scholarly journals Using Maximum Entropy Production to Describe Microbial Biogeochemistry Over Time and Space in a Meromictic Pond

2018 ◽  
Vol 6 ◽  
Author(s):  
Joseph J. Vallino ◽  
Julie A. Huber
Keyword(s):  
Entropy Production ◽  
Maximum Entropy ◽  
Time And Space ◽  
Maximum Entropy Production ◽  
Microbial Biogeochemistry ◽  
Over Time

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

2018 ◽  
Author(s):  
Joseph J. Vallino ◽  
Julie A. Huber
Keyword(s):  
Free Energy ◽  
Energy Dissipation ◽  
Metabolic Network ◽  
Entropy Production ◽  
Maximum Entropy ◽  
Reaction Rates ◽  
Field Observations ◽  
Time And Space ◽  
Maximum Entropy Production ◽  
Over Time

AbstractThe 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.

The mechanics of granitoid systems and maximum entropy production rates

2010 ◽  
Vol 368 (1910) ◽  
pp. 53-93 ◽  
Author(s):  
Bruce E. Hobbs ◽  
Alison Ord
Keyword(s):  
Entropy Production ◽  
Maximum Entropy ◽  
Melt Inclusions ◽  
Selection Process ◽  
Finite Thickness ◽  
Control Valve ◽  
Entropy Production Rate ◽  
Constitutive Behaviour ◽  
Maximum Entropy Production ◽  
Physical Height

A model for the formation of granitoid systems is developed involving melt production spatially below a rising isotherm that defines melt initiation. Production of the melt volumes necessary to form granitoid complexes within 10 4 –10 7 years demands control of the isotherm velocity by melt advection. This velocity is one control on the melt flux generated spatially just above the melt isotherm, which is the control valve for the behaviour of the complete granitoid system. Melt transport occurs in conduits initiated as sheets or tubes comprising melt inclusions arising from Gurson–Tvergaard constitutive behaviour. Such conduits appear as leucosomes parallel to lineations and foliations, and ductile and brittle dykes. The melt flux generated at the melt isotherm controls the position of the melt solidus isotherm and hence the physical height of the Transport/Emplacement Zone. A conduit width-selection process, driven by changes in melt viscosity and constitutive behaviour, operates within the Transport Zone to progressively increase the width of apertures upwards. Melt can also be driven horizontally by gradients in topography; these horizontal fluxes can be similar in magnitude to vertical fluxes. Fluxes induced by deformation can compete with both buoyancy and topographic-driven flow over all length scales and results locally in transient ‘ponds’ of melt. Pluton emplacement is controlled by the transition in constitutive behaviour of the melt/magma from elastic–viscous at high temperatures to elastic–plastic–viscous approaching the melt solidus enabling finite thickness plutons to develop. The system involves coupled feedback processes that grow at the expense of heat supplied to the system and compete with melt advection. The result is that limits are placed on the size and time scale of the system. Optimal characteristics of the system coincide with a state of maximum entropy production rate.

scholarly journals Relaxation Processes and the Maximum Entropy Production Principle

Entropy ◽  
2010 ◽  
Vol 12 (3) ◽  
pp. 473-479 ◽  
Author(s):  
Paško Županović ◽  
Srećko Botrić ◽  
Davor Juretić ◽  
Domagoj Kuić
Keyword(s):  
Entropy Production ◽  
Maximum Entropy ◽  
Relaxation Processes ◽  
Maximum Entropy Production

scholarly journals A Maximum Entropy Production Evaporation – Transpiration Product for Australia

2019 ◽  
Author(s):  
Olanrewaju Abiodun ◽  
Okke Batelaan ◽  
Huade Guan ◽  
Jingfeng Wang
Keyword(s):  
Entropy Production ◽  
Maximum Entropy ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Production Model ◽  
Model Parameters ◽  
Drought Period ◽  
Maximum Entropy Production ◽  
Millennium Drought ◽  
Mean Square Errors

Abstract. The aim of this research is to develop evaporation and transpiration products for Australia based on the maximum entropy production model (MEP). We introduce a method into the MEP algorithm of estimating the required model parameters over the entire Australia through the use of pedotransfer function, soil properties and remotely sensed soil moisture data. Our algorithm calculates the evaporation and transpiration over Australia on daily timescales at the 5 km2 resolution for 2003–2013. The MEP evapotranspiration (ET) estimates are validated using observed ET data from 20 Eddy Covariance (EC) flux towers across 8 land cover types in Australia. We also compare the MEP ET at the EC flux towers with two other ET products over Australia; MOD16 and AWRA-L products. The MEP model outperforms the MOD16 and AWRA-L across the 20 EC flux sites, with average root mean square errors (RMSE), 8.21, 9.87 and 9.22 mm/8 days respectively. The average mean absolute error (MAE) for the MEP, MOD16 and AWRA-L are 6.21, 7.29 and 6.52 mm/8 days, the average correlations are 0.64, 0.57 and 0.61, respectively. The percentage Bias of the MEP ET was within 20 % of the observed ET at 12 of the 20 EC flux sites while the MOD16 and AWRA-L ET were within 20 % of the observed ET at 4 and 10 sites respectively. Our analysis shows that evaporation and transpiration contribute 38 % and 62 %, respectively, to the total ET across the study period which includes a significant part of the “millennium drought” period (2003–2009) in Australia. The data (Abiodun et al., 2019) is available at https://doi.org/10.25901/5ce795d313db8.

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