Authors:
(1) Harrison B. Smith, Earth-Life Science Institute, Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, Japan, and Blue Marble Space Institute of Science, Seattle, Washington, USA (hbs@elsi.jp);
(2) Lana Sinapayen, Sony Computer Science Laboratories, Kyoto, Japan and National Institute for Basic Biology, Okazaki, Japan (lana.sinapayen@gmail.com). Table of Links Abstract and 1. Introduction 2. Methods 2.1. Modeling Panspermia and Terraformation 2.2. Identifying the Presence of Terraformed Planets and 2.3. Software and Availability 3. Results 3.1. Panspermia can increase the correlation between planets’ compositions and positions 3.2. Likely terraformed planets can be identified from clustering 4. Summary and Discussion 5. Acknowledgements and References APPENDIX A. Appendix ABSTRACT A fundamental goal of astrobiology is to detect life outside of Earth. This proves to be an exceptional challenge outside of our solar system, where strong assumptions must be made about how life would manifest and interact with its planet. Such assumptions are required because of the lack of a consensus theory of living systems, or an understanding of the possible extent of planetary dynamics. Here we explore a model of life spreading between planetary systems via panspermia and terraformation. Our model shows that as life propagates across the galaxy, correlations emerge between planetary characteristics and location, and can function as a population-scale agnostic biosignature. This biosignature is agnostic because it is independent of strong assumptions about any particular instantiation of life or planetary characteristic—by focusing on a specific hypothesis of what life may do, rather than what life may be. By clustering planets based on their observed characteristics, and examining the spatial extent of these clusters, we demonstrate (and evaluate) a way to prioritize specific planets for further observation—based on their potential for containing life. We consider obstacles that must be overcome to practically implement our approach, including identifying specific ways in which better understanding astrophysical and planetary processes would improve our ability to detect life. Finally, we consider how this model leads us to think in novel ways about hierarchies of life and planetary scale replication. 1. INTRODUCTION It is difficult to attribute, with certainty, observable features of exoplanets to extraterrestrial life (Moore et al. 2017; Tasker et al. 2017; Green et al. 2021; Cockell 2022; Lenardic et al. 2022, 2023; Smith & Mathis 2023). This is exemplified by the insufficient (and often ill-defined) working definitions of life that are used to interpret observational data, and by the growing number of false positives for traditional biosignatures (Cleland & Chyba 2002; Benner 2010; Cleland 2012; Mix 2015; Schwieterman et al. 2016; Bich & Green 2018; Harman & Domagal-Goldman 2018; Schwieterman et al. 2018; Mariscal & Doolittle 2020; Janin 2021; Vickers et al. 2023). One way in which the community aims to overcome the problems with defining life is to develop “agnostic” biosignatures—detecting signs of life that are not particular to Earth-life or any other hypothetical instances of life (Marshall et al. 2021; Smith et al. 2021). Yet, agnostic biosignature proposals are sometimes built on restricted concepts of habitability (e.g., requiring rocky, watery planets), or simple anomaly detection (i.e., without using a working definition of life) (Kinney & Kempes 2022; Cleaves et al. 2023). A proposed remedy for the issues surrounding traditional biosignatures has been to use so-called “statistical” biosignatures—relying on integrating multiple lines of evidence to increase confidence in a discovery, or generating ensembles of data to better constrain the probabilities P(data|abiotic) and P(data|life) (in Bayesian speak). (Lin & Loeb 2015; Catling et al. 2018; Walker et al. 2018; Affholder et al. 2021; Bixel & Apai 2021). However, such statistical biosignatures often rely on assumptions about the prior probability of abiogenesis, or on the existence of unambiguous biosignatures for single planets. These approaches are often trying to solve more specific issues, like estimating the frequency of Earth-like life, the frequency of planets originating from panspermia compared to abiogenesis, or finding evidence of a specific metabolic process (Lin & Loeb 2015; Walker et al. 2018; Affholder et al. 2021; Checlair et al. 2021; Kovacevic 2022). Here we ask, can we detect the presence of life if we postulate that life is spreading between and terraforming planets?