Bootstrap confidence regions for canonical variates: Application to studies of evolutionary differentiation

Theory recently developed to construct confidence regions based on the parametric bootstrap is applied to add inferential information to graphical displays of sample centroids in canonical variate analysis. Problems of morphometric differentiation among subspecies and species are addressed using numerical resampling procedures.

Strong selection against hybrids at a hybrid zone in the Ensatina ring species complex and its evolutionary implications

The analysis of interactions between lineages at varying levels of genetic divergence can provide insights into the process of speciation through the accumulation of incompatible mutations. Ring species, and especially the Ensatina eschscholtzii system exemplify this approach. The plethodontid salamanders E. eschscholtzii xanthoptica and E. eschscholtzii platensis hybridize in the central Sierran foothills of California. We compared the genetic structure across two transects (southern and northern Calaveras Co.), one of which was resampled over 20 years, and examined diagnostic molecular markers (eight allozyme loci and mitochondrial DNA) and a diagnostic quantitative trait (color pattern). Key results across all studies were: (1) cline centers for all markers were coincident and the zones were narrow, with width estimates of 730 m to 2000 m; (2) cline centers at the northern Calaveras transect were coincident between 1981 and 2001, demonstrating repeatability over five generations; (3) there were very few if any putative F1s, but a relatively high number of backcrossed individuals in the central portion of transects: and (4) we found substantial linkage disequilibrium in all three studies and strong heterozygote deficit both in northern Calaveras, in 2001, and southern Calaveras. Both linkage disequilibrium and heterozygote deficit showed maximum values near the center of the zones. Using estimates of cline width and dispersal, we infer strong selection against hybrids. This is sufficient to promote accumulation of differences at loci that are neutral or under divergent selection, but would still allow for introgression of adaptive alleles. The evidence for strong but incomplete isolation across this centrally located contact is consistent with theory suggesting a gradual increase in postzygotic incompatibility between allopatric populations subject to divergent selection and reinforces the value of Ensatina as a system for the study of divergence and speciation at multiple stages. © 2005 The Society for the Study of Evolution. All rights reserved.

Application of an iterative method and an evolutionary algorithm in fuzzy optimization

This work develops two approaches based on the fuzzy set theory to solve a class of fuzzy mathematical optimization problems with uncertainties in the objective function and in the set of constraints. The first approach is an adaptation of an iterative method that obtains cut levels and later maximizes the membership function of fuzzy decision making using the bound search method. The second one is a metaheuristic approach that adapts a standard genetic algorithm to use fuzzy numbers. Both approaches use a decision criterion called satisfaction level that reaches the best solution in the uncertain environment. Selected examples from the literature are presented to compare and to validate the efficiency of the methods addressed, emphasizing the fuzzy optimization problem in some import-export companies in the south of Spain. © 2012 Brazilian Operations Research Society.

Efficient Forest Data Structure for Evolutionary Algorithms Applied to Network Design

The design of a network is a solution to several engineering and science problems. Several network design problems are known to be NP-hard, and population-based metaheuristics like evolutionary algorithms (EAs) have been largely investigated for such problems. Such optimization methods simultaneously generate a large number of potential solutions to investigate the search space in breadth and, consequently, to avoid local optima. Obtaining a potential solution usually involves the construction and maintenance of several spanning trees, or more generally, spanning forests. To efficiently explore the search space, special data structures have been developed to provide operations that manipulate a set of spanning trees (population). For a tree with n nodes, the most efficient data structures available in the literature require time O(n) to generate a new spanning tree that modifies an existing one and to store the new solution. We propose a new data structure, called node-depth-degree representation (NDDR), and we demonstrate that using this encoding, generating a new spanning forest requires average time O(root n). Experiments with an EA based on NDDR applied to large-scale instances of the degree-constrained minimum spanning tree problem have shown that the implementation adds small constants and lower order terms to the theoretical bound.

