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An Alternative Approach for Assessing Biogenicity
Joti Rouillard1, Mark van Zuilen2, Céline Pisapia2
1Laboratario de Estudios Cristalograficos, Instituto Andaluz de Ciencias de la Tierra, CSIC-Universidad de Granada, Armilla, Spain.
Abstract:
The search for signs of life in the ancient rock record, extreme terrestrial environments, and other planetary bodies requires a well-established, universal, and unambiguous test of biogenicity. This is notably true for cellular remnants of microbial life, since their relatively simple morphologies resemble various abiogenic microstructures that occur in nature. Although lists of qualitative biogenicity criteria have been devised, debates regarding the biogenicity of many ancient microfossils persist to this day. We propose here an alternative quantitative approach for assessing the biogenicity of putative microfossils. In this theoretical approach, different hypotheses-involving biology or not and depending on the geologic setting-are put forward to explain the observed objects. These hypotheses correspond to specific types of microstructures/systems. Using test samples, the morphology and/or chemistry of these systems are then characterized at the scale of populations. Morphologic parameters include, for example, circularity, aspect ratio, and solidity, while chemical parameters could include elementary ratios (e.g., N/C ratio), isotopic enrichments (e.g., δ13C), or chirality (e.g., molar proportion of stereoisomers), among others. Statistic trends distinguishing the different systems are then searched for empirically. The trends found are translated into "decision spaces" where the different systems are quantitatively discriminated and where the potential microfossil population can be located as a single point. This approach, which is formulated here on a theoretical level, will solve several problems associated with the classical qualitative criteria of biogenicity. Most importantly, it could be applied to reveal the existence of cellular life on other planets, for which characteristics of morphology and chemical composition are difficult to predict.
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