Patterns of complexity in biogenic rocks

2023-08-25 450 words 3 minutes

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Contents

Sample visualizer: correlating multi-scale complexity in astrobiological samples

Language: Python

1 Current State

While the scientific community still hasn't come up with a natural definition of Life, it is often described as a "complex" phenomenon.

In fact, most, if not all, astrobiology-focused missions, like NASA's Perseverance, are hoping to detect "complex" organic molecules, which are thought to be reliable signs of life (aka biosignatures).

Here again, the term "complex" is often used by astrobiologists when referring to Life and its derivatives. However, the term "complex" remains poorly constrained and the complexity of astrobiological samples is rarely quantified.

Through my current research I aim to address this issue by characterizing and quantifying the complexity of rock samples of astrobiological interest termed microbialites.

More specifically, I aim to quantify and correlate different "types" of complexity at various scales (i.e., nano-, micro-, and macro-).

I am particularly interested in the potential correlation between the morphological, molecular, and biological complexities within my samples and aim to answer the following questoins:

Are complex natural shapes necessarily accompanied by complex biological communities?

Are complex assemblages of organic molecules a direct consequence of complex biological communities?

2 The sample visualizer

Built with Plotly Dash, the Sample Visualizer is a web app helping me, and soon the entire astrobiology community, to visualize the different types and scales of complexity within my samples.

After taking 3D photogrammetric scans of my hand-sized samples, I compute various local and global fractal dimensions to quantify the morphological complexity of their shape.

Based on the obtained morphological mapping, I select subsamples that I will analyze in the laboratory for their organic molecular content.

The latter geochemical analyses will already give me tangible evidence of the active and inactive biological communities, which will be further investigated using DNA sequencing of the same subsamples.

The web app has not been published yet and only runs of my machine since it displays my unpublished data. I am currently working on making it usable by and accessible to the entire astrobiology community. Stay tuned!