Bipartite Graphs as Models of Population Structures in Evolutionary Multiplayer Games

PubMed Central

Peña, Jorge; Rochat, Yannick

2012-01-01

By combining evolutionary game theory and graph theory, “games on graphs” study the evolutionary dynamics of frequency-dependent selection in population structures modeled as geographical or social networks. Networks are usually represented by means of unipartite graphs, and social interactions by two-person games such as the famous prisoner’s dilemma. Unipartite graphs have also been used for modeling interactions going beyond pairwise interactions. In this paper, we argue that bipartite graphs are a better alternative to unipartite graphs for describing population structures in evolutionary multiplayer games. To illustrate this point, we make use of bipartite graphs to investigate, by means of computer simulations, the evolution of cooperation under the conventional and the distributed N-person prisoner’s dilemma. We show that several implicit assumptions arising from the standard approach based on unipartite graphs (such as the definition of replacement neighborhoods, the intertwining of individual and group diversity, and the large overlap of interaction neighborhoods) can have a large impact on the resulting evolutionary dynamics. Our work provides a clear example of the importance of construction procedures in games on graphs, of the suitability of bigraphs and hypergraphs for computational modeling, and of the importance of concepts from social network analysis such as centrality, centralization and bipartite clustering for the understanding of dynamical processes occurring on networked population structures. PMID:22970237

Stochastic nonlinear dynamics pattern formation and growth models

PubMed Central

Yaroslavsky, Leonid P

2007-01-01

Stochastic evolutionary growth and pattern formation models are treated in a unified way in terms of algorithmic models of nonlinear dynamic systems with feedback built of a standard set of signal processing units. A number of concrete models is described and illustrated by numerous examples of artificially generated patterns that closely imitate wide variety of patterns found in the nature. PMID:17908341

The influence of tie strength on evolutionary games on networks: An empirical investigation

NASA Astrophysics Data System (ADS)

Buesser, Pierre; Peña, Jorge; Pestelacci, Enea; Tomassini, Marco

2011-11-01

Extending previous work on unweighted networks, we present here a systematic numerical investigation of standard evolutionary games on weighted networks. In the absence of any reliable model for generating weighted social networks, we attribute weights to links in a few ways supported by empirical data ranging from totally uncorrelated to weighted bipartite networks. The results of the extensive simulation work on standard complex network models show that, except in a case that does not seem to be common in social networks, taking the tie strength into account does not change in a radical manner the long-run steady-state behavior of the studied games. Besides model networks, we also included a real-life case drawn from a coauthorship network. In this case also, taking the weights into account only changes the results slightly with respect to the raw unweighted graph, although to draw more reliable conclusions on real social networks many more cases should be studied as these weighted networks become available.

Pyvolve: A Flexible Python Module for Simulating Sequences along Phylogenies.

PubMed

Spielman, Stephanie J; Wilke, Claus O

2015-01-01

We introduce Pyvolve, a flexible Python module for simulating genetic data along a phylogeny using continuous-time Markov models of sequence evolution. Easily incorporated into Python bioinformatics pipelines, Pyvolve can simulate sequences according to most standard models of nucleotide, amino-acid, and codon sequence evolution. All model parameters are fully customizable. Users can additionally specify custom evolutionary models, with custom rate matrices and/or states to evolve. This flexibility makes Pyvolve a convenient framework not only for simulating sequences under a wide variety of conditions, but also for developing and testing new evolutionary models. Pyvolve is an open-source project under a FreeBSD license, and it is available for download, along with a detailed user-manual and example scripts, from http://github.com/sjspielman/pyvolve.

Evolutionary inference via the Poisson Indel Process.

PubMed

Bouchard-Côté, Alexandre; Jordan, Michael I

2013-01-22

We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114-124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments.

Evolutionary inference via the Poisson Indel Process

PubMed Central

Bouchard-Côté, Alexandre; Jordan, Michael I.

2013-01-01

We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114–124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments. PMID:23275296

A taxonomy for the evolution of human settlements on the moon and Mars

NASA Technical Reports Server (NTRS)

Roberts, Barney B.; Mandell, Humboldt C.

