We can imagine a population as a ball sitting at some point on this surface. We would expect the population to respond to selection by moving across the fitness surface. The steepness of the contour at a particular point on the surface indicates the strength of selection that the population with those particular allelic characteristics would experience. We would expect the population to move uphill through directional selection, towards the point of highest mean fitness, and to take the steepest route to the top. Once at the top, we would expect balancing selection to keep the population at those equilibrium allele frequencies. Imagine a point where the fittest in the population consist mostly of heterozygotes or AaBb because of an intermediate frequency of both alleles. The population is at the peak defined by the peak one. But for the population to get to a higher frequency, it would have to move through a valley of low fitness and move to peaks AAbB or AaBB or AABB which is what peak 2 attempts to represent. Most neutralists would argue that selection would not allow this to happen and selection in each little micro habitat optimizes the local peak.
In fact, that population (or deme in some cases) adapts to the local, not the highest peak is used as an argument for drift. This is because it will take a force such as drift to move the population across a "valley".
The population genetic view of adaptive landscapes portrays the surface as combinations of mean allele frequencies, and the population as a single point on the surface.
However, we can also use the adaptive landscape model to think about the evolution of phenotypes . Here, the peaks on the surface represent the relative fitnesses of particular phenotypes in a population. These phenotypes are defined by the X and Y axes or phenotype A and phenotype B. A and B may even represent alternative solutions to a particular survival problem. In this model, the population is more like the entire surface, and the peaks and valleys allow us to predict the distribution of phenotypes we would expect to see in that population. For example, with a fitness surface containing two high peaks connected by a not very low valley, we might expect to see a continuum of generalists, whereas a surface of multiple, steep peaks separated then by low valleys might lead us to predict distinct phenotypes or specialization within the population.
This model can also be used to examine the evolution of related species, each with their own optimal fitness with regard to some trait.
Problems
This concept portrays natural selection as an optimizing process, where selection essentially moves in direction of improving the fit of populations or species to their environments over long periods of time. Most biologist recognize adaptation but really do not look upon it as the result of selection moving toward some optimum and feel the "fits" are often less than optimum. So what the constraints are to optimality is probably the more important question, i. e, not what keeps a population or species moving to another peak, but what makes a certain combination of genes a peak for a particular population or species in the first place. The concept still has some relevance for molecular studies and still a central concept in population genetics. It may become more important as the new field of Evo Devo develops. It also is still used to envision differences in species or populations or phenotypes for future examination in evolutionary studies, but not as important as the concept of soft and hard selection right now for evolutionary ecology. The empirical ways to measure fitnesses on adaptive landscapes are also being replaced at the organismal level by newer approaches that study the "availability of linages".
You should be able to describe an adaptive landscape. Problems with this model have caused ecologists to look at other factors that can influence fitness, and in so doing so, maintain population genic variation.
Natural selection can, in theory, maintain a great deal of polymorphism by frequency dependence of fitnesses, as well as by heterozygote advantage.
Or selection can operate without running up an increased toll on survivorship, if it is soft selection rather than hard selection
3. Soft and hard selection. First coined by Wallace to in part address load and cost of selection, Evolution vol 29, No. 3 Sep. 1975
* soft selection: selective deaths are substituted for non selective background mortality
* hard selection: selection occurs as extra mortality, which occurs on top of the background mortality
Figure I. Representations of hard and soft selection. (a) The concept of hard and soft selection (with respect to population density only, for simplicity not showing frequency dependence). A population of N adults with average fecundity of 2F per female produces FN eggs. As maximum adult population size is limited to N by some external factor, such as availability of space or food, 2F–N eggs must die each generation. This mortality can be random with respect to genotype and, therefore, nonselective (in yellow), or selective (soft selection, in red), but cannot depress population size below N. Hard selection (in black) introduces an additional, density independent source of mortality, which reduces population size below N. (b) An early representation of hard versus soft selection in the context of a metapopulation. In(i), the small-grain breeder saves all heads bearing 60 or more seeds for planting and future selection; some experimental plots are entirely discarded under this scheme. In (ii), the breeder first samples a few heads from plants of each experimental plot, determines the statistical distribution of seeds per head for each plot, and then harvests what is estimated to be the best 5% of all heads of each plot for planting and further selection. Under this scheme, a few heads are saved from each plot regardless of its average number of seeds per head. Soft selection resembles the second scheme, hard selection the first. Black shading indicates those individuals that were selected to reproduce, no shading those that were not selected. selection incorporates the idea that most populations appear to be at K, and mortality becomes more selective as get nearer to K.
Read this paper for more information on this topic; focus on examples of soft and hard selection.
The important concept here is that soft selection allows variation in the phenotypes maintained in the population without causing substantial decreases in survivalship or reproduction.
4. Frequency dependent selection.
Please review the entire story of the happy face spider. This is a great example of frequency dependent selection, although the exactly how selection works in this particular example has not been fully tested.
http://evolution.berkeley.edu/evolibrary/article/0_0_0/happyface_01
5. Heterozygote advantage.
This is becoming the default hypothesis for a number of human health problems where deleterious alleles persist above the level expected given mutation rates and selection against them. Although some allele cause disease in the homozygous recessive state the, the alleles are maintained in the population because the heterozygous state is favoured by natural selection.
The classic and most researched example is that of sickle cell disease that is associated with increased resistance to malaria when the sickle cell allele is found in the heterozygous state.
https://www.biointeractive.org/classroom-resources/making-fittest-natural-selection-humans
Know the proposed heterozygote advantage associated with each of these diseases or gene (last term in list). Paper on heterozygote advantage
Thalassemia
Cystic fibrosis
Tay sachs
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CCR5 |
6. For prokaryotes. Prokaryotes have a unique ability to acquire variability through "horizontal or lateral" transfer.
https://evolution.berkeley.edu/evolibrary/news/080401_mrsa
https://evolution.berkeley.edu/evolibrary/article/side_0_0/turboevolution_01
and it never ends http://blogs.discovermagazine.com/80beats/2008/06/04/whoops-anti-bacterial-wipes-can-spread-disease-2/#.XErSsoWtWmk