报告题目：From abiotic self-organization to life detection issues… passing by early evolution
报告人：Dr. Joti Rouillard
Dr Joti Rouillard
A researcher in astrobiology and geobiology at USTC, and my current research interests includes 1) life detection protocols and 2) early life evolution, from a naturalist and modelling perspective.
Keywords: self-organization, astrobiology, early evolution
In this presentation, I will introduce different studies my colleagues and I conducted in the fields of astrobiology and early life.
Finding life on other planets constitutes a major challenge for humanity. However, numerous controversies arising during the search for the oldest life traces on Earth have put under light the difficulty to distinguish true microfossils from different types of abiotic objects. I will first give more details on one such type of abiotic object: self-organized mineral aggregates with shapes reminiscent of life, and named silica-carbonate biomorphs.
The intriguing shapes produced by this simple chemical system may be linked with cross-catalysis phenomena between two precipitation reactions. This hints at the possibility of creating similar self-organized precipitates in other chemical systems. Using a numerical model inspired by cellular automata, I will show how, provided simple conditions are fulfilled, all cross-catalytic coprecipitating systems can be expected to produce a wide variety of complex textures.
The common occurrence of abiotic systems looking like life means that it is important to elaborate rigorous, quantitative protocols for recognizing life on other planets. Current protocols for biogenicity assessments have several limitations, and machine learning may bias search towards Earth-like life. I will discuss two alternative approaches that may answer these issues and show promising results.
At the earliest stages of life history on Earth, the emergence of evolutionary processes is considered critical for life to progress towards the diversity and complexity it exhibits today. However, environment where life has appeared were probably unstable, with temperature, pH and redox conditions changing during time. If a population evolves to be more efficient under certain environmental conditions, it may be detrimental to long-term population survival because the environment changes over time. I will present a numerical model in which it is assessed under which conditions an evolving population of protocells could coexist or outcompete a non-evolving population.