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Chapter
Fourteen
Multi-cellular
Organismic-Population Systems
The multi-cellular organization of eukaryotic cells resulted in the
evolution of an entirely new level of systems organization of living systems
that can be referred to as organismic-population systems. One of the key
attributes of these systems is the process of the specialization of function of
cells through progressive mitosis, and the developmental differentiation of
organismic organization of these cells. This remains one of the unsolved
mysteries of the contemporary biological sciences. It is unknown clearly how DNA
structures work to control the growth and development and maturation of the
individual multi-cellular organism. The process in the first few hours seems
remarkably identical for all plants and animals. But the outcomes are remarkable
different for all species of organism that ever existed by the final stages of
gestational development. This level of articulation of living systems is thought
to have emerged sometimes between 1 and .5 billion years ago, as an immedite
precursor of the Cambrian Explosion of organismic life forms on earth. It
represented a revolutionary saltational jump in the organization of life and in
evolutionary development of living systems.
What is quite evident is this process of the organiismic differentiation
in the development of multicellular organisms that confer properties and
functions on the organism as a whole individual, highly integrated, is part of a
kind of living system that is little understood in terms of its control
functions and pathways of articulation.
Consideration of multicellular organisms as systems
brings us to the individual and, indirectly, the species-population level of the
organization of living systems. We can refer to the individual level of the
multi-cellular organism as the organiismic level of living systems, which are
distinguished by the functional and organismic differentiation and
specialization of cells to certain organ systems the result of which integration
results in one or more emergent properties that are associated with the organism
as an entire integrated entity, or living individual.
These emergent properties that are the consequence of
systems integration of entire organ systems, with distinctive specialized tissue
cells, confer adaptive advantages to the individual as well as reproductive
advantages to the specific population. It comes as a profound paradox that
natural selection of traits for multi-cellular organisms is on the basis of
phenotypic expression of these emergent organiismic properties, probably
controlled pleiotropically and polygenically, such that point mutation becomes
either unproductive or counterproductive to such expression. Genetic reshuffling
of haploid sex cells and sexual reproduction confer a level of genetic
variability for multicellular organisms that would otherwise be missing.
Most natural selection and evolutionary changes in
fact has occurred with multicellular organisms that reproduce sexually, and that
evolve rapidly in terms of the phenotypic expression of the organiismic
properties associated with the behavior and response patterning of individual
organisms.
We can refer to species specific starter cells, which
grow and colonize in patterns of developmental differentiation to create a
specific individual organism, that is defined by emergent properties from organ
system integration derived from the differential functioning of these cells.
There is a unity of all multi-cellular organisms in that the original starter
cells have a common identity. It is the ontological developmental outcomes that
the distinct characteristics of species specific organisms emerges.
Sexual reproduction provided another revolutionary
boost in the development of multi-cellular life forms, for this speicalized form
of reproduction greatly amplified gene-reshuffling that enhanced the individual
variability of complex multi-cellular organisms, conferring in general an
adaptive and long term evolutionary advantage upon such popoulations that were
sexually reproduced from both male and female progenitors.
The entire evolutionary direction in the rise of
multicellular organisms was the movement away from rapid rates of reproduction
towards increasingly differentiated and specialed modalities of organismic
reproduction that conferred greater K or equilibrium to the resulting
individuals and their populations of which they were a part.
Multicellular organisms are composed exclusively of
eukaryote cells, with true nucleus and cellular organelles that make them larger
and more complex systems than their bacteria cousins. If cells are the
prototypical system in many basic respects, then multi-cellular organisms
represent surely the epitome of the emergent properties possible with systems
integration. Multicellular organisms are in an analytical sense nothing but bags
of miscellaneous kinds of cells. These collections of cells have amazing
properties--locomotion, sophisticated perception of the environment, some level
of intelligence which enables the processing and response to the environment as
a whole. All of these properties by which multicellular organisms are identified
form the basis by which we define and identity these organisms as whole and
complete. Another way of looking at this is to see that if we remove any part of
such an organism, then there is surely some critical loss of functional
properties.
The cells that compose these organisms become highly specialized and
differentiated in function, and perform functions that go beyond that of
bacteria or single celled organisms. There has been an evolutionary trade-off in
independence of function for the enhanced survivability of the functional
properties that are conferred upon the organism as a whole. The internal
environment of the organism provides a "metasystem" context that
appears suitable for the survival and functioning of these highly specialized
eukaryotic cells. The cells are adapting to this internal environment, and
evolving within it, which indirectly relates to the functional properties
externally exhibited by the organism as a single whole.
It is evident that when these multicellular organisms evolve, they are
not evolving so much on a point-by-point basis with standard mutations, but
there is a streamlining of property traits occurring that appears to encompass
simultaneously numerous genetic points of mutation and change.
The eukaryote cells that are part of an organism all
differentiate from a single set of fused sex cells, and early embryionic
development is remarkably similar in all multi-cellular organisms. These cells
are capable of differentiating through cellular mitosis into a myriad of highly
specialed types of cells.
It is the relative sophistication of a typical
eukaryotic cell compared to a prototypical bacterium or prokaryote, that serves
to explain the possibility of greater differentiation of functional
specialization and form of eukaryotic cells. The presence of a true nucleus, of
cellular organelles, of mitochondria, golgii bodies, endoplasmic reticulum, and
of a lipid bilayer cell membrane with specialized protein transport and
communication structures, all serve to enable to larger eukaryote to achieve
greater differentiation of form. The presence of a full complement of DNA, in
multiple chromosomes, which is reproduced completely with each subsequent
cellular generation through mitosis, entails that the cell has the informational
capacity for differentiation along a species blue-print for the entire organism.
The cells have yielded a degree of independence found
and exhibited by bacteria or single-celled organisms, and trade off this
independence for an increased functioning capacity in adaptive survival and
reproductive success.This tradeoff confers adaptive survival for the organism as
a whole, and, indirectly, for the species or specific type of organism. Most
multicellular cells in fact yield their own reproductive function to specialized
sex cells, and grow only for replacement purposes.
Organiismic multicellular integration of living
systems above that of the single-cell represented a revolutionary step in the
development of living systems upon earth, and was a significant step towards the
development of complex evolutionary systems. It was a step not achieved
overnight in the natural history of life on earth, and appears to have required
from 1 to 1.5 billion years for the development of multicellular life forms, in
increasing varieties and complexities, to take off during the Cambrian
Explosion. The success of this level of living systems development can be
witnessed in the fossil record that yields myriad life forms and types, and the
emergence of millions of new species of multi-cellular organism. For all that is
discovered in a relatively sparse fossile record, there have been that many more
that probably once existed and became eventually extinct without a trace.
In all multi-cellular organiismic systems, we witness
the integration of highly differentiated and specialized cells into a single
organiismic whole, or individual organism, that is conferred with a set of
living properties that are unique both to that individual and to its type of
species. Survival of the individual cell becomes dependent entirely upon the
adaptive success and reproductive success of the individual organism as a whole,
and, again indirectly, upon the species or that particular type of organism.
