Relative fitness

Fig. 5.9. Wavelength selection by Genetic Algorithm a 15 optimum wavelength selected from 86 of the full spectrum b relative fitness (rf/104) of the rim in dependence of the number of generations, above fitness of the best solution, middle mean, below fitness of the worst solution (Fischbacher et al. [1994/96 1995])... 

The best relative fit examines the possibility of a dilution factor between a given sample (xi) and a group s profile (q) as explained by Mommsen (79) where ... 

Figure 5. Scatter plot showing principal component analysis for all 225 samples after best-relative-fit factors were applied (symbols indicate chemical subgroups o =outliers/loners A = Subgroup 4A B = Subgroup 4B).

Since this representation of sequence space would be extremely complicated to view and apprehend, we choose to use a simplified cartoon. The cartoon representation of a fitness landscape (Fig. 3) used in this chapter has only three dimensions. The z-axis scales the relative fitness of molecules. Fitness is arbitrarily defined, and may pertain to how well an RNA binds to a particular ligand, or how well it catalyzes a desired reaction. The sequences on the top of the cartoon peaks have a higher degree of fitness than the ones on the plateau. The xy-plane represents a two-dimensional apparition of much more complex sequence spaces. Sequences that have smaller Hamming distances would be closer... 

Expectations for Equation 13 were given by Equation 3. These observations and expectations can be substituted into Equation 8 to obtain estimates of the relative fitness coefficients. However, these estimates are based on the assumption of genotypic frequency equilibrium. Since this... 

In this paper we detail investigations conducted in 1987-88 of the dynamics of resistance to dicofol in populations of T. urticae and P. ulmi. First, we relate the susceptibility of field populations of both spider mite species collected from over 30 different New York apple orchards to the use of dicofol within those orchards. Next, we describe the changes in susceptibility to dicofol of caged, heterogeneous populations of T. urticae maintained for 10-15 generations in the absence of selection with dicofol. Selection coefficients estimating the relative fitness (under the experiment... 

To estimate the relative fitness of the genotypes, dicofol resistance was modelled as a monogenic, recessive trait (22) and it was assumed that any fitness cost associated with the resistance gene would also be recessive. Allelic frequencies for the resistance alleles, R and S, are denoted by q and p, respectively. 

The mortality estimates (m) are estimates of the sum of the SS and RS genotype frequencies. Therefore, 1-m is an estimate of the frequency of the RR genotype and (l-m)1 i3 an estimate for q. The method presented by Wood and Cook (42) was slightly modified and used to estimate s based on the above models and data. Wood and Cook used 1-s to represent the relative fitness of individuals susceptible to a pesticide when resistance to the pesticide was recessive. Here 1-s is the relative fitness for the RR genotype. 

In these experiments dicofol-resistant T. urticae showed a much lower relative fitness than dicofol-susceptible animals. 

The relative fitness of the resistant biotype compared with the sensitive biotype. This also is a factor between zero and one that is multiplied times the natural daily survival at each growth stage. If the resistant and sensitive biotypes are equally fit, this factor is one. 

Fitness. Fitness of the resistant isolates may be a potentially important factor in identifying strategies to manage fungicide resistance. If the resistant isolates are considerably less fit than sensitive ones, then reversion to sensitivity in a population becomes a realistic consideration. Unfortunately, if fitness of resistant types is very similar to that of sensitive types, there are few options. However, relative fitnesses of resistant and sensitive biotypes are rarely known, and knowledgeable application of model results awaits empirical evidence. 

The relative fitness of resistant and sensitive biotypes in the absence of fungicide selective pressure (untreated fruit) is a... 

The lower relative fitness in most triazine resistant weeds is a very important reason why they have been fairly easily controlled, and why more problems of cross-resistance or multiple resistance have not occurred where both a triazine and another type of herbicide have been used together repeatedly. However, some cases of such cross-resistance are now beginning to appear, consistent with the predictions by Gressel and Segel (12). 

Natural selection for a particular trait incurs an initial cost to the organism in terms of fitness, or its ability to survive and reproduce. In weeds selected for herbicide resistance, this generalization holds true for biotypes possessing the maternally inherited trait of triazine resistance. This mutation has a detrimental effect on photosynthesis that results in decreased biomass production and reproductive output. However, compensatory interactions of the chloroplast and nuclear genomes may partially overcome reduced productivity. Expression of reduced productivity also appears to be regulated by environmental conditions. Whether similar trends in relative fitness will be found in weeds resistant to other herbicides remains to be examined. 

In instances where resistance is due to increased amounts of detoxifying enzymes (e.g., paraquat, diclofop-methyl, and chlortoluron) (10-121. the cost of resistance might be a concomitant decrease in other essential proteins (2). Where resistance is due to a modification in substrate affinity of the target enzyme (e.g., sulfonylureas) (131. the organism may produce increased amounts of the enzyme to compensate for its altered activity (2). Both of these mechanisms of resistance could theoretically result in slower growth of the organism. Unfortunately, at the present, no data is available on the relative fitness of plants resistant to these four groups of herbicides. 

Since the determination of absorption coefficients is in only 10-23 fxm thick layers, only relative concentrations can be determined, given in Fig. 5.72. Accordingly the partial photochemical quantum yields can only be approximated. Their values in Table 5.9 demonstrate that the absorption coefficients are determined to be too small. However, their values relatively fit to the data obtained in stirred solutions. These results prove the ability of the formalism presented in this book to treat photokinetic data even under extreme conditions. 

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