[1] This is an astrobiological “hinge proposition” of the kind described by Kinney & Kempes as necessary to make sure “that the door of astrobiology can turn properly” under conditions of deep uncertainty (Kinney & Kempes 2022). It is also somewhat the converse of a question posed in other panspermia related work: Can the prevalence of panspermia be constrained when assuming we have a way to detect life? (Lin & Loeb 2015; Balbi & Grimaldi 2020; Grimaldi et al. 2021; Lingam et al. 2021; Kovacevic 2022). In fact, our postulates (of terraformation and panspermia) are less peculiar than they might at first seem: while existing work doesn’t always explicitly refer to terraformation, it must be assumed—in the sense that the mere presence of life stable at geological timescales would create environmental feedback with a planet, and if that life is to be detectable it must modify a planet’s observables. Such planetary modification by life is a well documented phenomena—e.g., the rise of O2 during the great oxygenation event (Lynas et al. 2021), or the rise of CO2 from human industrial activity (Olejarz et al. 2021)). The feasibility of interstellar lithopanspermia (nonintelligent exchange of material via rocks) has been discussed at length in other work (see e.g. CarrollNellenback et al. (2019); Grimaldi et al. (2021); Gobat (2021); Totani (2023) and references therein). Crucially, it appears plausible, although likelihoods and rates vary considerably depending on assumptions on timing, amount of material ejected, organismal hardiness, and capture rates, among other features. Arguments have likewise been made for the feasibility of directed interstellar panspermia by intelligent life (Wright et al. 2014). Ultimately, our postulates of panspermia and terraformation are merely well understood hallmarks of life (proliferation via replication, and adaptation with bi-directional environmental feedback), escalated to the planetary scale, and executed on an interstellar scale. We use a simulated model to show that statistical correlations between the spatial distribution of planets around different host stars, and their observable characteristics would itself be evidence of life, without the need for a separate biosignature that could reliably detect life on any given planet in isolation. The agnosticism of this biosignature is inseparable from its emergence at the scale of a population of planets—singleton planetary anomalies might be explained away by unknown geochemical processes, or targeted simply because they are anomalous (without a clear hypothesis of why they should be explained by life). Hypothesizing that life spreads via panspermia and terraformation allows us to search for biosignatures while forgoing any strong assumptions about not only the peculiarities of life (e.g., its metabolism) and planetary habitability (e.g., requiring surface liquid water) (Gobat 2021), but even the potential breadth of structure and chemical complexity underpinning living systems (Sol´e & Munteanu 2004; Kim et al. 2019; Bartlett et al. 2022; Wong et al. 2023). We first describe our model (Sec. 2.1) and approach for statistically identifying the presence of terraformed planets (Sec. 2.2). We show that evolving our model in time can increase the correlation between planets’ compositions and positions (Sec. 3.1). To identify specific planets likely to have been terraformed, we cluster planets by observable characteristics, then select clusters which are spatially localized and cause a decrease in correlation when removed (Secs. 2.2.3, 2.2.4 ). We evaluate these clusters by calculating how well they correctly classify terraformed planets as being terraformed, and non-terraformed planets as being non-terraformed (Sec. 3.2). Finally, we discuss how our results might change due to theoretical and observational constraints, identify specific ways in which better understanding astrophysical and planetary processes could improve life detection, and speculate on the concept of life at the scale of populations of planets. This paper is available on arxiv under CC BY-NC-ND 4.0 Deed license. [1] Here, “life spreading” refers to interstellar panspermia, and “terraforming planets” refers to modifying observable characteristics of planets. Authors: (1) Harrison B. Smith, Earth-Life Science Institute, Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, Japan, and Blue Marble Space Institute of Science, Seattle, Washington, USA (hbs@elsi.jp); (2) Lana Sinapayen, Sony Computer Science Laboratories, Kyoto, Japan and National Institute for Basic Biology, Okazaki, Japan (lana.sinapayen@gmail.com). Authors: Authors: (1) Harrison B. Smith, Earth-Life Science Institute, Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, Japan, and Blue Marble Space Institute of Science, Seattle, Washington, USA ( hbs@elsi.jp ); hbs@elsi.jp (2) Lana Sinapayen, Sony Computer Science Laboratories, Kyoto, Japan and National Institute for Basic Biology, Okazaki, Japan ( lana.sinapayen@gmail.com ). lana.sinapayen@gmail.com Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2. Methods 2.1. Modeling Panspermia and Terraformation 2.1. Modeling Panspermia and Terraformation 2.2. Identifying the Presence of Terraformed Planets and 2.3. Software and Availability 2.2. Identifying the Presence of Terraformed Planets and 2.3. Software and Availability 