No multi-cellular organisms occur only as a lone
individual, but always occur as part of a larger population of related
individuals, and it is a key design strategy of multicellular life forms of all
types that there is strength in numbers, that though a few individuals may
perchance perish unsuccessfully, there will remain enough of viable population
balance to continue the line successfully.
Adaptive functioning for multicellular organisms
therefore occurs upon two levels simultaneously, and these two levels interact
with one another. We can speak of the adaptive function and biological
equilibrium of the individual organism that primarily, in the context of sexual
reprodution, involves the first of the two imperatives of biological systems,
and then we can, for sexually reproducing species, refer to the second level of
social adaptation and equilibrium, which leads to successful reproduction of
both the individual and the population as a whole. These two levels of
adaptation for sexually reproducing taxa clearly interact in a systems manner,
providing evolutionary advantage to species specific communities. The trade-off
of K-adapted species, of course, is both the problem of over-specialization and
narrowing of niche profile, which is related to the second problem of the
tendency towards environment circumscription due primarily to niche exploitation
and relative over-population, resulting in taxon cycles of growth and collapse
of entire populations and the degradative stress of the ecosystems of which
these populations are a component.
Therefore, in multicellular organisms, especially
those involved in sexual reproduction, evolutionary development occurs from the
feedback between two levels, the organiismic level of the adaptive functioning
and health of the individual organism, which is the host body of the cells it
harbors, and the larger specific population of which that individual is a
potential reproductive member. Sexual reproduction favors social behavior of the
group, while individual health favors adaptive success of the individual,
meeting both requirements in successful evolutionary development, adaptive and
reproductive success.
Adaptive and reproductive feedback between the level
of the individual organism and the larger population of which that organism is a
part is a critical system underlying natural selection and speciation of
organisms, and this has been a relatively continuous process resulting in long
term cellular differentiation and the emergence of new organiismic systems and
properties.
Each individual multicellular organism that is born
and developed to maturity is a unique individual, unless the primary process of
reproduction was by means of cloning. High levels of individual variation along
almost every trait profile assures a high degree of genetic and ultimately
adaptive variability for a population, which assures that some members of the
population will be capable of successfully adapting to widely fluctuating
environmental circumstances.
Playing
the Game of Life
The
Almost Closed World Hypothesis, Fitness-Selection Matrices & the Systematics
of Living and Dying
I have reached the point in the development of a
model of evolution that we must venture into a more complete mathematical
description of the processes involved in natural selection. In general, I build
a basic set of descriptive explanations that attempt to account for and describe
these processes. From this, I propose to apply models derived from game theory
and various mathematical theories to the understanding of natural selection in
organic evolution.
At least on one level, nature, being blind to the
outcomes, plays a game of chance in producing genetic variability even at the
cost of adaptive fitness. This can be described as a min-max optimization
strategy in which the outcomes of different selection pathways cannot be known
beforehand. Of course, theoretically Evolution is a non-constant sum game, and
therefore it is impossible to model in finite and general terms, but a simple
matrix model is useful in understanding the fundamental process in simplified
form.
Life plays a game that is always with itself, so to
speak. This is a part of an almost closed world hypothesis. Selection, fitness,
and evolution are all blind processes. Each time an organism reshuffles the deck
and each time a population redistributes its genetic pattern, it does so largely
without knowing the consequences and without really being able to consider them.
The question implicitly being asked in the reshuffling act, which is the act of
reproduction, is what will be the net outcome of the next round, especially in
terms of its reiteration. Not being able to know outcomes, or plan strategies,
life has adopted a purely chance or random min-max strategy, which, in the
structure of the long run, tends always to be the strategy of optimization of
gains and losses.
This game can be characterized as one that is played
by an organism with itself, a "game of n-tuple evolutionary double
solitaire." The analogy of a card game is a fitting one in understanding
natural selection, genetics and evolution. Each kind of organism has its own way
of laying out the cards, its own rules for playing the deck. Each card would
represent both a set of traits (trait-fitness value) that have some kind of
adaptive-reproductive bearing on the individual, and the possible outcomes of
this value (trait-selection value) depending on prevailing conditions.
The attribution of intentionality structure to
evolutionary process, when we speak of selection strategies, expectations of
death, or even intelligence itself, is an unfortunate consequence of our own
limited language. The attribution of "intentionality" is even smuggled
implicitly into the term "natural selection" itself, as if nature is
making some choice and selecting in some deliberate or preplanned way. This term
was derived from Darwin's observation of "selection" in the process of
the cultural breeding of plants and animals. We could as well call it natural
election but it is more like a grand lottery system. Intentionality structure
that connotes deliberate planning can only be attributed to fairly large brained
animals that exhibit some degree of planning in their adaptive survival, and
this is almost always in very limited and bound contexts.
The almost closed world hypothesis arises from the
notion that if possible, all life forms would seek closure upon their world.
Closure in this sense would be a form of static un-changeability--a form of
equilibrium that is permanent. This is a natural consequence of their own world
closure. Each organism, biologically, exists bound within a world of its own
making. It is the world that it has inherited, and that in a fundamental sense
it cannot change except through accident. For most creatures, competition with
other forms of life or even other organisms, is merely a fact of life that
occurs much like a reflexive response. There is little equivocation. If anxiety
arises in an animal, it is a consequence of hormonal adaptations to stress and
fear. A closed world leads to equilibrium and stasis within eco-systemic
frameworks.
But we must emphasize an almost closed world. Though
all life (except perhaps human beings) tend to seek its own closure with its
world, and many more or less achieve this, if life were completely existent in
closed bubbles then there would have been no evolution in the first place.
If the world were closed, each time the genetic deck
is reshuffled, the outcomes would be the same--what is reflected and
theoretically expected in the normal model of Hardy-Weinberg equilibrium. But
there is a large element of random chance introduced into this process, and this
chance reflects noise and uncertainty in the transmission process. This chance
occurs on two levels, not just in chance mutations of alleles, but in the
relative fitness-selection that afterwards visits upon those alleles.
It is like death, disguised as a statistician,
knocking randomly upon houses in a neighborhood, on perchance to see if anybody
is home. K-A fit dominant homozygous individuals stay home every third day.
Heterozygous individuals can be found at home ever other day, and homozygous
recessive individuals everyday.
Thus, individual organisms get to play two games of
chance. The first, the game of adaptive survival, is to decide whether it should
remain at home on any given day, or go out to look for food. It cannot know if
death will come knocking at the doorstep, or is in the field counting heads and
counting coup in the old food chain.
This game is played every day in the same way. The
odds are usually not completely random, as evolution always is built upon
successful foundations. Creatures, trying to close their worlds just like their
ancestors tried to do, inherit patterns that are largely automatic or habitual.
