Gaia as a complex adaptive system

We define the Gaia system of life and its environment on Earth, review the status of the Gaia theory, introduce potentially relevant concepts from complexity theory, then try to apply them to Gaia. We consider whether Gaia is a complex adaptive system (CAS) in terms of its behaviour and suggest that the system is self-organizing but does not reside in a critical state. Gaia has supported abundant life for most of the last 3.8 Gyr. Large perturbations have occasionally suppressed life but the system has always recovered without losing the capacity for large-scale free energy capture and recycling of essential elements. To illustrate how complexity theory can help us understand the emergence of planetary-scale order, we present a simple cellular automata (CA) model of the imaginary planet Daisyworld. This exhibits emergent self-regulation as a consequence of feedback coupling between life and its environment. Local spatial interaction, which was absent from the original model, can destabilize the system by generating bifurcation regimes. Variation and natural selection tend to remove this instability. With mutation in the model system, it exhibits self-organizing adaptive behaviour in its response to forcing. We close by suggesting how artificial life ('Alife') techniques may enable more comprehensive feasibility tests of Gaia.     

The biosphere theory of V. I. Vernadsky and the Gaia theory of James Lovelock: a comparative analysis of the two theories and traditions

James Hutton (1726-1797) regarded Earth as a super-organism and physiology the science to study it. A strong line of evidence for an intimate relationship of biological and abiotic processes on Earth leads from Hutton to the Gaia theory of J. Lovelock. A less known in the West but important approach to the biosphere as a self-regulating system (the biosphere theory) was proposed V.I. Vernadsky (1863-1945). The main concern of this paper revolves around the question: What is the difference between Gaia and the biosphere? To approach the problem of Earth as a super-organism one can use also the biosphere theory of V. N. Beklemishev (1890-1962), who examined the biosphere from a morphological viewpoint.     

Ecological succession as an energy dispersal process

Ecological succession is described by the 2nd law of thermodynamics. According to the universal law of the maximal energy dispersal, an ecosystem evolves toward a stationary state in its surroundings by consuming free energy via diverse mechanisms. Species are the mechanisms that conduct energy down along gradients between repositories of energy which consist of populations at various thermodynamic levels. The salient characteristics of succession, growing biomass production, increasing species richness and shifting distributions of species are found as consequences of the universal quest to diminish energy density differences in least time. The analysis reveals that during succession the ecosystem's energy transduction network, i.e., the food web organizes increasingly more effective in the free energy reduction by acquiring new, more effective and abandoning old, less effective species of energy transduction. The number of species does not necessarily peak at the climax state that corresponds to the maximum-entropy partition of species maximizing consumption of free energy. According to the theory of evolution by natural selection founded on statistical physics of open systems, ecological succession is one among many other evolutionary processes.     

Maximum entropy production and general trends in biospheric evolution

The biosphere has greatly shaped the past evolution of the Earth system. Here I argue that life evolved to maximize planetary entropy production. The evolution of the Earth system through time has thus evolved as far away from thermodynamic equilibrium as possible. I describe the implications of this hypothesis for the evolution of the global cycles of water and carbon and the implied consequences for biospheric evolution. This thermodynamic perspective of Earth’s biospheric evolution extends the views of Vernadski and Lovelock and puts it on a quantitative foundation.     

Ecosphere,biosphere, or Gaia? What to call the global ecosystem

The terms biosphere, ecosphere, and Gaia are used as names for the global ecosystem. However, each has more than one meaning. Biosphere can mean the totality of living things residing on the Earth, the space occupied by living things, or life and life-support systems (atmosphere, hydrosphere, lithosphere, and pedosphere). Ecosphere is used as a synonym of biosphere and as a term for zones in the universe where life as we know it should be sustainable. Gaia is similar to biosphere (in the sense of life and life-support systems) and ecosphere (in the sense of biosphere as life and life-support systems), but, in its most extreme form, refers to the entire planet as a living entity. A case is made for avoiding the term Gaia (at least as a name for the planetary ecosystem), restricting biosphere to the totality of living things, and adopting the ecosphere as the most apt name for the global ecosystem.     

