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The near-term capability to characterize terrestrial exoplanet atmospheres may bring us closer to discovering alien life through atmospheric data. However, remotely detectable candidate biosignature gases are subject to possible false positive signals as they can also be produced abiotically. To distinguish biological, abiotic and anomalous sources of these atmospheric gases, we take a complex systems approach using chemical reaction network analysis of planetary atmospheres. We simulated 30,000 terrestrial atmospheres, organized in two datasets: Archean Earth-like worlds and modern Earth-like worlds. For Archean Earth-like worlds we study cases where CH4 is produced abiotically via serpentinization, biologically via methanogenesis, or from anomalous sources. We also simulate modern Earth-like atmospheres with and without industrial CFC-12. Network properties like mean degree and average shortest path length effectively distinguish scenarios where CH4 is produced from methanogenesis and serpentinization, with biologically driven networks exhibiting higher connectivity and efficiency. Network analysis also distinguishes modern Earth atmospheres with CFC-12 from those without, with industrially polluted networks showing increased mean degree. Using Bayesian analysis, we demonstrate how atmospheric network property statistics can provide stronger confidence for ruling out biological explanations compared to gas abundance statistics alone. Our results confirm how a network theoretic approach allows distinguishing biological, abiotic and anomalous atmospheric drivers, including ruling out life-as-we-know-it as a possible explanation. Developing statistical inference methods for spectral data that incorporate network properties could significantly strengthen future biosignature detection efforts., Comment: 22 pages (including references), 4 figures, 1 table

Inferring the properties of exoplanets from their atmospheres, while confronting low resolution and low signal-to-noise in the context of the quantities we want to derive, poses rigorous demands upon the data collected from observation. Further compounding this challenge is that inferences of exoplanet properties are built from forward models, which can include errors due to incomplete or inaccurate assumptions in atmospheric physics and chemistry. The confluence of observational noise and model error makes developing techniques to identify predictive features that are robust to both low s/n and model error increasingly important for exoplanet science. We demonstrate how both issues can be addressed simultaneously by taking advantage of underutilized multivariate information already present in current atmospheric models, including thermodynamic statistics and reaction network structure. To do so, we provide a case study of the prediction of vertical mixing (parameterized as eddy diffusion) in hot Jupiter atmospheres and show how prediction efficacy depends on what model information is used - e.g. chemical species abundances, network statistics, and/or thermodynamic statistics. We also show how the variables with the most predictive power vary with planetary properties such as temperature and metallicity. Our results demonstrate how inferences built on single metrics do not have utility across all possible use cases. We also show how statistical measures derived from network analyses tend to be better predictors when accounting for the possibility of missing data or observational uncertainty. We discuss future directions applying multivariate and network model information as a framework for increasing confidence in inferences aimed at extracting features relevant to exoplanet atmospheres and future applications to the detection of life on terrestrial worlds., Comment: 52 pages (including supplement); 10 figures and 2 tables in main text, 17 figures in supplement

The search for life on exoplanets is one of the grand scientific challenges of our time. The strategy to date has been to find (e.g., through transit surveys like Kepler) Earth-like exoplanets in their stars habitable zone, then use transmission spectroscopy to measure biosignature gases, especially oxygen, in the planets atmospheres (e.g., using JWST, the James Webb Space Telescope). Already there are more such planets than can be observed by JWST, and missions like the Transiting Exoplanet Survey Satellite and others will find more. A better understanding of the geochemical cycles relevant to biosignature gases is needed, to prioritize targets for costly follow-up observations and to help design future missions. We define a Detectability Index to quantify the likelihood that a biosignature gas could be assigned a biological vs. non-biological origin. We apply this index to the case of oxygen gas, O2, on Earth-like planets with varying water contents. We demonstrate that on Earth-like exoplanets with 0.2 weight percent (wt%) water (i.e., no exposed continents) a reduced flux of bioessential phosphorus limits the export of photosynthetically produced atmospheric O2 to levels indistinguishable from geophysical production by photolysis of water plus hydrogen escape. Higher water contents >1wt% that lead to high-pressure ice mantles further slow phosphorus cycling. Paradoxically, the maximum water content allowing use of O2 as a biosignature, 0.2wt%, is consistent with no water based on mass and radius. Thus, the utility of an O2 biosignature likely requires the direct detection of both water and land on a planet.

For the first time in human history, we will soon be able to apply the scientific method to the question "Are We Alone?" The rapid advance of exoplanet discovery, planetary systems science, and telescope technology will soon allow scientists to search for life beyond our Solar System through direct observation of extrasolar planets. This endeavor will occur alongside searches for habitable environments and signs of life within our Solar System. While the searches are thematically related and will inform each other, they will require separate observational techniques. The search for life on exoplanets holds potential through the great diversity of worlds to be explored beyond our Solar System. However, there are also unique challenges related to the relatively limited data this search will obtain on any individual world. This white paper reviews the scientific community's ability to use data from future telescopes to search for life on exoplanets. This material summarizes products from the Exoplanet Biosignatures Workshop Without Walls (EBWWW). The EBWWW was constituted by a series of online and in person activities, with participation from the international exoplanet and astrobiology communities, to assess state of the science and future research needs for the remote detection of life on planets outside our Solar System., Comment: This is a white paper that was submitted to the National Academies of Sciences Study: Astrobiology Science Strategy for the Search for Life in the Universe

In the coming years and decades, advanced space- and ground-based observatories will allow an unprecedented opportunity to probe the atmospheres and surfaces of potentially habitable exoplanets for signatures of life. Life on Earth, through its gaseous products and reflectance and scattering properties, has left its fingerprint on the spectrum of our planet. Aided by the universality of the laws of physics and chemistry, we turn to Earth's biosphere, both in the present and through geologic time, for analog signatures that will aid in the search for life elsewhere. Considering the insights gained from modern and ancient Earth, and the broader array of hypothetical exoplanet possibilities, we have compiled a state-of-the-art overview of our current understanding of potential exoplanet biosignatures including gaseous, surface, and temporal biosignatures. We additionally survey biogenic spectral features that are well-known in the specialist literature but have not yet been robustly vetted in the context of exoplanet biosignatures. We briefly review advances in assessing biosignature plausibility, including novel methods for determining chemical disequilibrium from remotely obtainable data and assessment tools for determining the minimum biomass required for a given atmospheric signature. We focus particularly on advances made since the seminal review by Des Marais et al. (2002). The purpose of this work is not to propose new biosignatures strategies, a goal left to companion papers in this series, but to review the current literature, draw meaningful connections between seemingly disparate areas, and clear the way for a path forward., Comment: Open Access Article. 46 pages, 13 figures