article for as long as you need it


Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Analyses of phylodiversity across the seafloor.
Fig. 2: Biomes possess divergent phylogenetic signatures.
Fig. 3: Distinct pathways of diversification and migration occur in shallow and deep seas.

Data availability

All data necessary to repeat the analyses described here have been made available through the Dryad digital data repository (


  1. Selig, E. R. et al. Global priorities for marine biodiversity conservation. PLoS ONE 9, e82898 (2014).

    Article  ADS  Google Scholar 

  2. Krug, A. Z., Jablonski, D., Valentine, J. W. & Roy, K. Generation of Earth’s first-order biodiversity pattern. Astrobiology 9, 113–124 (2009).

    Article  ADS  Google Scholar 

  3. Brown, J. H. Why are there so many species in the tropics? J. Biogeogr. 41, 8–22 (2014).

    Article  Google Scholar 

  4. Mannion, P. D., Upchurch, P., Benson, R. B. J. & Goswami, A. The latitudinal biodiversity gradient through deep time. Trends Ecol. Evol. 29, 42–50 (2014).

    Article  Google Scholar 

  5. Mittelbach, G. G. et al. Evolution and the latitudinal diversity gradient: speciation, extinction and biogeography. Ecol. Lett. 10, 315–331 (2007).

    Article  Google Scholar 

  6. Jablonski, D., Roy, K. & Valentine, J. W. Out of the tropics: evolutionary dynamics of the latitudinal diversity gradient. Science 314, 102–106 (2006).

    Article  ADS  CAS  Google Scholar 

  7. Rex, M. A. & Etter, R. J. Deep-Sea Biodiversity: Pattern and Scale (Harvard Univ. Press, Cambridge, 2010).

    Google Scholar 

  8. Woolley, S. N. C. et al. Deep-sea diversity patterns are shaped by energy availability. Nature 533, 393–396 (2016).

    Article  ADS  CAS  Google Scholar 

  9. O’Hara, T. D., Rowden, A. A. & Bax, N. J. A Southern Hemisphere bathyal fauna is distributed in latitudinal bands. Curr. Biol. 21, 226–230 (2011).

    Article  Google Scholar 

  10. O’Hara, T. D., Hugall, A. F., Thuy, B., Stöhr, S. & Martynov, A. V. Restructuring higher taxonomy using broad-scale phylogenomics: the living Ophiuroidea. Mol. Phylogenet. Evol. 107, 415–430 (2017).

    Article  Google Scholar 

  11. Rohling, E. J. The Oceans: A Deep History (Princeton Univ. Press, Princeton, 2017).

    Google Scholar 

  12. Bouchet, P., Lozouet, P. & Sysoev, A. An inordinate fondness for turrids. Deep Sea Res. Part II Top. Stud. Oceanogr. 56, 1724–1731 (2009).

    Article  ADS  Google Scholar 

  13. Macpherson, E. et al. Biogeography of the deep-sea galatheid squat lobsters of the Pacific Ocean. Deep Sea Res. Part I Oceanogr. Res. Pap. 57, 228–238 (2010).

    Article  ADS  Google Scholar 

  14. Cairns, S. Deep-water corals: an overview with special reference to diversity and distribution of deep-water scleractinian corals. Bull. Mar. Sci. 81, 311–322 (2007).

    Google Scholar 

  15. Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O. The global diversity of birds in space and time. Nature 491, 444–448 (2012).

    Article  ADS  CAS  Google Scholar 

  16. Bribiesca-Contreras, G., Verbruggen, H., Hugall, A. F. & O’Hara, T. D. The importance of offshore origination revealed through ophiuroid phylogenomics. Proc. R. Soc. B 284, 20170160 (2017).

    Article  Google Scholar 

  17. Leprieur, F. et al. Quantifying phylogenetic beta diversity: distinguishing between ‘true’ turnover of lineages and phylogenetic diversity gradients. PLoS ONE 7, e42760 (2012).

