Biogeochemical Cycling in a High-Altitude Andean Lake: Insights into Potential Microbial Metabolisms During the Noachian and Hesperian Periods on Mars
Bibliographic record
Abstract
This PhD aimed to identify metabolic processes potentially prevalent in martian paleolakes to inform the selection and identification of biosignatures in present and future missions. To achieve this aim, I studied a high-altitude lake (HAL) with geochemical and climatological characteristics similar to those predicted for Yellowknife Bay, Gale Crater, Mars, during the Noachian-Hesperian transition. During the Noachian-Hesperian transition, the martian climate has been suggested as semi-arid to arid, cold, with high ultraviolet radiation (UV) levels. To identify the most appropriate analogue, ecoregions where HALs had been described had daily UV radiation flux, annual precipitation, diurnal temperature fluctuation, and mean daily temperature analysed. Using machine-learning approaches, the geochemical composition of fluids from HALs was compared to thermochemically modelled martian fluids. The Central Andean dry Puna was identified as having a climate representative of Noachian-Hesperian Mars, appropriate geological context due to the active volcanism within the Central Andes, and HALs with water chemistry similar to thermochemical models. As such, Laguna de Antofagasta (LDA), a high-altitude Andean Lake, was selected to be investigated. Geochemical analysis indicated that LDA was oligotrophic, with sediment comprised of weathered minerals from igneous sources. Bacteria were the dominant domain, representing >99% of total prokaryotes identified, with members of the Pseudomonadota and Bacteroidota being the dominant phyla. Canonical correspondence analysis (CCA) indicated that S, total C, and DO significantly impact microbial community composition across sampling sites. Metagenomic analyses identified sulphur-oxidation as the dominant metabolism within the LDA benthic environment, with members of the genera <i>Thiobacillus, Sulfuricaulis,</i> and <i>Thiocapsa</i> accounting for 92.59 % of total reads sequenced from sedimentary samples. Nitrate was also identified as an important electron acceptor, with genes associated with denitrification and dissimilatory nitrate reduction to ammonium (DNRA) consistently detected. The dominance of this environment by S-oxidisers highlights sulphur-oxidation as a Mars-relevant metabolism. Results also suggest that sulphide may influence nitrogenous compounds in martian paleolake environments. Understanding connectivity between biogeochemical cycles under Mars-relevant conditions can inform current and future sampling efforts and subsequent biosignature detection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".