1991-01-01

A proposed structure is described for partnerships with shared interests and investments to develop the technology and approach for evolutionary surface systems for the moon and Mars. Five models are presented for cooperation with specific references to the technical evolutionary path of the surface systems. The models encompass the standard customer/provider relationship, a concept for exclusive government use, a joint venture with a government-sponsored non-SEI market, a technology joint-development approach, and a redundancy model to insure competitive pricing. The models emphasize the nonaerospace components of the settlement technologies and the decentralized nature of surface systems that make the project suitable for private industrial development by several companies. It is concluded that the taxonomy be considered when examining collaborative opportunities for lunar and Martian settlement.

Evolutionary dynamics of the traveler's dilemma and minimum-effort coordination games on complex networks.

PubMed

Iyer, Swami; Killingback, Timothy

2014-10-01

The traveler's dilemma game and the minimum-effort coordination game are social dilemmas that have received significant attention resulting from the fact that the predictions of classical game theory are inconsistent with the results found when the games are studied experimentally. Moreover, both the traveler's dilemma and the minimum-effort coordination games have potentially important applications in evolutionary biology. Interestingly, standard deterministic evolutionary game theory, as represented by the replicator dynamics in a well-mixed population, is also inadequate to account for the behavior observed in these games. Here we study the evolutionary dynamics of both these games in populations with interaction patterns described by a variety of complex network topologies. We investigate the evolutionary dynamics of these games through agent-based simulations on both model and empirical networks. In particular, we study the effects of network clustering and assortativity on the evolutionary dynamics of both games. In general, we show that the evolutionary behavior of the traveler's dilemma and minimum-effort coordination games on complex networks is in good agreement with that observed experimentally. Thus, formulating the traveler's dilemma and the minimum-effort coordination games on complex networks neatly resolves the paradoxical aspects of these games.

Evolutionary dynamics of the traveler's dilemma and minimum-effort coordination games on complex networks

NASA Astrophysics Data System (ADS)

Iyer, Swami; Killingback, Timothy

2014-10-01

The traveler's dilemma game and the minimum-effort coordination game are social dilemmas that have received significant attention resulting from the fact that the predictions of classical game theory are inconsistent with the results found when the games are studied experimentally. Moreover, both the traveler's dilemma and the minimum-effort coordination games have potentially important applications in evolutionary biology. Interestingly, standard deterministic evolutionary game theory, as represented by the replicator dynamics in a well-mixed population, is also inadequate to account for the behavior observed in these games. Here we study the evolutionary dynamics of both these games in populations with interaction patterns described by a variety of complex network topologies. We investigate the evolutionary dynamics of these games through agent-based simulations on both model and empirical networks. In particular, we study the effects of network clustering and assortativity on the evolutionary dynamics of both games. In general, we show that the evolutionary behavior of the traveler's dilemma and minimum-effort coordination games on complex networks is in good agreement with that observed experimentally. Thus, formulating the traveler's dilemma and the minimum-effort coordination games on complex networks neatly resolves the paradoxical aspects of these games.

Properties of LEGUS Clusters Obtained with Different Massive-Star Evolutionary Tracks

NASA Astrophysics Data System (ADS)

Wofford, A.; Charlot, S.; Eldridge, J. J.

We compute spectral libraries for populations of coeval stars using state-of-the-art massive-star evolutionary tracks that account for different astrophysics including rotation and close-binarity. Our synthetic spectra account for stellar and nebular contributions. We use our models to obtain E(B - V ), age, and mass for six clusters in spiral galaxy NGC 1566, which have ages of < 50 Myr and masses of > 5 x 104M⊙ according to standard models. NGC 1566 was observed from the NUV to the I-band as part of the imaging Treasury HST program LEGUS: Legacy Extragalactic UV Survey. We aim to establish i) if the models provide reasonable fits to the data, ii) how well the models and photometry are able to constrain the cluster properties, and iii) how different the properties obtained with different models are.

Bottleneck Effect on Evolutionary Rate in the Nearly Neutral Mutation Model

PubMed Central

Araki, H.; Tachida, H.

1997-01-01

Variances of evolutionary rates among lineages in some proteins are larger than those expected from simple Poisson processes. This phenomenon is called overdispersion of the molecular clock. If population size N is constant, the overdispersion is observed only in a limited range of 2Nσ under the nearly neutral mutation model, where σ represents the standard deviation of selection coefficients of new mutants. In this paper, we investigated effects of changing population size on the evolutionary rate by computer simulations assuming the nearly neutral mutation model. The size was changed cyclically between two numbers, N(1) and N(2) (N(1) > N(2)), in the simulations. The overdispersion is observed if 2N(2)σ is less than two and the state of reduced size (bottleneck state) continues for more than ~0.1/u generations, where u is the mutation rate. The overdispersion results mainly because the average fitnesses of only a portion of populations go down when the population size is reduced and only in these populations subsequent advantageous substitutions occur after the population size becomes large. Since the fitness reduction after the bottleneck is stochastic, acceleration of the evolutionary rate does not necessarily occur uniformly among loci. From these results, we argue that the nearly neutral mutation model is a candidate mechanism to explain the overdispersed molecular clock. PMID:9335622

Studying the evolutionary significance of thermal adaptation in ectotherms: The diversification of amphibians' energetics.

