Matching Items (7)
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- All Subjects: astrobiology
- All Subjects: stellar evolution
- Creators: Walker, Sara I
Description
The origin of Life on Earth is the greatest unsolved mystery in the history of science. In spite of progress in almost every scientific endeavor, we still have no clear theory, model, or framework to understand the processes that led to the emergence of life on Earth. Understanding such a processes would provide key insights into astrobiology, planetary science, geochemistry, evolutionary biology, physics, and philosophy. To date, most research on the origin of life has focused on characterizing and synthesizing the molecular building blocks of living systems. This bottom-up approach assumes that living systems are characterized by their component parts, however many of the essential features of life are system level properties which only manifest in the collective behavior of many components. In order to make progress towards solving the origin of life new modeling techniques are needed. In this dissertation I review historical approaches to modeling the origin of life. I proceed to elaborate on new approaches to understanding biology that are derived from statistical physics and prioritize the collective properties of living systems rather than the component parts. In order to study these collective properties of living systems, I develop computational models of chemical systems. Using these computational models I characterize several system level processes which have important implications for understanding the origin of life on Earth. First, I investigate a model of molecular replicators and demonstrate the existence of a phase transition which occurs dynamically in replicating systems. I characterize the properties of the phase transition and argue that living systems can be understood as a non-equilibrium state of matter with unique dynamical properties. Then I develop a model of molecular assembly based on a ribonucleic acid (RNA) system, which has been characterized in laboratory experiments. Using this model I demonstrate how the energetic properties of hydrogen bonding dictate the population level dynamics of that RNA system. Finally I return to a model of replication in which replicators are strongly coupled to their environment. I demonstrate that this dynamic coupling results in qualitatively different evolutionary dynamics than those expected in static environments. A key difference is that when environmental coupling is included, evolutionary processes do not select a single replicating species but rather a dynamically stable community which consists of many species. Finally, I conclude with a discussion of how these computational models can inform future research on the origins of life.
ContributorsMathis, Cole (Nicholas) (Author) / Walker, Sara I (Thesis advisor) / Davies, Paul CW (Committee member) / Chamberlin, Ralph V (Committee member) / Lachmann, Michael (Committee member) / Arizona State University (Publisher)
Created2018
Description
Biochemical reactions underlie all living processes. Their complex web of interactions is difficult to fully capture and quantify with simple mathematical objects. Applying network science to biology has advanced our understanding of the metabolisms of individual organisms and the organization of ecosystems, but has scarcely been applied to life at a planetary scale. To characterize planetary-scale biochemistry, I constructed biochemical networks using global databases of annotated genomes and metagenomes, and biochemical reactions. I uncover scaling laws governing biochemical diversity and network structure shared across levels of organization from individuals to ecosystems, to the biosphere as a whole. Comparing real biochemical reaction networks to random reaction networks reveals the observed biological scaling is not a product of chemistry alone, but instead emerges due to the particular structure of selected reactions commonly participating in living processes. I perform distinguishability tests across properties of individual and ecosystem-level biochemical networks to determine whether or not they share common structure, indicative of common generative mechanisms across levels. My results indicate there is no sharp transition in the organization of biochemistry across distinct levels of the biological hierarchy—a result that holds across different network projections.
Finally, I leverage these large biochemical datasets, in conjunction with planetary observations and computational tools, to provide a methodological foundation for the quantitative assessment of biology’s viability amongst other geospheres. Investigating a case study of alkaliphilic prokaryotes in the context of Enceladus, I find that the chemical compounds observed on Enceladus thus far would be insufficient to allow even these extremophiles to produce the compounds necessary to sustain a viable metabolism. The environmental precursors required by these organisms provides a reference for the compounds which should be prioritized for detection in future planetary exploration missions. The results of this framework have further consequences in the context of planetary protection, and hint that forward contamination may prove infeasible without meticulous intent. Taken together these results point to a deeper level of organization in biochemical networks than what has been understood so far, and suggests the existence of common organizing principles operating across different levels of biology and planetary chemistry.
Finally, I leverage these large biochemical datasets, in conjunction with planetary observations and computational tools, to provide a methodological foundation for the quantitative assessment of biology’s viability amongst other geospheres. Investigating a case study of alkaliphilic prokaryotes in the context of Enceladus, I find that the chemical compounds observed on Enceladus thus far would be insufficient to allow even these extremophiles to produce the compounds necessary to sustain a viable metabolism. The environmental precursors required by these organisms provides a reference for the compounds which should be prioritized for detection in future planetary exploration missions. The results of this framework have further consequences in the context of planetary protection, and hint that forward contamination may prove infeasible without meticulous intent. Taken together these results point to a deeper level of organization in biochemical networks than what has been understood so far, and suggests the existence of common organizing principles operating across different levels of biology and planetary chemistry.