Does Evolution matter?: a case study in Brazil of the effects of an evolutionary-thinking academic atmosphere in postgraduate students' belief in God/religious belief

Although the theory of evolution is more than 150 years old, a substantial proportion of the world population does not mention it when explaining the origin of human beings. The usual alternative conception is offered by creationism, one of the main obstacles to full acceptance of evolution in many countries. National polls have demonstrated that schooling and religiosity are negatively correlated, with scientists being one of the least religious professionals. Herein we analyzed both (1) the profile of 1st semester undergraduate students and (2), thesis and dissertations, concerning religious and evolutionary thoughts from Biology and Veterinary Schools at the largest university of South America. We have shown that students of Biology are biased towards evolution before they enter university and also that the presence of an evolutionary-thinking academic atmosphere influences the deism/religiosity beliefs of postgraduate students.

Evolutionary methods for self-organizing cooperation in peer-to-peer networks

The Peer-to-Peer network paradigm is drawing the attention of both final users and researchers for its features. P2P networks shift from the classic client-server approach to a high level of decentralization where there is no central control and all the nodes should be able not only to require services, but to provide them to other peers as well. While on one hand such high level of decentralization might lead to interesting properties like scalability and fault tolerance, on the other hand it implies many new problems to deal with. A key feature of many P2P systems is openness, meaning that everybody is potentially able to join a network with no need for subscription or payment systems. The combination of openness and lack of central control makes it feasible for a user to free-ride, that is to increase its own benefit by using services without allocating resources to satisfy other peers’ requests. One of the main goals when designing a P2P system is therefore to achieve cooperation between users. Given the nature of P2P systems based on simple local interactions of many peers having partial knowledge of the whole system, an interesting way to achieve desired properties on a system scale might consist in obtaining them as emergent properties of the many interactions occurring at local node level. Two methods are typically used to face the problem of cooperation in P2P networks: 1) engineering emergent properties when designing the protocol; 2) study the system as a game and apply Game Theory techniques, especially to find Nash Equilibria in the game and to reach them making the system stable against possible deviant behaviors. In this work we present an evolutionary framework to enforce cooperative behaviour in P2P networks that is alternative to both the methods mentioned above. Our approach is based on an evolutionary algorithm inspired by computational sociology and evolutionary game theory, consisting in having each peer periodically trying to copy another peer which is performing better. The proposed algorithms, called SLAC and SLACER, draw inspiration from tag systems originated in computational sociology, the main idea behind the algorithm consists in having low performance nodes copying high performance ones. The algorithm is run locally by every node and leads to an evolution of the network both from the topology and from the nodes’ strategy point of view. Initial tests with a simple Prisoners’ Dilemma application show how SLAC is able to bring the network to a state of high cooperation independently from the initial network conditions. Interesting results are obtained when studying the effect of cheating nodes on SLAC algorithm. In fact in some cases selfish nodes rationally exploiting the system for their own benefit can actually improve system performance from the cooperation formation point of view. The final step is to apply our results to more realistic scenarios. We put our efforts in studying and improving the BitTorrent protocol. BitTorrent was chosen not only for its popularity but because it has many points in common with SLAC and SLACER algorithms, ranging from the game theoretical inspiration (tit-for-tat-like mechanism) to the swarms topology. We discovered fairness, meant as ratio between uploaded and downloaded data, to be a weakness of the original BitTorrent protocol and we drew inspiration from the knowledge of cooperation formation and maintenance mechanism derived from the development and analysis of SLAC and SLACER, to improve fairness and tackle freeriding and cheating in BitTorrent. We produced an extension of BitTorrent called BitFair that has been evaluated through simulation and has shown the abilities of enforcing fairness and tackling free-riding and cheating nodes.

