Ecosystem biogeochemistry considered as a distributed metabolic network ordered by maximum entropy production

Abstract

We examine the application of the maximum entropy production principle for describing ecosystem biogeochemistry. Since ecosystems can be functionally stable despite changes in species composition, we use a distributed metabolic network for describing biogeochemistry, which synthesizes generic biological structures that catalyse reaction pathways, but is otherwise organism independent. Allocation of biological structure and regulation of biogeochemical reactions is determined via solution of an optimal control problem in which entropy production is maximized. However, because synthesis of biological structures cannot occur if entropy production is maximized instantaneously, we propose that information stored within the metagenome allows biological systems to maximize entropy production when averaged over time. This differs from abiotic systems that maximize entropy production at a point in space-time, which we refer to as the steepest descent pathway. It is the spatio-temporal averaging that allows biological systems to outperform abiotic processes in entropy production, at least in many situations. A simulation of a methanotrophic system is used to demonstrate the approach. We conclude with a brief discussion on the implications of viewing ecosystems as self-organizing molecular machines that function to maximize entropy production at the ecosystem level of organization.

Towards an Evolutionary Model of Animal-Associated Microbiomes

“…An important caveat is that this argument is based on the assumptions that all species have an equal propensity to acquire the necessary functions from the horizontal gene pool and can then utilize those functions equivalently. It has been proposed that irrespective of the final taxonomic configuration of a microbiome, biogeochemically it will obtain the same entropic state given the biophysiochemical constraints [109]. At the genetic and enzymatic levels, this is also consistent with the notion of functional convergence in spite of species variation [106].…”

It is not the entropy you produce, rather, how you produce it

“…When the nature of these constraints becomes part of the theory itself, we suggest that some basic difference in the 'rules' for applying MEP will emerge between physical-chemical systems and those containing biology. Some fundamental difference was postulated by Vallino (2010), who states that the 'difference between abiotic and biotic processes is that the former always follows a pathway of steepest descent (of entropy production), while the latter follows a pathway dictated by information that leads to greater entropy production when averaged over time'. (Parenthetical material added.…”

Maximum entropy production in environmental and ecological systems

“…The last six papers deal with various aspects of biotic organisms, ranging from the scale of bacteria (Ž upanović et al 2010) to plants (Dewar 2010) to food webs (Meysman & Bruers 2010;Vallino 2010) and ecosystems (Holdaway et al 2010;Schymanski et al 2010). Ž upanović et al (2010) take a thermodynamic view of bacterial chemotaxis-the ability of some bacteria to direct their movement towards certain chemicals such as glucose.…”

“…While they found that hypothesis (i) was valid in all cases they tested, they found that hypotheses (ii) and (iii) do not always hold within the context of their model. Vallino (2010) uses a distributed metabolic network to test the applicability of MEP to biogeochemical transformations. He points out that biological structures cannot occur if entropy production is maximized instantaneously and argues that it is the spatio-temporal averaging (maximizing longterm entropy production rather than instantaneous entropy production) that allows biological systems to outperform abiotic processes in entropy production.…”