Download The Nature of the Organism: Life Has a Life of Its Own

The Nature of the Organism
Life Has a Life of Its Own
DANIEL R. BROOKSa
Department of Zoology, University of Toronto, Toronto, Ontario M5S 3G5, Canada
ABSTRACT: The question of closure in biological systems is central to understanding the origins of the biological variation and complexity upon which
various forms of selection act. Much of evolutionary theory, especially in the
second half of the twentieth century, is concerned with the consequences of environmental selection acting on biodiversity, but neglects questions of the origin of that diversity. This has permitted us to act as if an explanation of
consequences was the ultimate explanation in biology. However, Darwin
understood that evolution was both information driven and information constrained. The link between evolutionary constraints and closure can be profitably explored by starting with Darwin’s notion of the primacy of “the nature
of the organism” over “the nature of the conditions” articulated in the sixth
edition of Origin of Species. Contemporary ideas of self-organization, emergence, complexity, and inherent (developmental and phylogenetic) constraints
can be seen as an elaboration and refinement of Darwin’s views if we adopt the
following perspective: (1) information is cheap, not costly, to produce, but may
have costly consequences; and (2) information is produced by systems that are
informationally closed but remain thermodynamically open.
INTRODUCTION
We are inundated daily by cheaply produced, yet organized information, transmitted without regard for our capacity to absorb it. If we tried to accumulate all of
it, it would overwhelm us. How do we deal with this assault? We engage in acts of
selection, destroying the information that we do not want to provide space for the
information we desire. Even the amount of desirable information is growing rapidly
and would overwhelm us if we did not find ways to store and transmit information
more efficiently. Thus it is with life. Every day the planet is inundated by cheaply
produced, yet highly organized and redundant biological information, transmitted in
the form of organisms without regard for the planet’s capacity to support it. Most of
that information is eliminated, but the biosphere houses enormous biocomplexity,
suggesting the evolution of novel ways to store and transmit biological information
more efficiently.
For many years, evolutionary biologists have sought ways to show that the selection
filtering process could also be responsible for the production of increasingly organized,
complex, and variable biological information. This effort has been unsuccessful. The
aAddress for correspondence: Department of Zoology, University of Toronto, Toronto, ON
M5S 3G5 CANADA. Voice: 416-978-3139; fax: 416-978-6665.
[email protected]
257
258
ANNALS NEW YORK ACADEMY OF SCIENCES
organizing principles for storing and transmitting information electronically are not
embodied in the delete button that eliminates unwanted information. Likewise, the
causal interaction between selection processes and biological information is simplifi cation rather than organization. Selection processes eliminate organisms, they do not
measure, interpret, create, organize, or add to them. They are causally important in constraining evolution, but they are not creative. They are not writers but editors, not sculptors but art critics, not factory assemblers but quality control assessors. Recently, there
has been interest in the notion that the organisms themselves are the source of the
organization upon which selection acts. 1–31 This perspective, based on the notion that
organisms are functional wholes with respect to the way they engage their surroundings, as well as with respect to their internal organization, has an interesting history. It
may also hold the key to developing a more inclusive, or unified, evolutionary theory.
THE NATURE OF THE ORGANISM
The Basic Units of Selection
Long before the advent of modern evolutionary thinking in the nineteenth century, organisms were recognized as a primary focus for observation and explanation of
biological systems. Darwin32 extended this tradition by reserving a central role for
organisms and organismal diversity in his theory of evolution by natural selection.
He believed that evolutionary change resulted from the interaction of two factors,
which he called “the nature of the organism” and “the nature of the conditions”. He
proposed that the nature of the organism
…seems to be much more the important; for nearly similar variations sometimes arise
under, as far as we can judge, dissimilar conditions; and, on the other hand, dissimilar
variations arise under conditions which appear to be nearly uniform.
