Reconstructing the reproductive mode of an Ediacaran macro-organism

Journal name:
Nature
Volume:
524,
Pages:
343–346
Date published:
DOI:
doi:10.1038/nature14646
Received
Accepted
Published online

Enigmatic macrofossils of late Ediacaran age (580–541 million years ago) provide the oldest known record of diverse complex organisms on Earth, lying between the microbially dominated ecosystems of the Proterozoic and the Cambrian emergence of the modern biosphere1. Among the oldest and most enigmatic of these macrofossils are the Rangeomorpha, a group characterized by modular, self-similar branching and a sessile benthic habit2, 3, 4. Localized occurrences of large in situ fossilized rangeomorph populations allow fundamental aspects of their biology to be resolved using spatial point process techniques5. Here we use such techniques to identify recurrent clustering patterns in the rangeomorph Fractofusus, revealing a complex life history of multigenerational, stolon-like asexual reproduction, interspersed with dispersal by waterborne propagules. Ecologically, such a habit would have allowed both for the rapid colonization of a localized area and for transport to new, previously uncolonized areas. The capacity of Fractofusus to derive adult morphology by two distinct reproductive modes documents the sophistication of its underlying developmental biology.

At a glance

Figures

  1. Fractofusus specimens from Newfoundland, Canada.
    Figure 1: Fractofusus specimens from Newfoundland, Canada.

    a, F. andersoni specimen from the H14 surface. b, F. misrai from the ‘E’ surface, showing a large size-class partial specimen (~20 cm, above) alongside a small size-class specimen (3.5 cm in length, below). Scale bars, 1 cm. Photographs are non-retrodeformed.

  2. PCF for mapped taxa.
    Figure 2: PCF for mapped taxa.

    For all plots the x axis is the inter-point distance between organisms in metres. On the y axis, PCF = 1 indicates CSR, <1 indicates segregation and >1 indicates aggregation. a, PCF for Fractofusus on the ‘D’ surface (1,040 specimens), ‘E’ surface (1,141 specimens) and H14 surface (1,214 specimens). Grey shaded area depicts the bounds of 99 Monte Carlo simulations of CSR. Since the PCF curves are not completely within these areas, the CSR hypothesis is rejected and one can assume that the Fractofusus distributions on all three surfaces form cluster patterns (pDd < 0.01, pEd < 0.01, pH14d < 0.01). b, PCF for non-CSR ‘E’ surface taxa (charniid 76 specimens, Charniodiscus 326 specimens, Primocandelabrum 311 specimens and Thectardis 39 specimens). Grey shaded area depicts 99 Monte Carlo simulations of the best-fit H14 surface model of double Thomas cluster process. Note how the ‘E’ surface Fractofusus PCF follows the H14 surface PCF very closely, and can be modelled by the same process (pd = 0.51). Other ‘E’ surface taxa have markedly different PCF to the Fractofusus PCF. c, PCF for the three size-classes of Fractofusus on H14 surface. Grey shaded area depicts the 99 Monte Carlo simulations of CSR. The large size-class (350 specimens) exhibits CSR (pd = 0.30); the intermediate size-class (310 specimens) shows aggregation <0.10 m (single Thomas cluster model, pd = 0.51). The small size-class (554 specimens) shows a large aggregation <0.08 m and a lesser aggregation between 0.08 m and 0.20 m (double Thomas cluster model, pd = 0.72).

  3. Isotropy plots from the H14 surface for each size-class of Fractofusus, providing a visualization of specimen positions relative to one another.
    Figure 3: Isotropy plots from the H14 surface for each size-class of Fractofusus, providing a visualization of specimen positions relative to one another.

    The vertical axis on each part depicts the colour map of specimens per square metre normalized to account for different densities between size-classes. A peak (>1) is shown in green or yellow and depicts aggregation, while a dip (<1) is shown in blue and depicts segregation. If there are no directional effects then the colour map in every direction from the centre point should be similar. a, The large size-class shows strong anisotropy, with aggregation of up to four normalized specimens per square metre. b, c, In contrast the medium (b) and small (c) size-classes show isotropy, namely a relative evenness of aggregations with a maximum density variation up to 0.5 normalized specimens per square metre.

  4. Schematic diagram showing simplified Fractofusus spatial arrangements.
    Figure 4: Schematic diagram showing simplified Fractofusus spatial arrangements.

