Wind‐related features observed by the rover Spirit in Gusev crater, Mars, include patches of soil on the surface, some of which are organized into bed forms. Windblown grains include dust (inferred to be <3 μm in diameter), sands (up to a few hundred μm in diameter), and granules (>2 mm in diameter). Microscopic Imager data show the sands and granules to be rounded and relatively spherical, typical of grains transported long distances by the wind. The interior of bed forms exposed by rover operations suggests the infiltration of dust among the grains, indicating that these sands are not currently experiencing saltation. Orientations of 1520 features (such as bed forms and ventifacts) along Spirit's traverse from the landing site (the Columbia Memorial Station) to West Spur in the Columbia Hills suggest primary formative winds from the north‐northwest, which correlate with measurements of features seen in orbiter images and is consistent with afternoon winds predicted by atmospheric models. A secondary wind from the southeast is also suggested, which correlates with predictions for nighttime/early morning winds. Wind abrasion is indicated by ventifacts in the form of facets and grooves cut into rocks, the orientations of which also indicate prevailing winds from the north‐northwest. Orientations of many aeolian features in the West Spur area, however, have more scatter than elsewhere along the traverse, which is attributed to the influence of local topography on the patterns of wind. Active dust devils observed on the floor of Gusev from the Columbia Hills demonstrate that dust is currently mobile. Sequential images of some dust devils show movement as rapid as 3.8 m/s, consistent with wind velocities predicted by atmospheric models for the afternoon, when most of the dust devils were observed. Sands accumulated on the rover deck in the same period suggest that some sands in the Columbia Hills experience active saltation. “Two‐toned” rocks having a light band coating at their bases are considered to represent partial burial by soils and subsequent exposure, while “perched” rocks could represent materials lowered onto other rocks by deflation of supporting soils. Measurements of the heights of the light bands and the perched rocks range from <1 cm to 27 cm, indicating local deflation by as much as 27 cm.
The Mars Exploration Rover Spirit and its Athena science payload have been used to investigate a landing site in Gusev crater. Gusev is hypothesized to be the site of a former lake, but no clear evidence for lacustrine sedimentation has been found to date. Instead, the dominant lithology is basalt, and the dominant geologic processes are impact events and eolian transport. Many rocks exhibit coatings and other characteristics that may be evidence for minor aqueous alteration. Any lacustrine sediments that may exist at this location within Gusev apparently have been buried by lavas that have undergone subsequent impact disruption.
Science missions have limited lifetimes, necessitating an efficient investigation of the field site. The efficiency of onboard cameras, critical for planning, is limited by the need to downlink images to Earth for every decision. Recent advances have enabled rovers to take follow‐up actions without waiting hours or days for new instructions. We propose using built‐in processing by the instrument itself for adaptive data collection, faster reconnaissance, and increased mission science yield. We have developed a machine learning pixel classifier that is sensitive to texture differences in surface materials, enabling more sophisticated onboard classification than was previously possible. This classifier can be implemented in a Field Programmable Gate Array (FPGA) for maximal efficiency and minimal impact on the rest of the system's functions. In this paper, we report on initial results from applying the texture‐sensitive classifier to three example analysis tasks using data from the Mars Exploration Rovers.
Several mass spectrometry and spectroscopic techniques have been used in the search for molecular biomarkers on Mars. A major constraint is their capability to detect and identify large and complex compounds such as peptides or other biopolymers. Multiplex immunoassays can detect these compounds, but antibodies must be produced for a large number of sequence-dependent molecular targets. Ancestral Sequence Reconstruction (ASR) followed by protein "resurrection" in the lab can help to narrow the selection of targets. Herein, we propose an immunoanalytical method to identify ancient and universally conserved protein/peptide sequences as targets for identifying ancestral biomarkers in nature. We have developed, tested, and validated this approach by producing antibodies to eight previously described ancestral resurrected proteins (three β-lactamases, three thioredoxins, one Elongation Factor Tu, and one RuBisCO, all of them theoretically dated as Precambrian), and used them as a proxy to search for any potential feature of them that could be present in current natural environments. By fluorescent sandwich microarray immunoassays (FSMI), we have detected positive immunoreactions with antibodies to the oldest β-lactamase and thioredoxin proteins (ca. 4 Ga) in samples from a hydrothermal environment. Fine epitope mapping and inhibitory immunoassays allowed the identification of well-conserved epitope peptide sequences that resulted from ASR and were present in the sample. We corroborated these results by metagenomic sequencing and found several genes encoding analogue proteins with significant matches to the peptide epitopes identified with the antibodies. The results demonstrated that peptides inferred from ASR studies have true counterpart analogues in Nature, which validates and strengthens the well-known ASR/protein resurrection technique and our immunoanalytical approach for investigating ancient environments and metabolisms on Earth and elsewhere.