Darwin thought that organisms were historically and developmentally cohesive
wholes and, therefore, it was in the “nature of the organism” to produce offspring
that were all highly similar (but not identical) to each other and to their parents and
other ancestors. He also postulated that reproduction produced variation without
regard for environmental conditions and, therefore, it was in the “nature of the organism” to produce these offspring in numbers far exceeding the resources available
for their support. When this inherent overproduction produced variety in critical
characters, natural selection preserved the versions that were functionally superior
in that particular environmental context (adaptations). Whenever an environment
changes, those organisms that already had the adaptations necessary to survive
would do so, whereas those lacking appropriate adaptations would not. Selection did
not create the adaptations, it only determined which adaptations, if any, would be favored for survival. Thus, production of organismal diversity required that organisms
be at once autonomous from, and sensitive to, the environment. Darwin’s perspective
contrasted sharply with Lamarck’s proposal that adaptation was an immediate and
directed response by organisms to their surroundings. Lamarck also believed that the
nature of the organism was important in the production of diversity, but only because
all organisms have the same ability to change according to their needs. Hence,
whereas Darwin postulated that the “nature of the organism” included autonomous,
BROOKS: NATURE OF THE ORGANISM
259
self-regulating properties, Lamarck believed that the “nature of the organism” was
to be directly and completely connected to the environment.
The distinction between Lamarckian adaptationism and Darwinian selectionism
became increasingly blurred in the second half of the century, as biologists focused
more attention on parts of organisms, and less on organisms as wholes. This movement, driven by the successes of population genetics and the development of molecular methods, may have been an unconscious response to discoveries of the
developmental complexities underlying the transition from DNA to phenotypes;
complexities that threatened to swamp theories based upon the mantra of a one
gene–one trait–one selection vector. Whatever the reasons, evolutionary biology lost
Darwin’s panoramic view of biological diversity.
Organisms as Energy Flow Systems
Lotka33,34 was among the first twentieth century authors to discuss biological
systems, including organisms, in terms of energy flows and energy partitioning. He
recognized that biological systems persist in space and time by transforming energy
from one state to another in ways that generate and maintain organized structure.
This is manifested through heat-generating transformations, involving a net loss of
energy from the system, usually in the form of heat, and conservative transformations, involving changing free energy into stored states (i.e., structure).8–9,25
Because all conservative transformations in biological systems are coupled with heat
generating transformations, there is a heavy energetic cost associated with maintaining structure. Lotka33 suggested that the interplay between flow and partitioning of
energy in biological systems slows the rate at which energy stored by conservative
transformations is degraded by heat-generating transformations.
The development of nonequilibrium thermodynamics in the second half of this
century35,36 has allowed us to generalize Lotka’s view of the “nature of the organism”. Living systems are nonequilibrium thermodynamic systems, exchanging matter and energy irreversibly with their surroundings and maintaining themselves in far
from equilibrium conditions. The basic features of nonequilibrium systems can be
summarized heuristically by
dS = deS + diS, diS > 0.
Total entropy changes (dS) are partitioned into deS, which measures exchanges
between the system and its surroundings (changes in the surroundings); and diS,
which measures production by irreversible processes internal to the system (changes
within the system).35,36 We can also call this heuristic equation the cost of living for
organisms, because all organisms must take in high grade energy and matter and dissipate lower grade energy to their surroundings in order to survive. Energy degraded
in the uptake of raw materials from the surroundings into the system is dissipated
into the surroundings (deS). These exchanges are accompanied by a great deal of
waste; hence, deS is very large compared with diS.
Internal production ( diS) includes: (1) dissipation from the system, called the
external dissipation function ( ψα, or heat-generating transformations). Heatgenerating processes occur when energy and entropy flow in opposite directions,
entropy production tending to move the system towards disordered states; and (2) dissipation within the system, called the bound dissipation function ( ψµ, or conservative
transformations). Conservative transformations are characterized by energy and
260
ANNALS NEW YORK ACADEMY OF SCIENCES
entropy flowing in the same direction, entropy production being retained within the
system and tending to move the system towards more structured states. In biological
systems, ψµ can be further separated into allocations for accumulating biomass ( ψ µb )
and allocations for accumulating genealogical information ( ψ µi ). Heuristically7
d i S = ψ α + ψ µb + ψ µi .
Thus, organisms have a dualistic nature. As open thermodynamic systems, they
must simultaneously interact with their surroundings and perform critical functions
internally. They maintain themselves in a viable state by exchanging matter and energy irreversibly with their surroundings, taking in relatively high grade energy and
using it to perform useful work within themselves. This requires sensing of, and
causal engagement with, the surroundings, mediated by a physical distinction between the organism and its surroundings. For all organisms, this boundary is provided by cell membranes, which are simultaneously physical barriers between the
inside and outside of the organism and highly selective mechanisms for modulating
the exchange of matter and energy between the organism and its surroundings.