Dynamics of Spatial Game Theory Networks with Novel Modifications

Introduction: Advances in biotechnology have shed light on many biological processes. In biological networks, nodes are used to represent the function of individual entities within a system and have historically been studied in isolation. Network structure adds edges that enable communication between nodes. An emerging fieldis to combine node function and network structure to yield network function. One of the most complex networks known in biology is the neural network within the brain. Modeling neural function will require an understanding of networks, dynamics, andneurophysiology. It is with this work that modeling techniques will be developed to work at this complex intersection. Methods: Spatial game theory was developed by Nowak in the context of modeling evolutionary dynamics, or the way in which species evolve over time. Spatial game theory offers a two dimensional view of analyzingthe state of neighbors and updating based on the surroundings. Our work builds upon this foundation by studying evolutionary game theory networks with respect to neural networks. This novel concept is that neurons may adopt a particular strategy that will allow propagation of information. The strategy may therefore act as the mechanism for gating. Furthermore, the strategy of a neuron, as in a real brain, isimpacted by the strategy of its neighbors. The techniques of spatial game theory already established by Nowak are repeated to explain two basic cases and validate the implementation of code. Two novel modifications are introduced in Chapters 3 and 4 that build on this network and may reflect neural networks. Results: The introduction of two novel modifications, mutation and rewiring, in large parametricstudies resulted in dynamics that had an intermediate amount of nodes firing at any given time. Further, even small mutation rates result in different dynamics more representative of the ideal state hypothesized. Conclusions: In both modificationsto Nowak's model, the results demonstrate the network does not become locked into a particular global state of passing all information or blocking all information. It is hypothesized that normal brain function occurs within this intermediate range and that a number of diseases are the result of moving outside of this range.

Evolutionary demography of long-lived monocarpic perennials: a time-lagged integral projection model

1. The evolution of flowering strategies (when and at what size to flower) in monocarpic perennials is determined by balancing current reproduction with expected future reproduction, and these are largely determined by size-specific patterns of growth and survival. However, because of the difficulty in following long-lived individuals throughout their lives, this theory has largely been tested using short-lived species (< 5 years). 2. Here, we tested this theory using the long-lived monocarpic perennial Campanula thyrsoides which can live up to 16 years. We used a novel approach that combined permanent plot and herb chronology data from a 3-year field study to parameterize and validate integral projection models (IPMs). 3. Similar to other monocarpic species, the rosette leaves of C. thyrsoides wither over winter and so size cannot be measured in the year of flowering. We therefore extended the existing IPM framework to incorporate an additional time delay that arises because flowering demography must be predicted from rosette size in the year before flowering. 4. We found that all main demographic functions (growth, survival probability, flowering probability and fecundity) were strongly size-dependent and there was a pronounced threshold size of flowering. There was good agreement between the predicted distribution of flowering ages obtained from the IPMs and that estimated in the field. Mostly, there was good agreement between the IPM predictions and the direct quantitative field measurements regarding the demographic parameters lambda, R-0 and T. We therefore conclude that the model captures the main demographic features of the field populations. 5. Elasticity analysis indicated that changes in the survival and growth function had the largest effect (c. 80%) on lambda and this was considerably larger than in short-lived monocarps. We found only weak selection pressure operating on the observed flowering strategy which was close to the predicted evolutionary stable strategy. 6. Synthesis. The extended IPM accurately described the demography of a long-lived monocarpic perennial using data collected over a relatively short period. We could show that the evolution of flowering strategies in short- and long-lived monocarps seem to follow the same general rules but with a longevity-related emphasis on survival over fecundity.

Neutral biodiversity theory can explain the imbalance of phylogenetic trees but not the tempo of their diversification

Numerous evolutionary studies have sought to explain the distribution of diversity across the limbs of the tree of life. At the same time, ecological studies have sought to explain differences in diversity and relative abundance within and among ecological communities. Traditionally, these patterns have been considered separately, but models that consider processes operating at the level of individuals, such as neutral biodiversity theory (NBT), can provide a link between them. Here, we compare evolutionary dynamics across a suite of NBT models. We show that NBT can yield phylogenetic tree topologies with imbalance closely resembling empirical observations. In general, metacommunities that exhibit greater disparity in abundance are characterized by more imbalanced phylogenetic trees. However, NBT fails to capture the tempo of diversification as represented by the distribution of branching events through time. We suggest that population-level processes might therefore help explain the asymmetry of phylogenetic trees, but that tree shape might mislead estimates of evolutionary rates unless the diversification process is modeled explicitly.

