time rescaling and pattern formation in biological evolution

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ARTICLE IN PRESSG ModelBIO 3469 18BioSystems xxx (2014) xxxxxx

Contents lists available at ScienceDirect

BioSystems

jo ur nal home p age: www.elsev ier .com/ locate /b iosystems

Time re ica

Abir U. IgQ1Department of

a r t i c l

Article history:Received 5 FebReceived in reAccepted 20 M

Keywords:BiospreadingEpigenetic chaHeterochronyHeterotopyQuantum meaUncertainty

rocesing intructosystmentangi

featchange canle pa

1. Introdu

The evoin the external time and space and arising from the pre-existingcomplexity at the level of elements constituting complex systems.Such approach generates paradoxes and contradictions of the scaleexceeding signicantly the inconsistencies inherent to the New-tonian mechanics and leads to the appearance of evolutionarytheories conother and dthat time aobservers isThis relatiomodern biodescribed bunitary whspacetimethe statemespacetimeinteractions

In previostate (IQS) of macroscoQ22007; Igammacromole

Tel.: +1 70E-mail add

highs of nnd

underlies the morphogenetic events (Igamberdiev, 2012). In theevolutionary process we move beyond the individual organism andits intrinsic IQS. This means that the no-cloning theorem, stated byWootters and Zurek (1982) and Dieks (1982), imposes limitationsthat forbid creation of the identical copies of an arbitrary unknown

http://dx.doi.o0303-2647/

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51e this article in press as: Igamberdiev, A.U., Time rescaling and pattern formation in biological evolution. BioSystems (2014),doi.org/10.1016/j.biosystems.2014.03.002

travening in their basic foundations, contradicting eachenying any compromise. The opposite view claimingnd space intrinsically result from relations between

not fully explored with regard to biological evolution.nal approach arises to Lebniz and was introduced tology by Robert Rosen. It describes the loop causalityy two domains, one being related to the undifferentiatedole and another to the differentiated selected local, and characterized by the complementarity betweennt that the general geometry of spacetime causes local

to emerge, and the statement that local spacetime produce the general geometry (Rosen, 1991).us papers I developed the concept of internal quantumshielded by error-correction and keeping the identitypic system at the quantum level (Igamberdiev, 2004,berdiev, 2008). The IQS percolates from the level ofcules to the unity of a complex multicellular organism,

9 864 4567; fax: +1 709 864 3018.ress: [email protected]

quantum state. However, although perfect copies of an unknownquantum state are prohibited by this theorem, it does not prohibitthe production of imperfect copies. This opens a possibility of mul-tiplication and evolution of quantum systems via coupling a largerauxiliary system to the system undergoing cloning and applying aunitary transformation to the combined system. In case of ttingchoice of the unitary transformation, some components of the com-bined system will evolve into approximate copies of the originalsystem. Thus evolution occurs as a transformation of the quantumsystem coupled to its environment. The internal observers, actingas measuring agents, constitute a network of interactions betweenorganisms mediated by the environment, in which the renementof the wave function generates objective patterns corresponding toperception of the reality of external world (Igamberdiev, 2008).

The imperfect cloning means also interruption and mul-tiplication of the agency establishing and holding IQS. Amisunderstanding, which often arises in analysing quantum mea-surement, comes from postulating the necessity of consciousobserver for xing measurement result. This postulation is not sup-ported even at the level of brain. Benjamin Libets experimentssuggest that consciousness appears as the epiphenomenon of brain

rg/10.1016/j.biosystems.2014.03.0022014 Published by Elsevier Ireland Ltd.

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72scaling and pattern formation in biolog

amberdiev

Biology, Memorial University of Newfoundland, St. Johns, NL A1B 3X9, Canada

e i n f o

ruary 2014vised form 14 March 2014arch 2014

nge

surement

a b s t r a c t

Biological evolution is analyzed as a pthemselves in the environment resulterochrony) followed by spatial reconsevolution is the incompleteness of bithe uncertainty of quantum measureinterpretation of information in the chents are used for establishment of newinvolves the anticipatory epigenetic generally be forecasted but can providorganization and leading to predictab

ction

lutionary process is commonly analyzed as occurring

and attubulestate al evolution

s of continuous measurement in which biosystems interpret changes of both. This leads to rescaling of internal time (het-ions of morphology (heterotopy). The logical precondition ofems internal description, while the physical precondition is. The process of evolution is based on perpetual changes inng world. In this interpretation the external biospheric gradi-ures of organization. It is concluded that biological evolutiones in the interpretation of genetic symbolism which cannotalization of structural transformations dened by the existingtterns of form generation.

2014 Published by Elsevier Ireland Ltd.

er levels of organization through the system of micro-ervous system. The dual unity of the coherent internalof mechanical movement of the macroscopic body

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ARTICLE IN PRESSG ModelBIO 3469 182 A.U. Igamberdiev / BioSystems xxx (2014) xxxxxx

states while the reduction of uncertainty in volition acts takesplace in the unconscious prior to their awareness (Libet, 1985).Several examples of the unconscious choice in behavior of ani-mals of different levels of organization were established in researchof Gunji grThe result nomenon bevent havinries interprinterpretatidriving forcThe semiotitum measudevice is insemiotic reinterpretedherent histmoreover, tThe relationsic and obseas a self-gr

2. Quantum

In modconcept is snomenon oThe quantuing itself airreversibili1993; Shiofunction is measurableaction of a measuring proceeds inbecomes mto an iteratment and ecan be orgacourse of inble for the ma system cazation and descriptionary increasappears asded into it,genetic symthat they coQ3

The inteof the measits possible as the unceplexity as aincrease inlution. Inderecursive emof environminto this enown presento Magdalement becomcomplexityin turn, pro

in the course of measurement at the next level of recursion. Uncer-tainty comes about as a necessary consequence of such embeddingmeasurement. Thus the increase in complexity occurs simply as aresult of quantum measurement. Biological evolution, viewed as

tion beco

app qu

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ns tots itss of er (1catalcientpationly r

Wherableycle

Matu The hes patiogic bycleat red by pletens oeori

the similxist prov009)m thw stport

The ted be frove termal

the snal ile eltaphhat ctem.g forentss a q). A ing aia extemf itsscall tim

destvremeen tim

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139e this article in press as: Igamberdiev, A.U., Time rescaling and patdoi.org/10.1016/j.biosystems.2014.03.002

oup (see e.g. Fukano et al., 2004; Migita et al., 2005).of measurement can be xed not as a conscious phe-ut as a consistent history representing soft decoherenceg semiotic value. A modication of the consistent histo-etation of quantum mechanics, dened as the semioticon by Christiansen (1985), introduces semiosis as ae of decoherence and evolution of quantum systems.c interpretation is based on the understanding of quan-rement as an internal process where the measuringcluded into the measured reality, thus establishing alation between the device and the quantum system

by the observing agent. In this interpretation deco-ories are rened through their signicative validity;he formation of sign itself is equivalent to this reduction.al view introduces dual time reference frames (intrin-rvational) and leads to the comprehension of evolutionowing Logos in the sense of Heraclitus.

