Annoying Creationists
Perhaps if I post this reference so kindly given by Delphi then you might understand why mutation and selection can not do what you assert.
http://en.wikipedia.org/wiki/Fitness_landscape
You are trying to assert that hundreds, perhaps thousands of genes can be transformed in order to evolve a lizard population into a bird population. There is no mathematical or empirical basis for this type of speculation. Mutation and selection can only transform a tiny number of genes subject to selection conditions. This is why three drug therapy combination works for the treatment of HIV despite the fact that HIV is a very rapidly reproducing virus with huge populations and high mutation rates. Despite this, effective three drug combination therapy profoundly slow the ability of this virus to find a trajectory on the fitness landscape to optimize fitness against three selection conditions. If you were to use the same three drugs sequentially, the population could easily evolve to these selection conditions in weeks.
When you try to extrapolate this mathematical behavior to a slowly reproducing lizard population with much small population size than HIV and much smaller mutation rates, you can not transform these huge lizard genomes into bird genomes. It is mathematically impossible. The mutation and selection sorting/optimization process simply does not work this way. The concept of common descent is mathematically and empirically irrational and the persistent evolutionist assertion that mutation and selection does to this contributes to the premature death of millions of people with diseases subject to mutation and selection. Here is another example of how the mutation and selection sorting/optimization process actually works. http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15766932
Perhaps if I post this reference so kindly given by Delphi then you might understand why mutation and selection can not do what you assert.
http://en.wikipedia.org/wiki/Fitness_landscape
Fitness landscapes in evolutionary optimization said:Apart from the field of evolutionary biology, the concept of a fitness landscape has also gained importance in evolutionary optimization methods such as genetic algorithms or evolutionary strategies. In evolutionary optimization, one tries to solve real-world problems (e.g., engineering or logistics problems) by imitating the dynamics of biological evolution. For example, a delivery truck with a number of destination addresses can take a large variety of different routes, but only very few will result in a short driving time. In order to use evolutionary optimization, one has to define for every possible solution s to the problem of interest (i.e., every possible route in the case of the delivery truck) how 'good' it is. This is done by introducing a scalar-valued function f(s) (scalar valued means that f(s) is a simple number, such as 0.3, while s can be a more complicated object, for example a list of destination addresses in the case of the delivery truck), which is called the fitness function or fitness landscape. A high f(s) implies that s is a good solution. In the case of the delivery truck, f(s) could be the number of deliveries per hour on route s. The best, or at least a very good, solution is then found in the following way. Initially, a population of random solutions is created. Then, the solutions are mutated and selected for those with higher fitness, until a satisfying solution has been found.
Fitness landscapes in evolutionary optimization said:
Evolutionary optimization techniques are particularly useful in situations in which it is easy to determine the quality of a single solution, but hard to go through all possible solutions one by one (it is easy to determine the driving time for a particular route of the delivery truck, but it is almost impossible to check all possible routes once the number of destinations grows to more than a handful).
The concept of a scalar valued fitness function f(s) also corresponds to the concept of a potential or energy function in physics. The two concepts only differ in that physicists traditionally think in terms of minimizing the potential function, while biologists prefer the notion that fitness is being maximized. Therefore, multiplying a potential function by -1 turns it into a fitness function, and vice versa.
You are trying to assert that hundreds, perhaps thousands of genes can be transformed in order to evolve a lizard population into a bird population. There is no mathematical or empirical basis for this type of speculation. Mutation and selection can only transform a tiny number of genes subject to selection conditions. This is why three drug therapy combination works for the treatment of HIV despite the fact that HIV is a very rapidly reproducing virus with huge populations and high mutation rates. Despite this, effective three drug combination therapy profoundly slow the ability of this virus to find a trajectory on the fitness landscape to optimize fitness against three selection conditions. If you were to use the same three drugs sequentially, the population could easily evolve to these selection conditions in weeks.
When you try to extrapolate this mathematical behavior to a slowly reproducing lizard population with much small population size than HIV and much smaller mutation rates, you can not transform these huge lizard genomes into bird genomes. It is mathematically impossible. The mutation and selection sorting/optimization process simply does not work this way. The concept of common descent is mathematically and empirically irrational and the persistent evolutionist assertion that mutation and selection does to this contributes to the premature death of millions of people with diseases subject to mutation and selection. Here is another example of how the mutation and selection sorting/optimization process actually works. http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15766932
Examples like this demonstrate empirically what Dr Schneider’s model shows mathematically and what the Wikipedia reference to fitness landscape are describing with single versus multiple conditions and the ability of a population to find a trajectory on the fitness landscape and to find an optima. It is the number of selection conditions and the number of genes targeted which dominates the mathematical and empirical behavior of the mutation and selection sorting/optimization process.The 2362 strain of Bacillus sphaericus (Bs) Neide is a highly mosquitocidal bacterium used in commercial bacterial larvicides primarily to control mosquitoes of the genus Culex. Unfortunately, Bs is at high risk for selecting resistance in mosquito populations, because its binary toxin apparently only binds to a single receptor type on midgut microvilli. A potential key strategy for delaying resistance to insecticidal proteins is to use mixtures of toxins that act at different targets within the insect, especially mixtures that interact synergistically. We tested this hypothesis for delaying the phenotypic expression of resistance by exposing Culex quinquefasciatus Say larvae to Bs alone or in combination with Cyt1A from Bacillus thuringiensis subsp. israelensis. Two laboratory lines of Cx. quinquefasciatus, one sensitive to Bs and the other containing Bs resistance alleles, were subjected to intensive selection pressure for 20 generations with either Bs 2362 or a 3:1 mixture of Bs 2362+Cyt1A. At the end of the study, the sensitive line had evolved >1000-fold resistance when selected with Bs alone, whereas the parallel line selected with Bs+Cyt1A exhibited only low resistance toward this mixture (RR95, 1.4). Similar results were observed in the lines containing Bs resistance alleles. Both lines selected with Bs+Cyt1A exhibited substantial resistance to Bs in the absence of Cyt1A. Although selection with Bs+Cyt1A did not prevent the underlying evolution of resistance to Bs, these results suggest that a mixture of Bs with other endotoxins, particularly one like Bs+Cyt1A in which the components interact synergistically, will provide longer lasting and more effective mosquito control than Bs alone.