Organisms as Information Systems
Information theory was developed from two perspectives, communications theory and physical measurement theory. These perspectives overlap in the belief that
information is (1) anything transmitted from a source through a channel to a receiver
and (2) an abstraction rather than a material part of the system. In communications
theory, the amount of information sent from a source is calculated by using a statistical entropy function. Errors in transmission can result from poor encoding at the
source or from noise in the transmission channel. The meaningful information is that
subset of information transmitted that is actually recorded by the receiver (there may
or may not be a separate decoder). Thus, processes affecting transmission and reception of information thus decrease the entropy of the message from its maximal value
at the source. Physical entropies are expected to increase as a result of work done on
the system, so the communications view of entropy is often considered nonphysical.
Gatlin37 attempted to relate the communications view of information to biological systems. She argued that the genetic system was the source, reproduction and ontogeny the channel, and the environment the receiver. Genetic information thus
became phenotypic signals as a result of reproduction and ontogeny, and become
meaningful biological information as a result of environmental selection on the phenotypes. Brooks and McLennan38 pointed out, however, that the environment cannot
be a receiver in a physical sense, because its only causal interaction with biological
information is the possible elimination of some of it; it does not measure or interpret
the information. Rather, the environment acts as interference in the channel, or as a
delete button monitoring incoming messages, eliminating relatively less fit organisms in a population. This seems to reinforce the notion that the communications theory view of information is nonphysical, and hence nocausal, and nonexplanatory.
If biological information is a material part of biological systems, however, it is
possible for biological systems to be their own sources and receivers.15,19,20,24,28,38
Gatlin construed the receiver as part of the surroundings—i.e., localized in space.
Organisms are localized in time as well as in space, so the receiver can be a time. The
source is a genetic system at time t0, the channel is reproduction and ontogeny, and
BROOKS: NATURE OF THE ORGANISM
261
the receiver is the same genetic system at any given time t1, …, tn; thus, the receiver
is temporally distinct from the source. If an information source precedes its receiver
in time, it can produce the system that acts as receiver and that system can then become a source itself. This perspective has been used by information theorists to design self-correcting computer programs, programs that can enhance their own
abilities to store and transmit information efficiently. This reinforces the biological
view, because DNA has significant self-repair capabilities.
Physical measurement theory distinguishes free information, an abstraction
involved in descriptive exercises from bound information, referring to material properties of the system (but not stating that information is a material part of the system
per se).39 Bound information is determined with respect to the complexions
(microstates) of the system, and is calculated by using a statistical entropy function.
In contrast to communications theory, bound information is expected to exist only in
systems for which there is a non-arbitrary microstate/macrostate distinction. Bound
information is defined by
I = Hmax − Hobs,
where Hmax refers to the totally relaxed state of the system (usually estimated by a
randomization of the observed components of the system). Brillouin defined I as
negentropy, which is converted into bound information by measurement (measuring
devices are receivers); hence, negentropy is equal to information. Thus, information
is physical, but is not a material part of the system.
Biological information has communication functions and a physicochemical
basis that is a material part of the system. What is needed is an account of biological
information that is (1) physically realistic (can be shown to have an objective basis),
(2) intrinsic to the system (is a material part of the system) rather than to devices for
measuring the system, and (3) can grow spontaneously over time. The two basic issues with respect to information and entropy are (1) whether information can be a
material part of a system rather than just an abstract representation and (2) whether
or not there is an objective difference between macrostates and microstates in calculations of informational entropies. In an effort to solve this problem, Collier10–13
proposed that physical (equal to material) information systems occur as arrays, or
multidimensional messages, in which macrostate and microstate distinctions are
distinguished nonarbitrarily. This view is related to concepts of the causal capacity
of a system, or to its ability to impose distinctions on its surroundings. In a way, the
emphasis is on how the system produces effects on measuring devices and not on
how the measuring devices are affected. In order for this information to be related to
physical concepts there must be (1) a physical (material) basis for the information,
(2) an energetic cost in producing the information, and (3) a real (nonarbitrary)
macrostate/microstate distinction. Since the discovery of the chemical structure and
function of DNA, there has been a material basis for biological information that
satisfies (1).