PubMed

Nespolo, Roberto F; Figueroa, Julio; Solano-Iguaran, Jaiber J

2017-08-01

A fundamental problem in evolutionary biology is the understanding of the factors that promote or constrain adaptive evolution, and assessing the role of natural selection in this process. Here, comparative phylogenetics, that is, using phylogenetic information and traits to infer evolutionary processes has been a major paradigm . In this study, we discuss Ornstein-Uhlenbeck models (OU) in the context of thermal adaptation in ectotherms. We specifically applied this approach to study amphibians's evolution and energy metabolism. It has been hypothesized that amphibians exploit adaptive zones characterized by low energy expenditure, which generate specific predictions in terms of the patterns of diversification in standard metabolic rate (SMR). We complied whole-animal metabolic rates for 122 species of amphibians, and adjusted several models of diversification. According to the adaptive zone hypothesis, we expected: (1) to find "accelerated evolution" in SMR (i.e., diversification above Brownian Motion expectations, BM), (2) that a model assuming evolutionary optima (i.e., an OU model) fits better than a white-noise model and (3) that a model assuming multiple optima (according to the three amphibians's orders) fits better than a model assuming a single optimum. As predicted, we found that the diversification of SMR occurred most of the time, above BM expectations. Also, we found that a model assuming an optimum explained the data in a better way than a white-noise model. However, we did not find evidence that an OU model with multiple optima fits the data better, suggesting a single optimum in SMR for Anura, Caudata and Gymnophiona. These results show how comparative phylogenetics could be applied for testing adaptive hypotheses regarding history and physiological performance in ectotherms. Copyright © 2016 Elsevier Ltd. All rights reserved.

Inferring evolution of gene duplicates using probabilistic models and nonparametric belief propagation.

PubMed

Zeng, Jia; Hannenhalli, Sridhar

2013-01-01

Gene duplication, followed by functional evolution of duplicate genes, is a primary engine of evolutionary innovation. In turn, gene expression evolution is a critical component of overall functional evolution of paralogs. Inferring evolutionary history of gene expression among paralogs is therefore a problem of considerable interest. It also represents significant challenges. The standard approaches of evolutionary reconstruction assume that at an internal node of the duplication tree, the two duplicates evolve independently. However, because of various selection pressures functional evolution of the two paralogs may be coupled. The coupling of paralog evolution corresponds to three major fates of gene duplicates: subfunctionalization (SF), conserved function (CF) or neofunctionalization (NF). Quantitative analysis of these fates is of great interest and clearly influences evolutionary inference of expression. These two interrelated problems of inferring gene expression and evolutionary fates of gene duplicates have not been studied together previously and motivate the present study. Here we propose a novel probabilistic framework and algorithm to simultaneously infer (i) ancestral gene expression and (ii) the likely fate (SF, NF, CF) at each duplication event during the evolution of gene family. Using tissue-specific gene expression data, we develop a nonparametric belief propagation (NBP) algorithm to predict the ancestral expression level as a proxy for function, and describe a novel probabilistic model that relates the predicted and known expression levels to the possible evolutionary fates. We validate our model using simulation and then apply it to a genome-wide set of gene duplicates in human. Our results suggest that SF tends to be more frequent at the earlier stage of gene family expansion, while NF occurs more frequently later on.

A model for a knowledge-based system's life cycle

NASA Technical Reports Server (NTRS)

Kiss, Peter A.

1990-01-01

The American Institute of Aeronautics and Astronautics has initiated a Committee on Standards for Artificial Intelligence. Presented here are the initial efforts of one of the working groups of that committee. The purpose here is to present a candidate model for the development life cycle of Knowledge Based Systems (KBS). The intent is for the model to be used by the Aerospace Community and eventually be evolved into a standard. The model is rooted in the evolutionary model, borrows from the spiral model, and is embedded in the standard Waterfall model for software development. Its intent is to satisfy the development of both stand-alone and embedded KBSs. The phases of the life cycle are detailed as are and the review points that constitute the key milestones throughout the development process. The applicability and strengths of the model are discussed along with areas needing further development and refinement by the aerospace community.

