Deeply Rooted: The Story of Congaree National Park

This photo-essay book was written to fulfill requirements for completion of a senior thesis project to graduate with honors from the South Carolina Honors College. Its purpose is to promote the enjoyment and preservation of the Congaree National Park by educating the public on the historical and ecological significance of the land and the many activities it has to offer. Despite its proximity to downtown Columbia, there remains a lack of public awareness about the park and the amazing activities and opportunities it has to offer. I have compiled information and pictures that will best depict the unique qualities of the area. This project was a culmination of research, photography, hiking, and wildlife identification resulting in the publication of a photo-essay book on the Congaree National Park. The book describes specific areas of the park, as well as, the historical, cultural, and natural significance; includes a nature guide for common invasive species and native plant and animal species; and discusses management, volunteering, and recreational activities. This book, which will be available to University of South Carolina students and local residents, will serve as a gateway to establish background understanding of the importance of the land, as well as motivate individuals to visit the Congaree National Park

Accurate and Efficient Expression Evaluation and Linear Algebra

We survey and unify recent results on the existence of accurate algorithms for evaluating multivariate polynomials, and more generally for accurate numerical linear algebra with structured matrices. By "accurate" we mean that the computed answer has relative error less than 1, i.e., has some correct leading digits. We also address efficiency, by which we mean algorithms that run in polynomial time in the size of the input. Our results will depend strongly on the model of arithmetic: Most of our results will use the so-called Traditional Model (TM). We give a set of necessary and sufficient conditions to decide whether a high accuracy algorithm exists in the TM, and describe progress toward a decision procedure that will take any problem and provide either a high accuracy algorithm or a proof that none exists. When no accurate algorithm exists in the TM, it is natural to extend the set of available accurate operations by a library of additional operations, such as $x+y+z$, dot products, or indeed any enumerable set which could then be used to build further accurate algorithms. We show how our accurate algorithms and decision procedure for finding them extend to this case. Finally, we address other models of arithmetic, and the relationship between (im)possibility in the TM and (in)efficient algorithms operating on numbers represented as bit strings.Comment: 49 pages, 6 figures, 1 tabl

Transition probabilities for general birth-death processes with applications in ecology, genetics, and evolution

A birth-death process is a continuous-time Markov chain that counts the number of particles in a system over time. In the general process with $n$ current particles, a new particle is born with instantaneous rate $\lambda_n$ and a particle dies with instantaneous rate $\mu_n$. Currently no robust and efficient method exists to evaluate the finite-time transition probabilities in a general birth-death process with arbitrary birth and death rates. In this paper, we first revisit the theory of continued fractions to obtain expressions for the Laplace transforms of these transition probabilities and make explicit an important derivation connecting transition probabilities and continued fractions. We then develop an efficient algorithm for computing these probabilities that analyzes the error associated with approximations in the method. We demonstrate that this error-controlled method agrees with known solutions and outperforms previous approaches to computing these probabilities. Finally, we apply our novel method to several important problems in ecology, evolution, and genetics

Evolution in fine-grained environments. II. Habitat selection as a homeostatic mechanism