Thermodynamic stability of ecosystems

The stability of ecosystems during periods of stasis in their macro-evolutionary trajectory is studied from a non-equilibrium thermodynamic perspective. Individuals of the species are considered as units of entropy production and entropy exchange in an open thermodynamic system. Within the framework of the classical theory of irreversible thermodynamics, and under the condition of constant external constraints, such a system will naturally evolve toward a globally stable thermodynamic stationary state. It is thus suggested that the ecological steady state, or stasis, is a particular case of the thermodynamic stationary state, and that the evolution of community stability through natural selection is a manifestation of non-equilibrium thermodynamic directives. Furthermore, it is argued that punctuation of stasis leading to ecosystem succession, may be a manifestation of non-equilibrium "phase transitions" brought on by a change of external constraints through a thermodynamic critical point.     

An Indicator to Evaluate the Thermodynamic Maturity of Industrial Process Units in Industrial Ecology

The article suggests a measure to evaluate the thermodynamic maturity of industrial systems at the level of single process units. The measure can be quantified with reasonable confidence on the basis of entropy production as defined by irreversible thermodynamics theory. It quantifies, for one process unit, the distance between its actual state of operation and its state with minimum entropy production or optimum exergy efficiency, when the two states are constrained with a fixed production capacity of the process unit. We suggest that the minimum entropy production state is a mature state, or that processes that operate at this state are mature. We propose to call the measure "the thermodynamic maturity indicator" (π), and we define it as the ratio between the minimum entropy production and the actual entropy production. We calculated π on the basis of literature data for some examples of industrial process units in the chemical and process industry (i.e., heat exchanger, chemical reactor, distillation column, and paper drying machine). The proposed thermodynamic measure should be of interest for industrial ecology because it emerges from the entropy production rate, a dynamic function that can be optimized and used to understand the thermodynamic limit to improving the exergy efficiency of industrial processes. Although not a tool for replacing one process with another or comparing one technology to another, π may be used to assess actual operation states of single process units in industrial ecology.     

Do evolution and ecology need the Gaia hypothesis?

Gaia theory, which describes the life-environment system of the Earth as stable and self-regulating, has remained at the fringes of mainstream biological science owing to its historically inadequate definition and apparent incompatibility with individual-level natural selection. The key issue is whether and why the biosphere might tend towards stability and self-regulation. We review the various ways in which these issues have been addressed by evolutionary and ecological theory, and relate these to 'Gaia theory'. We then ask how this theory extends the perspectives offered by these disciplines, and how it might be tested by novel modelling approaches and laboratory experiments using emergent technologies.     

Information dynamics in living systems: prokaryotes, eukaryotes, and cancer

Background

Living systems use information and energy to maintain stable entropy while far from thermodynamic equilibrium. The underlying first principles have not been established.

Findings

We propose that stable entropy in living systems, in the absence of thermodynamic equilibrium, requires an information extremum (maximum or minimum), which is invariant to first order perturbations. Proliferation and death represent key feedback mechanisms that promote stability even in a non-equilibrium state. A system moves to low or high information depending on its energy status, as the benefit of information in maintaining and increasing order is balanced against its energy cost. Prokaryotes, which lack specialized energy-producing organelles (mitochondria), are energy-limited and constrained to an information minimum. Acquisition of mitochondria is viewed as a critical evolutionary step that, by allowing eukaryotes to achieve a sufficiently high energy state, permitted a phase transition to an information maximum. This state, in contrast to the prokaryote minima, allowed evolution of complex, multicellular organisms. A special case is a malignant cell, which is modeled as a phase transition from a maximum to minimum information state. The minimum leads to a predicted power-law governing the in situ growth that is confirmed by studies measuring growth of small breast cancers.

Conclusions

We find living systems achieve a stable entropic state by maintaining an extreme level of information. The evolutionary divergence of prokaryotes and eukaryotes resulted from acquisition of specialized energy organelles that allowed transition from information minima to maxima, respectively. Carcinogenesis represents a reverse transition: of an information maximum to minimum. The progressive information loss is evident in accumulating mutations, disordered morphology, and functional decline characteristics of human cancers. The findings suggest energy restriction is a critical first step that triggers the genetic mutations that drive somatic evolution of the malignant phenotype.     

Entropy consumption in primary photosynthesis

Knox and Parson have objected to our previous conclusion on possible negative entropy production during primary photochemistry, i.e., from photon absorption to primary charge separation, by considering a pigment system in which primary photochemistry is not specifically considered. This approach does not address our proposal. They suggest that when a pigment absorbs light and passes to an excited state, its entropy increases by hν/T. This point is discussed in two ways: (i) from considerations based on the energy gap law for excited state relaxation; (ii) using classical thermodynamics, in which free energy is introduced into the pigment (antenna) system by photon absorption. Both approaches lead us to conclude that the excited state and the ground state are isoentropic, in disagreement with Knox and Parson. A discussion on total entropy changes specifically during the charge separation process itself indicates that this process may be almost isoentropic and thus our conclusions on possible negentropy production associated with the sequence of reactions which go from light absorption to the first primary charge separation event, due to its very high thermodynamic efficiency, remain unchanged.     