Artificial Intelligence Software Engineering (AISE) model

NASA Technical Reports Server (NTRS)

Kiss, Peter A.

1990-01-01

The American Institute of Aeronautics and Astronautics has initiated a committee on standards for Artificial Intelligence. Presented are the initial efforts of one of the working groups of that committee. A candidate model is presented for the development life cycle of knowledge based systems (KBSs). The intent is for the model to be used by the aerospace community and eventually be evolved into a standard. The model is rooted in the evolutionary model, borrows from the spiral model, and is embedded in the standard Waterfall model for software development. Its intent is to satisfy the development of both stand-alone and embedded KBSs. The phases of the life cycle are shown and detailed as are the review points that constitute the key milestones throughout the development process. The applicability and strengths of the model are discussed along with areas needing further development and refinement by the aerospace community.

Detection of lithium in the cool halo dwarfs Groombridge 1830 and HD 134439: Implications for internal stellar mixing and cosmology

NASA Technical Reports Server (NTRS)

Deliyannis, Constantine P.; Ryan, Sean G.; Beers, Timothy C.; Thorburn, Julie A.

1994-01-01

Lithium abundances in halo stars, when interpreted correctly, hold the key to uncovering the primordial Li abundance Li(sub p). However, whereas standard stellar evolutionary models imply consistency in standard big bang nucleosynthesis (BBN), models with rotationally induced mixing imply a higher Li(sub p), possibly implying an inconsistency in standard BBN. We report here Li detections in two cool halo dwarfs, Gmb 1830 and HD 134439. These are the coolest and lowest Li detections in halo dwarfs to date, and are consistent with the metallicity dependence of Li depletion in published models. If the recent report of a beryllium deficiency in Gmb 1830 represents a real Be depletion, then the rotational models would be favored. We propose tests to reduce critical uncertainties.

Constraints and spandrels of interareal connectomes

PubMed Central

Rubinov, Mikail

2016-01-01

Interareal connectomes are whole-brain wiring diagrams of white-matter pathways. Recent studies have identified modules, hubs, module hierarchies and rich clubs as structural hallmarks of these wiring diagrams. An influential current theory postulates that connectome modules are adequately explained by evolutionary pressures for wiring economy, but that the other hallmarks are not explained by such pressures and are therefore less trivial. Here, we use constraint network models to test these postulates in current gold-standard vertebrate and invertebrate interareal-connectome reconstructions. We show that empirical wiring-cost constraints inadequately explain connectome module organization, and that simultaneous module and hub constraints induce the structural byproducts of hierarchies and rich clubs. These byproducts, known as spandrels in evolutionary biology, include the structural substrate of the default-mode network. Our results imply that currently standard connectome characterizations are based on circular analyses or double dipping, and we emphasize an integrative approach to future connectome analyses for avoiding such pitfalls. PMID:27924867

Constraints and spandrels of interareal connectomes.

PubMed

Rubinov, Mikail

2016-12-07

Interareal connectomes are whole-brain wiring diagrams of white-matter pathways. Recent studies have identified modules, hubs, module hierarchies and rich clubs as structural hallmarks of these wiring diagrams. An influential current theory postulates that connectome modules are adequately explained by evolutionary pressures for wiring economy, but that the other hallmarks are not explained by such pressures and are therefore less trivial. Here, we use constraint network models to test these postulates in current gold-standard vertebrate and invertebrate interareal-connectome reconstructions. We show that empirical wiring-cost constraints inadequately explain connectome module organization, and that simultaneous module and hub constraints induce the structural byproducts of hierarchies and rich clubs. These byproducts, known as spandrels in evolutionary biology, include the structural substrate of the default-mode network. Our results imply that currently standard connectome characterizations are based on circular analyses or double dipping, and we emphasize an integrative approach to future connectome analyses for avoiding such pitfalls.

An evolutionary algorithm that constructs recurrent neural networks.