    Article  ADS  CAS  Google Scholar 

  18. Davis, M. P., Midford, P. E. & Maddison, W. P. Exploring power and parameter estimation of the BiSSE method for analyzing species diversification. BMC Evol. Biol. 13, 38 (2013).

    Article  Google Scholar 

  19. FitzJohn, R. G., Maddison, W. P. & Otto, S. P. Estimating trait-dependent speciation and extinction rates from incompletely resolved phylogenies. Syst. Biol. 58, 595–611 (2009).

    Article  Google Scholar 

  20. Rabosky, D. L. & Goldberg, E. E. Model inadequacy and mistaken inferences of trait-dependent speciation. Syst. Biol. 64, 340–355 (2015).

    Article  CAS  Google Scholar 

  21. Gillman, L. N. & Wright, S. D. Species richness and evolutionary speed: the influence of temperature, water and area. J. Biogeogr. 41, 39–51 (2014).

    Article  Google Scholar 

  22. Rohde, K. Latitudinal gradients in species diversity: the search for the primary cause. Oikos 65, 514–527 (1992).

    Article  Google Scholar 

  23. Rabosky, D. L. et al. An inverse latitudinal gradient in speciation rate for marine fishes. Nature 559, 392–395 (2018).

    Article  ADS  CAS  Google Scholar 

  24. Brown, A. & Thatje, S. Explaining bathymetric diversity patterns in marine benthic invertebrates and demersal fishes: physiological contributions to adaptation of life at depth. Biol. Rev. Camb. Phil. Soc. 89, 406–426 (2014).

    Article  Google Scholar 

  25. Thuy, B. et al. Ancient origin of the modern deep-sea fauna. PLoS ONE 7, e46913 (2012).

    Article  ADS  CAS  Google Scholar 

  26. O’Hara, T. D. in Australian Echinoderms: Biology, Ecology and Evolution (eds Byrne, M. & O’Hara, T. D.) 137–153 (CSIRO Publishing and Australian Biological Resources Study, Melbourne and Canberra, 2017).

  27. Spano, C. A., Hernández, C. E. & Rivadeneira, M. M. Evolutionary dispersal drives the latitudinal diversity gradient of stony corals. Ecography 39, 836–843 (2016).

    Article  Google Scholar 

  28. Crame, J. A. Key stages in the evolution of the Antarctic marine fauna. J. Biogeogr. 45, 986–994 (2018).

    Article  Google Scholar 

  29. Brey, T. et al. Do Antarctic benthic invertebrates show an extended level of eurybathy? Antarct. Sci. 8, 3–6 (1996).

    Article  ADS  Google Scholar 

  30. Clarke, A. & Crame, J. A. Evolutionary dynamics at high latitudes: speciation and extinction in polar marine faunas. Phil. Trans. R. Soc. B 365, 3655–3666 (2010).

    Article  Google Scholar 

  31. Stöhr, S., O’Hara, T. D. & Thuy, B. Global diversity of brittle stars (Echinodermata: Ophiuroidea). PLoS ONE 7, e31940 (2012).

    Article  ADS  Google Scholar 

  32. Hugall, A. F., O’Hara, T. D., Hunjan, S., Nilsen, R. & Moussalli, A. An exon-capture system for the entire class Ophiuroidea. Mol. Biol. Evol. 33, 281–294 (2016).

    Article  CAS  Google Scholar 

  33. Stamatakis, A. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics 22, 2688–2690 (2006).

    Article  CAS  Google Scholar 

  34. Sanderson, M. J. R8s: inferring absolute rates of molecular evolution and divergence times in the absence of a molecular clock. Bioinformatics 19, 301–302 (2003).

    Article  CAS  Google Scholar 

  35. Drummond, A. J. & Rambaut, A. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol. Biol. 7, 214 (2007).

    Article  Google Scholar 

  36. O’Hara, T. D., Hugall, A. F., Thuy, B. & Moussalli, A. Phylogenomic resolution of the class Ophiuroidea unlocks a global microfossil record. Curr. Biol. 24, 1874–1879 (2014).