3. Results 3.1. Panspermia can increase the correlation between planets’ compositions and positions 3.1. Panspermia can increase the correlation between planets’ compositions and positions 3.2. Likely terraformed planets can be identified from clustering 3.2. Likely terraformed planets can be identified from clustering 4. Summary and Discussion 4. Summary and Discussion 5. Acknowledgements and References 5. Acknowledgements and References APPENDIX APPENDIX A. Appendix A. Appendix ABSTRACT A fundamental goal of astrobiology is to detect life outside of Earth. This proves to be an exceptional challenge outside of our solar system, where strong assumptions must be made about how life would manifest and interact with its planet. Such assumptions are required because of the lack of a consensus theory of living systems, or an understanding of the possible extent of planetary dynamics. Here we explore a model of life spreading between planetary systems via panspermia and terraformation. Our model shows that as life propagates across the galaxy, correlations emerge between planetary characteristics and location, and can function as a population-scale agnostic biosignature. This biosignature is agnostic because it is independent of strong assumptions about any particular instantiation of life or planetary characteristic—by focusing on a specific hypothesis of what life may do, rather than what life may be. By clustering planets based on their observed characteristics, and examining the spatial extent of these clusters, we demonstrate (and evaluate) a way to prioritize specific planets for further observation—based on their potential for containing life. We consider obstacles that must be overcome to practically implement our approach, including identifying specific ways in which better understanding astrophysical and planetary processes would improve our ability to detect life. Finally, we consider how this model leads us to think in novel ways about hierarchies of life and planetary scale replication. 1. INTRODUCTION It is difficult to attribute, with certainty, observable features of exoplanets to extraterrestrial life (Moore et al. 2017; Tasker et al. 2017; Green et al. 2021; Cockell 2022; Lenardic et al. 2022, 2023; Smith & Mathis 2023). This is exemplified by the insufficient (and often ill-defined) working definitions of life that are used to interpret observational data, and by the growing number of false positives for traditional biosignatures (Cleland & Chyba 2002; Benner 2010; Cleland 2012; Mix 2015; Schwieterman et al. 2016; Bich & Green 2018; Harman & Domagal-Goldman 2018; Schwieterman et al. 2018; Mariscal & Doolittle 2020; Janin 2021; Vickers et al. 2023). One way in which the community aims to overcome the problems with defining life is to develop “agnostic” biosignatures—detecting signs of life that are not particular to Earth-life or any other hypothetical instances of life (Marshall et al. 2021; Smith et al. 2021). Yet, agnostic biosignature proposals are sometimes built on restricted concepts of habitability (e.g., requiring rocky, watery planets), or simple anomaly detection (i.e., without using a working definition of life) (Kinney & Kempes 2022; Cleaves et al. 2023). A proposed remedy for the issues surrounding traditional biosignatures has been to use so-called “statistical” biosignatures—relying on integrating multiple lines of evidence to increase confidence in a discovery, or generating ensembles of data to better constrain the probabilities P(data|abiotic) and P(data|life) (in Bayesian speak). (Lin & Loeb 2015; Catling et al. 2018; Walker et al. 2018; Affholder et al. 2021; Bixel & Apai 2021). However, such statistical biosignatures often rely on assumptions about the prior probability of abiogenesis, or on the existence of unambiguous biosignatures for single planets. These approaches are often trying to solve more specific issues, like estimating the frequency of Earth-like life, the frequency of planets originating from panspermia compared to abiogenesis, or finding evidence of a specific metabolic process (Lin & Loeb 2015; Walker et al. 2018; Affholder et al. 2021; Checlair et al. 2021; Kovacevic 2022). Here we ask, can we detect the presence of life if we postulate that life is spreading between and terraforming planets?