measurement, time, and growth of complexity

ern theoretical biology the internal measurementuggested as a background for explanation of the phe-f life (Pattee, 1989; Igamberdiev, 1993; Matsuno, 1995).m measurement is an irreversible phenomenon exhibit-s a reduction of the potential eld. Its relation toty of time was discussed earlier (Igamberdiev, 1985,kawa and Hu, 1995). However the collapse of wavenot equivalent to time because it does not generate a

duration. The quantum measurement represents themeasuring device on the measured system. When thedevice is a part of measured system, the measurementternally in relation to the whole system and the latterore complex as a result of measurement itself. This leadsive recursive process which appears as the develop-volution of the system. The quantum measuring devicenized in such way that it encodes the system in theteraction with the measured object and makes it possi-easurement to proceed in a regular way. In this case,

n memorize the evolutionary complication of organi-evolve further, in other words it contains an internal

memorizing the measurement result. The evolution-e of complexity becomes possible when the genotype

a system distinct from the phenotype and embed- which separates energy-degenerate rate-independentbols from the rate-dependent dynamics of constructionntrol (Pattee, 2001).rnal measuring device measures, among other elementsured system, itself in the state of measuring, which lim-accuracy of quantum measurement and manifests itselfrtainty principle (Matsuno, 1992). The increase in com-

result of quantum measurement corresponds to the complexity of living organisms in the course of evo-ed, evolution can be viewed as a potentially innitebedding process, where life evolves as measurement

ent, and, through living organisms, becomes embeddedvironment, which affects its further development by itsce (Rojdestvenski and Igamberdiev, 1999). Accordingf (1996), a measurement (observation) of the environ-es a source of evolution of the living system itself. The

of environment increases as a result of life itself, which,duces more complexity in life as reection of this fact

adaptalution,world.

Theperformsipatiomodeling whhappecatalysfeatureSchustof the an efisms sitself, o2011).measuhyperctem of2011).tinguis(anticiand lohypercture thdeneincomrelatiologic thwithinsense there enot be et al., 2

Froof a neto sup2007).supporIQS freeffectinal themakesnizatioavailabas a mevalue tthe sysexistinstatembasis i(Fig. 1acquirment vthe syssome otime reinternaby Rojmeasubetweformation in biological evolution. BioSystems (2014),

to the tness landscape changing in the course of evo-mes its own cause, a universal property of the living

earance of measurable time occurs in the systems thatantum measurements in a regular way, with low dis-energy (Igamberdiev, 1993, 2004). These systems are

hypercycles, which we dene as the structures appear-he subset of a substrate set of the catalytic system

be the matrix for generating and reproducing the set ofelf (Igamberdiev, 1999). This denition keeps the mainthe original notion of hypercycle given by Eigen and979). The hypercyclic system is closed in the way that allysts needed for an organism to stay alive (representing

causation according to Aristotle and forming organ-temporal structure) must be produced by the organismelying on matter and energy from outside (Letelier et al.,n hypercycles appear, time becomes an independent

variable due to internal reproducible changes. Eigens is a formalized representation of the autopoietic sys-rana and Varela or Rosens (M, R) system (Leteiler et al., Q4

system becomes an internal autonomous clock that dis-the past (memory), the present (life), and the futuren based on the reproducible model), so the modelingecome possible within the system (Rosen, 1985). The

having own embedded description, becomes a struc-alizes computation in accordance with its internal logicthe embedded description. The latter has a property ofness which is reected in the fact that quantum cor-f the systems states are associated with undecidablees, i.e. can potentially generate statements not denedsystem. The undecidability can be interpreted in thear to Gdels incompleteness theorem, meaning thatpropositions, expressible in the formal logic, which can-en or disproven (Van den Nest and Briegel, 2008; Briegel.e quantum mechanical point of view, the emergenceatement can acquire a new error-correction meaningthe internal quantum state (IQS) (Igamberdiev, 2004,IQS keeps the system organizationally invariant. It isy the set of error-correcting commands that aim to keepm external demolitions which corresponds to its lowmperature of a nanokelvin range shielded from exter-

inuences (Igamberdiev, 2007, 2012). A new statementystem more complex, with its all spatiotemporal orga-nvariance be rescaled. In the course of evolution, anement of a formal system (similarly to a word when usedor) can acquire another (in addition to already existing)ontributes to formation of a new level of organization in

The logical basis of this action is the incompleteness ofmal system that allows assigning arbitrary values to the

non-provable within that system, while the physicaluantum uncertainty arising in quantum measurementnew statement can arise from existing elements by

double function, however, for xation of this new state-pansion of existing formal system, some redundancy of

is needed, which can be achieved by multiplication of elements. The creation of meta-statement will lead toing in the system. The phenomenon of rescaling of thee in systems with nite number of states was analyzedenski and Cottam (2000) in the context of the internalnt concept in biology. They established a connectione rescaling and generalized statistics and suggested to

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ARTICLE IN PRESSG ModelBIO 3469 18A.U. Igamberdiev / BioSystems xxx (2014) xxxxxx 3

Fig. 1. P

use a generaeter. Thus tthe measurincreasing o

When Gvalue, the rcontradictoity attainininternalizestion of newplace, and tin reductioncess corresQ5to Bauer (1tionary proliving stateis observednical progreis incorporafrom embedof the modeenhancemeof the modings to Gdas a prior cagency of inorganizatiolar to creatiirreversibilifoundationsting the trulogical oper

The notidescriptionmunicationby the timetory statemof the transQ6ration. Gungenerating tion consistcoarse-graiidenticatiois read andsystems are

course of adaptation. A possibility of such mode of adaptation isreected in genome structure.

ome is a system which possesses an internal complemen-etween linear texts and their superposition. Relevantly tompl

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250hysical and logical processes underlying biological evolution.

lized notion of entropy to set the time rescaling param-he growth of complexity comes from inseparability ofing device from the measured system, and results inf complexity of both the system and the environment.del numbers are introduced, empowered by a neweduction of uncertainty takes place and separation ofry statements is realized. The internal semiotic activ-g new values appears as an endo-observer agency that

Gdel numbers. As a consequence, even without addi- elements, the division in internal temporal scale takeshe whole time of the system is rescaled, which results

of uncertainty and increase of complexity. This pro-ponds to increase in external work, which, according935), is the main characteristic feature of the evolu-cess. It aims to exploit additional resources to maintain

of evolving biosystem. The increase of external work also in the social evolution due to continuous tech-ss. While the future in the structure of internal timeted as anticipation according to the model generatedded description, time rescaling will result in a changel of anticipation, generally in its development towardnt and better exibility. Thus evolution is the changeel of anticipation due to empowering of new mean-el statements. The act of anticipation can be consideredondition for the appearance of a new endo-observerternal measurement. The emergence of a new level ofn cannot be recursively described; it is a process simi-ng a new formula, which was not present initially. The

