Evolution__3rd_Edition

216 PART 2 / Evolutionary Genetics
Adaptive topographies may have
multiple peaks
A population may become
“trapped” on a local peak
Wright believed that, because the genes at different loci interact, a real multidimensional
fitness surface would often have multiple peaks, with valleys between them
(Figure 8.8b). The kind of reasoning involved is abstract rather than concrete. We need
to imagine a large number of loci, many with more than one allele, with the alleles at the
different loci interacting epistatically in their effects on fitness. Epistatic interactions,
we now imagine, are common because organisms are highly integrated entities compared
with the atomistic chromosomal row of Mendelian genes from which organisms
grow up: the genes will have to interact to produce an organism. As we saw above,
developmental interactions among genes do not automatically generate epistatic
fitness interactions among loci. The extent to which undoubted developmental interaction
will produce a multiply peaked fitness surface is therefore open to question; but
the possibility is plausible. (Wright called the genes that interact favorably to produce
an adaptive peak an “interaction system.”)
In the coadapted genes controlling mimicry in Papilio memnon, the mimetic
genotypes occupy fitness peaks and the recombinants occupy various fitness valleys.
The actual shape of the adaptive topography in nature is, however, a more advanced
question than can be tackled here. The point of this section is to define what an adaptive
topography is, and to point out that its visual simplicity can be useful in thinking about
evolution when many gene loci are interacting.
8.13 The shifting balance theory of evolution
Wright used his idea of adaptive topographies in a general theory of evolution. He
imagined that real topographies would have multiple peaks, separated by valleys, and
that some peaks would be higher than others. When the environment changed, and
competing species evolved new forms, the shape of the adaptive topography for a population
would change too. The surface would also change shape when a new mutation
arose. A new allele at a locus may interact with genes at other loci differently from the
existing alleles, and the fitnesses of the genes at the other loci will then be altered;
genetic changes will take place at other loci to adjust to the new mutant. All the time,
natural selection will be a hill-climbing process, directing the population up toward the
currently nearest peak. When the surface changes, the direction to the nearest peak may
change, and selection will then send the population off in the new upward direction.
Natural selection, even in so far as it is a hill-climbing (i.e., mean fitness maximizing)
process, is only a local hill-climbing process. In theory, the local fitness peak could be in
the opposite direction from a higher, or global, peak (Figure 8.9). Natural selection,
however, will direct the population to the local peak. Now suppose that the mean
fitness of a population is a measure of the quality of its adaptations, such that a population
with a higher mean fitness has better adaptations than a population with a lower
mean fitness. Because natural selection seeks out only local peaks, natural selection may
not always allow a population to evolve the best possible adaptations. A population
could be stuck on a merely locally adaptive peak. Natural selection works against
“valley crossing,” where fitness is lower. (Mean fitness cannot always be equated with
quality of adaptation. In the simple case in which one allele is superior to another (see
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