Entropy consumption in primary photosynthesis

Knox and Parson have objected to our previous conclusion on possible negative entropy production during primary photochemistry, i.e., from photon absorption to primary charge separation, by considering a pigment system in which primary photochemistry is not specifically considered. This approach does not address our proposal. They suggest that when a pigment absorbs light and passes to an excited state, its entropy increases by hnu/T. This point is discussed in two ways: (i) from considerations based on the energy gap law for excited state relaxation; (ii) using classical thermodynamics, in which free energy is introduced into the pigment (antenna) system by photon absorption. Both approaches lead us to conclude that the excited state and the ground state are isoentropic, in disagreement with Knox and Parson. A discussion on total entropy changes specifically during the charge separation process itself indicates that this process may be almost isoentropic and thus our conclusions on possible negentropy production associated with the sequence of reactions which go from light absorption to the first primary charge separation event, due to its very high thermodynamic efficiency, remain unchanged.     

Thermodynamic analysis of protein interactions with biosensor technology

A methodology using biosensor technology for combined kinetic and thermodynamic analysis of biomolecular interactions is described. Rate and affinity constants are determined with BIAcore. Thermodynamics parameters, changes in free energy, enthalpy and entropy, are evaluated from equilibrium data and by using rate constants and transition state theory. The methodology using van't Hoff theory gives complementary information to microcalorimetry, since only the direct binding is measured with BIAcore whereas microcalorimetry measures all components, including e.g. hydration effects. Furthermore, BIAcore gives possibilities to gain new information by thermodynamic analysis of the rate constants.     

The origin of autonomous agents by natural selection

We propose conditions in which an autonomous agent could arise, and increase in complexity. It is assumed that on the primitive Earth there arose a recycling flow-reactor containing spontaneously formed oil droplets or lipid aggregates. These droplets grew at a basal rate by simple incorporation of lipid phase material, and divided by external agitation. This type of system was able to implement a natural selection algorithm once heredity was added. Macroevolution became possible by selection for rarely occurring chemical reactions that produced holistic autocatalytic molecular replicators (contained within the aggregate) capable of doubling at least as fast as the lipid aggregate, and which were also capable of benefiting the growth of its lipid aggregate container. No nucleotides or monomers capable of modular heredity were required at the outset. To explicitly state this hypothesis, a computer model was developed that employed an artificial chemistry, exhibiting conservation of mass and energy, incorporated within each individual of a population of lipid aggregates. This model evolved increasingly complex self-sustaining processes of constitution, a result that is also expected in real chemistry.     

Cumulative benefit games: achieving cooperation when players discount the future

The science of thermodynamics is concerned with understanding the properties of inanimate matter in so far as they are determined by changes in temperature. The Second Law asserts that in irreversible processes there is a uni-directional increase in thermodynamic entropy, a measure of the degree of uncertainty in the thermal energy state of a randomly chosen particle in the aggregate. The science of evolution is concerned with understanding the properties of populations of living matter in so far as they are regulated by changes in generation time. Directionality theory, a mathematical model of the evolutionary process, establishes that in populations subject to bounded growth constraints, there is a uni-directional increase in evolutionary entropy, a measure of the degree of uncertainty in the age of the immediate ancestor of a randomly chosen newborn. This article reviews the mathematical basis of directionality theory and analyses the relation between directionality theory and statistical thermodynamics. We exploit an analytic relation between temperature, and generation time, to show that the directionality principle for evolutionary entropy is a non-equilibrium extension of the principle of a uni-directional increase of thermodynamic entropy. The analytic relation between these directionality principles is consistent with the hypothesis of the equivalence of fundamental laws as one moves up the hierarchy, from a molecular ensemble where the thermodynamic laws apply, to a population of replicating entities (molecules, cells, higher organisms), where evolutionary principles prevail.     

Non-equilibrium thermodynamics of temporally oscillating chemical reactions.

