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Using maximum entropy production to describe microbial biogeochemistry over time and space in a meromictic pond

View ORCID ProfileJoseph J. Vallino, View ORCID ProfileJulie A. Huber
doi: https://doi.org/10.1101/266346
Joseph J. Vallino
1Marine Biological Laboratory, Ecosystems Center, Woods Hole, MA, US
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  • For correspondence: jvallino@mbl.edu
Julie A. Huber
2Woods Hole Oceanographic Institution, Marine Chemistry & Geochemistry, Woods Hole, MA, US
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Abstract

The maximum entropy production (MEP) conjecture posits that systems with many degrees of freedom will likely organize to maximize the rate of free energy dissipation. Previous work indicates that biological systems can outcompete abiotic systems by maximizing free energy dissipation over time by utilizing temporal strategies acquired and refined by evolution, and over space via cooperation. In this study, we develop an MEP model to describe biogeochemistry observed in Siders Pond, a phosphate limited meromictic system located in Falmouth, MA that exhibits steep chemical gradients due to density-driven stratification that supports anaerobic photosynthesis as well as microbial communities that catalyze redox cycles involving O, N, S, Fe and Mn. The MEP model uses a metabolic network to represent microbial redox reactions, where biomass allocation and reaction rates are determined by solving an optimization problem that maximizes entropy production over time and a 1D vertical profile constrained by an advection-dispersion-reaction model. We introduce a new approach for modeling phototrophy and explicitly represent aerobic photoautotrophs, anoxygenic photoheterotrophs and anaerobic photoautotrophs. The metabolic network also includes reactions for heterotrophic bacteria, sulfate reducing bacteria, sulfide oxidizing bacteria and aerobic and anaerobic grazers. Model results were compared to observations of biogeochemical constituents collected over a 24 hour period at 8 depths at a single 15 m deep station in Siders Pond. Maximizing entropy production over long (3 d) intervals produced results more similar to field observations than short (0.25 d) interval optimizations, which support the importance of temporal strategies for maximizing entropy production over time. Furthermore, we found that entropy production must be maximized locally instead of globally where energy potentials are degraded quickly by abiotic processes, such as light absorption by water. This combination of field observations with modeling results show that microbial systems in nature can be accurately described by the maximum entropy production conjecture applied over time and space.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted February 16, 2018.
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Using maximum entropy production to describe microbial biogeochemistry over time and space in a meromictic pond
Joseph J. Vallino, Julie A. Huber
bioRxiv 266346; doi: https://doi.org/10.1101/266346
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Using maximum entropy production to describe microbial biogeochemistry over time and space in a meromictic pond
Joseph J. Vallino, Julie A. Huber
bioRxiv 266346; doi: https://doi.org/10.1101/266346

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