Eco-evolutionary Dynamics of Individual-Based Food Webs

The past decade has seen the rise of high resolution datasets. One of the main surprises of analysing such data has been the discovery of a large genetic, phenotypic and behavioural variation and heterogeneous metabolic rates among individuals within natural populations. A parallel discovery from theory and experiments has shown a strong temporal convergence between evolutionary and ecological dynamics, but a general framework to analyse from individual-level processes the convergence between ecological and evolutionary dynamics and its implications for patterns of biodiversity in food webs has been particularly lacking. Here, as a first approximation to take into account intraspecific variability and the convergence between the ecological and evolutionary dynamics in large food webs, we develop a model from population genomics and microevolutionary processes that uses sexual reproduction, genetic-distance-based speciation and trophic interactions. We confront the model with the prey consumption per individual predator, species-level connectance and prey–predator diversity in several environmental situations using a large food web with approximately 25,000 sampled prey and predator individuals. We show higher than expected diversity of abundant species in heterogeneous environmental conditions and strong deviations from the observed distribution of individual prey consumption (i.e. individual connectivity per predator) in all the environmental conditions. The observed large variance in individual prey consumption regardless of the environmental variability collapsed species-level connectance after small increases in sampling effort. These results suggest (1) intraspecific variance in prey–predator interactions has a strong effect on the macroscopic properties of food webs and (2) intraspecific variance is a potential driver regulating the speed of the convergence between ecological and evolutionary dynamics in species-rich food webs. These results also suggest that genetic–ecological drift driven by sexual reproduction, equal feeding rate among predator individuals, mutations and genetic-distance-based speciation can be used as a neutral food web dynamics test to detect the ecological and microevolutionary processes underlying the observed patterns of individual and species-based food webs at local and macroecological scales.

MATHEMATICAL STUDIES ON THE EVOLUTIONARY CHANGE OF DNA SEQUENCES

With the aim of understanding the mechanism of molecular evolution, mathematical problems on the evolutionary change of DNA sequences are studied. The problems studied and the results obtained are as follows: (1) Estimation of evolutionary distance between nucleotide sequences. Studying the pattern of nucleotide substitution for the case of unequal substitution rates, a new mathematical formula for estimating the average number of nucleotide substitutions per site between two homologous DNA sequences is developed. It is shown that this formula has a wider applicability than currently available formulae. A statistical method for estimating the number of nucleotide changes due to deletion and insertion is also developed. (2) Biases of the estimates of nucleotide substitutions obtained by the restriction enzyme method. The deviation of the estimate of nucleotide substitutions obtained by the restriction enzyme method from the true value is investigated theoretically. It is shown that the amount of the deviation depends on the nucleotides in the recognition sequence of the restriction enzyme used, unequal rates of substitution among different nucleotides, and nucleotide frequences, but the primary factor is the unequal rates of nucleotide substitution. When many different kinds of enzymes are used, however, the amount of average deviation is generally small. (3) Distribution of restriction fragment lengths. To see the effect of undetectable restriction fragments and fragment differences on the estimate of nucleotide differences, the theoretical distribution of fragment lengths is studied. This distribution depends on the type of restriction enzymes used as well as on the relative frequencies of four nucleotides. It is shown that undetectability of small fragments or fragment differences gives a serious underestimate of nucleotide substitutions when the length-difference method of estimation is used, but the extent of underestimation is small when the site-difference method is used. (4) Evolutionary relationships of DNA sequences in finite populations. A mathematical theory on the expected evolutionary relationships among DNA sequences (nucleons) randomly chosen from the same or different populations is developed under the assumption that the evolutionary change of nucleons is determined solely by mutation and random genetic drift. . . . (Author's abstract exceeds stipulated maximum length. Discontinued here with permission of author). UMI ^

Disrupting evolutionary processes: The effect of habitat fragmentation on collared lizards in the Missouri Ozarks