A model of genotype specific habitat selection is developed for an organism subject to within-lifetime environmental fluctuations. Habitat selection is first overlaid upon both hard and soft selection Levene models with either discrete or continuous habitats. It is shown that even if all genotypes have identical physiological and fitness responses within a habitat, habitat selection can still maintain a polymorphism. In other words, physiological divergence is not a necessary prerequisite for divergence in habitat preferences. Within-lifetime environmental variability is then assumed to occur within each chosen habitat. It is shown that habitat selection acts as an evolutionary filter that can enhance the fitness impact of some niches and effectively eliminate the impact of others such that it generally increases the chances for a polymorphism under soft selection. However, density-dependent effects obscure the relationship between physiological fitness and evolutionary outcome. Indeed, it is possible for selection to favor an allele causing its bearers to preferentially go to the niche to which they are least physiologically adapted. Hence, changes in habitat preference can evolve before an organism has completely adapted physiologically to a new habitat. The fitness impact of habitat selection interacts with both homeostatic avoidance mechanisms (i.e., short-term buffering) and with tolerance (long-term) mechanisms. In general, habitat selection will be most favored in those organisms deficient in long-term tolerance. Moreover, habitat selection tends to accentuate selection favoring short-term avoidance mechanisms. Thus, organisms displaying much habitat selection should have poor physiological long-term tolerances but effective physiological short-term avoidance mechanisms. Finally, if the fitness costs associated with habitat selection are too large to be ignored and are comparable for all genotypes, habitat selection directs the selective pressures back onto the physiological homeostatic capabilities. Hence, the very existence and extent of habitat selection depends critically upon the physiological capabilities of the organism.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/24361/1/0000630.pd

Strategy abundance in 2x2 games for arbitrary mutation rates

We study evolutionary game dynamics in a well-mixed populations of finite size, N. A well-mixed population means that any two individuals are equally likely to interact. In particular we consider the average abundances of two strategies, A and B, under mutation and selection. The game dynamical interaction between the two strategies is given by the 2x2 payoff matrix [(a,b), (c,d)]. It has previously been shown that A is more abundant than B, if (N-2)a+Nb>Nc+(N-2)d. This result has been derived for particular stochastic processes that operate either in the limit of asymptotically small mutation rates or in the limit of weak selection. Here we show that this result holds in fact for a wide class of stochastic birth-death processes for arbitrary mutation rate and for any intensity of selection.Comment: version 2 is the final published version that contains minor changes in response to referee comment

Mutation-Selection Balance: Ancestry, Load, and Maximum Principle

We show how concepts from statistical physics, such as order parameter, thermodynamic limit, and quantum phase transition, translate into biological concepts in mutation-selection models for sequence evolution and can be used there. The article takes a biological point of view within a population genetics framework, but contains an appendix for physicists, which makes this correspondence clear. We analyze the equilibrium behavior of deterministic haploid mutation-selection models. Both the forward and the time-reversed evolution processes are considered. The stationary state of the latter is called the ancestral distribution, which turns out as a key for the study of mutation-selection balance. We find that it determines the sensitivity of the equilibrium mean fitness to changes in the fitness values and discuss implications for the evolution of mutational robustness. We further show that the difference between the ancestral and the population mean fitness, termed mutational loss, provides a measure for the sensitivity of the equilibrium mean fitness to changes in the mutation rate. For a class of models in which the number of mutations in an individual is taken as the trait value, and fitness is a function of the trait, we use the ancestor formulation to derive a simple maximum principle, from which the mean and variance of fitness and the trait may be derived; the results are exact for a number of limiting cases, and otherwise yield approximations which are accurate for a wide range of parameters. These results are applied to (error) threshold phenomena caused by the interplay of selection and mutation. They lead to a clarification of concepts, as well as criteria for the existence of thresholds.Comment: 54 pages, 15 figures; to appear in Theor. Pop. Biol. 61 or 62 (2002

Evolutionary Games with Affine Fitness Functions: Applications to Cancer

We analyze the dynamics of evolutionary games in which fitness is defined as an affine function of the expected payoff and a constant contribution. The resulting inhomogeneous replicator equation has an homogeneous equivalent with modified payoffs. The affine terms also influence the stochastic dynamics of a two-strategy Moran model of a finite population. We then apply the affine fitness function in a model for tumor-normal cell interactions to determine which are the most successful tumor strategies. In order to analyze the dynamics of concurrent strategies within a tumor population, we extend the model to a three-strategy game involving distinct tumor cell types as well as normal cells. In this model, interaction with normal cells, in combination with an increased constant fitness, is the most effective way of establishing a population of tumor cells in normal tissue.Comment: The final publication is available at http://www.springerlink.com, http://dx.doi.org/10.1007/s13235-011-0029-

Impact of target site distribution for Type I restriction enzymes on the evolution of methicillin-resistant Staphylococcus aureus (MRSA) populations.