Energy dissipated from the system as a result of work done (heat-generating transformations, or ψα of diS) is intropy,12 which stands for internal entropy or overhead.40
Energy converted into structure (conservative transformations, or ψµ of diS) is enformation,12 standing for encoded information. Conservative processes within biological
systems are coupled with heat-generating processes, so that there is an energetic cost
associated with the production and maintenance of biological information. Intropy
262
ANNALS NEW YORK ACADEMY OF SCIENCES
and enformation are interconvertable (e.g., energy brought in from the surroundings
can be converted into glycogen, which can then be converted into heat). Intropy is converted into enformation by cohesive properties of the system. Cohesion is thus analogous to inertia, which provides resistance to change. Cohesive properties, ranging
from molecular affinities to cell–cell adhesion to genetic compatibility, mate recognition, and genealogy, also provide resistance to fluctuations from lower levels, allowing
macroscopic properties to emerge. The major transitions in evolution41 are all associated with the emergence of new forms of cohesion that permit information to be stored
and transmitted more efficiently. Cohesive properties provide the key to understanding
microstate/macrostate distinctions in biological systems.
Microstate/macrostate distinctions are determined objectively by part/whole associations. The number of accessible microstates is increased by the production of
new components, either at a given level or by opening up new levels of organization.
Biological systems accomplish this by conservative transformations. For example,
autocatalytic processes producing monomers make “monomer space” available for
molecular evolution. Some monomers have high chemical affinities for each other
and spontaneously clump into dimers and polymers. Once polymers begin to form,
“polymer space” becomes available to the evolving system. At this level, polymers
are macrostates, and monomer and dimer distributions are microstates. Causal interactions among polymers create new levels of organization in which polymer distributions are the microstates, new levels of organization are the macrostates, and so
on. Each new functional level creates a hierarchy of increasing structural intricacy,
manifested by increasing allocation of the entropy production in structure. Therefore, the allocation of diS to ψµ might be proportional to increases in entropy due to
the expansion of phase space resulting from the creation of new possible microstates.
A protein coding unit might be considered a macrostate, whereas all the actual
sequences that code for that protein would be the microstates; a locus could be a
macrostate, and all alleles corresponding to that locus the microstates; phenotypes
could be macrostates, and all genotypes corresponding to a given phenotype would
be microstates.10,42,43 This formulation answers objections that biological informational entropies do not include a macrostate/microstate distinction; Wicken44 first
noted that this was a critical issue to be resolved and it remains problematical for
those who fail to appreciate the relevance of the “nature of the organism”.45 Encoded
information is also the carrier of the cohesive properties; thus, production of biological information involves simultaneous production of variation and constraints, ensuring that genealogy will be a combination of continuity and change.
SUMMARY
Organisms are physical information systems, a type of nonequilibrium thermodynamic system, that are open to exchanges of matter and energy but that maintain
a relatively closed internal information system that functions to reproduce the
system and to perpetuate lineages through time. They are able to impose themselves
and their functions on their surroundings and, thus, are self-stabilizing and selforganizing. They produce organized complexity cheaply (diS is small compared to
deS and the portion of diS allocated for the information system is small; in part,
BROOKS: NATURE OF THE ORGANISM
263
because a small number of chemical templates are used to generate many organisms), variably (because even chemical templates are subject to the statistical mechanical vagaries of the Second Law of Thermodynamics), and functionally
(because organisms must exchange matter and energy with their surroundings in
order to maintain themselves), but without regard for details of the surroundings
(because the information system is embodied in relatively autonomous internal
chemical production, diS, of the system). As the source and receiver of organized
information, they can be the embodiment of the organizing principles for that information. Thus, biological systems transmit information through, not to, their surroundings. This supports Darwin’s view that it is the (autonomous, selfish, closed, or
isolated) nature of the organism that creates the necessary conditions for selection
processes to occur.
Treating biological systems as physical information systems provides a causal
basis for the origin of selection processes consistent with their well documented consequences. All organisms are intimately tied together in the structure of the
biosphere, because they are all simultaneously parts of larger genealogical and ecological wholes. The significance of the duality of organismal diversity is most apparent in the recognition that new types of organisms are derived from preexisting
organisms, but at the same time, almost all organisms make extensive use of the
biodiversity that predated their origins. Newly evolved organisms always have an
impact on preexisting ones. Because it is in the nature of the organism to be relatively autonomous from its surroundings, these interactions are not necessarily positive,
often taking the form of “conflicts of interest”. The evolutionary resolution of these
conflicts of interest has produced an increasingly complex biosphere.41 Selection
processes originate as a result of the necessity that biological systems obtain matter
and energy from their surroundings, coupled with the relative autonomy of their information systems, which permits production of organisms regardless of the details
of their surroundings. Without the constraints provided by this autonomy, there
would be no selection; at the same time, however, constraints provide systems with
macroscopic properties that limit the ways in which, and the extent to which, the system will respond to selection. Each major transition in evolution has been associated
with the emergence of organisms, and by extension the entire biosphere, with enhanced abilities to produce, maintain, and transmit information cohesively, and also
associated with the emergence of novel forms of selection resulting from the evolution of those new organisms.41 In this way, each newly evolved form of organism becomes intimately involved with both local and global ecology, maintaining the
biosphere as a relatively isolated system with its own windows of vitality.46
ACKNOWLEDGMENTS
I thank Gertrudis Van de Vijver and Jerry Chandler for the opportunity to participate in the Ghent conference and to present these ideas, although responsibility for
grievous errors rests solely with me. Funds for this study were provided by an operating grant from the Natural Sciences and Engineering Research Council of Canada.