    Article  Google Scholar 

  37. Tomczak, M. & Godfrey, J. S. Regional Oceanography: An Introduction 2nd edn (Daya Publishing House, Delhi, 2003).

  38. Faith, D. P. Conservation evaluation and phylogenetic diversity. Biol. Conserv. 61, 1–10 (1992).

    Article  Google Scholar 

  39. Davies, R. G. et al. Environmental predictors of global parrot (Aves: Psittaciformes) species richness and phylogenetic diversity. Glob. Ecol. Biogeogr. 16, 220–233 (2007).

    Article  Google Scholar 

  40. Webb, C. O., Ackerly, D. D., McPeek, M. A. & Donoghue, M. J. Phylogenies and community ecology. Annu. Rev. Ecol. Syst. 33, 475–505 (2002).

    Article  Google Scholar 

  41. Clarke, K. R. & Warwick, R. M. A taxonomic distinctness index and its statistical properties. J. Appl. Ecol. 35, 523–531 (1998).

    Article  Google Scholar 

  42. Tucker, C. M. et al. A guide to phylogenetic metrics for conservation, community ecology and macroecology. Biol. Rev. Camb. Phil. Soc. 92, 698–715 (2017).

    Article  Google Scholar 

  43. Vane-Wright, R. I., Humphries, C. J. & Williams, P. H. What to protect? Systematics and the agony of choice. Biol. Conserv. 55, 235–254 (1991).

    Article  Google Scholar 

  44. Jetz, W. et al. Global distribution and conservation of evolutionary distinctness in birds. Curr. Biol. 24, 919–930 (2014).

    Article  CAS  Google Scholar 

  45. Miglietta, M. P., Faucci, A. & Santini, F. Speciation in the sea: overview of the symposium and discussion of future directions. Integr. Comp. Biol. 51, 449–455 (2011).

    Article  Google Scholar 

  46. Isaac, N. J. B., Turvey, S. T., Collen, B., Waterman, C. & Baillie, J. E. M. Mammals on the EDGE: conservation priorities based on threat and phylogeny. PLoS ONE 2, e296 (2007).

    Article  ADS  Google Scholar 

  47. Rabosky, D. L. & Goldberg, E. E. FiSSE: a simple nonparametric test for the effects of a binary character on lineage diversification rates. Evolution 71, 1432–1442 (2017).

    Article  Google Scholar 

  48. Graham, C. H. & Fine, P. V. A. Phylogenetic beta diversity: linking ecological and evolutionary processes across space in time. Ecol. Lett. 11, 1265–1277 (2008).

    Article  Google Scholar 

  49. Baselga, A. Partitioning the turnover and nestedness components of beta diversity. Glob. Ecol. Biogeogr. 19, 134–143 (2010).

    Article  Google Scholar 

  50. Oksanen, J. et al. vegan: community ecology package. R package version 2.3-5 (2016).

  51. Maechler, M., Rousseeuw, P., Struyf, A., Hubert, M. & Hornik, K. cluster: cluster analysis basics and extensions. R package version 2.0.6 (2017).

  52. FitzJohn, R. G. Diversitree: comparative phylogenetic analyses of diversification in R. Methods Ecol. Evol. 3, 1084–1092 (2012).

    Article  Google Scholar 

  53. Paradis, E., Claude, J. & Strimmer, K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20, (2004).

  54. Revell, L. J. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3, 217–223 (2012).

    Article  Google Scholar 

  55. Beaulieu, J. M., O’Meara, B. C. & Donoghue, M. J. Identifying hidden rate changes in the evolution of a binary morphological character: the evolution of plant habit in campanulid angiosperms. Syst. Biol. 62, 725–737 (2013).