Gentarity bthis, coviewedintervaembedRNA amolecuing pocompltive coits temfor ongenomgeneracombinthe pois analimposssimulttime n

Thereprodseverareprodfollowary chbecausfunctiosideredstructuincludthe consignicas leadductiofrom tevolutof comtion ofinternaforecastion offor meset of sQuantucal repe this article in press as: Igamberdiev, A.U., Time rescaling and pattern doi.org/10.1016/j.biosystems.2014.03.002

ty of evolution can be explained in terms of its logical. It is determined by the fact that the Gdel formula set-th value cannot be obtained through a set of reversibleations.on of past in the system, represented in the embedded

as a memory, can be described as an asynchronous com- in which the transmitter and the receiver are separated

interval. In fact, time is an engine to separate contradic-ents (Gunji, 1994) and the inequality of the statementmitter and of the receiver is the example of such sepa-ji and Kusunoki (1997) suggested a model of interactionemergent phenomena based on incomplete identica-ing of alternate procedure of constructing a map fromned data in a system without boundary. Incompleten connected with uncertainty in measurement process

interpreted as a cause for new realizations. Biological adapting to the environment that is changing in the

from the leto the phenKochen, 20becomes ththe paralleling biologic

3. Nomoth

Change be describeor relationsvariability laws and anE.g. in leaf tions are leformation in biological evolution. BioSystems (2014),

ementarity means that text and hypertext cannot behe same moment: they should be separated by times an example of uncertainty between the system and its. Overlapping genes, alternatively splicing sequences,NA editing, introns, and recombination according toaddresses are the features of this hypertext generat-ally innite number of language games. Genome as anguage exists as a complementary set of its alterna-ations resulting in logical paradoxes which determinel dynamics (Isalan, 2009). This superposition is a basisesis, adaptation and evolution. Thus, the total truea superposition of contradictory arrangements, whiche single arrangement at concrete moment of time. Theial capacity of genome increases by many times through

mobile genetic elements. An ambiguity in meanings to the quantum uncertainty principle in which it isto strictly dene the position and impulse of particleusly, or to x certain energy in a very short period ofary for its registration.blem of a minimum size of the autocatalytic self-g system and its composition has been discussed inrks (Sharov, 1991, 2009; Steel et al., 2013). Self-n itself is a creative process of placing text in texty self-growth of this joint structure. Any evolution-

also begins from placing text in text. This is possiblest of genome serves for realization of such non-trivialoreover, even point mutations or deletions can be con-enerative if they are placed in the repeated (e.g. diploid)oubling is a premise of metasystem transition, whichplication of the original system and establishment of

over multiple copies (Turchin, 1977). The evolutionary of gene duplication was considered by Ohno (1970)o neofunctionalization. The advantage of sexual repro-n casual combinatorial generation of new statementseparate texts that can acquire meanings, thus it resistsy degradation. It becomes a prerequisite for growingity and further evolution. The combinatorial interac-rochronic texts generates a new system in which thee is rescaled in a new way that generally cannot beThe heterochronic duplication occurring via hybridiza-orally different organisms generates more possibilitiestem transition. Thus, the incompleteness of embeddedols is the formal cause of evolution (Igamberdiev, 1986).ncertainty in the course of measurement is the physi-tation of this incompleteness (Matsuno, 1992). It spansvel of elementary particles to biological evolution andomenon of free will and consciousness (Conway and06). Incomplete identication within a larger systeme initial challenge for systems evolution. Fig. 1 shows

representation of physical and logical events underly-al evolution.

etic constraints of the evolutionary process

of organisms in their individual life or in evolution cand in terms of alteration of the composition of parts

between parts. The morphological and evolutionaryfollows certain rules that can be called nomotheticalalyzed as symmetrical transformations (Meyen, 1974). Q7evolution some transitions are possible, other transi-ss probable and some are prohibited. The probability of

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transition depends on stage of development, on evolutionary posi-tion of species and on their geographical location. The sequenceof evolutionary transitions of a certain structure can be viewedas a recursion process called refrain by Meyen (1974). This typeof recursionquantitativtopologicalpre-fractal unfolding ubook of DAsive compebiological tr

Actuallyplex numb2D space. Wsurement, toccurs whe(Igamberdimined by thtime intervaing them. Tseparated bment. Thuscorrespondments wheof recursivelimits will amemorizati( = lim Fn+formation, 2004).

The pattself-similarand larger matics, the iterative naproper Fiboratio and thsystem undThus the coFibonacci gtionary unfbased on mof numericathe fractal cspatiotempfrom the auon metaboltain their hlevels (Dam

The evolsystems ordicted withsystem, whit. On the oof organizaQ8according thomology sera and uporganizatioparallel and

Ln(a + b + c

A difculem of form

generally reduced to spatial archetype but has a temporal con-stituent expressed in certain transformation principles. In the lawof homological series, a new statement corresponds to the radical,while the one-level (intraspecies, intragenus, etc.) variability picks

ngeshe pns catoretatweveformantsspatiocesnizattrancicectioing ombeus bforms (Merstion inaton p

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follows the principle of self-similarity in which thee invariants may not conserve but the qualitative (e.g.) characteristics will be preserved. This means that astructure is generated, in which we cannot trace itsp to innity thus deviating it from classical fractals. Thercy Thompson (1917) remains the most comprehen-ndium of nomothetical laws operating in the course ofansformations.

fractal is an iteration arising from the set of com-ers by squaring them, i.e. by reecting them to thee discussed earlier that in course of quantum mea-

he simplest and most general way of transformationn a new domain is composed of two previous domainsev, 2004). In this process, the evolving state is deter-e two contradictory values of the system separated byl, and the value in time future is acquired after address-

wo contradictory statements taken as sequential valuesy time interval are composed to obtain the third state-

the next statement (quantitatively modeled as havingent value) is composed from the two previous state-n they are memorized as real numbers in the course

process: Fn+2 = Fn + Fn+1. In this case, certain recursiveppear as fundamental canons of perfection formed ason within reective loops. The notion of golden section1/Fn), which commonly appears in biological patternfollows from this type of memorization (Igamberdiev,

erns based on the golden rectangle and golden ratio, are, and each part of the structure is similar to smaller partsparts, which makes it a pre-fractal. In modern mathe-golden ratio occurs in fractal geometry due to its ownture (Gulick and Scott, 2010). The fractal property of thenacci system is proven in mathematics, and the goldene specic inversion property intrinsic to the Fibonaccierlie the Fibonacci fractal (Yudin and Startzev, 2012).ntinuous quantum measurement has a property of theenerator. The golden section in the course of evolu-olding implicates the principle of optimal constructionaximal simplicity, which is characterized by minimuml relations between integer and its parts, that indicateharacter of recursive processes (Radyuk, 2001). Fractaloral patterns and rhythms can originate in hypercyclesto-regulatory feedback loops. Maps and clocks basedic hypercycles are used by living organisms to main-omeodynamic equilibrium and biodiversity at differentiani, 2002).utionary process takes place via resetting the values ofganizational invariance. Such resetting cannot be pre-

certainty and can be evaluated in the newly evolvedich is embedded in a new environment modied byther hand, many traits are independent on the valuestional invariance forming homology series of variationo Vavilovs law. Vavilov (1922) formulated the law oferies as a rule claiming that different taxa (species, gen-) are distinguished by their radicals (Ln) representingnal invariance while the changes in traits (a, b, c. . .) are

can be predicted:

+ d + e + f + g + h + i + k )

lty to dene radicals can be related to the prob-ulating organizational invariance because it is not

up chaIn t

decisioanticipInterprity, hoactual (Cherdber of this prreorgational nonspethe selunfoldthe nuing. Thprior inproces

Undsideratdetermpretatiinto atain oreectcertainical sinand arpatternnizatiosystemstand we neand anbased basic 1996).

