4.4 Article

Exoplanet Biosignatures: A Framework for Their Assessment

Journal

ASTROBIOLOGY
Volume 18, Issue 6, Pages 709-738

Publisher

MARY ANN LIEBERT, INC
DOI: 10.1089/ast.2017.1737

Keywords

Bayesian statistics; Biosignatures; Drake equation; Exoplanets; Habitability; Planetary science

Funding

  1. NASA Astrobiology Institute's Virtual Planetary Laboratory [NNA 13AA93A]
  2. NExSS
  3. NASA [NNX15AM07G, NNX15AR63H]
  4. NASA

Ask authors/readers for more resources

Finding life on exoplanets from telescopic observations is an ultimate goal of exoplanet science. Life produces gases and other substances, such as pigments, which can have distinct spectral or photometric signatures. Whether or not life is found with future data must be expressed with probabilities, requiring a framework of biosignature assessment. We present a framework in which we advocate using biogeochemical Exo-Earth System models to simulate potential biosignatures in spectra or photometry. Given actual observations, simulations are used to find the Bayesian likelihoods of those data occurring for scenarios with and without life. The latter includes false positives wherein abiotic sources mimic biosignatures. Prior knowledge of factors influencing planetary inhabitation, including previous observations, is combined with the likelihoods to give the Bayesian posterior probability of life existing on a given exoplanet. Four components of observation and analysis are necessary. (1) Characterization of stellar (e.g., age and spectrum) and exoplanetary system properties, including external exoplanet parameters (e.g., mass and radius), to determine an exoplanet's suitability for life. (2) Characterization of internal exoplanet parameters (e.g., climate) to evaluate habitability. (3) Assessment of potential biosignatures within the environmental context (components 1-2), including corroborating evidence. (4) Exclusion of false positives. We propose that resulting posterior Bayesian probabilities of life's existence map to five confidence levels, ranging from very likely (90-100%) to very unlikely (<10%) inhabited.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.4
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available