Supervisors and Institutions
Stromatolites are laminated domes, cones, ridges and columns of sediment formed by living organisms. How do non-biological factors shape these structures and form pseudofossils mimicking them?
Stromatolites are finely laminated domes, cones, ridges and columns produced by the binding, trapping, and (especially) precipitation of mineral particles by bacterial communities at the sediment-water interface. Growing stromatolites (a.k.a. “living rocks”) are found in several aquatic environments on Earth today, and fossil examples ~3.5 billion years old are among the oldest evidence of life on Earth. Unlike cellular microfossils, stromatolites could be large enough (centimetres-to-metres) to be photographed by rovers if they exist on Mars. But it is still unclear how much we can learn about ancient life from stromatolite-like forms in the rock record. Non-biological (physical) processes shape the morphology of stromatolites in important, poorly understood ways and can even generate similar forms in the complete absence of living processes. Numerical modelling has shown that stromatolite growth can be simulated using a few simple rules such as radial expansion, random particle accretion, and relaxation/diffusion (e.g., Grotzinger & Rothman, 1996; Dupraz et al., 2006; Curtis et al., 2021). Experiments have shown that colloid droplets sprayed over a flat surface generate stromatolite-like laminated domes and columns (McLoughlin et al., 2008); similar deposits build up on factory floors where cars are spray-painted. A natural analogue may be the deposition of silica in splash zones around hot springs, which can form domes and columns often interpreted as siliceous stromatolites. Hot-spring silica deposits on Mars have already been identified by some astrobiologists as possible stromatolites (Ruff et al., 2016), highlighting the need for new research into the role of biological and non-biological processes in generating such forms (McMahon & Cosmidis, 2021). This project will use numerical, experimental, and traditional geological methods to explore abiotic controls on the growth of stromatolites and similar structures so that we can better decipher ancient examples.
How accurately can numerical methods predict the three-dimensional form of stromatolites growing under different physical and chemical conditions?
Can biogenic and abiogenic stromatolite-like forms be differentiated in morphospace?
Can the precipitation of minerals/amorphous phases from finely dispersed droplets generate stromatolite-like forms abiotically?
How good are existing criteria for discriminating between stromatolites and abiotic pseudo-stromatolites, and can they be improved?
How widespread is pseudo-stromatolite formation likely to have been on the early Earth and Mars?
This project will involve (a) precipitation experiments in the laboratory, (b) numerical modelling of stromatolite growth, and (c) structural analysis of real stromatolite fossils. There is some flexibility about the balance between these approaches.
Work in years 1–2 will concentrate on a mixture of: (1) (re)constructing numerical models of stromatolite growth to incorporate physical factors such as hydrodynamic forcing and variable sediment supply; (2) preliminary experiments to produce and characterize laminated silica and carbonate mineral deposits in the laboratory with and without a cyanobacterial inoculum; (3) three-dimensional reconstruction and growth analysis of complex fossil stromatolites by serial sectioning.
In years 2–3, these methods will be used to generate publishable datasets addressing the five research questions above. Additional relevant methodologies may include statistical analysis of morphology/morphospace, petrographic and geochemical analysis of samples, and fieldwork to examine modern and/or ancient stromatolites in situ.
A comprehensive training programme will be provided comprising both specialist scientific training and generic transferable and professional skills.
This project would suit a geoscience graduate with knowledge of palaeobiology, sedimentology, and geochemistry OR a physical science graduate with strong skills in numerical and computational methods. Experience in laboratory-based practical work and coding (e.g., Python, C++) would be an advantage.
Curtis, A., Wood, R., Bowyer, F., Shore, A., Curtis‐Walcott, A., & Robertsson, J. (2021). Modelling Ediacaran metazoan–microbial reef growth. Sedimentology, 68(5), 1877-1892.
Dupraz, C., Pattisina, R., & Verrecchia, E. P. (2006). Translation of energy into morphology: simulation of stromatolite morphospace using a stochastic model. Sedimentary Geology, 185(3-4), 185-203.
Grotzinger, J. P., & Rothman, D. H. (1996). An abiotic model for stromatolite morphogenesis. Nature, 383(6599), 423-425.
McLoughlin, N., Wilson, L. A., & Brasier, M. D. (2008). Growth of synthetic stromatolites and wrinkle structures in the absence of microbes–implications for the early fossil record. Geobiology, 6(2), 95-105.
McMahon, S., & Cosmidis, J. (2021). False biosignatures on Mars: Anticipating Ambiguity. J. Geol. Soc. London. In press: available on request from S. McMahon
Ruff, S. W., & Farmer, J. D. (2016). Silica deposits on Mars with features resembling hot spring biosignatures at El Tatio in Chile. Nature communications, 7(1), 1-10.