4. Res

Thetion oforganiwhichchangelular ointerprin genoingful homeostructuin molferent phylogis charinternacorrespin bioland thinterprformation in biological evolution. BioSystems (2014),

from already established sets.rocess of evolution, nomothetic and selection-basedan work together. The meaning of newly generatedy models can be tested via the selection process.ion of new statements has a high degree of exibil-r beyond this exibility the rules of selection of thes apply. This process can be called rather episelectiveev et al., 1996) because it operates on a countable num-ally ordered structures capable of self-reproduction. Ins, the appearance of new correlations is expressed inion of the phenotypic variation pattern, and the direc-sformations of the phenotype occur on the basis of

and randomly directed effects of selection. Althoughn process does not add to explanation of nomotheticf patterns during the evolutionary process, it restrictsr of possibilities that can be realized in such unfold-iological evolution appears as partially directed, and aation about the tness space determines the unfolding

elkikh, 2014).anding of evolution as partially directed suggests con-of the genotypephenotype interaction as not that ofion but as interpretation (Kull, 1998). In these inter-atterns, the closed loops of causation are mappedle coherent spacetime frame (Rosen, 1993). Cer-al values that can be redundantly repeated in anyoop correspond to the topological inevitability ofelopmental and evolutionary processes. These topolog-rities inevitably emerge during epigenetic realization,tained and transformed in pattern formation. Thesee not encoded but unfolded within the whole orga-hich is in line with the basic idea that the wholenot be reduced to its internal description. To under-ation of pattern formation to underlying phenomena,o go beyond the concept of genetic determinatione fundamental principles of biological organizationpercolation between different levels spanning fromtum phenomena to life and consciousness (Conrad,

g of internal time and epigenetic evolution

th of complexity is particularly evident upon forma-ryotic cells and then of multicellular organisms. Thesehave complex programs of temporal development,

over their whole life but most drastic spatiotemporale place at early stages in embryogenesis. In multicel-isms, all cells possess the same genetic text, which is

in different ways. In evolution, changes are introduced, but still changes in interpretation remain more mean-

changes in genetic information itself. The discovery ofenes causing the development of specic morphologicalLewis, 1994) rooted the emerging discipline of evo-devor genetics. Genome is a dynamic open system with dif-ibilities of its reading. The relationship of ontogeny andin this context can be represented as follows. Ontogenyized by reproduction of structures of truth values of theical calculus of biosystems and the evolutionary processs to assigning truth values at the external level. Thus,we are dealing with the two levels of algebraic logic,lationship can be found in a non-trivial indeterministon.

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tienne Geoffroy Saint-Hilaire for the rst time consideredtransformations of species as a consequence of inherited changesin embryos caused by changes in the environment and assumedthat early smation of liin Le Guyadof epigenetorganisms persistencefurther inhbook On Grates coulding similaricould be usspacetimerescaling. Induced the can organismin genotypegenetic assenvironmenrepertoire.

From theof energy dcoherent stHeisenbergthe conformhyper-restoare essentiaof accumulwhich can b(Beloussov,this subsysttems that wa higher precase is decrapoptosis. Tof all multicof time resc

The reduditions of fof new strusuggested taddition; aas new staidea based extended bing of devewas suggesis not adapable for useKirby, 1998role; they Q9tion. Berg (ontogenesisaccelerationof exaptatioprocesses afunctional r

The meciliates. Thcontaining polyploid mcleus by amicronucleits genes, w

vegetative growth. It was shown that maternal RNA templatesprovide both an organizing guide for DNA rearrangements anda template that can transmit spontaneous mutations that may

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tages of ontogenesis are most important for transfor-ving organisms (Geoffroy Saint-Hilaire, 1838; revieweder, 2004). Karl Ernst von Baer dened the mechanismic evolution in more detail by explaining change asinterpretation of itself in changing environment and

of this interpretation over generations which can beerited (Baer, 1828). DArcy Thompson (1917) in hisrowth and Form postulated that differential growth

produce variations in form. He showed the underly-ties in body plans and how geometric transformationsed to explain the variations. The locally measurable

of biological organisms is transformed through time agreement with these ideas, Waddington (1959) intro-oncept of canalization, which refers to the ability of

to produce the same phenotype despite variations or environment, and identied a mechanism called

imilation which would allow organisms response total stress to become a xed part of its developmental

framework of quantum measurement, a local increaseissipation can result in a shorter time of holding theate (IQS) of a subsystem according to the energy-times uncertainty ratio and consequently to changes inational dynamics of cytoskeleton and in the scales ofration processes (Igamberdiev, 2012). These processesl in morphogenetic events and provide a possibility

ation of additional energy and making an extra-worke used for building-up of new morphological structures

2012). This leads to rescaling of the individual time ofem and to a possibility of inclusion of additional subsys-ould support holding the IQS of the whole system withcision and for a more prolonged time. The most radicaleasing the internal time of a subsystem to zero by thehis process plays an important role in morphogenesisellular organisms and provides a powerful mechanismaling and pattern formation.ction of individual time of a subsystem is one of con-urther complication of organization and of additionctural and dynamical levels to it. Stephen Jay Gouldhe approach to explaining evolution called terminalccording to it every evolutionary advance was addedge by reducing the duration of the older stages, theon observations of neoteny (Gould, 2010). This wasy more general ideas of heterochrony (changes in tim-lopment) as a mechanism for evolutionary change. Itted that a new feature may appear as exaptation, whichtation but its anticipation, i.e. a feature that is avail-ful cooptation by descendants (Gould and Vrba, 1982;). These features enhance tness but do not have currentare empowered by meaning in the course of evolu-1922) called them anticipations of phylogenesis by and suggested that they play a role in phylogenetic, i.e. in time rescaling. There are various examplesns that play role as pre-adaptations, e.g. many cyclicppeared rst as casual constructs and then acquiredoles.chanisms of epigenetic inheritance were studied inese unicellular organisms represent a unique grouptwo nuclei: a small diploid micronucleus and a largeacronucleus. The latter is generated from the micronu-

mplication of the genome and heavy editing. Theus serves as the germ line nucleus but does not expresshile the macronucleus provides the nuclear RNA for

arise dLandwis realarisingarationmulticTherefof evol

Parreorgaand sorich sodescribfor DNmutatiRNA aseral rostatemno dethe trinconsisttem, pRecursbest wlowed (RNA) cated lcompoplastic