    Article  Google Scholar 

  56. Goldberg, E. E., Lancaster, L. T. & Ree, R. H. Phylogenetic inference of reciprocal effects between geographic range evolution and diversification. Syst. Biol. 60, 451–465 (2011).

    Article  Google Scholar 

  57. Harmon, L. J., Weir, J. T., Brock, C. D., Glor, R. E. & Challenger, W. GEIGER: investigating evolutionary radiations. Bioinformatics 24, 129–131 (2008).

    Article  CAS  Google Scholar 

  58. Siqueira, A. C., Oliveira-Santos, L. G. R., Cowman, P. F. & Floeter, S. R. Evolutionary processes underlying latitudinal differences in reef fish biodiversity. Glob. Ecol. Biogeogr. 25, 1466–1476 (2016).

    Article  Google Scholar 

  59. Beaulieu, J. M. & O’Meara, B. C. Detecting hidden diversification shifts in models of trait dependent speciation and extinction. Syst. Biol. 65, 583–601 (2016).

    Article  Google Scholar 

  60. Rabosky, D. L. Automatic detection of key innovations, rate shifts, and diversity-dependence on phylogenetic trees. PLoS ONE 9, e89543 (2014).

    Article  ADS  Google Scholar 

  61. Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S 4th edn (Springer, New York, 2002).

  62. Amante, C. & Eakins, B. W. ETOPO1 1 Arc-Minute Global Relief Model: Procedures, Data Sources and Analysis. Technical Memorandum NESDIS NGDC-24 (National Geophysical Data Center, NOAA, 2009).

  63. Chaudhary, C., Saeedi, H. & Costello, M. J. Bimodality of latitudinal gradients in marine species richness. Trends Ecol. Evol. 31, 670–676 (2016).

    Article  Google Scholar 

Download references


T.D.O., A.F.H. and N.J.B. were supported by the Marine Biodiversity Hub, funded through the National Environmental Science Program (NESP) and administered through the Australian Government’s Department of the Environment and Energy. S.N.C.W. was supported by the Global Ocean Biodiversity Initiative funded by the International Climate Initiative (IKI). CSIRO Marine National Facility provided sea time and personnel on the RV Investigator for the ‘Sampling the abyss’ voyage IN2017_V03. Museums Victoria and Muséum National d’Histoire Naturelle, Paris provided the majority of tissue samples. K. Naughton extracted the DNA; library preparation, target capture and sequencing was done through the Georgia Genomics Facility and Arbor Biosciences.

Reviewer information

Nature thanks D. Allen, F. L. Condamine, P. Snelgrove and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Authors and Affiliations



T.D.O. and A.F.H. designed the research and assembled the data. T.D.O., A.F.H. and S.N.C.W. performed the phylodiversity analyses and T.D.O., A.F.H. and G.B.-C. performed the macro-evolutionary analyses. All authors contributed to interpretation and discussion of results. T.D.O., A.F.H. and N.J.B. drafted the paper with substantial input from all authors.

Corresponding author

Correspondence to Timothy D. O’Hara.

Ethics declarations

Competing interests

The authors declare no competing interests.

Extended data figures and tables

Extended Data Fig. 1 Maps and plots of collection and sequencing effort.

a, Map of sample sites across the study area, with land masses defined using the ETOPO1 dataset62. The study area, a trapezoid shape on this geographical projection, contains equal area polygons per latitude spaced either side of 150° E. Red dots indicate shallow sites (0–200 m), green dots indicate samples obtained from the upper to mid-bathyal (200–2,000 m) and blue dots indicate samples from the lower bathyal and abyss (>2,000 m); many sites overlap. Sampling over our study area is concentrated around continental margins with few expeditions to the abyssal plain or mid-ocean ridges. b, Collection effort (for example, the numbers of trawls, dredges or submersible collections) over our study area is, as expected, highest in shallow water (0–100 m) followed by cells at upper to mid-bathyal depths. Variation in collection effort does not explain the latitudinal and bathymetric gradients in species richness for this data8. Although collection effort is much lower at lower bathyal and abyssal depths (2,000–4,000 m), this is offset by a general increase in the size of observed species ranges with depth. Many abyssal ophiuroids are widespread across temperate and tropical latitudes. c, The percentage of species with DNA data is high (>70%) over the entire study area, except below 2,000 m across tropical latitudes (mean, 52%; minimum, 41%). However, these depths are relatively species-poor and sequencing effort across the entire tropical deep-sea biome (as defined in Fig. 1g) exceeds 70%.