They are nocturnal or crepuscular, they restrict activities to certain zones and
avoid others; they eat only fruit or grains or leaves from trees, so on and so
forth.
In this game, death will eventually visit, whether an
organism remains at home to breed or goes out to feed. The question is when, and
how soon. Less fit individuals will be chosen earlier than more fit individuals,
on average. This means that unfit embryos with weak hearts do not even get out
the door. It means that those old individuals that survive countless days
represent the peak of their generation's outdated fitness curve. We might say
that the relative equilibrium and adaptational success of a population can be
measured by the number and age of post-reproductive organisms it can sustain. If
death comes counting before the individual organism is able to move to the
second round of the game of life, then the final verdict of
"non-fitness" is rung in.
Thus selection regimes that directly affect
reproductive rates through removal of premature individuals that do not have
"non-deleterious" traits are disruptive regimes that leads to
disequilibrium. This form of selection I have called non-differential selection.
If an organism makes it to the second round, the
reproductive round, the individual actually gets to reshuffle the cards its been
playing with all the time up until that point. It does so at this stage in a
sexual manner, mostly. Thus it must mate with some sexual counterpart.
I do not want to get sidetracked on the issue of mate
choice and patterns of sexual selection, which itself, as choice or selection
implies some kind of intentionality structure. Again, life has a supreme and
often sublime way of working out all these minor details.
The point I wish to emphasize here is that of the
possibility of sexual reproduction itself, as a gradational capacity of
evolutionary development. Sexual reproduction accomplishes an assorting and
genetic accounting that is far more flexible and lends its self to much greater
chance variability of pattern than asexual forms of reproduction.
Sexually
reproductive creatures get to mix the deck with one another, so to speak,
whereas asexually reproductive forms of life are stuck with the same deck they
are born with. This basic gradational evolutionary trait complex lends great
credibility to the notion that life tends to maximize its variability of genetic
potential in each round of the game.
Why is one allele dominant and another recessive?
This can only be explained by a genetic relationship. Selection in some previous
population favored the expression of the dominant allele and the repression of
the recessive. Dominance-recessiveness for any given trait complex or set of
traits is therefore genetically controlled. We can talk hypothetically of a set
of genetic controlling traits that act as pattern determination devices that
govern the phenotypic expression of the total trait-configuration of an
individual.
Thus, all traits may not be genetically or
functionally equal in either the ontogenetic or the evolutionary development of
an individual. Certain controlling genes may have decisive influence in the
outcomes of an individual. It stands to reason therefore, that mutational
patterns that are alleged to affect all genes in a random and more-or-less
equality of opportunity manner, may have uneven and unequal consequences
depending on the genes that they do affect.
An outcome of this would be that while most mutations
might be relatively neutral and non-deleterious, most such mutations may also be
rather unproductive and non-positive as well. These forms of genetic changes
would occur on average most of the time, and lead to a storing of both a great
fitness load and a great adaptational hoard of hidden variability within a
reproductively successful population.
At the same time, it can be expected that the chance
mutation of key-genes might most often result in deleterious trait
configurations, pushing these kinds of variations out to the tails of the normal
population curve. But it is also remotely possible that selection and mutation
favoring certain variant key or controlling genes might have a revolutionary
adaptive significance for its successful organism. A consequence of this might
be a switching of dominance-recessiveness of pattern between alleles, among
other kinds of trait-outcomes.
A principle rule of the evolutionary structure of the
long run is something like Murphy's law: If something can happen, it eventually
will happen.
Thus, in the second round, the organism reshuffles
the deck it plays with, most often always exchanging half its cards with other
members. In the second round, it gets to reshuffle the cards as many times as is
allowed for that species. Each time the cards are reshuffled, a new deck is
created and assigned to a new organism. Once the parent organism shuffles as
many times as possible, its game is essentially over, and it returns to playing
its own cards on a daily basis.
The challenge of the second round is not only to
produce as many new decks as possible but to produce decks that are as
substantial and as robust as possible without being able to know beforehand what
these may be. In an absolute sense, we can say that an r-deck will tend to be
smaller and more limited in choices than a K-deck. Of course, there are
trade-offs. Producing large robust decks means making fewer overall decks, and
producing many small decks precludes the possibility of making hefty decks. If
one or two new cards are added at each second round of the game, then decks
gradually grow in size with successive generations. This sense of allocation
leads to consideration of an important and probably long neglected facet of
life. The total number of cards, or instances of cards, allowed to any one
organism to play with in the second round are probably more or less the same for
all organisms, whether big or small, simple or complex. There is an inherent, or
approximate, conservation of cards being played with per organism, per
generation, on average. But the relational values of the cards must change
considerably.
Of course, we need to reiterate in this analogy the
almost closed world of the organism. Already, the sexual exchange of cards
represents a kind of openness not otherwise available to organisms. It creates a
world more open than otherwise, but still not unbounded in an absolute sense.
There is a paradox in this such that creatures can be
seen to behave in ways that lead to the opening of their worlds, through
maximizing and increasing trait variability. At the same time, they also
function normally in ways that lead to the closing of their worlds, through
trait fitness and adaptive equilibrium, or maximizing trait-predictability and
hence reduction of variability. I believe this is the min-max aspect of the game
of life.
Creatures create a world that is as open as possible
for their offspring, and then the offspring attempt to close this open world as
much as possible back upon themselves until their turn to play the second round
comes up.
In what ways is the world open for a creature? In
terms of the trait-card game, we may say that the relative openness of the game
is an uncertainty value that is based on the fact that other creatures make
choices that influence the outcome of the organism's game. Thus it is an
imperfect game of solitaire, polluted by the choices that other organisms may
make in the course of playing their own games that limit the choices an organism
may make in any turn of the game. In each turn, competitive interactions with
other creatures, only if indirect, set constraints on the number and kinds of
cards an organism may get to play. The cards at this stage are not exchanged in
interaction. The choices made between and by organisms are mostly random and
blind.
At this stage, the game becomes a kind of poker or
gambling game in which each player's deal determines some finite outcome for all
players, even if the game is played in a solitary way. Each player has chips
that are controlled by the cards. The chips are the expression of fitness and
survival, the outcome values. These chips are exchanged in the course of the
play, and there may be a central pool of chips that are taken from at each turn
by each player. If a player loses all its chips before it gets to the second
round, it is out of the game. It is negatively selected.
Attributions of structural pattern or of even
implicit strategic intentionality to indirect selection processes again bespeaks
a kind of fallacy of misplaced intentionality. Indirect selection patterns are
to be understood as natural responses to a range of circumstances that are
themselves largely undetermined products of chance and probability. Selection in
a direct form is a completely random process. If it occurs as the result of
indirect patterning, we can say that the process becomes probabilistically or
stochastically nonrandom of occurrence. A non-random pattern of indirect
selection therefore is a semi-determined system.