    The actual number of clusters, and clusters within those clusters, is higher than shown (23 clusters each containing 12 clusters of 3 specimens on the H14 surface), making their direct visual detection challenging. No overlapping specimens are shown because, while the best-fit models allow for overlaps, the observed PCF between the small size-class (Extended Data Fig. 4c, d) and the large size-class (Fig. 2b) shows a small segregation (<3 cm) away from the model behaviour, and a similar, non-significant segregation for the large size-class.

  5. Map and simplified stratigraphic column showing the position of studied bedding planes with bedding plane maps of Fractofusus.
    Extended Data Fig. 1: Map and simplified stratigraphic column showing the position of studied bedding planes with bedding plane maps of Fractofusus.

    a, Newfoundland, eastern Canada. Dashed area indicates region of interest in b. b, The Avalon and Bonavista Peninsulas, eastern Newfoundland. Locations of the bedding planes are indicated. c, Stratigraphic column (not to scale) compiled of information from the Avalon and Bonavista Peninsulas; lithological units in each region are treated as correlative in this study, but work is continuing to determine the validity of this assumption. The ‘E’ surface at Mistaken Point has been dated to 565 ± 3 Ma (ref. 12). There are currently no available radiometric dates from the Bonavista Peninsula. df, Maps of Fractofusus positions on the ‘D’ surface (d), the ‘E’ surface (e) and the H14 surface (f). In e the largest specimens are in light blue, medium specimens in mid-blue and smallest specimens in dark blue.

  6. Retrodeformation calculations on the Mistaken Point surfaces.
    Extended Data Fig. 2: Retrodeformation calculations on the Mistaken Point surfaces.

    a, b, Plots of the lengths versus widths of discs from the ‘D’ surface, Mistaken Point (a), and the ‘E’ surface, Mistaken Point (b). The gradient of the line defines the retrodeformation factor, which for the ‘D’ surface is 1.35 ± 0.11 (R2 = 0.92) and for the ‘E’ surface is 1.71 ± 0.08 (R2 = 0.75). c, Fractofusus PCF on the ‘E’ surface with (solid line) and without (dashed line) retrodeformation. The grey shaded area depicts the boundary of 99 Monte Carlo simulations for the model which provided the best-fit model to the retrodeformed data, which has a good fit on the non-retrodeformed data (pd = 0.60).

  7. Size distribution analysis of Fractofusus for the H14 surface.
    Extended Data Fig. 3: Size distribution analysis of Fractofusus for the H14 surface.

    a, Size–frequency distributions for Fractofusus, (n = 1,214); b, the results of the Bayesian information criterion52, 53 (univariate data). Squares and triangles correspond to models assuming equal and unequal variance, respectively. High values of the Bayesian information criterion correspond to a good model fit, so the best-fit model is a three-component equal variance model using log-normalized length data. ce, Rose diagrams plotting the directional orientation of the different size-classes of Fractofusus on the H14 surface showing large size-class (<11.0 cm, n = 350) (c), intermediate size-class (5.5–11.0 cm, n = 310) (d) and small size-class (<5.5 cm, n = 554) (e). The angles of the Fractofusus central axis are relative to north (0°). There is no strong orientation preference for any of the size-classes.

  8. Distance measures for the size data from H14 surface.
    Extended Data Fig. 4: Distance measures for the size data from H14 surface.

    For all plots, the x axis is the inter-point distance between organisms (in metres). a, Mark correlation function5, where 1 corresponds to a lack of correlation of size, such that Fractofusus size is independent and identically distributed. A value of <1 corresponds to a positive dependency (in contrast to PCF) and >1 corresponds to a negative dependency. Small Fractofusus on the H14 surface (<0.3 cm) are more likely to be found near each other than expected by random. b, The ‘E’ surface PCF (solid line) showing the model that fits the data best, a double Thomas cluster model (dotted line, pd = 0.56), and the simulation envelope for 99 Monte Carlo simulations (grey shaded area). c, d, PCF for the best-fit models for the bivariate size-classes of Fractofusus on the H14 surface showing LCMs for small with medium size-classes (pd = 0.74) (c) and LCMs for medium with large size-classes (pd = 0.66) (d). e, The PCF of the largest size-class of H14 (solid line), showing the CSR Monte Carlo simulation envelope in grey, with the ‘D’ surface PCF (dotted line, pd = 0.56). f, Nearest neighbour distances (solid line, pd = 0.01) with CSR Monte Carlo simulation envelope in grey.