264
ANNALS NEW YORK ACADEMY OF SCIENCES
REFERENCES
1. B AK, P. 1996. How Nature Works: The Science of Self-Organized Criticality. Copernicus. New York.
2. B ROOKS, D.R. 1990. The unified theory, macroevolution, and historical ecology. In
The Plant Diversity of Malesia. P. Baas et al., Eds. :379–386. Kluwer. Amsterdam.
3. B ROOKS, D.R. 1992. Incorporating origins into evolutionary theory. In Undertsanding
Origin: Contemporary Ideas on the Genesis of Life, Mind and Society. F. Varela &
J.P. Dupuy, Eds. :191–212. Reidel/Kluwer Associates. Amsterdam.
4. B ROOKS, D.R. 1994. Entropy, information and evolving biological systems. Theor.
Hist. Sci. 4: 31–49.
5. B ROOKS, D.R. 1997. Biological evolution as a microcosm of cosmological evolution.
Bridges 4: 9–35.
6. B ROOKS, D.R. 1998. The unified theory of evolution and selection processes. In Evolutionary Systems: Biological and Epistemological Perspectives on Selection and SelfOrganization. G. Van de Vijver, S.N. Salthe & M. Delpos, Eds. :113–128. Kluwer
Academic Publ. Dordrecht.
7. B ROOKS, D.R. & E.O. W ILEY. 1988. Evolution as Entropy: Toward a Unified Theory
of Biology, 2nd edit. University of Chicago Press. Chicago.
8. B ROOKS, D.R., J. C OLLIER, B.A. M AURER, J.D.H. S MITH & E.O. W ILEY. 1989.
Entropy and information in evolving biological systems. Biol. Philos. 4: 407–432.
9. B ROOKS, D.R. & D.A. M CL ENNAN. 1991. Phylogeny, Ecology and Behavior: A
Research Program in Comparative Biology. University of Chicago Press. Chicago.
10. C OLLIER, J. 1986. Entropy in evolution. Biol. Philos. 1: 5–24.
11. C OLLIER, J. 1988. The dynamics of biological order. In Entropy, Information and Evolution: New Perspectives on Physical and Biological Evolution. B. Weber,
D.J. Depew & J.D. Smith, Eds. :227–242. MIT Press. Cambridge, MA.
12. C OLLIER, J. 1990. Two faces of Maxwell’s demon reveal the nature of irreversibility.
Stud. Hist. Philos. Sci. 21: 257–268.
13. C OLLIER, J. 1998. Information increase in biological systems: how does adaptation fit?
In Evolutionary Systems: Biological and Epistemological Perspectives on Selection
and Self-Organization, G. Van de Vijver, S.N. Salthe & M. Delpos, Eds. :129–140.
Kluwer Academic Publ. Dordrecht.
14. C OWAN, G., D. P INES & D. M ELZNER, Eds. 1994. Complexity: Metaphors, Models and
Reality. Addison-Wesley. Reading, MA.
15. C SANYI, V. 1989. Evolutionary Systems and Society: A General Theory. Duke University Press. Durham, NC.
16. D EPEW, D. & B. W EBER. 1995. Darwinism Evolving. Bradford Books (MIT). Cambridge, MA.
17. G LADYSHEV, G.P. 1996. Thermodynamic direction of biological evolution: model and
reality. Izvestiya akademii nauk seriya biologicheskaya 4: 389–397.
18. H OLLAND, J. 1995. Hidden Order: How Adaptation Builds Complexity. AddisonWesley. Reading, MA.
19. K AMPIS, G. 1991. Self-Modifying Systems in Biology and Cognitive Science: A New
Framework for Dynamics, Information and Complexity. Pergamon. Oxford.