We might say, as Fisher said in relation to an ideal
form of optimal adaptation that always tracks environmental change, that on
average, over the long run, any selection outcome and any adaptational change at
a particular point is expected to result in a 50/50 chance of outcome.
Furthermore, I believe that any systematic model of
natural selection must explain it as a feedback process operating on two levels
simultaneously. A model based only on normal population genetics describes only
one level of this patterning. And it describes even that level inadequately as
it by definition factors out the exceptions by favoring the normal curve.
In this framework, we can see that the cycle can be
interrupted at almost any point, the significance of which is the death of the
organism. This cycle can be interpreted in two ways, either from the standpoint
of an individual organism and its environmental and social interaction with
other organisms. It may also be construed from the standpoint of a population as
a collection of organisms in interaction within the group and between other
groups. Therefore, in terms of its representation of group dynamics, we can see
that interruption of the process at any point is the equivalent of extinction.
We can say that the optimal strategy in the long run
is one that seeks to minimize losses and maximize gains at every throw of the
dice--losses being construed as population in terms of loss of life, and gains
in terms of reproductive increase. We may construe this in terms of a simple
matrix contrasting reproduction and adaptation, fitness and selection:
|
|
Reproduction |
Adaptation |
|
Fitness |
Maximization |
Optimization |
|
Selection |
Optimization |
Minimization |
If we put this simple four-square table into the form
of a graph along the axis of selection/fitness and reproduction/adaptation, then
we get the following considerations:
We can infer from this kind of model that there is an oscillatory cycle
that defines stable min-max and central points in a pendulum pathway, as well as
intermediary transitional saddle points that are inherently unstable in this
state trajectory. According the first diagram of the model, inputs and outputs
from without the system would tend to occur at stable nodes rather than at
saddle nodes, making such a system internally resilient and coherent in relation
to outside social interactions. Two other sets of inputs help to govern this
process, that is environmental fluctuation, which is inherently unpredictable
and therefore uncontrollable, and genetic mutation, which is also
uncontrollable. These kinds of forces tend to occur at saddle transition points
in the overall cycle, hence tend to be inherently disequilibriating, except that
they can serve indirectly in favor of the min-max strategy by further minimizing
variability by adaptational selection and maximizing reproductive variability by
reproductive selection.
Each cycle can be thought of as a generational round.
We can see that this generational round sets the relative evolutionary clock for
each species, and the absolute rate of this clock for all species is a
size-dependent relationship, such that it spins faster for smaller,
shorter-lived, r-selected species, and slower for larger, longer-lived,
K-selected species. This relationship is a relatively linear regression, and is
related directly to the absolute size of the organism and also is based upon the
presumption of an absolute constant rate of expected mutation, in the large.
We can see in this model an important intrinsic
difference between r- and K-selected populations and individuals. K-selected
groups will have populations that are by definition more age-heterogeneous than
r selected groups, which will tend to be more age-homogeneous. The standard
deviation and variance of age of a population profile of a K-group is expected
to be much greater than the standard deviation and variance of age of a
population profile of an r-group. This is in part related to the idea that in
K-selected groups, larger body size on average is linearly related to longer
life span and longer rates of growth. This is also related to longer lag periods
between changing rates of death and birth, and also delayed reproduction and the
retention of post-reproductive individuals in a population. This kind of age
heterogeneity may have a consequence of minimizing the effects of
non-differentiating selection upon the population.
In other words, non-differentiating negative
selection that is tied to relative density independence is less likely to affect
a highly age-heterogeneous group than an age-homogeneous group. Environmental
fluctuations that affect rates of birth and differential rates of death in any
given population in an ecosystem are less likely to adversely affect the entire
K-population, rendering such effects relatively density-dependent, than an
entire r-population. K-populations, by slowing down their clocks, are more
evenly distributed through time, hence widening the limits of tolerance to
environmental fluctuations by the population to very broad bands. If the net
reproductive potential of an entire population is conserved over the long run,
then fluctuating seasonal conditions would impact differentially upon the net
reproductive capacity of the population as a whole. K-type organisms engaged in
reproduction are probably inherently more susceptible and vulnerable to
fluctuating uncertainty values in the environment than otherwise. A pregnant
female is probably less able to evade predators and more susceptible to
fluctuations of food supply. Such a population could not afford to invest all
its reproductive potential in a single seasonal bloom, but must rely on
distributive spacing over time to minimize the null effects of adverse
selection.
Another way of looking at this is to see that within
any K-population, individuals are more evenly distributed around the entire
pathway of the cycle, hence the cycle itself is inherently, internally more
coherent and balanced. If selective factors impinge at any one point in the
cycle, which can always be sent as episodic and temporary, the likelihood is
that relatively fewer individuals will be involved. Thus, K-populations can be
said to be intrinsically more stable than r-populations.
On the other extreme of the continuum, r-selected
populations must invest their total reproductive potential in a single seasonal
bloom, a climactic mass reproductive episode. While a K-population is bent on a
pathway that attempts to minimize the effects of adverse selection, at the cost
of minimizing reproductive rates, the r-population is bent on an opposite course
of maximizing the benefits of reproductive success, at the cost of maximizing
selective adversity. The result is that for any given r-population, not only is
the cycle more rapid, but the population is more likely to be unevenly
distributed around the curve, such that the entire system is inherently
fluctuating and imbalanced and occurs in periodic or episodic, rather than in a
continuous, manner. Negative selective factors impinging on the curve at any
particular point, are therefore inherently more likely to affect the entire
group, or more members of the group, proportionately.
This brings up the question and possibility of
age-selection as a form of natural selection. It is known for instance that some
diseases occurring in the wild affect the reproductiveness of the female and the
survivorship of the offspring. These types of diseases appear to
"target" the reproductive and pre-reproductive.
But if r-populations are bent on a crash and dash,
boom, bloom and doom cycle than K-populations, they are in a sense also
inherently more crash-resilient than K-populations. If K-populations do crash,
it spells disruption of the entire cycle, rather than just at one point or phase
of the cycle, such that they will crash in proportionately more devastating
ways. K-populations cannot rebound as quickly nor as completely as r-populations
from a crash. Leftover members of a K-population crash are probably inherently
more susceptible to negative selection factors during the post-crash period.
This is true just on a statistical basis alone, because they can only reproduce
fewer numbers over longer periods of time. Thus any random point-selection is
liable to have greater resonance upon the remaining group. It suggests that once
a species has climbed up the r-K gradient to the apex of the pyramid it occupies
over a long evolutionary curve, it has no where else to go but back down to the
bottom. Phyletic size increase in the fossil record might be an indicator and
precursor of a pathway that is headed eventually towards extinction.