  9. Artistic reconstruction of Fractofusus on the H14 surface, Bonavista Peninsula.
    Extended Data Fig. 5: Artistic reconstruction of Fractofusus on the H14 surface, Bonavista Peninsula.

    The bottom right features a large Fractofusus around which there are five to eight medium specimens clustered. Each of the medium specimens also has small specimens clustered around them. The small specimens therefore form an independent double cluster pattern, namely clusters of clusters. Artwork by C.G.K.

Tables

  1. Best-fit univariate cluster models
    Extended Data Table 1: Best-fit univariate cluster models
  2. Best-fit univariate double cluster models
    Extended Data Table 2: Best-fit univariate double cluster models
  3. Best-fit double Thomas cluster models fitted onto other taxa
    Extended Data Table 3: Best-fit double Thomas cluster models fitted onto other taxa
  4. Best-fit univariate cluster models on heterogeneous backgrounds for /`E/' surface taxa
    Extended Data Table 4: Best-fit univariate cluster models on heterogeneous backgrounds for ‘E’ surface taxa
  5. Models for bivariate analysis between different size-classes of Fractofusus on the H14 surface
    Extended Data Table 5: Models for bivariate analysis between different size-classes of Fractofusus on the H14 surface

References

  1. Liu, A. G, Kenchington C. G. & Mitchell, E. G. Remarkable insights into the paleoecology of the Avalonian Ediacaran biota. Gondwana Res. 27, 13551380 (2015)
  2. Gehling, J. G. & Narbonne, G. M. Spindle-shaped Ediacara fossils from the Mistaken Point assemblage, Avalon Zone, Newfoundland. Can. J. Earth Sci. 44, 367387 (2007)
  3. Narbonne, G. M. Modular construction of early Ediacaran complex life forms. Science 305, 11411144 (2004)
  4. Hoyal Cuthill, J. F. & Conway Morris, S. Fractal branching organizations of Ediacaran rangeomorph fronds reveal a lost Proterozoic body plan. Proc. Natl Acad. Sci. USA 111, 1312213126 (2014)
  5. Illian, J., Penttinen, A., Stoyan, H. & Stoyan, D. Statistical Analysis and Modelling of Spatial Point Patterns Vol. 70 (John Wiley, 2008)
  6. Wood, D. A., Dalrymple, R. W., Narbonne, G. M., Gehling, J. G. & Clapham, M. E. Paleoenvironmental analysis of the late Neoproterozoic Mistaken Point and Trepassey formations, southeastern Newfoundland. Can. J. Earth Sci. 40, 13751391 (2003)
  7. Darroch, S. A. F., Laflamme, M. & Clapham, M. E. Population structure of the oldest known macroscopic communities from Mistaken Point, Newfoundland. Paleobiology 39, 591608 (2013)
  8. Wiegand, T., Gunatilleke, S., Gunatilleke, N. & Okuda, T. Analyzing the spatial structure of a Sri Lankan tree species with multiple scales of clustering. Ecology 88, 30883102 (2007)
  9. Landing, E., Narbonne, G. M., Myrow, P., eds. Trace fossils, small shelly fossils and the Precambrian–Cambrian boundary. Bull. NY State Mus. 463, 181 (1988)
  10. Clapham, M. E., Narbonne, G. M. & Gehling, J. G. Paleoecology of the oldest known animal communities: Ediacaran assemblages at Mistaken Point, Newfoundland. Paleobiology 29, 527544 (2003)
  11. Hofmann, H. J., O’Brien, S. J. & King, A. F. Ediacaran biota on Bonavista Peninsula, Newfoundland. Can. J. Paleontol. 82, 136 (2008)
  12. Benus, A. P. Sedimentological context of a deep-water Ediacaran fauna (Mistaken Point Formation, Avalon zone, eastern Newfoundland). Bull. NY State Mus. 463, 89 (1988)
  13. Narbonne, G. M., Laflamme, M., Trusler, P. W., Dalrymple, R. W. & Greentree, C. Deep-water Ediacaran fossils from northwestern Canada: Taphonomy, ecology, and evolution. J. Paleontol. 88, 207223 (2014)
  14. Brasier, M. D., Antcliffe, J. B. & Liu, A. G. The architecture of Ediacaran fronds. Palaeontology 55, 11051124 (2012)
  15. Diggle, P. Statistical Analysis of Spatial Point Patterns 2nd edn (Arnold, 2003)
  16. Baddeley, A. & Turner, R. Practical maximum pseudolikelihood for spatial point patterns. Aust. NZ J. Stat. 42, 283322 (2000)
  17. Chiu, S. N., Stoyan, D., Kendall, W. S. & Mecke, J. Stochastic Geometry and its Applications 3rd edn (John Wiley, 2013)
  18. Lin, Y., Chang, L., Yang, K., Wang, H. & Sun, I. Point patterns of tree distribution determined by habitat heterogeneity and dispersal limitation. Oecologia 165, 175184 (2011)
  19. Droser, M. L. & Gehling, J. G. Synchronous aggregate growth in an abundant new Ediacaran tubular organism. Science 319, 16601662 (2008)
  20. Gaylord, B., Reed, D. C., Raimondi, P. T. & Washburn, L. Macroalgal spore dispersal in coastal environments: mechanistic insights revealed by theory and experiment. Ecol. Monogr. 76, 481502 (2006)
  21. Shanks, A. L. Pelagic larval duration and dispersal distance revisited. Biol. Bull. 216, 373385 (2009)
  22. Gaylord, B., Reed, D., Raimondi, P., Washburn, L. & McLean, S. A physically based model of macroalgal spore dispersal in the wave and current-dominated nearshore. Ecology 83, 12391251 (2002)