ContributorsSmith, Harrison Brodsky (Author) / Walker, Sara I (Thesis advisor) / Anbar, Ariel D (Committee member) / Line, Michael R (Committee member) / Okie, Jordan G. (Committee member) / Romaniello, Stephen J. (Committee member) / Arizona State University (Publisher)
Created2018
Description
Stellar mass loss has a high impact on the overall evolution of a star. The amount<br/>of mass lost during a star’s lifetime dictates which remnant will be left behind and how<br/>the circumstellar environment will be affected. Several rates of mass loss have been<br/>proposed for use in stellar evolution codes, yielding discrepant results from codes using<br/>different rates. In this paper, I compare the effect of varying the mass loss rate in the<br/>stellar evolution code TYCHO on the initial-final mass relation. I computed four sets of<br/>models with varying mass loss rates and metallicities. Due to a large number of models<br/>reaching the luminous blue variable stage, only the two lower metallicity groups were<br/>considered. Their mass loss was analyzed using Python. Luminosity, temperature, and<br/>radius were also compared. The initial-final mass relation plots showed that in the 1/10<br/>solar metallicity case, reducing the mass loss rate tended to increase the dependence of final mass on initial mass. The limited nature of these results implies a need for further study into the effects of using different mass loss rates in the code TYCHO.
ContributorsAuchterlonie, Lauren (Author) / Young, Patrick (Thesis director) / Shkolnik, Evgenya (Committee member) / Starrfield, Sumner (Committee member) / School of Earth and Space Exploration (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
I present a catalog of 1,794 stellar evolution models for solar-type and low-mass stars, which is intended to help characterize real host-stars of interest during the ongoing search for potentially habitable exoplanets. The main grid is composed of 904 tracks, for 0.5-1.2 M_sol at scaled metallicity values of 0.1-1.5 Z_sol and specific elemental abundance ratio values of 0.44-2.28 O/Fe_sol, 0.58-1.72 C/Fe_sol, 0.54-1.84 Mg/Fe_sol, and 0.5-2.0 Ne/Fe_sol. The catalog includes a small grid of late stage evolutionary tracks (25 models), as well as a grid of M-dwarf stars for 0.1-0.45 M_sol (856 models). The time-dependent habitable zone evolution is calculated for each track, and is strongly dependent on stellar mass, effective temperature, and luminosity parameterizations. I have also developed a subroutine for the stellar evolution code TYCHO that implements a minimalist coupled model for estimating changes in the stellar X-ray luminosity, mass loss, rotational velocity, and magnetic activity over time; to test the utility of the updated code, I created a small grid (9 models) for solar-mass stars, with variations in rotational velocity and scaled metallicity. Including this kind of information in the catalog will ultimately allow for a more robust consideration of the long-term conditions that orbiting planets may experience.
In order to gauge the true habitability potential of a given planetary system, it is extremely important to characterize the host-star's mass, specific chemical composition, and thus the timescale over which the star will evolve. It is also necessary to assess the likelihood that a planet found in the "instantaneous" habitable zone has actually had sufficient time to become "detectably" habitable. This catalog provides accurate stellar evolution predictions for a large collection of theoretical host-stars; the models are of particular utility in that they represent the real variation in stellar parameters that have been observed in nearby stars.
In order to gauge the true habitability potential of a given planetary system, it is extremely important to characterize the host-star's mass, specific chemical composition, and thus the timescale over which the star will evolve. It is also necessary to assess the likelihood that a planet found in the "instantaneous" habitable zone has actually had sufficient time to become "detectably" habitable. This catalog provides accurate stellar evolution predictions for a large collection of theoretical host-stars; the models are of particular utility in that they represent the real variation in stellar parameters that have been observed in nearby stars.
ContributorsTruitt, Amanda Rosendall (Author) / Young, Patrick (Thesis advisor) / Anbar, Ariel (Committee member) / Desch, Steven (Committee member) / Patience, Jennifer (Committee member) / Shkolnik, Evgenya (Committee member) / Arizona State University (Publisher)
Created2017
Description
Universal biology is an important astrobiological concept, specifically for the search for life beyond Earth. Over 1.2 million species have been identified on Earth, yet all life partakes in certain processes, such as homeostasis and replication. Furthermore, several aspects of biochemistry on Earth are thought to be universal, such as the use of organic macromolecules like proteins and nucleic acids. The presence of many biochemical features in empirical data, however, has never been thoroughly investigated. Moreover, the ability to generalize universal features of Earth biology to other worlds suffers from the epistemic problem of induction. Systems biology approaches offer means to quantify abstract patterns in living systems which can more readily be extended beyond Earth’s familiar planetary context. In particular, scaling laws, which characterize how a system responds to changes in size, have met with prior success in investigating universal biology.
This thesis rigorously tests the hypothesis that biochemistry is universal across life on Earth. The study collects enzyme data for annotated archaeal, bacterial, and eukaryotic genomes, in addition to metagenomes. This approach allows one to quantitatively define a biochemical system and sample across known biochemical diversity, while simultaneously exploring enzyme class scaling at both the level of both individual organisms and ecosystems. Using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the Joint Genome Institute’s Integrated Microbial Genomes and Microbiomes (JGI IMG/M) database, this thesis performs the largest comparative analysis of microbial enzyme content and biochemistry to date. In doing so, this thesis quantitatively explores the distribution of enzyme classes on Earth and adds constraints to notions of universal biochemistry on Earth.
