Supplementary data for: Hydrodynamic insights into the palaeobiology of the Ediacaran rangeomorph Fractofusus misrai
Data files
May 18, 2024 version files 25.03 GB
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15_cm_simulations.zip
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F.misrai_low.stl
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README.md
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Table_S1.docx
May 20, 2024 version files 25.07 GB
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15_cm_simulations.zip
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F.misrai_low.stl
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Figure_S1.pdf
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Figure_S2_.pdf
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Figure_S3.pdf
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Figure_S4_.pdf
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Figure_S5.pdf
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Figure_S6.pdf
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Figure_S7.pdf
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Figure_S8.pdf
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README.md
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Table_S1.docx
May 24, 2024 version files 25.07 GB
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15_cm_simulations.zip
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F.misrai_low.stl
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Figure_S1.pdf
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Figure_S2_.pdf
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Figure_S3.pdf
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Figure_S4_.pdf
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Figure_S5.pdf
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Figure_S6.pdf
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Figure_S7.pdf
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Figure_S8.pdf
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README.md
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Table_S1.docx
Abstract
The Ediacaran of Newfoundland preserves some of the oldest complex macroscopic communities several of which are dominated by the fractal-like rangeomorph genus Fractofusus. Here we use computational fluid dynamics and a detailed reconstruction of Fractofusus misrai to document for the first time hydrodynamic phenomena associated with this sediment-reclining organism and its rangeomorph elements that: are relevant to interpreting feeding strategies, explain the recently documented rheotropic growth oblique to currents, and provide insights into their impact on the Ediacaran seafloor. Obliquely oriented Fractofusus are common, likely representing a compromise between maximized aspect ratio and minimization of drag. Flow patterns on the upper surface of Fractofusus are consistent with the collection of dissolved and finely particulate nutrients, as well as gas exchange. Fractofusus produce a long wake downstream, demonstrating that reclining Rangeomorpha had potential to modify sedimentation patterns on the ancient seafloor by potentially allowing deposition of fine grained bypassing sediment.
README: Supplementary data for: Hydrodynamic insights into the palaeobiology of the Ediacaran rangeomorph Fractofusus misrai
https://doi.org/10.5061/dryad.fxpnvx103
Supplementary materials include: 1) computational fluid dynamics (CFD) results from discretization and sensitivity tests conducted to determine optimal mesh sizes, balancing anatomical resolution with computational efficiency (Figs. S1-S3); 2) CFD simulation results from different sizes of F.misrai and general view of streamlines (Figs. S4-S6); 3) CFD simulation results from null models (Fig. S7); 4) flow velocity profile (Fig. S8); 5) all numeric results from CFD simulations (Table S1); 6) the Fractofusus misrai geometry; and 7) CFD simulation results.
Description of the data and file structure
Fig. S1-S3 show different mesh sizes for both the flow volume region (FVR) and the F. misrai geometry. Fractofusus misrai geometries, consisting of approximately 300,000 to 500,000 polygons, and the corresponding FVRs were meshed using standard algorithms with automatic sizing and a medium factor fineness. The resulting meshes consisted of approximately 2-4 million cells and 500.000-1 million nodes (Fig. S2).
Figs. S4-S5 show the CFD results from different sizes of F. misrai. Both small (Fig. S4) and medium (Fig. S5) F. misrai are displayed in different orientations relative to the simulated flow from (left to right). Both orientations show the eddying at the frond margin. Current perpendicular F. misrai also shows weak vortices on the upper surface of the frond both upcurrent of the axis of the frond, and also in the lee of the axis. Figure S6 shows a general view of streamlines coloured according to velocity (Ux) around different orientations of Fractofusus misrai. Fig. S7 shows CFD simulations of null models. Figure S8. shows th velocity profile (Ux) along vertical axis (z) from the bottom boundary of the fluid domain around Fractofusus misrai.
Table S1. Shows CFD simulations numeric results. Reference area is the exposed (frontal) area to the flow and reference length in the length along the x axes.
The F. misrai geometry is available. The intermediate size (15 cm) F. misrai CFD simulation set is available. Remaining results can be normalized using scaling laws. Additional results are available upon request.
Code/Software
The three-dimensional models of F. misrai were created using ZBrush Pixologic, Inc. (https://www.maxon.net/en/zbrush; by R. Nicholls), then post-processed using Rhinoceros 3D v.7 (https://www.rhino3d.com) and Blender v.3.4.1 (https://www.blender.org). Finally, results were analyzed with the post-processing visualization engine Paraview (https://www.paraview.org). Simulations of incompressible water flow were performed using CFD Simscale software (https://www.simscale.com).
Methods
Geometry of Fractofusus misrai
The three-dimensional models of F. misrai were created using ZBrush Pixologic, Inc. (https://www.maxon.net/en/zbrush; by R. Nicholls), then post-processed using Rhinoceros 3D v.7 (https://www.rhino3d.com) and Blender v.3.4.1 (https://www.blender.org). The geometry was built as a smoothed three million polygon mesh, capturing three orders of rangeomorph branching. Scaling followed published fossil dimensions, and geometries were oriented according to the statistical clusters in Pérez-Pinedo et al. 2023. Finally, results were analyzed with the post-processing visualization engine Paraview (https://www.paraview.org).