  23. Araki, K., Shimatani, K. & Ohara, M. Dynamics of distribution and performance of ramets constructing genets: a demographic–genetic study in a clonal plant, Convallaria keiskei. Ann. Bot. (Lond.) 104, 7179 (2009)
  24. Narbonne, G. M. & Gehling, J. G. Life after snowball: the oldest complex Ediacaran fossils. Geology 31, 2730 (2003)
  25. Peterson, K. J., Waggoner, B. & Hagadorn, J. W. A fungal analog for Newfoundland Ediacaran fossils? Integr. Comp. Biol. 43, 127136 (2003)
  26. Fedonkin, M. A. in Vendskaya Sistema 1, istoriko-geologicheskoe i paleontologicheskoe obosnovanie paleontologiya Vol. 1 (eds Sokolov, B. S. & Ivanovskiy, A. B.) 70106 (Nauka, 1985)
  27. Penny, A. M. et al. Ediacaran metazoan reefs from the Nama Group, Namibia. Science 344, 15041506 (2014)
  28. Yuan, X. et al. The Lantian biota: a new window onto the origin and early evolution of multicellular organisms. Chin. Sci. Bull. 58, 701707 (2013)
  29. Hua, H., Chen, Z., Yuan, X., Zhang, L. & Xiao, S. Skeletogenesis and asexual reproduction in the earliest biomineralizing animal Cloudina. Geology 33, 277280 (2005)
  30. Chen, L., Xiao, S., Pang, K., Zhou, C. & Yuan, X. Cell differentiation and germ–soma separation in Ediacaran animal embryo-like fossils. Nature 516, 238241 (2014)
  31. Clapham, M. E. in Quantifying the Evolution of Early Life (eds Laflamme, M., Schiffbauer, J. D. & Dornbos, S. Q.) 321 (Springer, 2011)
  32. Shen, B., Dong, L., Xiao, S. & Kowalewski, M. The Avalon explosion: evolution of Ediacara morphospace. Science 319, 8184 (2008)
  33. Liu, A. G., McIlroy, D., Antcliffe, J. B. & Brasier, M. D. Effaced preservation in the Ediacara biota and its implications for the early macrofossil record. Palaeontology 54, 607630 (2011)
  34. Narbonne, G. M., Laflamme, M., Greentree, C. & Trusler, P. Reconstructing a lost world: Ediacaran rangeomorphs from Spaniard’s Bay, Newfoundland. J. Paleontol. 83, 503523 (2009)
  35. Brasier, M. D. & Antcliffe, J. B. Evolutionary relationships within the Avalonian Ediacara biota: new insights from laser analysis. J. Geol. Soc. Lond. 166, 363384 (2009)
  36. R Core Team. R: a language and environment for statistical computing (R Foundation for Statistical Computing, 2013)
  37. Baddeley, A. & Turner, R. Spatstat: an R package for analyzing spatial point patterns. J. Stat. Softw. 12, 142 (2005)
  38. Berman, M. Testing for spatial association between a point process and another stochastic process. Appl. Stat. 35, 5462 (1986)
  39. Baddeley, A., Rubak, E. & Møller, J. Score, pseudo-score and residual diagnostics for spatial point process models. Stat. Sci. 26, 613646 (2011)
  40. Wiegand, T. & Moloney, K. Rings, circles, and null-models for point pattern analysis in ecology. Oikos 104, 209229 (2004)
  41. Wiegand, T., Kissling, W., Cipriotti, P. & Aguiar, M. Extending point pattern analysis for objects of finite size and irregular shape. J. Ecol. 94, 825837 (2006)
  42. Wiegand, T., Moloney, K., Naves, J. & Knauer, F. Finding the missing link between landscape structure and population dynamics: a spatially explicit perspective. Am. Nat. 154, 605627 (1999)
  43. Loosmore, N. B. & Ford, E. D. Statistical inference using the G or K point pattern spatial statistics. Ecology 87, 19251931 (2006)
  44. Wiegand, T. & Moloney, K. A. Handbook of Spatial Point-Pattern Analysis in Ecology (CRC, 2013)
  45. Levin, S. A. in Ecological Time Series Vol. 2 (eds Powell, T. M. & Steele, J. H.) 277326 (Springer, 1995)
  46. McIntire, E. J. & Fajardo, A. Beyond description: the active and effective way to infer processes from spatial patterns. Ecology 90, 4656 (2009)
  47. Fragoso, J. M., Silvius, K. M. & Correa, J. A. Long-distance seed dispersal by tapirs increases seed survival and aggregates tropical trees. Ecology 84, 19982006 (2003)
  48. Russo, S. E. & Augspurger, C. K. Aggregated seed dispersal by spider monkeys limits recruitment to clumped patterns in Virola calophylla. Ecol. Lett. 7, 10581067 (2004)
  49. Besag, J. Spatial interaction and the statistical analysis of lattice systems. J. R. Stat. Soc. B 36, 192236 (1974)
  50. Thomas, M. A generalization of Poisson’s binomial limit for use in ecology. Biometrika 36, 1825 (1949)
  51. Grabarnik, P., Myllymäki, M. & Stoyan, D. Correct testing of mark independence for marked point patterns. Ecol. Model. 222, 38883894 (2011)
  52. Fraley, C. & Raftery, A. E. MCLUST version 3: an R package for normal mixture modeling and model-based clustering (Department of Statistics, Washington University, 2006)
  53. Fraley, C. & Raftery, A. E. Bayesian regularization for normal mixture estimation and model-based clustering. J. Classific. 24, 155188 (2007)
  54. Pélissier, R. & Goreaud, F. A practical approach to the study of spatial structure in simple cases of heterogeneous vegetation. J. Veg. Sci. 12, 99108 (2001)
  55. Stoyan, D., Kendall, W. S. & Mecke, J. Stochastic Geometry and its Applications 2nd edn (Springer, 1995)

