morphogenesis1 coast print.jpg

CNRA: MORPHOGENESIS I. COAST, SHRUB, FOREST
— 2021

VIDEO, CUSTOM SOFTWARE, NEURAL NETWORK (NEURAL CELLULAR AUTOMATA), DATA VISUALIZATION OF EDNA METABARCODING ANALYSIS OF CALIFORNIA SOIL MICROBIAL DIVERSITY

By Biomedia Studio: Hye Min Cho, Maura Palacios, Maru Garcia

Commissioned piece by the California Natural Resources Agency (CNRA)

Morphogenesis I : coast, shrub, forest is a piece that fuses the tools of molecular biology and artificial intelligence to help understand the complex landscapes of soil microbial biodiversity across three California ecosystems: coast, shrub and forest.

The visuals are a product of data analysis of a microbial dataset produced by the CALeDNA program (1), which includes soil samples collected by community scientists. The samples were processed for eDNA (DNA found in the environment) metabarcoding, which allows for the detection of the community composition across different regions. A custom software was developed using a variation of Neural Cellular Automata (2), a dynamic system that produces visuals starting from a seed and evolving in discrete steps. This method was chosen based on the biological mechanisms of single-cell growth self-assembling into highly complex organisms. In Morphogenesis I, each initial seed corresponds to a sampling area within an ecosystem including the coordinates and relative concentration of the different microbial communities. The visuals show textures, which are interpreted as the presence and interaction of the bacterial phylums corresponding to each sampling area. The impactful visuals capture the beauty and complexity of soil microbial communities and the importance of soil as a source of life.

(1) Lin, Meixi et al. “Landscape analyses using eDNA metabarcoding and Earth observation predict community biodiversity in California.” Ecological applications: a publication of the Ecological Society of America vol. 31,6 (2021): e02379. doi:10.1002/eap.2379

(2) Mordvintsev, A. et al. “Growing Neural Cellular Automata.” Distill (2020): n. pag.

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