Computational Fluid dynamics (CFD)
Discretization and sensitivity tests were conducted to determine optimal mesh sizes, balancing anatomical resolution with computational efficiency (computing cores, CPU usage; Figs. S1-S2) at which results are independent of the mesh size. Fractofusus misrai geometries, consisting of approximately 300,000 to 500,000 polygons, and the corresponding FVRs were meshed using Simscale standard-finite-volume meshing algorithms with automatic sizing and a medium factor fineness. The resulting mesh consists of tetrahedral and hexahedral elements. Various mesh fineness factors and region refinements were applied around the fossil geometry to explore the ideal computational parameters. Simulations of incompressible water flow [density (ρ) ≃ 1,000 kg/m3; dynamic viscosity (μ) ≃ 0.001 kg/(m⋅s)] around the reconstructed F. misrai geometry were performed using CFD Simscale software (https://www.simscale.com). Reynold numbers (Re) were calculated based on the characteristic length of Fractofusus (L 0.05, 0.15, 030) ranging from 2683 ~ 64411 (Table. S1). Our flow regimes are around the turbulent transition for flows around an obstacle Re 20000. However, it is important to note that our reconstructed fossil geometry shows a very complex rough surface which results in ‘tripped’ boundary layers leading to critical implications in Reynolds number thresholds, meaning it is possible to have turbulent flows at lower Reynolds numbers. Nevertheless, the aim of this study is to simulate the turbulent hydrodynamic conditions experienced by Fractofusus on the seafloor during the interval prior to the sediment-laden obrution events that smothered and killed them. The clear-water inter-turbiditic background currents travelled at low velocities over vast distances interacting with the roughness of the seafloor. In doing so they could be expected to have encountered innumerable obstacles of variable shapes and sizes, including seafloor topography (pits, mounds, ripples, scours, clasts, the bodies of living and dead erect and reclining organisms, channelization, etc). That is to say that the fronds we see on the Ediacaran bedding planes were not the first obstacles that the passing current was exposed to. Even if a such a current passed over a smooth seabed for such long distances, the skin friction alone would ensure turbulence at the velocities typical of modern deep ocean settings. Direct measurements of flow at the seafloor demonstrates persistent (turbulent) currents even from the deep featureless ocean abyssal plain. Additionally, oceanographic measurements estimate the viscous sublayer beneath abyssal currents, based on seafloor current data, to be ~5 mm. Fractofusus and most other sources of seafloor roughness would have projected through the viscous sublayer serving to maintain turbulent conditions at the Ediacaran seafloor. Reynolds numbers associated with modern boundary layers are of order 106 to 107. In order to simulate currents of comparable strength (U ~ 10 cm/s; U/u* ~ 30–35) K-Omega Shear Stress Transport SST model was used to solve the Reynolds-averaged Navier–Stokes (RANS) equations, with a stationary solver used to compute the steady-state solution across all simulations. This model is known to better predict flow separation patterns than most RANS models. Additionally, laminar model simulations covering the entire spectrum of modelled sizes, velocities, and orientations were tested for comparison, though laminar flows are not expected in natural deep marine settings (Table. S1). The computational domain consisted of a three-dimensional rectangular FVR, measuring 400cm x 200cm x 40cm allowing fully developed flows. A velocity inlet condition was fixed at the -X end of the FVG with three different flow velocities (Ux = 0.05 m/s, 0.1 m/s, 0.2 m/s) while a zero-pressure outlet boundary condition was applied on the opposite +X end. The boundaries on the sides and top featured wall slip-boundary conditions, whereas the lower boundary and the F. misrai geometry were assigned no-slip boundary conditions. Lastly, our palaeobiological reconstruction of F. misrai was affixed to the computational domain on the bottom boundary. The organism reconstructions were modelled in three different sizes: small (5cm x 1.5cm), medium (16cm x 5cm), and large (30cm x 10cm) (Figs. 4, S3-S5). These were positioned in different orientations with respect to the flow: parallel (0º), and perpendicular (90º) as well as oblique (35º-52º) based on the clusters determined by Pérez-Pinedo et al. 2023. Flow dynamics from the somewhat analogous modern cold-water coral-rich areas in southwest Grand Banks were used to characterize the background clear water, turbulent, flow regimes from the Capelin Gulch site.The results were compared to a null model in the form of an ellipse lacking rangeomorph elements and fully merged into the bottom boundary without projecting primary branches. The Velocity magnitude (Ux) and streamlines were visualized and drag forces (FD) were computed for each simulation by integrating pressure and skin-friction over the boundary. The distribution of the pressures and viscous (shear) forces along the elements were integrated, all the overall forces and moments calculated. To compute FD, the projected (frontal) area of the fossil geometries was calculated (Table. S1). Due to meshing difficulties, FD values were calculated using a small millimetre-scale base for F. misrai that was bound to the bottom boundary. Finally, FD was explored by decomposing the normal force of pressure for each element of the surface mesh.