PubMed

Angeline, P J; Saunders, G M; Pollack, J B

1994-01-01

Standard methods for simultaneously inducing the structure and weights of recurrent neural networks limit every task to an assumed class of architectures. Such a simplification is necessary since the interactions between network structure and function are not well understood. Evolutionary computations, which include genetic algorithms and evolutionary programming, are population-based search methods that have shown promise in many similarly complex tasks. This paper argues that genetic algorithms are inappropriate for network acquisition and describes an evolutionary program, called GNARL, that simultaneously acquires both the structure and weights for recurrent networks. GNARL's empirical acquisition method allows for the emergence of complex behaviors and topologies that are potentially excluded by the artificial architectural constraints imposed in standard network induction methods.

Image-Guided Rendering with an Evolutionary Algorithm Based on Cloud Model

PubMed Central

2018-01-01

The process of creating nonphotorealistic rendering images and animations can be enjoyable if a useful method is involved. We use an evolutionary algorithm to generate painterly styles of images. Given an input image as the reference target, a cloud model-based evolutionary algorithm that will rerender the target image with nonphotorealistic effects is evolved. The resulting animations have an interesting characteristic in which the target slowly emerges from a set of strokes. A number of experiments are performed, as well as visual comparisons, quantitative comparisons, and user studies. The average scores in normalized feature similarity of standard pixel-wise peak signal-to-noise ratio, mean structural similarity, feature similarity, and gradient similarity based metric are 0.486, 0.628, 0.579, and 0.640, respectively. The average scores in normalized aesthetic measures of Benford's law, fractal dimension, global contrast factor, and Shannon's entropy are 0.630, 0.397, 0.418, and 0.708, respectively. Compared with those of similar method, the average score of the proposed method, except peak signal-to-noise ratio, is higher by approximately 10%. The results suggest that the proposed method can generate appealing images and animations with different styles by choosing different strokes, and it would inspire graphic designers who may be interested in computer-based evolutionary art. PMID:29805440

Massive stars in advanced evolutionary stages, and the progenitor of GW150914

NASA Astrophysics Data System (ADS)

Hamann, Wolf-Rainer; Oskinova, Lidia; Todt, Helge; Sander, Andreas; Hainich, Rainer; Shenar, Tomer; Ramachandran, Varsha

2017-11-01

The recent discovery of a gravitational wave from the merging of two black holes of about 30 solar masses each challenges our incomplete understanding of massive stars and their evolution. Critical ingredients comprise mass-loss, rotation, magnetic fields, internal mixing, and mass transfer in close binary systems. The imperfect knowledge of these factors implies large uncertainties for models of stellar populations and their feedback. In this contribution we summarize our empirical studies of Wolf-Rayet populations at different metallicities by means of modern non-LTE stellar atmosphere models, and confront these results with the predictions of stellar evolution models. At the metallicity of our Galaxy, stellar winds are probably too strong to leave remnant masses as high as ~30 M⊙, but given the still poor agreement between evolutionary tracks and observation even this conclusion is debatable. At the low metallicity of the Small Magellanic Cloud, all WN stars which are (at least now) single are consistent with evolving quasi-homogeneously. O and B-type stars, in contrast, seem to comply with standard evolutionary models without strong internal mixing. Close binaries which avoided early merging could evolve quasi-homogeneously and lead to close compact remnants of relatively high masses that merge within a Hubble time.

Towards a physics of evolution: Critical diversity dynamics at the edges of collapse and bursts of diversification

NASA Astrophysics Data System (ADS)

Hanel, Rudolf; Kauffman, Stuart A.; Thurner, Stefan

2007-09-01

Systems governed by the standard mechanisms of biological or technological evolution are often described by catalytic evolution equations. We study the structure of these equations and find an analogy with classical thermodynamic systems. In particular, we can demonstrate the existence of several distinct phases of evolutionary dynamics: a phase of fast growing diversity, one of stationary, finite diversity, and one of rapidly decaying diversity. While the first two phases have been subject to previous work, here we focus on the destructive aspects—in particular the phase diagram—of evolutionary dynamics. The main message is that within a critical region, massive loss of diversity can be triggered by very small external fluctuations. We further propose a dynamical model of diversity which captures spontaneous creation and destruction processes fully respecting the phase diagrams of evolutionary systems. The emergent time series show rich diversity dynamics, including power laws as observed in actual economical data, e.g., firm bankruptcy data. We believe the present model presents a possibility to cast the famous qualitative picture of Schumpeterian economic evolution, into a quantifiable and testable framework.

Multi-objective evolutionary algorithms for fuzzy classification in survival prediction.

