The persistence of a chlorophyll spectral biosignature from Martian evaporite and spring analogues under Mars-like conditions

Abstract

Spring and evaporite deposits are considered two of the most promising environments for past habitability on Mars and preservation of biosignatures. Manitoba, Canada hosts the East German Creek (EGC) hypersaline spring complex, and the post impact evaporite gypsum beds of the Lake St. Martin (LSM) impact. The EGC complex has microbial mats, sediments, algae and biofabrics, while endolithic communities are ubiquitous in the LSM gypsum beds. These communities are spectrally detectable based largely on the presence of a chlorophyll absorption band at 670 nm; however, the robustness of this feature under Martian surface conditions was unclear. Biological and biology-bearing samples from EGC and LSM were exposed to conditions similar to the surface of present day Mars (high UV flux, 100 mbar, anoxic, CO_2 rich) for up to 44 days, and preservation of the 670 nm chlorophyll feature and chlorophyll red-edge was observed. A decrease in band depth of the 670 nm band ranging from ∼16 to 80% resulted, with correlations seen in the degree of preservation and the spatial proximity of samples to the spring mound and mineral shielding effects. The spectra were deconvolved to Mars Exploration Rover (MER) Pancam and Mars Science Laboratory (MSL) Mastcam science filter bandpasses to investigate the detectability of the 670 nm feature and to compare with common mineral features. The red-edge and 670 nm feature associated with chlorophyll can be distinguished from the spectra of minerals with features below ∼1000 nm, such as hematite and jarosite. However, distinguishing goethite from samples with the chlorophyll feature is more problematic, and quantitative interpretation using band depth data makes little distinction between iron oxyhydroxides and the 670 nm chlorophyll feature. The chlorophyll spectral feature is observable in both Pancam and Mastcam, and we propose that of the proposed EXOMARS Pancam filters, the PHYLL filter is best suited for its detection.

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