Numerical Modelling of Surface/Subsurface Methanogen Bioburden at Gale Crater Using Methane Production and Destruction Processes

Introduction: Methane on Mars was first detected using ground-based telescopes [1] and Martian orbiters [2] in the early 2000s. Since then, the Mars Science Laboratory (Curiosity Rover) has detected additional methane in the Martian atmosphere using the Sample Analysis at Mars (SAM) instrument [3]. Observations of atmospheric methane have prompted further investigation into the putative biotic or abiotic mechanisms of its production. Potential mechanisms include modern and/or ancient microbial methanogenesis, deep subsurface geothermal processes, abiotic Fischer-Tropsch Type reactions after serpentinization, or thermogenesis of organics [4]. Our presentation will explore the plausibility of modern microbial processes as a contributing production mechanism to the methane emissions presently observed on Mars.

Modelling Production of Methane: The generation rate of methane is set by the methane flux derived at Gale of 1.5 x 10^-10 kg m^-2 sol^-1 [5]. While this value is agnostic as to the methane production mechanism, it can be converted to a maximum bioburden (assuming all methane is produced biogenically) by combining it with experiments performed by Harris and Schuerger [6] which outline the production of methane from Methanosarcina barkeri under simulated Martian surface conditions (0°C, 7-12 mbar, CO₂ dominated gas mixture). Results from [6] demonstrated CH₄ production, although genes involved in the hydrogenotrophic pathway of methanogenesis were significantly downregulated compared to ideal M. barkeri growth conditions (30°C, 1500 mbar, 80:20 H₂:CO₂). The full experiment involved 6 runs of methane production rate measurements, each run varying by atmospheric composition, atmospheric pressure, and temperature. Based on these experiments, we created a model of methane production by methanogenesis (Fig 1.). This figure displays a comparison of modeled versus measured methane production rates using values obtained by [6]. Temperature, CO₂, H₂, and the methanogen surface density (cells m^-2) serve as adjustable model constraints to simulate a range of environmental scenarios, including Mars- or Earth-like conditions. Variations in these parameters have yielded promising results.

Predicted Bioburden Below 30m in the Subsurface: With methanogens located below the annual temperature wave (at least 30m below the surface) we can solve for the total bioburden of methanogens required (Fig 2.). The temperature and depth axes were defined using a thermal gradient of 5 K/km [7] starting from the mean surface temperature of Gale Crater and extending to approximately 400 K consistent with experimental findings that methanogenesis may occur at temperatures exceeding 100°C [8]. Depth may then be determined using the value for the thermal gradient.

Figure 2 illustrates the dependance on pH₂ bioavailability for increased bioproductivity of methanogens. At greater temperatures and availability of pH₂, fewer methanogens are required for methane production using a rate constant of 1.05 x 10^-13 cells m^-2 s^-1 [5]. Conversely, at low temperatures and availability of H₂, more methanogens are needed using the same rate constant. Kral et al. [9] [10] identified H₂ as a primary electron donor driving methanogenic metabolism under simulated Martian conditions.

Examining the Evolution of Atmospheric Concentrations using an Atmospheric Box Model: Closer than 30m to the surface, methane production from methanogens will vary daily and annually as the temperature to which they are exposed changes. Rapid changes in methane emitted requires the production model to be coupled to a destruction model. Thus, to examine how the atmospheric concentration near the surface changes in response, a box model was developed to demonstrate the production/destruction couple and the resulting CH₄ concentrations. The destruction mechanism used to model the observed CH₄ measurements was outlined by [11] and involved perchlorate-rich Martian soils that when activated by UV irradiation oxidized adsorbed alkanes.

To set up our simplified box model a 1 m² homogeneous atmospheric column was created containing CO₂ at 610 Pa, an H₂ abundance of 15 ppmv and surface temperatures given by [12]. These conditions along with a methanogen cell count of 1.0 x 10¹⁷ cells m^-2 produce the blue line shown in Figure 3 below.

The orange line utilized the same CO₂ and H₂ abundances, however the temperature was adjusted to reflect conditions at approximately 30 m depth, where temperatures corresponded to the thermal average of Gale Crater.     

At surface conditions (Fig 3), the modeled atmospheric methane was slowly generated overnight when temperatures were coolest and when the destruction process was inhibited by lack of sunlight. During the day, there was a steep decline in methane observed in methane concentration until concentrations become so low that destruction was ineffective. After the lowest methane was achieved at 0.5 sol, methane concentrations steadily rose throughout the day as ground temperatures increased. The population of methanogens was kept at 1.0 x 10¹⁷ cells m^-2 for the duration of the simulations. Cell counts increased to 8.0 x 10¹⁷ m^-2 when simulating conditions at depth (~30 m). Here, similar overall diurnal trends were observed; however, minimum methane concentration was reduced by nearly an order of magnitude by midday and was likely attributable to the increased maximum methane concentration prior to sunrise, enhancing the efficiency of the destruction mechanism following sunrise.

Conclusions: Diurnal patterns observed in Figure 3 are distinct from patterns expected solely by atmospheric processes, warranting further investigation into possible sources and sinks of methane on Mars. The development of an accurate model that can predict methane concentrations, rate of methanogenesis, and/or methanogen cell counts are crucial to understanding if methanogenic metabolism is a possible source for the methane currently observed on Mars.

References: [1] Formisano et al. (2004) Sci 306(5702), 1758–1761 [2] Mumma et al. (2009) Sci 323(5917), 1041-1045 [3] Webster et al. (2014) Sci 347(6220), 415-417 [4] Oehler and Etiope Astrobio 17(12), 1233-1264 [5] Moores et al. (2019) GRL 46(16), 9430-9438 [6] Harris and Schuerger (2025) Sci Rep 15(2880), 1-15 [7] Jones et al. (2011) Astrobio 11(10), 1017-1033 [8] Takai et al. (2008) Proc of the NAS 105(31), 10949–10954 [9] Kral et al. (2011) PSS 59(2-3), 264–70 [10] Kral et al. (2004) Origins of Life and Evolution of the Biosphere 34(6), 615–626 [11] Zhang et al. (2022) Icarus 376(114832):1–15 [12] Martinez et al. (2017) Space Sci Rev 212(1-2):295–338