PubMed

Jiménez, Fernando; Sánchez, Gracia; Juárez, José M

2014-03-01

This paper presents a novel rule-based fuzzy classification methodology for survival/mortality prediction in severe burnt patients. Due to the ethical aspects involved in this medical scenario, physicians tend not to accept a computer-based evaluation unless they understand why and how such a recommendation is given. Therefore, any fuzzy classifier model must be both accurate and interpretable. The proposed methodology is a three-step process: (1) multi-objective constrained optimization of a patient's data set, using Pareto-based elitist multi-objective evolutionary algorithms to maximize accuracy and minimize the complexity (number of rules) of classifiers, subject to interpretability constraints; this step produces a set of alternative (Pareto) classifiers; (2) linguistic labeling, which assigns a linguistic label to each fuzzy set of the classifiers; this step is essential to the interpretability of the classifiers; (3) decision making, whereby a classifier is chosen, if it is satisfactory, according to the preferences of the decision maker. If no classifier is satisfactory for the decision maker, the process starts again in step (1) with a different input parameter set. The performance of three multi-objective evolutionary algorithms, niched pre-selection multi-objective algorithm, elitist Pareto-based multi-objective evolutionary algorithm for diversity reinforcement (ENORA) and the non-dominated sorting genetic algorithm (NSGA-II), was tested using a patient's data set from an intensive care burn unit and a standard machine learning data set from an standard machine learning repository. The results are compared using the hypervolume multi-objective metric. Besides, the results have been compared with other non-evolutionary techniques and validated with a multi-objective cross-validation technique. Our proposal improves the classification rate obtained by other non-evolutionary techniques (decision trees, artificial neural networks, Naive Bayes, and case-based reasoning) obtaining with ENORA a classification rate of 0.9298, specificity of 0.9385, and sensitivity of 0.9364, with 14.2 interpretable fuzzy rules on average. Our proposal improves the accuracy and interpretability of the classifiers, compared with other non-evolutionary techniques. We also conclude that ENORA outperforms niched pre-selection and NSGA-II algorithms. Moreover, given that our multi-objective evolutionary methodology is non-combinational based on real parameter optimization, the time cost is significantly reduced compared with other evolutionary approaches existing in literature based on combinational optimization. Copyright © 2014 Elsevier B.V. All rights reserved.

Evolutionary model of an anonymous consumer durable market

NASA Astrophysics Data System (ADS)

Kaldasch, Joachim

2011-07-01

An analytic model is presented that considers the evolution of a market of durable goods. The model suggests that after introduction goods spread always according to a Bass diffusion. However, this phase will be followed by a diffusion process for durable consumer goods governed by a variation-selection-reproduction mechanism and the growth dynamics can be described by a replicator equation. The theory suggests that products play the role of species in biological evolutionary models. It implies that the evolution of man-made products can be arranged into an evolutionary tree. The model suggests that each product can be characterized by its product fitness. The fitness space contains elements of both sites of the market, supply and demand. The unit sales of products with a higher product fitness compared to the mean fitness increase. Durables with a constant fitness advantage replace other goods according to a logistic law. The model predicts in particular that the mean price exhibits an exponential decrease over a long time period for durable goods. The evolutionary diffusion process is directly related to this price decline and is governed by Gompertz equation. Therefore it is denoted as Gompertz diffusion. Describing the aggregate sales as the sum of first, multiple and replacement purchase the product life cycle can be derived. Replacement purchase causes periodic variations of the sales determined by the finite lifetime of the good (Juglar cycles). The model suggests that both, Bass- and Gompertz diffusion may contribute to the product life cycle of a consumer durable. The theory contains the standard equilibrium view of a market as a special case. It depends on the time scale, whether an equilibrium or evolutionary description is more appropriate. The evolutionary framework is used to derive also the size, growth rate and price distribution of manufacturing business units. It predicts that the size distribution of the business units (products) is lognormal, while the growth rates exhibit a Laplace distribution. Large price deviations from the mean price are also governed by a Laplace distribution (fat tails). These results are in agreement with empirical findings. The explicit comparison of the time evolution of consumer durables with empirical investigations confirms the close relationship between price decline and Gompertz diffusion, while the product life cycle can be described qualitatively for a long time period.

Approaches to Macroevolution: 1. General Concepts and Origin of Variation.