If each cycle of this model is a generational round,
it also represents the reproductive lifecycle of an individual. If this round is
a single year, or a single season, then all individuals of a population within
this cycle can be expected to arrive at the terminus of the cycle at
approximately the same time. The only way of avoiding this would be to make
reproduction a continuous and random process in the population, as might be the
case with some single celled organisms. If, for instance with canines, the
reproductive life cycle can be placed over a decade, rather than just in a
single season, then multiple breeding seasons would tend to distribute a
population out over a larger spectrum of the cycle. Such intermediate cycles
would still be subject to perturbations and susceptible to fluctuations, such
that in any given season there may be a bloom or a bust in net reproductive
success.
In reconstructing our model, two further
considerations need to be taken into account. This model encompasses a single
cycle and thus entails a reiterative or recursive process of oscillation. It is
still defined in terms of only a single normal population, rather than in terms
of an entire ecosystem encompassing multiple possible populations and it refers
us back to the original problem in natural selection. We can identify selection
fairly easily, but at what point does selection result into speciation.
In a simplified sense, we may state that a speciation
event would be represented by significant changes in initial values of the
cyclical system we have previously described, such that the profiles resulting
from the articulation of the system would be minimally different as to
characterize two different population matrices. This is sort of beating the bush
around the issue of reproductive isolation, which alone appears insufficient as
an explanation for con-specific differences.
We can understand speciation in a simple way if we
assign some mostly arbitrary composite values to each of the four corners of the
system, plus input and output values that occur stochastically, and we develop
transformation equations regulating the transition between states. At each
round, we would record the changes in initial values that have occurred. We
would do this for each subsequent round. We would develop a matrix to represent
the entire population, and we would perform the same sets of operations for each
individual. Over time, we would compare the restart values with the initial
start values.
If the differences in the primary variables are
substantially altered, then there is an overall profile of change in the two
decks of cards. There must be some cut-off point at which we can say that the
subsequent population is substantially separate and different from the initial
population, such that we can presume phyletic speciation has occurred. This can
be judged perhaps by comparing the decks of cards, such that if we reshuffled
two dissimilar decks together, it would yield a fresh set of decks that would be
reproductively dysfunctional, minimally speaking. The resulting deck could no
longer be used.
This issue relates indirectly in simple form to the
second question of inter-specific interaction within ecosystems. We can see that
inter-specific interaction can occur at several levels in the system, and
influence the variables that are attached to the transition equations in the
model, as well as the outcomes of the individual and population parameters. The
transition equations have the challenge of taking these different sets of
interactive variables with other species, especially, I believe, with
con-specific species, into faithful account.
Species appear, over the short term at least,
relatively stable and robust. Oscillatory cycles of selection can reverse the
fortunes of any breeding population countless times about some normal standard
of deviation. One round might push the curve in one direction, another in the
opposite direction, but always to rebound again about some intermediate norm
defined by the initial population parameters.
We must construe this oscillatory mechanism as
something that in its state-trajectory may lead to a number of different
patterned outcomes, depending on its initial starting conditions and
intermediate variations. It is the alternative state-trajectories that such
oscillatory mechanisms may take in the large that determines speciation pathways
and evolutionary outcomes.
In one sense, the cycle above describes the pathway
of a pendulum that oscillates about a "center of gravity." We can
depict this as below:
This model emphasizes the periodicity of fluctuation,
where there are limit lines about reproductive rate and death rates on either
end about a centerline of equilibrium. This model would characterize r-selected
populations more than a K-selected population, because in a more K-selected
population in equilibrium, individuals would occupy all three stable nodes at
the same time, and would be distributed in a balanced way in the entire system.
A hypothetical r-selected population would more likely occupy only or mostly one
node at any one moment.
Another way of describing the difference, I believe,
is to say that an r-type system is in general uni-directional at any one time,
hence inherently imbalanced, whereas a K-type system tends to be bi-directional
at any one time, hence inherently balanced.
In a simple pendulum system representing extreme
r-type species, mechanisms like drift, shifting balance, bottleneck and
founder-effect, geographic dispersion and isolation are probably sufficient to
account for speciation over the long run. But even for these r-selected
populations, this model may in fact be over-simplistic, and hence the
traditional mechanisms of speciation described for it may be insufficient.
For a K-type system at least, the correct state
trajectory is defined by a second-order non-linear control mechanism, in which
there are possible four alternative state trajectory patterns depending upon
initial starting conditions. Speciation directions or pathways are therefore to
be considered the result of these alternative state-trajectories.
I believe these models provide the appropriate
conceptual framework for understanding evolutionary process in terms of natural
selection and speciation. From these models, I propose the hypothetical
construction of an analog of a form of natural intelligence that functions upon
two levels simultaneously and that sufficiently describes the patterning of
evolutionary process as a form of "blind strategy."
Faithful mathematical representation of longer-term
speciation processes takes us to nonlinear control and nonlinear programming
theory, underlying optimization theory as well as stochastic programming of
minimum and maximum problems in which some of the variables are random and
therefore uncontrollable. In general, it can be said that the values used in the
original equations are themselves complex and composite variables that are
solved by the use of differential equations and linear functions. In other
words, a rendering of speciation processes in nature might be approached by
means of computer programming involving functions inscribing differential
equations, matrices, and vectors. To approach the problem of speciation
evolution in less complex terms is to risk over-simplification. Such full model
is beyond the scope of this book.
The presupposition of a min-max optimization theory
suggests the influence of a relay control system that operates upon the system
at minimum and maximum values, which can be interpreted as birth rates and death
rates respectively, or alternatively as trait-fitness and selection. It can be
expected that the cycle described above will oscillate in a normal manner about
its central axis, within range of its maximum and minimum limits, but will
become unstable if these limits are exceeded. At this point, disruptive
selection occurs, the consequences of which would be the system adopting an
unstable equilibrium pattern, resulting in a long-term state trajectory leading
to outcomes reflecting either phylogenic or cladogenic speciation, or
extinction.
Programming challenges suggest it is better to begin
the construction of such a model from the ground up, rather than theoretically
from the top down, and to build one program at a time, tying these together to
create integrated larger programs that would represent ecosystems.
Co-evolutionary structures of ecosystems can be depicted as interdependent
coalitional and competitive network structures derivable from the multiplication
of such systems in nature.
This kind of programming model is beyond the scope of
this current work. Here suffice it to say that the basic variables representing
fitness and selection are composite and complex, representing Eigenvalues of
vector equations. Thus, at the level of trait description, we may distinguish
between separate values of positive and negative fitness, as well as positive
and negative selection, among other values that are part of that function. We
are led as well into complex combinations of matrix, differential and integral
equations. These combinations occur at multiple levels of the individual, the
population and the species as a whole, which can be considered to be a
continuous series of recurring and multiple populations over a definite period
of time.
The conclusion to be derived from this is that there
is no one equation, nor one single set of equations, which can describe all
processes occurring in evolution in a sufficient manner. Equations like
Hardy-Weinberg Equilibrium describe normal distributions of populations but it
becomes increasingly difficult to represent change mechanisms representing
differential selection and speciation, especially in a systematic way, in terms
of simple linear equilibrium equations.
