Exoplanet Biosignatures: Future Directions
Walker, Sara I.
Kiang, Nancy Y.
Reinhard, Christopher T.
Schwieterman, Edward W.
Shkolnik, Evgenya L.
Smith, Harrison B.
- Publisher: Mary Ann Liebert, Inc.
(issn: 1531-1074, eissn: 1557-8070)
Astrophysics - Earth and Planetary Astrophysics | Special Collection: Exoplanet BiosignaturesGuest Editors: Mary N. Parenteau, Nancy Y. Kiang, Shawn Domagal-Goldman (in reverse alphabetical order)Review Articles
Table of Contents 1. Introduction 2. Setting the Stage: What Is Life? What Is a Biosignature? 3. Detecting Unknown Biology on Unknown Worlds: A Bayesian Framework 3.1. Habitability in the Bayesian framework for biosignatures 4. P(data|abiotic) 4.1. Stellar environment 4.2. Climate and geophysics 4.2.1. Coupled tectonic–climate models 4.2.2. Community GCM projects for generating ensemble statistics for P(data|abiotic) and P(data|life) 4.3. Geochemical environment 4.3.1. Anticipating the unexpected: statistical approaches to characterizing atmospheres of non-Earth-like worlds 5. P(data|life) 5.1. Black-box approaches to living processes 5.1.1. Type classification of Seager et al. (2013a) 188.8.131.52. Energy capture (type I) 184.108.40.206. Biomass capture (type II) 220.127.116.11. Other uses (type III) 18.104.22.168. Products of modification of gases (type IV) 5.1.2. Alternatives for type classification 22.214.171.124. Type I, energy capture 126.96.36.199. Type II, biomass capture 188.8.131.52. Type III, “other uses” 184.108.40.206. Type IV 5.1.3. When is it appropriate to deconstruct a black box? 5.2. Life as improbable chemistry 5.3. Life as an evolutionary process 5.3.1. Life as a coevolution with its planet: Earth as an example 5.3.2. Calculating conditional probabilities in biological evolution from past biogeochemical states 5.4. Insights from universal biology 5.4.1. Network biosignatures 5.4.2. Universal scaling laws, applicable to other worlds? 6. P(life) 6.1. P(emerge): constraining the probability of the origins of life 6.2. Biological innovations and the conditional probabilities for living processes 7. A Bayesian Framework Example: Detecting Atmospheric Oxygen 8. Tuning Search Strategies Based on the Bayesian Framework 9. Conclusions Acknowledgments Author Disclosure Statement References Abbreviations Used