A limited number of Methicillin-resistant Staphylococcus aureus (MRSA) clones are responsible for MRSA infections worldwide, and those of different lineages carry unique Type I restriction-modification (RM) variants. We have identified the specific DNA sequence targets for the dominant MRSA lineages CC1, CC5, CC8 and ST239. We experimentally demonstrate that this RM system is sufficient to block horizontal gene transfer between clinically important MRSA, confirming the bioinformatic evidence that each lineage is evolving independently. Target sites are distributed randomly in S. aureus genomes, except in a set of large conjugative plasmids encoding resistance genes that show evidence of spreading between two successful MRSA lineages. This analysis of the identification and distribution of target sites explains evolutionary patterns in a pathogenic bacterium. We show that a lack of specific target sites enables plasmids to evade the Type I RM system thereby contributing to the evolution of increasingly resistant community and hospital MRSA

On the general one-dimensional XY Model: positive and zero temperature, selection and non-selection

We consider $(M,d)$ a connected and compact manifold and we denote by $\mathcal{B}_i$ the Bernoulli space $M^{\Z}$ of sequences represented by $$x=(... x_{-3},x_{-2},x_{-1},x_0,x_1,x_2,x_3,...),$$ where $x_i$ belongs to the space (alphabet) $M$. The case where $M=\mathbb{S}^1$, the unit circle, is of particular interest here. The analogous problem in the one-dimensional lattice $\mathbb{N}$ is also considered. %In this case we consider the potential $A: {\cal B}=M^\mathbb{N} \to \mathbb{R}.$ Let A: \mathcal{B}_i \rar \R be an {\it observable} or {\it potential} defined in the Bernoulli space $\mathcal{B}_i$. The potential $A$ describes an interaction between sites in the one-dimensional lattice $M^\mathbb{Z}$. Given a temperature $T$, we analyze the main properties of the Gibbs state $\hat{\mu}_{\frac{1}{T} A}$ which is a certain probability measure over ${\cal B}_i$. We denote this setting "the general XY model". In order to do our analysis we consider the Ruelle operator associated to $\frac{1}{T} A$, and, we get in this procedure the main eigenfunction $\psi_{\frac{1}{T} A}$. Later, we analyze selection problems when temperature goes to zero: a) existence, or not, of the limit (on the uniform convergence) $$V:=\lim_{T\to 0} T\, \log(\psi_{\frac{1}{T} A}),\,\,\,\,\text{a question about selection of subaction},$$ and, b) existence, or not, of the limit (on the weak$^*$ sense) $$\tilde{\mu}:=\lim_{T\to 0} \hat{\mu}_{\frac{1}{T}\, A},\,\,\,\,\text{a question about selection of measure}.$$ The existence of subactions and other properties of Ergodic Optimization are also considered

Accurate statistical model of comparison between multiple sequence alignments

Comparison of multiple protein sequence alignments (MSA) reveals unexpected evolutionary relations between protein families and leads to exciting predictions of spatial structure and function. The power of MSA comparison critically depends on the quality of statistical model used to rank the similarities found in a database search, so that biologically relevant relationships are discriminated from spurious connections. Here, we develop an accurate statistical description of MSA comparison that does not originate from conventional models of single sequence comparison and captures essential features of protein families. As a final result, we compute E-values for the similarity between any two MSA using a mathematical function that depends on MSA lengths and sequence diversity. To develop these estimates of statistical significance, we first establish a procedure for generating realistic alignment decoys that reproduce natural patterns of sequence conservation dictated by protein secondary structure. Second, since similarity scores between these alignments do not follow the classic Gumbel extreme value distribution, we propose a novel distribution that yields statistically perfect agreement with the data. Third, we apply this random model to database searches and show that it surpasses conventional models in the accuracy of detecting remote protein similarities