I have reached the conclusion that under normal
circumstances most trait variability is probably neutral about a modal line and
therefore non-deleterious. If any trait-change has a 50/50 chance of being
deleterious or non-deleterious, then in the long run trait-changes should
balance out and be largely self-canceling. Trait variability and change by
itself does not necessarily lead to a reduction of fitness, and in general may
be good for a population in the long run of wide-spectrum adaptation. Therefore,
especially large populations might normally accommodate a heavy load of
variation without suffering substantial penalization for carrying such a load.
The question of load is more than offset by the savings account or reservoir of
genetic flexibility that maintaining genetic variation entails. Thus as much as
there may be genetic load associated with maintenance of less fit individuals in
a population, there might also be a hidden hoard in doing so that is only
expressed during periods of eco-systemic destabilization and disequilibrium.
Most populations probably regularly emit members of
their groups, which emission is a form of selection. I will call this diffusion
selection or dispersing selection and I construe it to be a complementary aspect
of stabilizing or disrupting and diversifying selection. In such a manner,
groups regularly explore the boundaries and beyond the boundaries of their
world, in several senses. Diffusion selection is the better alternative than
direct selection, as it does not represent the waste and absolute loss entailed
in the latter form.
To the extent that there can be said to be an
expectation of direct selection, it seems reasonable to conclude that migration
would be the better alternative. To what extent this is a deliberate strategy,
rather than an automatic consequence of conditions, is probably a moot point.
Creatures normally explore the limits of this system by whatever means they have
available to them. They do this naturally and as a matter of course, without
considering the consequences of their actions.
The chances are that the more marginal or peripheral
types of individuals are those that are the candidates for emission from the
system. They can be said to be more r-type in their patterning. But this is not
by any means a golden rule to be obeyed by all members. A great deal of this
shedding process is probably purely happenstance, and may be about as random and
stochastic as mutation itself.
Such processes offer several possibilities. It offers
the possibility for adaptive radiation and gene flow over broader areas. It
offers the possibility for reduction of load and of stabilization of a saturated
system about equilibrium. In strong forms, it offers a bottlenecking process
that can lead to rapid evolutionary development. It can also lead to a founder
effect in a new colony. Colonization of a new area, or even just admission in a
new system, can alter the balance of that system. Even if the survival rate of
immigrating individuals is very low, the impact of this process of immigration
can have a counter-adaptational effect within a neighboring ecosystem. It could
stimulate counter-migration in the reverse direction of other displaced life
forms.
This perspective offers two points of view. First,
all selection is by definition in population genetics direct selection meaning
direct removal of non-fit members by death. Therefore, all other forms of
selection are essentially indirect and derivative patterns, of life attempting
to avoid or minimize the expectation of death and simultaneously trying to
achieve or maximize the expectation of reproductive survivorship. In this sense,
direct fitness is the success of reproduction, and is the complement of direct
selection. Therefore, varying forms of fitness represent indirect patterns of
fitness adaptation that life adopts to hedge its bets for success.
From an eco-systemic point of view, varying forms of
indirect fitness and selection are classifiable in one of two ways:
1. Whether the system is rising (succeeding) through
successful reproduction;
2. Whether the system is falling (failing) through
preclusive negative selection that affects premature individuals before
reproduction.
Therefore a selection pattern has a positive form if
it results in a net gain for the system, and a negative symmetrical form if it
results in a net loss for the system. In this manner, diffusion selection in an
extreme form that has negative consequences becomes a kind of directional,
disruptive or peripheralizing selection.
Defining functional systems in terms of their
consequences, and not their causes, are of course tautological, but this is
admissible tautology if we are describing feedback systems that are essentially
on some level partly closed, as the consequences indirectly become the causes.
Therefore, all forms of life tend to increase
trait-variability as much as possible, and the most direct way of achieving this
is through maintaining high rates of reproduction, even at the expense of
carrying capacity, equilibrium and increased negative selection. Populations
will thus become more K-selected in a focused way, while retaining a fundamental
r-selection strategy that directs towards the periphery of its realm.
Excess population is normally thrown off, or cast off
from a system, at regular rates defined by relative measures of differential
fitness and saturation of the system. Thus, the costs of increased reproductive
rates are avoided and eco-systemic stability can be maintained for the
indefinite long run.
Normalizing and diversifying diffusive selection is
an optimization pattern that represents an excellent means for a population to
control itself, as it accomplishes two goals at the same time--that of
maximizing its reproductive gain, while at the same time minimizing its
world-openness. Casting off individuals achieves a state of parity within the
boundaries of the normal population.
The expected rate of migration will be tied within an
island model not only to a rate of extinction, but to the equilibrium of death
and birth of a population. Old species do not necessarily have to go extinct to
accommodate the entrance and colonization of new species in the same ecosystem.
The consequences are a net reduction of K of each
species as a result of increasing species diversity, in order to maintain the
net-K or saturated equilibrium of the overall system. Hence, if an area is by
definition bounded, then species diversity must be inversely proportional to
relative average K achieved by any one species within the system. In this sense,
K is maintained not only by internal factors of equilibrium of death and birth
rates, except that these are influenced by patterns of diffusion displacement or
by invasion.
If relative K is somehow inversely proportional to
species diversity and area, then the higher the diversity, the greater the net
resistance of such a system to intrusive colonization by non-member populations.
At the same time, the more critical or delicate the balance of the system at a
supersaturated state, such that if and when invasive colonization does occur, it
can lead to disruptive selection occurring with other competitive populations
within the system.
Birth rates are always maximized under normalizing
conditions, leading to maximization of post-reproductive death rates. This
should be an inherently disequilibriating pattern, but it tends to be countered
by adaptational patterns of an organism and other organisms in relative K
states, by attempts to maintain niche-closure over the world represented by the
eco-system. This is accomplished either by regular diffusion or periodic
"infusion." Diffusion will serve to maintain equilibrium or increase
equilibrium to a higher level, while "infusion" will serve to lower
the level of equilibrium by crowding or restriction of space.
Thus, added gain in maintaining a pattern of regular
diffusion is the possibility of increasing the niche territory that a breeding
population can occupy, especially if back flow can occur between colonized
areas. Diffusion itself, and its rate, must be a consequence of a system that is
locally at carrying capacity. It is a high-pressure system that increases the
likelihood of either random or selective diffusion occurring. Saturated systems
approximating equilibrium can afford, indeed need, to emit fit and non-fit
organisms alike if it is either to maintain equilibrium at high levels or
increase these levels of equilibrium.
If diffusive selection is indeed selective, it means
that nonrandom patterns will occur such that some sub-segment of the population
curve are expected to become displaced out of the ecosystem to a
disproportionate degree. This does not necessarily have to be the least adapted
or less fit organisms, though on average it probably usually is. Maintaining
random diffusive selection would be a means for a population to insure equality
of death opportunity, which is a min-max strategy for reproductive optimization.