Shaas a Reaccidesystemtions. Treprodand inving nuin DNAdirectling theprocessystema way to be a

Theon theexpres(Shishkorganiand thto desctions fof biosone ofThus enetic sorganiontogeequilibresultsThe chber of acquisformation in biological evolution. BioSystems (2014),

somatic growth to the next generation (Nowacki and, 2009). This suggests that the somatic ciliate genome

epigenome, formed through templates and signals previous generations. In ciliates we have a spatial sep-

ween the edited and non-edited genome, while in ther organisms it refers more to the temporal separation.

iliates represent a unique object to study the mechanismary exibility (Landweber and Kari, 1999).

noncoding RNA molecules instruct whole-genomeion. This includes removal of nearly all noncoding DNA

the remaining fragments, producing extremely gene-c genomes (Nowacki et al., 2010). Nowacki et al. (2011)w the RNA templates provide both an organizing guiderrangements and a template that can transport somatico the next generation. They dene this biological role forculpt genomic information in cells. Thus the most gen-RNA consists in generation of possibility of new Gdel, which can be memorized in genome. In fact, there isn for the general function of all various forms of RNA in

structure of the central dogma (DNARNAprotein). Itimplementation of the dynamic exibility in the sys-ing mechanisms of generation of Gdel statements.s not possible in the dual system gene-protein, in the

can generate only a strict evolution by mutations fol-lection. In the system with the intermediate componentexibility arises and evolution appears as a sophisti-age game in which RNA becomes a part of the temporal

moderating incomplete identication and increasingetween genes and their realized functions.(2013) suggests changing our understanding of genomenly Memory subject to change by copying errors and

o an intricately formatted Read-Write (RW) data storagestantly subject to cellular modications and inscrip-

inscriptions occur over three distinct time-scales (celln, multicellular development and evolutionary change)

a variety of different processes at each time scale (form-rotein complexes, epigenetic formatting and changesuence structure). The writing capacity of the genomepends on generating new statements and empower-y meanings. Therefore it is not a direct writing but thediated logically by a generative capacity of the formal

physically by a reduction of uncertainty. There is always new interpretation to be memorized and for heredityory.enetic approach to understanding evolution is basedrity of living organization, and according to it, heredityanalization of development toward a stable nal state006). Canalization can be considered as a typical self-n process leading to complementarity between partsole (Gunji and Ono, 2012). It is generally impossible

normal genotype in terms of xed allelic states. Devia-normal phenotype characterize a space of possibilitiesms responses, and every evolutionary shift stabilizesalternative ontogenetic pathways within the system.ion is a process of continuous reparation of the ontoge-ity at the cost of increasing complication of the integraln and its each step is a compelled reorganization of the

system toward a new ultimate systems stable non- state. Increase in stability of realization of the latterrogressive remodeling of the earlier stages of ontogeny.s caused by these stabilizing processes result in a num-ifestations, such as initially labile expression of news, the remodeling of their morphogenesis with time and

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the predominant maintenance of ancestral traits in late ontogenyof the closest descendants (Shishkin, 2012).

The consistent patterns of heterochrony in relation to plantevolution were outlined by Takhtajan (1946). He noted that thephenomenamost primisive idioadaevolutionarity, and the In case of nadifference ocialization evolutionarof general dorganism istouches notthe systemative evoluticomes to betime rescalization andexample ofopment leaat the earlieplasticity.

KauffmaQ10maps andas generic morphogeninformationplating) whaction). Thenon-recursiliving beinggering dynathe transfeand corresp1998).

The maithe only souand the moheritability(Cherdantsemation, it wof the adaptsystems, whthe evolutiological struontogeny (sevolutionaralgorithms 2012). Chantime of indi

5. Biosphe

In the conal gradienThis represthe dynamtion (Nizatvia couplinUmwelt) tothe combinorganisms i

via empowering by meaning of new statements followed by rescal-ing of internal time, it is worth to explore if the temporal changesin biological processes during individual development are linked tobiospheric factors that directly affect temporal processes in biosys-

nd paolvees of ere i

geol orbitems

(19uatortitud

gher s of . Thibe dcroe

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of heterochrony are expressed in the highest degree intive groups of a given taxon. In the course of progres-ptive specialization of the phylogenetic branches, they heterochrony of characters gradually comes to equal-characters of organisms become more and more coeval.rrow one-sided specialization the strengthening of thef expression levels of separate characters occurs. Despe-opens possibilities of further evolution by increasingy plasticity. Large systematic units emerged by meansegeneration and following progressive evolution. The

subjected to profound reconstruction, which however all parts. In case of stronger correlation of characters,tic group gets more advanced on the way of idioadap-on but the phenomenon of evolutionary heterochrony

weaker. The profound evolutionary changes based oning we can nd in gametophyte reduction and special-

prolongation of the sporophyte phase. This trend is an neoteny, i.e. of the change in time of individual devel-ding to acquisition of the ability to sexual reproductionr than adult stage and resulting in a higher evolutionary

n (1993) claimed that the occurrence of positional ordered spatial heterogeneities can be understoodself-organized properties in biological systems: thus,esis includes complementary interaction of the digital

(encoding) with the non-digital information (tem-ich reads (decodes) the code (i.e. realizes reective

interaction between these two types of informationvely forms an interpretant for the semiotic system of. The information based on specic recognitions trig-mical energy-driven processes appears as non-digital;r of digital information is realized within hypercyclesonds to operation of the genetic code (Igamberdiev,

n material of evolution is the intraindividual variation,rce of which is the mechanics of morphogenesis itself,

rphological evolution can take place at an initially zero and zero adaptive value of morphological differencesv and Grigorieva, 2010). In the studies of pattern for-as shown that morphogenesis becomes a driving forceively silent, but directional evolution of the developingich seems to be the only possible way of originating ofnary novelties, both in evolution and ontogeny of bio-ctures (Cherdantsev and Scobeyeva, 2012). The linearuccession of the developmental stages) is a secondaryy phenomenon originating from cyclic self-organizingof the active shell shaping (Cherdantsev and Grigorieva,ges in cyclic processes result in rescaling of the linearvidual development.

ric factors of time rescaling

urse of evolution, biological systems recognize exter-ts and acquire a capacity of rescaling according to them.ents a continuous global adaptation process based onic negotiation between the global and local informa-o and Gunji, 2013). In this process, evolution is realizedg a part of environment recognized by the system (the

the system itself with the following transformation ofed system. The global tness landscape for all livings biosphere. While major evolutionary changes proceed

tems acan invthe ratBiosphon theEarthsbiosysMeyenthe eqwith laand hiperiodpump)it can the mamostlyare cotion inits abiohighernew ge

