A decades-old pursuit to explore for life beyond Earth has received new impetus with a recent discovery that promises to simplify and make routine the task of searching for life on distant planets where signs of life are hard to detect. A team of astrobiologists, chemists, and planetary scientists built the model to assess whether, based on what’s known about an alien environment but very little else, that environment could host certain kinds of life. It takes into account organism types, environmental variables, and the probability of survival in a harsh planetary climate. The idea is to inform future telescope missions and life-detection strategies throughout the cosmos.
NASA’s New Habitability Model Calculates Odds of Life on Alien Worlds with Limited Data
As per a report from The Conversation, the model, dubbed the “quantitative habitability framework”, was developed as part of NASA’s Alien Earths project. It throws out the usual “follow the water” guideline and rather compares the environmental conditions to the demands of organisms that inhabit Earth or even theoretical alien counterparts. This probabilistic approach quantifies the odds that life might be compatible with
a given habitat and provides realistic expectations for scientists regarding where and how to look for the presence of life in the universe.
The open-source tool, which was built to be adaptable, was further validated with organisms that live within extreme environments on Earth, such as insects that live in the Himalayas and microbes that live in Earth’s depths, to assess their chances of survival in alien environments such as in the Martian subsurface and beneath Europa’s oceans.
Researchers can calculate the likelihood of life on planets or moons using evidence-based approaches, without needing the full chemical and atmospheric data, to help interpret biosignatures and optimise telescope targeting.
The framework is designed to assess whether environments may be able to host known or hypothetical alien life. The framework is intended to grow over time to include extremophiles and simulations.