A high pressure system tends to be a healthy system
as well, at least in the short term, in that it can resist the infusion of
competing organisms into the area, on average. It thus maintains a positive
balance or positive bank account with the outside world. It can afford to trade
off part of its total value, to maintain the stability of the internal
reservoir. If a population system slips into a negative net balance, it means
that it becomes depressurized and susceptible to invasive infusion. It takes in
outside value that tends to be chaotic if it crosses the reproductive boundary.
It falls into a "debit" cycle.
Thus complex relative K states of population
groupings exist in dynamic equilibrium to one another based on exchange rates
between competing systems. We thus have an econometric model of evolution at the
level of the ecosystem, as well. The absolute K of any population grouping would
be measured by the area it effectively encompasses, or its total niche, and
therefore the resources that are in its behavioral purview to control.
Relative K arises as the result of the shifting
balance of control and area that results from continuous and periodic processes
of diffusion and infusion between contiguous areas. Successful colonization of
an invading species or group cannot but help lead to eco-systemic restriction of
absolute K for all other species of the system, either directly or indirectly.
If these other alternate species do not restrict
their behavioral range, their system becomes supersaturated or over-pressurized.
In a fundamental sense, it becomes relatively depressurized in the sense that it
occupies an area too great for its population to control, yielding adaptational
advantage to other populations for invasion or expansion of control by default
of restriction. It accomplishes this restriction through directional selection
or extreme normalizing selection patterns. It must either increase its rate of
diffusion or its rate of negative selection will follow.
It is to be expected, as a consequence of this
pattern, therefore, that the opposite disequilibriating pattern of selection
represents a failure to resolve the inherent paradox of an organism's min-max
game. It cannot achieve maximization of reproductive gain, and it can no longer
maintain relative closure upon its world. The net result is a failure to
maintain relative K, and general disequilibriation of the organism's game.
In such a condition, a population can be considered
to be open to invasion and displacement by an invading or colonizing out-group.
Back migration of like or similar species may by reverse gene flow restabilize
such a population. This is a side-benefit of continuous diffusing selection.
Whether such a population gets "invaded" and displaced or replaced,
remains a matter of chance.
High rates of population reproduction is a sign of
healthy adaptations and positive blanket fitness, and continues in face of an
implicit expectation that there will be high rates of death randomly distributed
in a population due to negative selection.
Counter-adaptations by other competitive species are
an expected outcome of systems in which relative K is defined by the
maximization of reproduction and internal density, and by gradients of
diffusion-infusion between contiguous systems. Ecosystems under stable
conditions can tolerate a wide latitude of trait and behavioral variability.
They can tolerate both high rates of reproduction and high rates of death
without fundamental disturbance. Thus they can run in high gear at rapid rates,
without fundamental disturbance. Ecosystems start off in low gear and gradually
accelerate in time. In healthy systems, there is a net gain in population, and
increased diversity of life.
In positive selection regimes, trait variability is
amplified with increasing density and high rates of population growth. In such
regimes, death is essentially non-selective and equal. Deleterious trait
characteristics will lead to selection before reproduction. Great stores of
trait variation, describable as alternate alleles that govern the same trait
complexes accumulate in a species over time as the long-term consequence of
mutation, drift, population increase, wide-spread adaptation, differential
selection and gene flow, and can become hyper developed in such contexts. There
is a hidden load paid for such development, as the average fitness of any single
trait complex is thereby reduced for any given set of circumstances, even though
the overall range of fitness is considerably broadened. At any time when
circumstances prevail leading to uneven trait selection, death becomes selective
and no longer equally distributed.
The development of a broad-spectrum alternate allele
trait complex in a large population near equilibrium describes a form of
diversifying selection that is uniformly positive (or potential equality) for
all non-deleterious alleles.
Contrasted to this is a form of uniformly negative
but unequal trait selection that occurs under unusual but not infrequent
conditions. This form of selection I call disrupting. In general, there is high
death rate and low birth rate. In particular, individuals are removed
prematurely from the population, either antecedent to or consequent to
partition. Death rate falls abnormally heavy or disproportionately upon
individuals before they have a chance to successfully reproduce. In an
equilibrium model, it can be expected that counterbalancing would remove all
post-productive individuals of the population, but selection in this case,
tending to be negative, is also blind.
Even if birth rates increased, selection would remove
normal individuals with almost the same force as it removed those characterized
by deleterious alleles. This entails that there is no direct connection between
birth and death rates as implied in equilibrium theory. It also entails that
selection and fitness, though interdependent and complementary processes are
also fundamentally independent of one another. Selection can take out fit as
well as non-fit individuals on a random basis. A sign of maladaptation of a
population to an ecosystem, and a symptom of distress in ecosystems, are high
rates of relatively nonrandom death coupled with decreased rates of
reproduction. There is a net loss of population and population instability.
In general, conditions causing disrupting selection
are any combination of environmental degradation, environmental shifts,
competitive exclusion or displacement, and the loss of a foundational linkage
within the food chain at a lower trophic level or within a co-evolutionary
network. A condition is describable where a species is adapted to several
different co-evolutionary frameworks at the same time, and as such serves as an
intermediary linkage between both frameworks. Removal of such a linkage, or its
disruption from interdependencies within one or another framework, can result in
reverberations in other frameworks as well. In such a way, a regional or global
system that has achieved super-saturation of all or most of its ecosystems is
primed for mass extinction following gross systemic disequilibrium. It is a
chain reaction that sets in throughout the biotic realm.
Other forms of trait-selection are describable within
this framework. Balancing and stabilizing selection are differential forms of
diversifying selection that favor either the center or the margins. Social
selection, adaptation and counter-adaptive selection processes are
"specialized" forms favoring varieties of certain allele complexes,
but not necessarily at the expense of other alleles in other conditions. In
general, directional selection can be seen as an incipient form of disruptive
selection that tends to favor only one or a limited number of genotypic forms
and that can easily lead to situations that degrade into disruptive selection.
The extreme forms of disruption selection are marginalizing or peripheralizing
selection, which pushes trait variability to a minimum on the tail of a normal
curve, or else mass selection, which leads to extinction.
In conclusion, it is to be seen clearly that in an
almost (but not entirely) closed systems, states of equilibrium, hence normal
population distribution patterns of genetics, is not entirely sufficient for the
explanation of why speciation occurs, and appears to have occurred as frequently
as it has. "Normal" models stress a conservative view of evolutionary
development that naturally assigns a slow even and gradualist tempo to
evolutionary changes. Populations do little more than drift along, with an
ocassional shift in balance occurring.
More "marginal" and less conventional
models would view evolutionary process as occurring at the peripheries of the
population, at the edge, so to speak, and generally credits much higher rates of
development and speciation. Such models tend therefore to be more dynamic and
less conservative concerning the forces of selection and change operating on
populations.