Two thermodynamic quantities are introduced: the entropy change due to a variation of chemical affinity from a steady, state. to some other state and the corresponding entropy production. The entropy change is always negative definite except at the steady state and is capable of being a Liapunov function. The phase-plane behaviour of the entropy production along the trajectory generated by kinetic equations is investigated in connection with the stability of steady state. The examples taken on that occasion are the Volterra-Lotka and Prigogine-Lefever models. The non-equilibrium thermodynamic properties common to the oscillating reactions in two-variable system are in general considered with an emphasis on the thermodynamic analysis for the direction of rotation of the trajectory generated by the two-variable kinetic equations.     

Two-dimensional differential scanning calorimetry: simultaneous resolution of intrinsic protein structural energetics and ligand binding interactions by global linkage analysis.

A general theoretical development for the design and analysis of two-dimensional thermal stability surfaces of proteins is presented. The surfaces are generated from multiple excess heat capacity profiles ( vs T) obtained at varying concentrations of an interacting ligand. The energetics of both the intrinsic protein stability and the protein-ligand interaction are simultaneously resolved by employing statistical thermodynamic models in global linkage analysis. This formalism allows resolution of the intrinsic protein folding-unfolding parameters (enthalpy, entropy, and heat capacity changes) as well as the ligand interaction parameters (binding stoichiometry, enthalpy, entropy, and heat capacity changes). The theory has been applied to the case of ribonuclease A and its interaction with cytidine-2'-monophosphate. The accuracy of the thermodynamic parameters obtained by this approach compares within error with those parameters that can be obtained by direct measurements.     

Measuring ecological characteristics of environmental building performance: Suggestion of an information-network model and indices to quantify complexity,power, and sustainability of energetic organization

The authors present preliminary study in pursuance of developing a flow network-based methodology of building performance evaluation, as current efficiency-centered methods do not fully account for the complex building performance in which nature, economy, and humans are inseparably involved. Based on the principle of entropy, this study defines building as a thermodynamic system that networks useful resources―energy, material and information―through close interconnection with the global environment. Measures of information content in energy-flow networking and ecological performance indicators from Shannon’s information theory, Ulanowicz’s ascendency principle, and Odum’s maximum empower principle are discussed and integratively applied to developing a generic building performance evaluation model. For the holistic indication of building sustainability, this work attempts to reconcile Ulanowicz’s and Odum’s statements about ecosystem development and also integrates emergy (spelled with an “m”) and information metrics. Environmental behaviour of the building model was tested with simulation to validate consistency with system-level principles. Results reveal that network complexity corresponds to system power and resilience (L) and fitness (F) tend to peak at an intermediate level of efficiency. This finding demonstrates applicability of Odum’s maximum power principle to building study, suggesting that increasing complexity (and power) of emergy-flow networking be a fundamental characteristic of sustainable building performance.     

Natural selection through survival alone,and the possibility of Gaia

Here I advance two related evolutionary propositions. (1) Natural selection is most often considered to require competition between reproducing “individuals”, sometimes quite broadly conceived, as in cases of clonal, species or multispecies-community selection. But differential survival of non-competing and non-reproducing individuals will also result in increasing frequencies of survival-promoting “adaptations” among survivors, and thus is also a kind of natural selection. (2) Darwinists have challenged the view that the Earth’s biosphere is an evolved global homeostatic system. Since there is only one biosphere, reproductive competition cannot have been involved in selection for such survival-promoting adaptations, they claim. But natural selection through survival could reconcile Gaia with evolutionary theory.     

Thermodynamic view on decision-making process: emotions as a potential power vector of realization of the choice

This research is devoted to possible mechanisms of decision-making in frames of thermodynamic principles. It is also shown that the decision-making system in reply to emotion includes vector component which seems to be often a necessary condition to transfer system from one state to another. The phases of decision-making system can be described as supposed to be nonequilibrium and irreversible to which thermodynamics laws are applied. The mathematical model of a decision choice, proceeding from principles of the nonlinear dynamics considering instability of movement and bifurcation is offered. The thermodynamic component of decision-making process on the basis of vector transfer of energy induced by emotion at the given time is surveyed. It is proposed a three-modular model of decision making based on principles of thermodynamics. Here it is suggested that at entropy impact due to effect of emotion, on the closed system—the human brain,—initially arises chaos, then after fluctuations of possible alternatives which were going on—reactions of brain zones in reply to external influence, an order is forming and there is choice of alternatives, according to primary entrance conditions and a state of the closed system. Entropy calculation of a choice expectation of negative and positive emotion shows judgment possibility of existence of “the law of emotion conservation” in accordance with several experimental data.