Sevthese clatitudspecieThe reshiftinin timeof migance bgreateATP syin fastesimplethe mitime rlogical(heteroembrysite ofThese tropicsorganient gengettingduplicaltereding new

ThegradieEarth wods ocyears. likely 2013) It is vemajor at the ing bivmost cto higsteepeformation in biological evolution. BioSystems (2014),

rticipate in setting biological time clock. Time rescaling changes in the rates at one or more of systems levels, i.e.metabolism, of protein turnover and of gene expression.nvolves oscillatory processes of different scales basedogical (plate tectonics) and astronomical (precession oft) phenomena that can directly affect time rescaling of

and determine evolutionary changes. It was shown by Q1187, 1992) that almost all taxa higher than genus haveial (tropical) origin. The average ages of taxa increasee with the tropics harboring both old and young taxalatitudes progressively lacking in younger taxa. Duringwarming they migrate to higher latitudes (equatorials process Meyen called phytospreading for plants andened as biospreading in general. At higher latitudes,volution rate decreases and evolutionary changes occurhin genera. The macroevolutionary changes in tropicsted, according to Meyen, with selective neutral salta-itions of low pressure of natural selection or at least ofonstituent. In other words, in tropical areas there is aibility of generation of uncertainties and formation ofc combinations that can be empowered by meaning.possible mechanisms of generation of heterochrony intions can be considered. The species migrated to higheruring the periods of climate warming) evolve to new

genera and only very rarely to higher taxa (families). process (in the periods of climate cooling) results inigrated species back to lower latitudes. The alterationevelopmental processes and turnover of living cycles

organisms may be achieved by variability in the bal-en the anabolic and catabolic processes, in particular bylvement of the pathways of respiration non-coupled tosis at higher latitudes. Futile recycling processes resulting cycles and lower biomass accumulations, leading torphology and smaller size (McNulty et al., 1988). Thuson of organisms to higher latitudes results in internaling: the duration of internal processes and morpho-ortions of these organisms will change. Time rescalingny), in particular, refers to the changes in duration ofesis of different organs, leading to alterations of theryonic initiation of a particular organ (heterotopy).

ges may be initially epigenetic. The migration back froming the next colder period can result in coexistence ofith different internal times but not signicantly differ-

ally and potentially keeping a possibility of crossing andile progeny, in particular if this is followed by genome. As a result, the advanced forms emerge possessingtiotemporal characteristics (archetypes) and constitut-gressive taxa.tuations of Earths climate forming evolution-drivingere particularly evident during icehouse epochs of the

the oscillations between glacial and interglacial peri-d with the periods of tens or hundreds of thousande oscillations were observed in the Pleistocene ande preceding epoch (late Pliocene) (De Schepper et al.,accompanied the origin and evolution of genus Homo.ely that similar oscillations occurred during the earlier

of icehouse climate 300 million years before present,o-Carboniferous boundary (Algeo et al., 2008). By tak-s as an example, Jablonski et al. (2006) suggested thats tend to originate in tropics and then expand outatitudes while retaining their tropical presence. Thetitudinal gradients occur in the geologically youngest

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clades and are consistent with dynamic processes involving pref-erential origination at low latitudes and poleward expansion overtime. The expansion of taxa correspond to expansion of niches,and during this expansion, the areas of refugia are formed inwhich, under a relative isolation, a secondary evolutionary pro-cess takes place increasing lower scale diversity of communitiesof these refugia. Range expansion of clades may occur via bridgespecies, which violate climate-niche conservatism to bridge thetropical-temperate boundary. Substantial time lags (5 millionyears) between the origins of tropical clades and their entry intothe temperate zone suggest that out of tropics events are rare ona per-clade basis. Clades with higher diversication rates withinthe tropics are likely to produce multiple bridge species, suggest-ing that high speciation rates promote the out of tropics dynamics(Jablonski et al., 2013). Svenning et al. (2008), by investigating palmspecies, conrmed the basic phytospreading tendencies for thisplant group. Dowle et al. (2013) further developed the concept ofgeographical pattern in evolution. They showed that species den-sity is higher in the tropics (low latitude) than in temperate regions(high latitude) resulting in a latitudinal biodiversity gradient. Thisgradient is supported by differences in latitude-dependent rates inmolecular evolution. Investigations of the metabolic backgroundof phytospreading (Allen et al., 2002; Brown et al., 2004) wereintended to provide a thermodynamic basis for the regulation ofspecies diversity and the organization of ecological communities.The main idea here is that the increased energy ow results ingeneration of metabolic bifurcations in major pathways. If the addi-tional energy, needed for closure of newly formed pathways andthus for formation of a new stable non-equilibrium state shieldingthe coherent quantum, does not strictly constrain the survival, thisresults in formation of more complicated evolutionary organization(Igamberdiev, 1999; Igamberdiev and Lea, 2002, 2006).

The reveerful enginsimilar mecplay importlar organism

Fig. 2. Biosph

and ows, accompanied by exchange of water between the oceanand the atmosphere, so the driving factor will be in switchingbetween hydrolysis and dehydration. Changes in salinity and saltcontent, temperature, electrochemical and optical characteristicsof water, ptors that deevents. Fig.biospheric cthe biosphemerging (e.times, thus

6. Conclus

The systing to Rosdescriptionnot providenew statemlimitations has its logicmal systemuncertaintygenerated sing environstructure wbuilding clof complexments perfoincreases thpatterns ofpatterns un

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of tric239.tsev, V

314tsev, Vystemsen, Persity

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rsible and oscillating biospreading represents a pow-e for evolution. Besides the equatorial pump, otherhanisms exploiting the existent natural gradients mayant role, in particular in early evolution of multicellu-s, including oscillations in the level of ocean or ebbs

eric triggering of the macroevolutionary process via time rescaling.

optimaratio. Tcoursetime rspheriin geno

Uncite

GolIgamb

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Algeo, T.oceaGeo

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Baer, K.ERee

BeloussoBios

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Brown, Jof ec

CherdanEvol

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ChristianUnivformation in biological evolution. BioSystems (2014),

H in closed water reservoirs will be among other fac-termine generation of heterochronic and heterotopic

2 schematically shows the sequence of events in theausation of evolution when changes in energy ows inre cause biospreading, leading to time rescaling and tog. via hybridization) of biological units having different

triggering the macroevolutionary process.

ion

ems having embedded internal description are, accord-en, anticipatory in the sense that the embedded

generates a model of their behavior. If the model does a correct result, they can evolve due to acquisition ofents inside the embedded description that overcomeof the existing model. Generation of new statementsal precondition in the incompleteness of internal for-

of biosystem and its physical precondition is quantum in the course of internal measurement. The newlytatements are empowered by meanings in the chang-ment. The internal time emerges in the hypercyclichen irreversible quantum measurements are used forocks with repeatable temporal patterns. The growthity is a consequence of internal quantum measure-rmed by the systems having embedded description. Ite amount of external work and generates nomothetic

spatiotemporal structures of evolving systems. Thesefold in a fractal-like manner and reproduce certainportions during their realizations such as the golden

living systems have their internal times, and in thevolution, time rescaling takes place. The processes ofing are triggered in epigenetic evolution by the bio-ameters causing time shift in metabolic processes andmobility.

erences Q12

midt (1940), Gunji et al. (2006), Rojdestvenski andv (2007) and Rosen (1978a, 1978b).