Extended Data Fig. 2 Latitudinal and bathymetric gradients for species richness, family richness and phylogenetic diversity.

af, Latitudinal (a, c, e) and bathymetric (b, d, f) gradients are shown for species richness (a, b), family richness (c, d) and phylogenetic diversity (e, f). Diversity peaks between 13 and 23° S and at a depth of between 200 and 700 m, declining in polar regions and abyss. A sub-equatorial peak of richness for shallow marine fauna has been observed for many marine datasets63. Across all latitudes, the bathymetric peak is in the upper to mid-bathyal, a pattern also recorded for numerous other eurybathyal invertebrates12,13,14. Our temperate mid-bathyal (1,000 m) latitudinal peak is compatible with northern Atlantic Ocean studies7. A, end of the Australian continental shelf; N, end of the New Zealand continental shelf; P, temperate–polar transition (south of Macquarie Island); T, tropical–temperate transition.

Extended Data Fig. 3 Additional latitudinal and bathymetric plots of diversity indices.

a, High levels of family-level richness extend into temperate regions and mid-bathyal depths. b, Phylogenetic radiations are concentrated in upper tropical habitats and Antarctica. c, The pattern of normalized mean phylogenetic pairwise distance between cells is similar to relative phylogenetic diversity (Fig. 1c). d, The frequency that observed phylogenetic diversity exceeded null models (in which randomized species are present in each cell while retaining cell species richness). e, f, Simpson’s phylogenetic beta diversity (Fig. 1f) factored into latitudinal (e) and bathymetric (f) components.

Extended Data Fig. 4 MuSSE randomization trials.

ac, Comparison of speciation (a), extinction (b) and transition (c) rates generated from our MuSSE Bayesian MCMC analysis (n = 10,000) compared to maximum likelihood analyses that resampled (n = 400) states (biomes) within species with multi-biome distributions. Box plots show the median, upper and lower quartile (boxes), and minimum and maximum (whiskers) rate values. The resampling results (blue) are broadly similar to the original MCMC run (green), indicating that biome misclassification did not significantly affect the results. One exception is the temperate shallow (TempS) to tropical shallow (TropS) transition rates, which were significantly different for resampling owing to the occurrence of subtropical species across the transition zone.

Extended Data Fig. 5 Phylodiversity and rate plots of ophiuroid subclades.

ac, The three major clades of extant Ophiuroidea10,36 contribute differently to overall patterns of phylogenetic diversity across our five biomes (Fig. 2). a, Clade A is rich in deep-sea and Antarctic species, although individual families have divergent distributions. The Antarctic is dominated by the Ophiopyrgidae whereas the Ophiomusaidae, Ophiosphalmidae, Astrophytidae and Euryalidae are largely absent from this region. Clade A has low species richness in the two shallow-water biomes. b, Clade B is rich in the tropical shallow, tropical deep-sea and temperate deep-sea biomes. It consists of one suborder (Ophiodermatina) that is heavily represented in tropical shallow-water biome and another (Ophiacanthina) that is largely present in deep-sea habitats, particularly on hard substrata such as seamounts. c, Clade C on the other hand is rich in tropical and temperate shallow-water biomes, including the families Ophiolepididae, Ophionereididae, Amphiuridae and Ophiotrichidae, and has relatively few lineages in the deep sea or Antarctica. d, Antarctic biome diversification rates are increased compared to other biomes. e, f, However, this is not an artefact of lowered molecular substitution rates or dominance by the family Ophiopyrgidae, as demonstrated by histograms of DR statistic rates (e) and PLRS estimated tip substitution rates (f), averaged by species per family per biome. Families per biomes with fewer than three species were omitted; Ophiopyrgidae are highlighted by stripes. Antarctic species in multiple families do not have relatively low molecular rates. Using the root-to-tip path length of the RAxML tree instead of substitution rate essentially gives the same result. Even within the Ophiopyrgidae, diversification rates for Antarctic species are much higher than for non-Antarctic species.