PubMed

Jablonski, David

2017-01-01

Approaches to macroevolution require integration of its two fundamental components, i.e. the origin and the sorting of variation, in a hierarchical framework. Macroevolution occurs in multiple currencies that are only loosely correlated, notably taxonomic diversity, morphological disparity, and functional variety. The origin of variation within this conceptual framework is increasingly understood in developmental terms, with the semi-hierarchical structure of gene regulatory networks (GRNs, used here in a broad sense incorporating not just the genetic circuitry per se but the factors controlling the timing and location of gene expression and repression), the non-linear relation between magnitude of genetic change and the phenotypic results, the evolutionary potential of co-opting existing GRNs, and developmental responsiveness to nongenetic signals (i.e. epigenetics and plasticity), all requiring modification of standard microevolutionary models, and rendering difficult any simple definition of evolutionary novelty. The developmental factors underlying macroevolution create anisotropic probabilities-i.e., an uneven density distribution-of evolutionary change around any given phenotypic starting point, and the potential for coordinated changes among traits that can accommodate change via epigenetic mechanisms. From this standpoint, "punctuated equilibrium" and "phyletic gradualism" simply represent two cells in a matrix of evolutionary models of phenotypic change, and the origin of trends and evolutionary novelty are not simply functions of ecological opportunity. Over long timescales, contingency becomes especially important, and can be viewed in terms of macroevolutionary lags (the temporal separation between the origin of a trait or clade and subsequent diversification); such lags can arise by several mechanisms: as geological or phylogenetic artifacts, or when diversifications require synergistic interactions among traits, or between traits and external events. The temporal and spatial patterns of the origins of evolutionary novelties are a challenge to macroevolutionary theory; individual events can be described retrospectively, but a general model relating development, genetics, and ecology is needed. An accompanying paper (Jablonski in Evol Biol 2017) reviews diversity dynamics and the sorting of variation, with some general conclusions.

Archeological insights into hominin cognitive evolution.

PubMed

Wynn, Thomas; Coolidge, Frederick L

2016-07-01

How did the human mind evolve? How and when did we come to think in the ways we do? The last thirty years have seen an explosion in research related to the brain and cognition. This research has encompassed a range of biological and social sciences, from epigenetics and cognitive neuroscience to social and developmental psychology. Following naturally on this efflorescence has been a heightened interest in the evolution of the brain and cognition. Evolutionary scholars, including paleoanthropologists, have deployed the standard array of evolutionary methods. Ethological and experimental evidence has added significantly to our understanding of nonhuman brains and cognition, especially those of nonhuman primates. Studies of fossil brains through endocasts and sophisticated imaging techniques have revealed evolutionary changes in gross neural anatomy. Psychologists have also gotten into the game through application of reverse engineering to experimentally based descriptions of cognitive functions. For hominin evolution, there is another rich source of evidence of cognition, the archeological record. Using the methods of Paleolithic archeology and the theories and models of cognitive science, evolutionary cognitive archeology documents developments in the hominin mind that would otherwise be inaccessible. © 2016 Wiley Periodicals, Inc.

Evolutionary game theory using agent-based methods.

PubMed

Adami, Christoph; Schossau, Jory; Hintze, Arend

2016-12-01

Evolutionary game theory is a successful mathematical framework geared towards understanding the selective pressures that affect the evolution of the strategies of agents engaged in interactions with potential conflicts. While a mathematical treatment of the costs and benefits of decisions can predict the optimal strategy in simple settings, more realistic settings such as finite populations, non-vanishing mutations rates, stochastic decisions, communication between agents, and spatial interactions, require agent-based methods where each agent is modeled as an individual, carries its own genes that determine its decisions, and where the evolutionary outcome can only be ascertained by evolving the population of agents forward in time. While highlighting standard mathematical results, we compare those to agent-based methods that can go beyond the limitations of equations and simulate the complexity of heterogeneous populations and an ever-changing set of interactors. We conclude that agent-based methods can predict evolutionary outcomes where purely mathematical treatments cannot tread (for example in the weak selection-strong mutation limit), but that mathematics is crucial to validate the computational simulations. Copyright © 2016 Elsevier B.V. All rights reserved.

Cancer heterogeneity and multilayer spatial evolutionary games.