A good compromise, born out to some extent in the
fossil record, is that of punctuated equilibrium in which a normally stable
population, typified perhaps by a basic and well represented type specimen that
is assumed to be prevalent. Indeed, in terms of dominant-recessive alleles this
sense of a dominant normal type may be embedded in the very character of genetic
redistribution and expression patterns.
The pattern over the long run intermittently steps
into a phase of rapid peripheral speciation, either leading to extinction of the
line or the radical emergence of different types. These new types are
fundamentally unlike the previous stem progenitor, or else phylogenically they
lead to a new group that replaces the old group with a new level of stability
and represented by a fundamentally different, but related, type specimen.
I am not sure that punctuated equilibrium is the best
compromise solution that we can come up with to explain patterns in the natural
history record. I think it is one possible outcome, that is the product of one
kind of pathway that evolution can take. The difficulty with the fossil record
is that it is inherently sketchy, made up of a few specimens, which, however
they are grouped, become the type-specimens for the lines they almost
exclusively represent, and many wide gulfs of missing linkages that would
explain smoother transitions between types.
Diffusive selection would under most circumstances
appear to be a very important if somewhat neglected mechanism underlying
evolutionary process, both normal and punctuated. It suggests a kind of model in
which diffusion resulting in successful colonization and adaptive radiation, can
lead to saturated systems that result in reinvasion of closely related but
reproductively isolated species, congenitorial or sibling or cousin species,
that would be the most trophic-taxonomically similar and therefore highly
competitive. This reinvasion of a newer and probably more fit species into the
territories or niches of its cousins would result either in displacement and
restriction, or else total replacement. If no reproductive boundary existed, the
two groups would remerge and the population characteristics would become more
homogenized and stabilized. But if speciation was carried to its natural
conclusion, then niche invasion or even just indirect selection circumscription,
can shift the balance of equilibrium in favor of the new group. This is an
on-going process. If it is intermittent, it is so only in the structure of the
short-run. Gaps develop in the fossil record because a lot of species and groups
get lost along the way, either displaced or replaced completely.
Thus, my model of evolution construes speciation as
more steady and regular than strongly punctuated models suggest, and yet as
intrinsically more dynamic and diversifying than strongly normalized models
imply with slow, slow rates of speciation.
Over the structure of the long run, odds that any
species or group of species will become extinct or evolve may be just 50/50.
This is just the same as the odds of the adaptive survival and reproductive
success of any individual organism, in the structure of the long run, is liable
to be just 50/50, all other things being equal. In this way, evolution is just
about as blind as anything can be. In such a framework, the best strategy is one
that optimizes one's random chances.
In closing this overwrought dialog, I will go back to
some primes. I will state the following:
1. Maximum evolutionary rates of speciation are a
function of the rates of reproduction and the relative size of the species, such
that, if plotted, there is a near linear regression line in which the slope of
size to reproductive rate is nearly constant.
2. Actual or achieved evolutionary rates of
speciation fluctuate about an optimal line as the result of random and nonrandom
selection processes that determine the net outcome. Rates can speed up or slow
down within some range of standard deviation about this line.
3. The line of speciation optimization tracks the
curve of speciation maximization.
4. Species act in such a way as to attempt to slow
down speciation by achieving some state of homeostatic equilibrium. They attempt
to achieve world closure of their system that is by definition almost closed but
always partially open.
5. Species are led therefore to act in such a way, by
maximizing rates of reproduction while maximizing adaptive fitness, upon which
such equilibrium rests, that leads indirectly to the acceleration of their
speciation, since partially open systems are, by definition of the long run,
inherently unstable systems.
6. There is always an adaptive trade-off in
trait-modification the net consequence of which is to induce greater adaptive
fitness but at the cost of greater reproductive fitness. If a population acts to
increase its reproductive rate at all costs (r), it must eventually sacrifice
adaptive fitness. If a population acts to improve its adaptive fitness (K) it
must eventually sacrifice its reproductive capacity.
7. This point beyond which trade-offs must be made is
defined as the relative equilibrium line of the group in relation to other
groups within its ecosystem. This is equal to the line of optimal reproduction.
8. Only by means of diffusion selection or random
direct selection can a group increase its carrying capacity or saturation
without incurring great trade--offs. The inherent biological imperative of all
organisms, which comes before and is independent of the evolutionary
reproductive imperative of all life, precludes for the most part the second
option. Diffusion selection is the primary means a population has to maintain
control over a partially open system.
9. Diffusion indirectly destabilizes systems by
destabilizing neighboring systems to which they are partly attached. Ecosystems
coexist and co-evolve in dynamic equilibrium with one another. To introduce
changes into one system is to induce reverberating changes in other systems.
10. The very mechanisms that induce stability within
the system established and controlled by a population, in the long run lead to
instability of that system as the indirect result of that system's interaction
with other systems. The differential functions that create instability in the
system established by a population, will, under another prevailing set of
conditions, cause that population to speciate more rapidly. The results of rapid
speciation can be the reestablishment of some new niche equilibrium in the
resulting population.
The object of this chapter has been to explain the
model of natural selection in as systematic terms as possible, short of the
delineation of a complex mathematical programming model, which would be a
minimum construct necessary to the problem of description. Even such a
sophisticated model though, could neither recount the steps of evolution that
life has already taken, nor could it accurately predict the steps that life will
take in the future. At best it would be an applied heuristic model to help us to
understand and better explain in theoretical terms the processes that do appear
to regularly occur in evolution.
It has been done with the idea of developing a more
complex and sophisticated account of natural selection processes underlying
evolutionary development. In general, this account leads to an understanding of
natural selection in evolution as a form of natural self-organized
"intelligence" that is essentially problem-solving in a blind,
distributed, and stochastic sense, but problem-solving nevertheless.
I wish to complete this final chapter of the second
part to emphasize the connection between biological systems and human systems,
which are a subset of biological systems. We live in an evolutionary epoch that
is distinguished by one single set of characteristics. These are the distinctive
characteristics of the human system that has come to dominate the biosphere in
many basic ways. I further address these issues in the first chapter of the
third part treating human systems.
Life has been a grand biological synthesis. Its
complexity and order is more than sublime when we consider that it was founded
essentially on stochastic mechanisms alone. The regularity exhibited in the
informational patterning of life is anything but chance, and can only be
faithfully understood in terms of systems science. This is essentially no
different than the grand stochastic pattern underlying the structure of the
total universe itself. I will undertake to show that the same stochastic pattern
of self-organizing systems can be employed in the accounting for human systems
and intelligent systems in general.
Blanket Copyright, Hugh M. Lewis, © 2005. Use of this text governed by fair use policy--permission to make copies of this text is granted for purposes of research and non-profit instruction only.
Last Updated: 08/25/09