<p> While it is clear that thermodynamics plays a nontrivial role in biological processes, exactly how this affects the macroscopic structuring of living systems is not fully understood. Thus, the objective of this dissertation was to investigate how thermodynamic variables such as exergy, entropy, and information are involved in biological processes such as cellular metabolism, ecological succession, and evolution. To this end, I have used a combination of mathematical modelling, <i>in silico</i> simulation, and both laboratory- and field-based experimentation. </p><p> To begin the dissertation, I review the basic tenets of biological thermodynamics and synthesize them with modern fluctuation theory, information theory, and finite time thermodynamics. In this review, I develop hypotheses concerning how entropy production rate changes across various time scales and exergy inputs. To begin testing these hypotheses I utilized a stochastic, agent-based, mathematical model of ecological evolution, The Tangled Nature Model. This model allows one to observe the dynamics of entropy production over time scales that would not be possible in real biological systems (i.e., 10<sup>6</sup> generations). The results of the model’s simulations demonstrate that the ecological communities generated by the model’s dynamics have increasing entropies, and that this leads to emergent order, organization, and complexity over time. To continue to examine the role of thermodynamics in biological processes I investigated the bioenergetics of marine microbes associated with benthic substrates on coral reefs. By utilizing both mesocosm and <i> in situ</i> experiments I have shown that these microbes change their power output, oxygen uptake, and community structure depending upon their available exergy. </p><p> Overall, the data presented herein demonstrates that ecological structuring and evolutionary change are, at least in part, determined by underlying thermodynamic mechanisms. Recognizing how physical processes affect biological dynamics allows for a more holistic understanding of biology at all scales from biochemistry, to ecological succession, and even long-term evolutionary change.</p><p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10827422 |
| Date | 01 May 2019 |
| Creators | Roach, Ty Noble Frederick |
| Publisher | University of California, San Diego |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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