This thesis rigorously tests the hypothesis that biochemistry is universal across life on Earth. The study collects enzyme data for annotated archaeal, bacterial, and eukaryotic genomes, in addition to metagenomes. This approach allows one to quantitatively define a biochemical system and sample across known biochemical diversity, while simultaneously exploring enzyme class scaling at both the level of both individual organisms and ecosystems. Using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the Joint Genome Institute’s Integrated Microbial Genomes and Microbiomes (JGI IMG/M) database, this thesis performs the largest comparative analysis of microbial enzyme content and biochemistry to date. In doing so, this thesis quantitatively explores the distribution of enzyme classes on Earth and adds constraints to notions of universal biochemistry on Earth.
ContributorsGagler, Dylan (Author) / Walker, Sara I (Thesis advisor) / Kempes, Chris (Committee member) / Trembath-Reichert, Elizabeth (Committee member) / Arizona State University (Publisher)
Created2020
Description
Astrobiology is premised on the idea that life beyond Earth can exist. Yet, everything known about life is derivative from life on Earth. To understand life beyond Earth, then, requires a definition of life that is abstracted beyond a particular geophysical context. To do this requires a formal understanding of the physical mechanisms by which matter is animated into life. At current, such descriptions are completely lacking for the emergence of life, but do exist for the emergence of consciousness. Namely, contemporary neuroscience offers definitions for universal physical processes that are in one-to-one correspondence with conscious experience. Since consciousness is a sufficient condition for life, these universal definitions of consciousness offer an interesting way forward in terms of the search for life in the cosmos. In this work, I systematically examine Integrated Information Theory (IIT), a well-established theory of consciousness, with the aim of applying it in both biological and astrobiological settings. Surprisingly, I discover major problems with Integrated Information Theory on two fronts: mathematical and epistemological. On the mathematical side, I show how degeneracies buried deep within the theory render it mathematically ill-defined, while on the epistemological side, I prove that the postulates of IIT are scientifically unfalsifiable and inherently metaphysical. Given that IIT is the preeminent theory of consciousness in modern neuroscience, these results have far-reaching implications in this field. In addition, I show that the epistemic issues of falsifiability that hamstring IIT apply quite generally to all contemporary theories of consciousness, which suggests a major reframing of the problem is necessary. The problems that I reveal in regard to defining consciousness offer an important parallel in regard to defining life, as both fields seek to define their topic of study in absence of an existing theoretical framework. To avoid metaphysical problems related to falsifiability, universal theories of both life and consciousness must be framed with respect to independent empirical observations that can be used to benchmark predictions from the theory. In this regard, I argue that the epistemic debate over scientific theories of consciousness should be used to inform the discussion regarding theoretical definitions of life.
ContributorsHanson, Jake (Author) / Walker, Sara I (Thesis advisor) / Desch, Steven J (Committee member) / Pavlic, Theodore P (Committee member) / Groppi, Christopher E (Committee member) / Shim, Sang-Heon (Committee member) / Arizona State University (Publisher)
Created2021
Description
With the ability to observe the atmospheres of terrestrial exoplanets via transit spectroscopy on the near-term horizon, the possibility of atmospheric biosignatures has received considerable attention in astrobiology. While traditionally exoplanet scientists looking for life focused on biologically relevant trace gases such as O2 and CH4, this approach has raised the spectre of false positives. Therefore, to address these shortcomings, a new set of methods is required to provide higher confidence in life detection. One possible approach is measuring the topology of atmospheric chemical reaction networks (CRNs). To investigate and assess this approach, the ability of network-theoretic metrics to distinguish the distance from thermochemical equilibrium in the atmosphere of hot jupiters was tested. After modeling the atmospheres of hot jupiters over a range of initial conditions using the VULCAN modeling package, atmospheric CRNs were constructed from the converged models and their topology measured using the Python package NetworkX. I found that network metrics were able to predict the distance from thermochemical equilibrium better than atmospheric species abundances alone. Building on this success, I modeled 30,000 terrestrial worlds. These models divided into two categories: Anoxic Archean Earth-like planets that varied in terms of CH4 surface flux (modeled as either biotic or abiotic in origin), and modern Earth-like planets with and without a surface flux of CCl2F2 (to represent the presence of industrial civilizations). I constructed atmospheric CRNs from the converged models, and analyzed their topology. I found that network metrics could distinguish between atmospheres with and without the presence of life or technology. In particular, mean degree and average shortest path length consistently performed better at distinguishing between abiotic and biotic Archean-like atmospheres than CH4 abundance.
ContributorsFisher, Theresa Mason (Author) / Walker, Sara I (Thesis advisor) / Hartnett, Hilairy (Committee member) / Line, Michael (Committee member) / Shkolnik, Evgenya (Committee member) / Okie, Jordan (Committee member) / Arizona State University (Publisher)
Created2023