Download references

Author information

Affiliations

  1. Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, UK

    • Emily G. Mitchell,
    • Charlotte G. Kenchington &
    • Nicholas J. Butterfield
  2. British Geological Survey, Keyworth, Nottingham NG12 5GG, UK

    • Charlotte G. Kenchington
  3. School of Earth Sciences, University of Bristol, Life Sciences Building, 24 Tyndall Avenue, Bristol BS8 1TQ, UK

    • Alexander G. Liu
  4. Department of Earth Sciences, University of Oxford, South Parks Road, Oxford OX1 3AN, UK

    • Jack J. Matthews

Contributions

E.G.M. conceived the project, collected data on the ‘D’ and ‘E’ surfaces and ran the analyses. C.G.K., A.G.L. and J.J.M. collected data on the H14 surface. All authors discussed the results and prepared the manuscript.

Competing financial interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to:

Author details

Extended data figures and tables

Extended Data Figures

  1. Extended Data Figure 1: Map and simplified stratigraphic column showing the position of studied bedding planes with bedding plane maps of Fractofusus. (570 KB)

    a, Newfoundland, eastern Canada. Dashed area indicates region of interest in b. b, The Avalon and Bonavista Peninsulas, eastern Newfoundland. Locations of the bedding planes are indicated. c, Stratigraphic column (not to scale) compiled of information from the Avalon and Bonavista Peninsulas; lithological units in each region are treated as correlative in this study, but work is continuing to determine the validity of this assumption. The ‘E’ surface at Mistaken Point has been dated to 565 ± 3 Ma (ref. 12). There are currently no available radiometric dates from the Bonavista Peninsula. df, Maps of Fractofusus positions on the ‘D’ surface (d), the ‘E’ surface (e) and the H14 surface (f). In e the largest specimens are in light blue, medium specimens in mid-blue and smallest specimens in dark blue.