Extended Data Fig. 6 Environmental patterns.

ad, Mean annual environmental data for each latitudinal (1.0°) and bathymetric (100 m) cell across our study area for comparison with phylodiversity analyses. A lens of relatively hot (a) salty (b) water occurs at shallow depths across tropical and temperate latitudes (0–40° S). Antarctic intermediate water sinks at sub-Antarctic latitudes and flows north to subtropical latitudes (20° S) at mid-bathyal depths (around 1,000 m). c, Deoxygenated ‘deep’ water flows southwards from the northern hemisphere at lower bathyal depths, shoaling off the Antarctic continent. Cold, dense, oxygen-rich ‘bottom’ water sinks near Antarctica, flowing northwards at abyssal depths. d, Yearly net primary production peaks at temperate latitudes over the study area, driving elevated carbon flux to the seafloor; Antarctic production is highly seasonal. e, Area of depth strata per degree of latitude across the study region, calculated by counting the number of cells of each category for each degree of latitude in the ETOPO162 raster GIS layer (0.01° resolution) and adjusting for the reducing circumference of the Earth with increased latitude. There is limited terrestrial, sublittoral and upper bathyal habitat in the Southern Ocean between the Australian/New Zealand continental masses and Antarctica.

Extended Data Fig. 7 Beta diversity and phylogenetic beta diversity.

Ordinations (nMDS), cluster dendrograms (UPGMA) and latitudinal and bathymetric representations of (phylogenetic) beta diversity clusters for each 1.0° latitude × 100 m depth cell across our study region. ac, Simpson’s phylogenetic beta diversity (pβSim) (a), Sorensen’s phylogenetic beta diversity (pβSor) (b) and Simpson’s beta diversity of the presence–absence of species (βSim) (c). Nine clusters (vertical red lines) are coloured to highlight coherent patterns across latitude and depth. The three methods showed broad similarities in grouping the fauna into tropical, temperate and polar regions and sublittoral, upper bathyal and lower bathyal–abyssal depth strata, although the cluster hierarchy can differ. The pβSim and βSim plots emphasized the strong compositional turnover between 100 and 300 m at tropical and temperate latitudes (Fig. 1f and Extended Data Fig. 3e). pβSor—which emphasizes species richness gradients in addition to compositional turnover—clustered upper to mid-bathyal cells (200–2,000 m) separately from those in the lower bathyal and abyss (>2,000 m), reflecting a zone of higher species richness and relative phylogenetic diversity (Fig. 1). The pβSim and βSim analyses also identified a small shallow-water subtropical cluster that reflects the heightened latitudinal turnover between 30 and 40° S9. The pβSor analysis separated two species-poor Antarctic deep-sea regions. The extent of the temperate sublittoral zone varied among analyses, possibly owing to it being a small zone of admixture and turnover. The number of clusters was reduced to five (Fig. 1g) for the MuSSE analyses (see Methods for rationale).

Extended Data Table 1 Biome parameter estimates
Extended Data Table 2 One-sided significance tests of the hypotheses

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

O’Hara, T.D., Hugall, A.F., Woolley, S.N.C. et al. Contrasting processes drive ophiuroid phylodiversity across shallow and deep seafloors. Nature 565, 636–639 (2019).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing