Variation of Geochemical Signatures and Correlation of Biomarkers in Icelandic Mars Analogue Environments

Exploration missions to Mars rely on rovers to perform deep analyses over small sampling areas; however, landing site selection is done using large-scale but low-resolution remote sensing data. Using Earth analogue environments to estimate the small-scale spatial and temporal distributions of key geochemical signatures and (for habitability studies) biomarkers helps ensure that the chosen sampling strategies meet mission science goals. We conducted two rounds of analogue expeditions to recent Icelandic lava fields. In July 2013, we tested correlation between three common biomarker assays: cell quantification via fluorescence microscopy, ATP quantification via bioluminescence, and quantitative PCR with universal primer sets. Sample sites were nested at four spatial scales (1 m, 10 m, 100 m, and > 1 km) and homogeneous at 'remote imaging' resolution (overall temperature, apparent moisture content, and regolith grain size). All spatial scales were highly diverse in ATP, bacterial 16S, and archaeal 16S DNA content; nearly half of sites were statistically different in ATP content at α = 0.05. Cell counts showed significant variation at the 10 m and 100 m scale; at the > 1 km scale, the mean counts were not distinguishable, but the median counts were, indicating differences in underlying distribution. Fungal 18S DNA content similarly varied at 1 m, 10 m, and 100 m scales only. Cell counts were not correlated with ATP or DNA content at any scale. ATP concentration and DNA content for all three primer sets were positively correlated. Bacterial DNA content was positively correlated with archaeal and fungal DNA content, though archaeal correlation was weak. Fungal and archaeal correlation was borderline. In July 2015, we repeated the sampling strategy, with the addition of a smaller-scale sampling grid of 10 cm and a third > 1 km location. This expedition also measured reflectance of the tephra cover and preserved mineral samples for future Raman spectroscopy in order to better distinguish between effects of geochemical variation and intrinsic biomarker variation.