[1] This is an astrobiological “hinge proposition” of the kind described by Kinney & Kempes as necessary to make sure “that the door of astrobiology can turn properly” under conditions of deep uncertainty (Kinney & Kempes 2022). It is also somewhat the converse of a question posed in other panspermia related work: Can the prevalence of panspermia be constrained when assuming we have a way to detect life? (Lin & Loeb 2015; Balbi & Grimaldi 2020; Grimaldi et al. 2021; Lingam et al. 2021; Kovacevic 2022). In fact, our postulates (of terraformation and panspermia) are less peculiar than they might at first seem: while existing work doesn’t always explicitly refer to terraformation, it must be assumed—in the sense that the mere presence of life stable at geological timescales would create environmental feedback with a planet, and if that life is to be detectable it must modify a planet’s observables. Such planetary modification by life is a well documented phenomena—e.g., the rise of O2 during the great oxygenation event (Lynas et al. 2021), or the rise of CO2 from human industrial activity (Olejarz et al. 2021)). The feasibility of interstellar lithopanspermia (nonintelligent exchange of material via rocks) has been discussed at length in other work (see e.g. CarrollNellenback et al. (2019); Grimaldi et al. (2021); Gobat (2021); Totani (2023) and references therein). Crucially, it appears plausible, although likelihoods and rates vary considerably depending on assumptions on timing, amount of material ejected, organismal hardiness, and capture rates, among other features. Arguments have likewise been made for the feasibility of directed interstellar panspermia by intelligent life (Wright et al. 2014). Ultimately, our postulates of panspermia and terraformation are merely well understood hallmarks of life (proliferation via replication, and adaptation with bi-directional environmental feedback), escalated to the planetary scale, and executed on an interstellar scale. We use a simulated model to show that statistical correlations between the spatial distribution of planets around different host stars, and their observable characteristics would itself be evidence of life, without the need for a separate biosignature that could reliably detect life on any given planet in isolation. The agnosticism of this biosignature is inseparable from its emergence at the scale of a population of planets—singleton planetary anomalies might be explained away by unknown geochemical processes, or targeted simply because they are anomalous (without a clear hypothesis of why they should be explained by life). Hypothesizing that life spreads via panspermia and terraformation allows us to search for biosignatures while forgoing any strong assumptions about not only the peculiarities of life (e.g., its metabolism) and planetary habitability (e.g., requiring surface liquid water) (Gobat 2021), but even the potential breadth of structure and chemical complexity underpinning living systems (Sol´e & Munteanu 2004; Kim et al. 2019; Bartlett et al. 2022; Wong et al. 2023). We first describe our model (Sec. 2.1) and approach for statistically identifying the presence of terraformed planets (Sec. 2.2). We show that evolving our model in time can increase the correlation between planets’ compositions and positions (Sec. 3.1). To identify specific planets likely to have been terraformed, we cluster planets by observable characteristics, then select clusters which are spatially localized and cause a decrease in correlation when removed (Secs. 2.2.3, 2.2.4 ). We evaluate these clusters by calculating how well they correctly classify terraformed planets as being terraformed, and non-terraformed planets as being non-terraformed (Sec. 3.2). Finally, we discuss how our results might change due to theoretical and observational constraints, identify specific ways in which better understanding astrophysical and planetary processes could improve life detection, and speculate on the concept of life at the scale of populations of planets. This paper is available on arxiv under CC BY-NC-ND 4.0 Deed license. This paper is available on arxiv under CC BY-NC-ND 4.0 Deed license. available on arxiv [1] Here, “life spreading” refers to interstellar panspermia, and “terraforming planets” refers to modifying observable characteristics of planets.

Part of HackerNoon's growing list of open-source research papers, promoting free access to academic material.

A Biosignature Based on Modeling Panspermia and Terraformation: Abstract and Introduction

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

A Biosignature Based on Modeling Panspermia and Terraformation: Appendix

A Biosignature Based on Modeling Panspermia and Terraformation: Modeling

A Biosignature Based on Modeling Panspermia and Terraformation: Identifying Terraformed Planets

A Biosignature Based on Modeling Panspermia and Terraformation: Correlation

A Biosignature Based on Modeling Panspermia and Terraformation: Identification

A Biosignature Based on Modeling Panspermia and Terraformation: Summary and Discussion

A Biosignature Based on Modeling Panspermia and Terraformation: Appendix

A Biosignature Based on Modeling Panspermia and Terraformation: Modeling

A Biosignature Based on Modeling Panspermia and Terraformation: Identifying Terraformed Planets

A Biosignature Based on Modeling Panspermia and Terraformation: Correlation

A Biosignature Based on Modeling Panspermia and Terraformation: Identification

A Biosignature Based on Modeling Panspermia and Terraformation: Summary and Discussion

Light-Mode

Classic

Newspaper

Minty

Dark-Mode

Neon Noir

Minty

HN StartUps