|
A
third noteworthy way of conceptualising the process of natural selection is in
terms of movement within a ‘fitness landscape.’ The
concept of the fitness landscape was first introduced by Sewall Wright in the
1930s and has proven a useful way to visualise how the addition of ‘parameters’
will influence the possible paths of evolution. This in turn can help us apply
the abstract idea of evolution to actual biology. The landscape is typically
pictured as a mountain range with several peaks of varying height, and valleys
in-between. The height at any point on the landscape corresponds to its fitness
value; i.e. the higher the point, the greater the fitness of an organism that
occupies that spot.
The
algorithmic conception makes clear how an organism undergoing Darwinian natural
selection will tend to increase its fitness value. When viewed in terms of
fitness landscapes it explains how the organism will move ‘up hill.’ As we saw
above, an over-simplistic view of natural selection as an algorithm results in
the fitness tending to infinity, but when contextualised on a fitness
landscape, the possible fitness values are constrained to just those in the
terrain; i.e. it can reach the top of a mountain or plateau, but can go no
further. Richard Dawkins used the model of fitness landscapes to great effect
in his 1996 book Climbing Mount
Improbable.
While
this conceptual tool adds needed complexity to a model of evolution, it has
several limitations. For example, it gives the false impression that the
landscape of possible adaptations is fixed. A more realistic representation of
the relationship between organisms, environment and fitness would show the
landscape changing as a result of the movement (i.e. adaptation) of organisms
within it. It also does not make sufficiently clear the influence that
adaptations in one organism will have on the fitness landscape of its peers. As
Dennett says: “there is a tight interaction between the shape of the fitness
landscape and the population that occupies it, creating a series of feedback loops
...The landscape is constantly shifting under your feet.”
It
is also tempting to assume that organisms that reach higher up the tallest
peaks are ‘better’ than those lower down or on shorter peaks. Like all models
and metaphors fitness landscapes have their limitations. The height of a point
on the landscape does not indicate a score of ‘goodness’ or complexity, but
solely the fitness of that organism to that local
environment.
Importantly,
it must be acknowledged that coming up with an objective value for fitness is
harder than it may seem. Working from a traditionally Darwinian perspective, we
might propose that fitness could be measured in terms of number of progeny
produced over unit time, but this is clearly inadequate since it does not
consider elephants to be very fit at all. Other possible measures of fitness
include: the complexity of individual organisms, the ability to survive in
multiple habitats, or to evolve quickly to changing environments, or total
biomass, or the ability to respond intelligently to complex problems. Gould is
quick to point out that for three out of five of these measures bacteria are
superior to humans.
A
detailed model of the overall fitness of organisms would probably require
several different landscapes, each representing a different aspect of
adaptations that influences overall fitness.
Printer-friendly
| Feedback | Contributed by: Adrian Wyard
|
