Encyclopedia of Evolution.pdf - Online Reading Center

chromosomes die when the cells die. The only changes that
persist beyond death are some of the mutations that occurred
in the germ line cells (the cells that produce eggs or sperm),
and then only if the person has children, and then only the
mutations that occurred before the person had children. In
the narrow sense, evolution acts only upon these inherited
(genetic) changes. If some individuals reproduce more than
others, the relative abundances of the genes of these individuals
will be different in the next generation (see natural
selection). This can happen only in populations. The alternative,
that the scars and experiences from a person’s entire
body or entire life can be passed on to future generations,
is named after one of its major 19th-century proponents,
Jean Baptiste de Lamarck (see Lamarckism). Even though
Charles Darwin himself considered this possibility, calling
it pangenesis, biologists now know that this process cannot
occur in organisms.
Lamarckian evolution can, however, occur in social interactions,
which is perhaps the major reason that the narrow
sense of evolution is not applied to them. Once the biological
basis of language had evolved, all further changes (such as the
development of specific languages by different tribes, the learning
and modification of languages by individuals) could be
passed on from one person, society, or generation to another
(see language, evolution of). Biological evolution usually
occurs slowly, because it has to wait for the right mutations to
come along in the germ line—and they may never do so. Social
evolution can occur rapidly, because as soon as a good new
idea comes along, everybody can adopt it. This is as true with
the invention of tool use by macaque monkeys, or the ability
of birds to open milk bottles, as it is with the rapid development
of new technologies in human society (see gene-culture
coevolution). Lamarckian social evolution has some parallels
with biological evolution, an idea explored by evolutionary
biologist Richard Dawkins (see Dawkins, Richard) with the
concept of memes, which are units of social evolution that correspond
to the genes of natural selection.
As Ernst Mayr has explained, evolution as presented by
Darwin has five tenets:
• Species are not constant; they change over time.
• All organisms had a common ancestral population.
• Evolutionary change occurs gradually.
• One species can diversify into more than one.
• Evolution occurs by natural selection.
Hardly anybody accepted all five tenets when Darwin first
presented them (see origin of species [book]). Darwin’s
evidence convinced most readers of the first two tenets. The
third, gradualism, is still debated (see punctuated equilibria).
The fourth tenet is accepted, but scientists still disagree
about how it occurs in many cases (see speciation). The triumph
of the fifth tenet had to wait until 60 years after Darwin’s
death (see modern synthesis).
Social evolution, though not evolution in the narrow
sense, may resemble biological evolution in a macroscale pattern.
When, for example, a new religion forms (as when Christianity
diverged from Judaism about two millennia ago), a
evolutionary algorithms
period of crisis occurs while the small, new religion seeks patterns
of belief and practice that make it recognizably distinct
from the large, old religion. Therefore a period of rapid evolution
can be said to occur in which most of the new beliefs
and practices take form, followed by a longer period of either
stasis or of much slower change. These changes allow the
new religion to be isolated from the old religion, permitting
it to evolve in its own direction. Isolation is necessary for the
evolution of new species and also appears to be important in
social evolution. In this manner, the speciation of a new religion
resembles the punctuated equilibria model of the evolution
of species. The resemblance, however, is only an analogy.
Finally, a distinction must be made between the process
of evolution (how it occurred) and the products of evolution
(what happened). It is one thing to describe an outline
of what happened in human evolution, and quite another to
explain why it happened the way it did. Evolution is both a
process and a product.
Of the many possible uses of the word evolution, scientists
usually restrict the use of the term to genetic changes
within populations, and the production of new species.
Further Reading
Blackmore, Susan. The Meme Machine. Oxford, U.K.: Oxford University
Press, 1999.
Fabian, A. C., ed. Evolution: Science, Society, and the Universe.
Cambridge, U.K.: Cambridge University Press, 1998.
Gould, Stephen Jay. “What does the dreaded ‘E’ word mean anyway?”
Chap. 18 in I Have Landed: The End of a Beginning in
Natural History. New York: Harmony, 2002.
Mayr, Ernst. What Evolution Is. New York: Basic Books, 2001.
Ormerod, Paul. Why Most Things Fail: Evolution, Extinction, and
Economics. New York: Pantheon, 2006.
evolutionary algorithms Also known as genetic algorithms,
evolutionary algorithms are computer program subunits
that use natural selection to achieve optimal solutions.
The concept of a genetic algorithm was originally proposed
by John Holland, the first person to receive a Ph.D. in computer
science. The evolutionary algorithm begins with a relatively
simple process, generates random mutations in that
process, then selects the best of the mutations. The choice
among mutations is made on the basis of the efficiency of the
process at producing a desired outcome. After numerous iterations,
an algorithm results that is typically much superior to
what a human programmer could have produced.
The similarity of evolutionary algorithms to natural
selection is evident. First, there must be a genetic process. In
the computer, it is the computer itself, both the hardware and
the original software with which it is provided. In organisms,
it is the genetic software (biochemical genetic machinery [see
DNA (raw material of evolution)], which stores and
expresses genetic information, and which allows mutations
to occur) and hardware (the cells, which provide metabolism).
Second, the mutations are generated at random, not by
a programmer or designer. Third, there is a clear definition
of what constitutes success or fitness. In the computer, it is