, H., Hower, J.C., Schwark, L., Herrmann, A., Heckel, P., 2008. Changes initrication during Late Carboniferous glacial-interglacial cycles. Nat.709714.wn, J.H., Gillooly, J.F., 2002. Global biodiversity, biochemical kinetics,ergetic-equivalence rule. Science 297, 15451548.28. Ueber Entwicklungsgeschichte der Thiere. In: Beobachtung und

Gebrder Borntrger, Knigsberg.., 2012. Morphogenesis as a macroscopic self-organizing process.s 109, 262279.Browne, D.E., Dur, W., Raussendorf, R., Van den Nest, M., 2009.ent-based quantum computation. Nat. Phys. 5, 1926.oly, J., Allen, A., Savage, V., West, G., 2004. Toward a metabolic theory. Ecology 85, 17711789.V.G., Kreslavsky, A.G., Severtsov, A.S., 1996. Episelective evolution.r. Rev. 11, 6987..G., Grigorieva, O.G., 2010. Morphogenetic bases and parametric sys-home evolution in plants of the genus Draba L. Russ. J. Dev. Biol. 41,

.G., Grigorieva, O.V., 2012. Morphogenesis of active shells. Biosystems328..G., Scobeyeva, V.A., 2012. Morphogenetic origin of natural variation.s 109, 299313..V., 1985. The semiotics of quantum non-locality. IMFUFA, Roskilde, pp. 60.

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775776777778779780781782783784785786787788789790791792793794795796797798



Conrad, M., 1996. Cross-scale information processing in evolution, development andintelligence. Biosystems 38, 97109.

Conway, J., Kochen, S., 2006. The free will theorem. Found. Phys. 36, 14411473.DArcy Thompson, W., 1917. On Growth and Form. Cambridge University Press,

London.Damiani, G., 2002. Metabolic hypercycles, universality and fractals in biological evo-

lution. In: Losa, G.A., Merlini, D., Nonnenmacher, T.F., Weibel, E.R. (Eds.), Fractalsin Biology and Medicine. Book Series: Mathematics and Biosciences in interac-tion, vol. III. Birkhauser, Basel, pp. 259269.

De Schepper, S., Groeneveld, J., Naafs, B.D., Van Renterghem, C., Hennissen, J., Head,M.J., Louwye, S., Fabian, K., 2013. Northern hemisphere glaciation during theglobally warm early late Pliocene. PLoS ONE 8, e81508.

Dieks, D., 1982. Communication by EPR devices. Phys. Lett. A 92, 271272.Dowle, E.J., Morgan-Richards, M., Trewick, S.A., 2013. Molecular evolution and the

latitudinal biodiversity gradient. Heredity 110, 501510.Eigen, M., Sc

OrganizatiFukano, T., H

backward-tle Dermes

Geoffroy Saintde Philoso

Goldschmidt, RGould, S.J., 201

heterochroGould, S.J., Vr

PaleobioloGulick, D., Sco

matical AsGunji, Y.-P., 1

theorem oGunji, Y.-P., H

localglobena 219, 1

Gunji, Y.P., Onasynchron

Igamberdiev, Gen. Biol.)

Igamberdiev, Obshchei B

Igamberdiev, Awork for c6573.

Igamberdiev, Atems. A sk95101.

Igamberdiev, Aof comput

Igamberdiev, and reect

Igamberdiev, Biosystem

Igamberdiev, Arelaxation

Igamberdiev, metabolism

Igamberdiev, Ain the atm

Isalan, M., 200Jablonski, D., R

of the latitJablonski, D., B

A., Valentiand thermProc. Natl.

Kirby, K.G., 19processing

Kull, K., 1998. Farr, G.L.Finnish Ac

Landweber, L.Fto a compu

Le Guyader, HChicago Pr

Letelier, J.C., Cmetabolic

Lewis, E.B., 1994. Homeosis the rst 100 years. Trends Genet. 10, 341343.Libet, B., 1985. Unconscious cerebral initiative and the role of conscious will in

voluntary action. Behav. Brain Sci. 8, 529566.Magdalef, R., 1996. Information and uncertainty in living systems, a view from ecol-

ogy. Biosystems 38, 141146.Matsuno, K., 1992. The uncertainty principle as an evolutionary engine. Biosystems

27, 6376.Matsuno, K., 1995. Quantum and biological computation. Biosystems 35, 209212.McNulty, A.K., Cummins, W.R., Pellizzari, A., 1988. A eld study of respiration rates

in leaves of arctic plants. Arctic 41, 15.Melkikh, A.V., 2014. Quantum information and the problem of mechanisms of bio-

logical evolution. Biosystems 115, 3345.Migita, M., Mizukami, E., Gunji, Y.P., 2005. Flexibility in starsh behavior by multi-

layered mechanism of self-organization. Biosystems 82, 107115.Nizato, T., Gunji, Y.P., 2013. Interactions between species and environments from

mpleti, M., obiol.i, M., Henetic022

i, M., ming389., 1970.H., 19812

M.S.,ogii (J.enskiion toenskit andnce, Tonal Senskiment,. (Ed.

rsburg., 1978el of a., 197scenc., 198ical Fo., 199., 199mind-

J.A., 2 10, 28A.A., 1. BiosyA.A., 2res asa, K., H

chaot, M.A461, M.Ae foss., Hord

961g, J.C.,ation dness. Jn, A.LArmen, V., 19

Nest, ecidabgton, ired cs, W.,803..V., Sth. Phy

799800801802803804805806807808809810811812813814815816817818819820821822823824825826827828829830831832833834835836837838839840841842843844845846847848849850851852853854855856857858859860861862863864865866867868869870871872873


huster, P., 1979. The Hypercycle: A Principle of Natural Self-on. Springer-Verlag, Berlin.amanishi, Y., Gunji, Y.P., 2004. Event detection by forward- andprediction, illustrating the analysis for behaviors of black larder bee-tes haemorrhoidalis Kster. Biosystems 78, 8191.-Hilaire, E., 1838. Notions Synthtiques, Historiques et Physiologiquesphie Naturelle. Dnain, Paris, pp. 138.., 1940. The Material Basis of Evolution. Yale Univ. Press, New Haven.0. Of coiled oysters and big brains: how to rescue the terminology ofny, now gone astray. Evol. Dev. 2, 241248.

ba, E.S., 1982. Exaptation a missing term in the science of form.gy 8, 415.tt, J. (Eds.), 2010. The Beauty of Fractals: Six Different Views. Mathe-sociation of America, Washington.994. Autonomic life as the proof of incompleteness and Lawveresf a xed point. Appl. Math. Comput. 61, 231267.aruna, T., Sawa, K., 2006. Principles of biological organization:

al negotiation based on material cause. Phys. D: Nonlinear Phenom-52167.o, R., 2012. Sociality of an agent during morphogenetic canalization:ous updating with potential resonance. Biosystems 109, 420429.A.U., 1985. Time in biological systems. Zhurnal Obshchei Biologii (J.