Humans affect biodiversity at the genetic, species, community, and ecosystem levels. This impact on genetic diversity is critical, because genetic diversity is the raw material of evolutionary change, including adaptation and speciation. Two forces affecting genetic variation are genetic drift (which decreases genetic variation within but increases genetic differentiation among local populations) and gene flow (which increases variation within but decreases differentiation among local populations). Humans activities often augment drift and diminish gene flow for many species, which reduces genetic variation in local populations and prevents the spread of adaptive complexes outside their population of origin, thereby disrupting adaptive processes both locally and globally within a species. These impacts are illustrated with collared lizards (Crotaphytus collaris) in the Missouri Ozarks. Forest fire suppression has reduced habitat and disrupted gene flow in this lizard, thereby altering the balance toward drift and away from gene flow. This balance can be restored by managed landscape burns. Some have argued that, although human-induced fragmentation disrupts adaptation, it will also ultimately produce new species through founder effects. However, population genetic theory and experiments predict that most fragmentation events caused by human activities will facilitate not speciation, but local extinction. Founder events have played an important role in the macroevolution of certain groups, but only when ecological opportunities are expanding rather than contracting. The general impact of human activities on genetic diversity disrupts or diminishes the capacity for adaptation, speciation, and macroevolutionary change. This impact will ultimately diminish biodiversity at all levels.

Patterns of variance in stage-structured populations: Evolutionary predictions and ecological implications

Variability in population growth rate is thought to have negative consequences for organism fitness. Theory for matrix population models predicts that variance in population growth rate should be the sum of the variance in each matrix entry times the squared sensitivity term for that matrix entry. I analyzed the stage-specific demography of 30 field populations from 17 published studies for pattern between the variance of a demographic term and its contribution to population growth. There were no instances in which a matrix entry both was highly variable and had a large effect on population growth rate; instead, correlations between estimates of temporal variance in a term and contribution to population growth (sensitivity or elasticity) were overwhelmingly negative. In addition, survivorship or growth sensitivities or elasticities always exceeded those of fecundity, implying that the former two terms always contributed more to population growth rate. These results suggest that variable life history stages tend to contribute relatively little to population growth rates because natural selection may alter life histories to minimize stages with both high sensitivity and high variation.

The challenge of paleoecological stasis: reassessing sources of evolutionary stability.

The paleontological record of the lower and middle Paleozoic Appalachian foreland basin demonstrates an unprecedented level of ecological and morphological stability on geological time scales. Some 70-80% of fossil morphospecies within assemblages persist in similar relative abundances in coordinated packages lasting as long as 7 million years despite evidence for environmental change and biotic disturbances. These intervals of stability are separated by much shorter periods of ecological and evolutionary change. This pattern appears widespread in the fossil record. Existing concepts of the evolutionary process are unable to explain this uniquely paleontological observation of faunawide coordinated stasis. A principle of evolutionary stability that arises from the ecosystem is explored here. We propose that hierarchical ecosystem theory, when extended to geological time scales, can explain long-term paleoecological stability as the result of ecosystem organization in response to high-frequency disturbance. The accompanying stability of fossil morphologies results from "ecological locking," in which selection is seen as a high-rate response of populations that is hierarchically constrained by lower-rate ecological processes. When disturbance exceeds the capacity of the system, ecological crashes remove these higher-level constraints, and evolution is free to proceed at high rates of directional selection during the organization of a new stable ecological hierarchy.

Evidence against the exon theory of genes derived from the triose-phosphate isomerase gene.

The exon theory of genes proposes that the introns of protein-encoding nuclear genes are remnants of the DNA spacers between ancient minigenes. The discovery of an intron at a predicted position in the triose-phosphate isomerase (EC 5.3.1.1) gene of Culex mosquitoes has been hailed as an evidential pillar of the theory. We have found that that intron is also present in Aedes mosquitoes, which are closely related to Culex, but not in the phylogenetically more distant Anopheles, nor in the fly Calliphora vicina, nor in the moth Spodoptera littoralis. The presence of this intron in Culex and Aedes is parsimoniously explained as the result of an insertion in a recent common ancestor of these two species rather than as the remnant of an ancient intron. The absence of the intron in 19 species of very diverse organisms requires at least 10 independent evolutionary losses in order to be consistent with the exon theory.