  2. Extended Data Figure 2: Retrodeformation calculations on the Mistaken Point surfaces. (170 KB)

    a, b, Plots of the lengths versus widths of discs from the ‘D’ surface, Mistaken Point (a), and the ‘E’ surface, Mistaken Point (b). The gradient of the line defines the retrodeformation factor, which for the ‘D’ surface is 1.35 ± 0.11 (R2 = 0.92) and for the ‘E’ surface is 1.71 ± 0.08 (R2 = 0.75). c, Fractofusus PCF on the ‘E’ surface with (solid line) and without (dashed line) retrodeformation. The grey shaded area depicts the boundary of 99 Monte Carlo simulations for the model which provided the best-fit model to the retrodeformed data, which has a good fit on the non-retrodeformed data (pd = 0.60).

  3. Extended Data Figure 3: Size distribution analysis of Fractofusus for the H14 surface. (111 KB)

    a, Size–frequency distributions for Fractofusus, (n = 1,214); b, the results of the Bayesian information criterion52, 53 (univariate data). Squares and triangles correspond to models assuming equal and unequal variance, respectively. High values of the Bayesian information criterion correspond to a good model fit, so the best-fit model is a three-component equal variance model using log-normalized length data. ce, Rose diagrams plotting the directional orientation of the different size-classes of Fractofusus on the H14 surface showing large size-class (<11.0 cm, n = 350) (c), intermediate size-class (5.5–11.0 cm, n = 310) (d) and small size-class (<5.5 cm, n = 554) (e). The angles of the Fractofusus central axis are relative to north (0°). There is no strong orientation preference for any of the size-classes.

  4. Extended Data Figure 4: Distance measures for the size data from H14 surface. (213 KB)

    For all plots, the x axis is the inter-point distance between organisms (in metres). a, Mark correlation function5, where 1 corresponds to a lack of correlation of size, such that Fractofusus size is independent and identically distributed. A value of <1 corresponds to a positive dependency (in contrast to PCF) and >1 corresponds to a negative dependency. Small Fractofusus on the H14 surface (<0.3 cm) are more likely to be found near each other than expected by random. b, The ‘E’ surface PCF (solid line) showing the model that fits the data best, a double Thomas cluster model (dotted line, pd = 0.56), and the simulation envelope for 99 Monte Carlo simulations (grey shaded area). c, d, PCF for the best-fit models for the bivariate size-classes of Fractofusus on the H14 surface showing LCMs for small with medium size-classes (pd = 0.74) (c) and LCMs for medium with large size-classes (pd = 0.66) (d). e, The PCF of the largest size-class of H14 (solid line), showing the CSR Monte Carlo simulation envelope in grey, with the ‘D’ surface PCF (dotted line, pd = 0.56). f, Nearest neighbour distances (solid line, pd = 0.01) with CSR Monte Carlo simulation envelope in grey.

  5. Extended Data Figure 5: Artistic reconstruction of Fractofusus on the H14 surface, Bonavista Peninsula. (710 KB)

    The bottom right features a large Fractofusus around which there are five to eight medium specimens clustered. Each of the medium specimens also has small specimens clustered around them. The small specimens therefore form an independent double cluster pattern, namely clusters of clusters. Artwork by C.G.K.

Extended Data Tables

  1. Extended Data Table 1: Best-fit univariate cluster models (159 KB)
  2. Extended Data Table 2: Best-fit univariate double cluster models (90 KB)
  3. Extended Data Table 3: Best-fit double Thomas cluster models fitted onto other taxa (63 KB)
  4. Extended Data Table 4: Best-fit univariate cluster models on heterogeneous backgrounds for ‘E’ surface taxa (102 KB)
  5. Extended Data Table 5: Models for bivariate analysis between different size-classes of Fractofusus on the H14 surface (84 KB)

Supplementary information

PDF files

  1. Supplementary Information (393 KB)

    This file contains Supplementary Table 1, Supplementary Text and Supplementary References.

Additional data