46, 471482 (in Russian).A.U., 1986. Problems of description of epigenetic systems. Zhurnaliologii (J. Gen. Biol.) 47, 592600 (in Russian)..U., 1993. Quantum mechanical properties of biosystems: a frame-omplexity, structural stability and transformations. Biosystems 31,

.U., 1998. Time, reectivity and information processing in living sys-etch for the unied information paradigm in biology. Biosystems 46,

.U., 1999. Foundations of metabolic organization: coherence as a basisational properties in metabolic networks. Biosystems 50, 116.A.U., 2004. Quantum computation, non-demolition measurements,ive control in living systems. Biosystems 77, 4756.A.U., 2007. Physical limits of computation and emergence of life.s 90, 340349..U., 2012. Biomechanical and coherent phenomena in morphogenetic

processes. Biosystems 109, 336345.A.U., Lea, P.J., 2002. The role of peroxisomes in the integration of

and evolution of land plants. Phytochemistry 60, 651674..U., Lea, P.J., 2006. Land plants equilibrate O2 and CO2 concentrationsosphere. Photosynth. Res. 87, 177194.9. Gene networks and liar paradoxes. Bioessays 31, 11101115.oy, K., Valentine, J.W., 2006. Out of the tropics: evolutionary dynamicsudinal diversity gradient. Science 314, 102106.elanger, C.L., Berke, S.K., Huang, S., Krug, A.Z., Roy, K., Tomasovych,ne, J.W., 2013. Out of the tropics, but how? Fossils, bridge species,al ranges in the dynamics of the marine latitudinal diversity gradient.

Acad. Sci. U. S. A. 110, 1048710494.98. Exaptation and torsion: toward a theory of natural information. Biosystems 46, 8188.Baerian biology: evolution by means of organisms interpretation. In:, Oksala, T. (Eds.), Emergence, Complexity, Hierarchy, Organization.ademy of Technology, Espoo, pp. 197200.., Kari, L., 1999. The evolution of cellular computing: natures solutiontational problem. Biosystems 52, 313.., 2004. Geoffroy Saint-Hilaire: A Visionary Naturalist. University ofess, Chicago.rdenas, M.L., Cornish-Bowden, A., 2011. From LHomme Machine to

closure: steps towards understanding life. J. Theor. Biol. 286, 100113.

incoNowack

MicrNowack

epig2214

Nowackgram367

Ohno, S.Pattee, H

23, 2Radyuk,

BiolRojdestv

relatRojdestv

menScienati

RojdestvsureYu.MPete

Rosen, Rmod

Rosen, Rsene

Rosen, Rolog

Rosen, RRosen, R

the Shapiro,

Rev.Sharov,

tionSharov,

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tumShishkin

37, 1Shishkin

in thSteel, M

332,Svennin

sicrich

TakhtajaSci.

TurchinVan den

undWaddin

acquWootter

802Yudin, V

Matformation in biological evolution. BioSystems (2014),

e information. Biosystems 111, 145155.Landweber, L.F., 2009. Epigenetic inheritance in ciliates. Curr. Opin.

12, 638643.aye, J.E., Fang, W.W., Vijayan, V., Landweber, L.F., 2010. RNA-mediated

regulation of DNA copy number. Proc. Natl. Acad. Sci. U. S. A. 107,144.Shetty, K., Landweber, L.F., 2011. RNA-mediated epigenetic pro-

of genome rearrangements. Annu. Rev. Genomics Hum. Genet. 12,

. Evolution by Gene Duplication. Springer-Verlag, New York.89. The measurement problem in articial world models. Biosystems

90. 2001. On biological essence of golden section. Zhurnal Obshchei

Gen. Biol.) 62, 403409 (in Russian)., I., Cottam, M.G., 2000. Time rescaling and generalized entropy in

the internal measurement concept. Physica A 278, 150160., I., Igamberdiev, A.U., 1999. Recursive embedding, quantum measure-

uncertainty principle. In: Hall, M.L.W., Wolby, J. (Eds.), Humanity,echnology: The Systemic Foundations of the Information Age. Inter-ociety for System Studies, Asilomar, pp. 347348., I.V., Igamberdiev, A.U., 2007. Recursive embedding, quantum mea-

uncertainty principle, and evolution of biological systems. In: Shilkov,), Viktor Alexandrovich Shtoff and Modern Philosophy of Science. St.

State University Publishers, pp. 190204 (in Russian).a. On anticipatory systems. I. When can a system contain a predictivenother? J. Soc. Biol. Struct. 1, 155162.8b. Feedforwards and global system failure general mechanism fore. J. Theor. Biol. 74, 579590.5. Anticipatory Systems. Philosophical, Mathematical and Method-undations. Pergamon Press, New York.1. Beyond dynamical systems. J. Soc. Biol. Struct. 14, 217220.3. Drawing the boundary between subject and object comments onbrain problem. Theor. Med. 14, 89100.013. How life changes itself: the Read-Write (RW) genome. Phys. Life7323.991. Self-reproducing systems structure, niche relations and evolu-stems 25, 237249.009. Coenzyme autocatalytic network on the surface of oil micro-

a model for the origin of life. Int. J. Mol. Sci. 10, 18381852.u, B.L., 1995. Decoherence, delocalization, and irreversibility in quan-

ic systems. Phys. Rev. E 52, 24972509.., 2006. Development and lessons of evolutionism. Russ. J. Dev. Biol.62.., 2012. Systemic grounds of morphogenesis and their manifestationil record. Paleontol. J. 46, 331342.ijk, W., Smith, J., 2013. Minimal autocatalytic networks. J. Theor. Biol.07.

Borchsenius, F., Bjorholm, S., Balslev, H., 2008. High tropical net diver-rives the New World latitudinal gradient in palm (Arecaceae) species

. Biogeogr. 35, 394406.., 1946. On the evolutionary heterochrony of characters. Proc. Acad.ian SSR 5, 7986.77. Phenomenon of Science. Columbia University Press, New York.M., Briegel, H.J., 2008. Measurement-based quantum computation andle logic. Found. Phys. 38, 448457.C.H., 1959. Canalization of development and genetic assimilation ofharacters. Nature 183, 16541655.

Zurek, W., 1982. A single quantum cannot be cloned. Nature 299,

artzev, E.S., 2012. The Fibonacci fractal is a new fractal type. Theor.s. 173, 13871402.

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Time rescaling and pattern formation in biological evolution1 Introduction2 Quantum measurement, time, and growth of complexity3 Nomothetic constraints of the evolutionary process4 Rescaling of internal time and epigenetic evolution5 Biospheric factors of time rescaling6 ConclusionUncited referencesReferences

time rescaling and pattern formation in biological evolution

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