20. K AMPIS, G. 1998. Evolution as its own cause and effect. In Evolutionary Systems:
Biological and Epistemological Perspectives on Selection and Self-Organization,
G. Van de Vijver, S.N. Salthe & M. Delpos, Eds. :255–265. Kluwer Academic Publ.
Dordrecht.
21. K AUFFMAN, S.A. 1993. The Origins of Order: Self-organization and Selection in Evolution. Oxford University Press. New York.
22. M ATSUNO, K. 1989. Protobiology: Physical Basis of Biology. CRC Press. Boca Raton,
Florida.
23. M ATSUNO, K. 1995. Consumer power as the major evolutionary force. J. Theor. Biol.
173: 137–145.
BROOKS: NATURE OF THE ORGANISM
265
24. M ATSUNO, K. 1998. Competence of natural languages for describing the physical origin of life. In Evolutionary Systems: Biological and Epistemological Perspectives on
Selection and Self-Organization, G. Van de Vijver, S.N. Salthe & M. Delpos, Eds.
:295–306. Kluwer Academic Publ. Dordrecht.
25. M AURER, B.A. & D.R. B ROOKS. 1991. Energy flow and entropy production in biological systems. J. Ideas 2: 48–53.
26. N IKLAS, K.J. 1999. Evolutionary walks through a land plant morphospace. J. Exper.
Bot. 50: 39–52.
27. O DLING-S CHMEE, F.J., K.N. L ALAND & M.W. F ELDMAN. 1996. Niche construction.
Amer. Nat. 86: 309–326.
28. R OCHA, L.M. 1998. Selected self-organization and the semiotics of evolutionary systems. In Evolutionary Systems: Biological and Epistemological Perspectives on
Selection and Self-Organization, G. Van de Vijver, S.N. Salthe & M. Delpos, Eds.
:341–358. Kluwer Academic Publ. Dordrecht.
29. S ALTHE, S.N. 1985. Evolving Hierarchical Systems: Their Structure and Representation. Columbia University Press. New York.
30. S ALTHE, S.N. 1993. Development and Evolution: Complexity and Change in Biology.
MIT Press. Boston, MA.
31. S ALTHE, S.N. 1998. The role of natural selection theory in understanding evolutionary
systems. In Evolutionary Systems: Biological and Epistemological Perspectives on
Selection and Self-Organization, G. Van de Vijver, S.N. Salthe & M. Delpos, Eds.
:13–20. Kluwer Academic Publ. Dordrecht.
32. D ARWIN, C. 1872. The Origin of Species. 6th edition. John Murray. London.
33. L OTKA, A.J. 1913. Evolution from the standpoint of physics, the principle of the persistence of stable forms. Sci. Amer. Suppl. 75: 345–346, 354, 379.
34. L OTKA, A.J. 1925. Elements of Physical Biology. Williams and Wilkins. Baltimore,
Maryland.
35. P RIGOGINE, I. & J.M. W IAME. 1946. Biologie et thermodynamique des phénomènes
irréversìbles. Experientia 2: 451–453.
36. P RIGOGINE, I. 1980. From Being to Becoming. W.H. Freeman. San Francisco.
37. G ATLIN, L.L. 1972. Information Theory and the Living System. Columbia University
Press. New York.
38. B ROOKS, D.R. & D.A. M CL ENNAN. 1990. Searching for a general theory of biological
evolution. J. Ideas 1: 35–46.
39. B RILLOUIN, L. 1962. Science and Information Theory. 2nd edit. Academic Press. New
York.
40. U LANOWICZ, R.E. 1986. Growth and Development: Ecosystems Phenomenology.
Springer-Verlag. New York.
41. M AYNARD S MITH, J. & E. S ZATHMARY. 1995. The Major Transitions in Evolution.
W.H. Freeman Spektrum. Oxford.
42. L AYZER, D. 1978. A macroscopic approach to population genetics. J. Theor. Biol. 73:
769–788.
43. L AYZER, D. 1980. Genetic variation and progressive evolution. Amer. Nat. 115: 809–
826.
44. W ICKEN, J.S. 1987. Evolution, Thermodynamics and Information: Extending the Darwinian Paradigm. Oxford University Press. Oxford.
45. K HALIL, E.L. 1995. Ecological economics and ecological Darwinism. J. Biol. Syst. 3:
1211–1244.
46. U LANOWICZ, R.E. 1997. Ecology: The Ascendant Perspective. Columbia University
Press. New York.