PubMed

Świerniak, Andrzej; Krześlak, Michał

2016-10-13

Evolutionary game theory (EGT) has been widely used to simulate tumour processes. In almost all studies on EGT models analysis is limited to two or three phenotypes. Our model contains four main phenotypes. Moreover, in a standard approach only heterogeneity of populations is studied, while cancer cells remain homogeneous. A multilayer approach proposed in this paper enables to study heterogeneity of single cells. In the extended model presented in this paper we consider four strategies (phenotypes) that can arise by mutations. We propose multilayer spatial evolutionary games (MSEG) played on multiple 2D lattices corresponding to the possible phenotypes. It enables simulation and investigation of heterogeneity on the player-level in addition to the population-level. Moreover, it allows to model interactions between arbitrary many phenotypes resulting from the mixture of basic traits. Different equilibrium points and scenarios (monomorphic and polymorphic populations) have been achieved depending on model parameters and the type of played game. However, there is a possibility of stable quadromorphic population in MSEG games for the same set of parameters like for the mean-field game. The model assumes an existence of four possible phenotypes (strategies) in the population of cells that make up tumour. Various parameters and relations between cells lead to complex analysis of this model and give diverse results. One of them is a possibility of stable coexistence of different tumour cells within the population, representing almost arbitrary mixture of the basic phenotypes. This article was reviewed by Tomasz Lipniacki, Urszula Ledzewicz and Jacek Banasiak.

Genetic hotels for the standard genetic code: evolutionary analysis based upon novel three-dimensional algebraic models.

PubMed

José, Marco V; Morgado, Eberto R; Govezensky, Tzipe

2011-07-01

Herein, we rigorously develop novel 3-dimensional algebraic models called Genetic Hotels of the Standard Genetic Code (SGC). We start by considering the primeval RNA genetic code which consists of the 16 codons of type RNY (purine-any base-pyrimidine). Using simple algebraic operations, we show how the RNA code could have evolved toward the current SGC via two different intermediate evolutionary stages called Extended RNA code type I and II. By rotations or translations of the subset RNY, we arrive at the SGC via the former (type I) or via the latter (type II), respectively. Biologically, the Extended RNA code type I, consists of all codons of the type RNY plus codons obtained by considering the RNA code but in the second (NYR type) and third (YRN type) reading frames. The Extended RNA code type II, comprises all codons of the type RNY plus codons that arise from transversions of the RNA code in the first (YNY type) and third (RNR) nucleotide bases. Since the dimensions of remarkable subsets of the Genetic Hotels are not necessarily integer numbers, we also introduce the concept of algebraic fractal dimension. A general decoding function which maps each codon to its corresponding amino acid or the stop signals is also derived. The Phenotypic Hotel of amino acids is also illustrated. The proposed evolutionary paths are discussed in terms of the existing theories of the evolution of the SGC. The adoption of 3-dimensional models of the Genetic and Phenotypic Hotels will facilitate the understanding of the biological properties of the SGC.

A Nonstationary Markov Model Detects Directional Evolution in Hymenopteran Morphology.

PubMed

Klopfstein, Seraina; Vilhelmsen, Lars; Ronquist, Fredrik

2015-11-01

Directional evolution has played an important role in shaping the morphological, ecological, and molecular diversity of life. However, standard substitution models assume stationarity of the evolutionary process over the time scale examined, thus impeding the study of directionality. Here we explore a simple, nonstationary model of evolution for discrete data, which assumes that the state frequencies at the root differ from the equilibrium frequencies of the homogeneous evolutionary process along the rest of the tree (i.e., the process is nonstationary, nonreversible, but homogeneous). Within this framework, we develop a Bayesian approach for testing directional versus stationary evolution using a reversible-jump algorithm. Simulations show that when only data from extant taxa are available, the success in inferring directionality is strongly dependent on the evolutionary rate, the shape of the tree, the relative branch lengths, and the number of taxa. Given suitable evolutionary rates (0.1-0.5 expected substitutions between root and tips), accounting for directionality improves tree inference and often allows correct rooting of the tree without the use of an outgroup. As an empirical test, we apply our method to study directional evolution in hymenopteran morphology. We focus on three character systems: wing veins, muscles, and sclerites. We find strong support for a trend toward loss of wing veins and muscles, while stationarity cannot be ruled out for sclerites. Adding fossil and time information in a total-evidence dating approach, we show that accounting for directionality results in more precise estimates not only of the ancestral state at the root of the tree, but also of the divergence times. Our model relaxes the assumption of stationarity and reversibility by adding a minimum of additional parameters, and is thus well suited to studying the nature of the evolutionary process in data sets of limited size, such as morphology and ecology. © The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

Adaptive dynamics on an environmental gradient that changes over a geological time-scale.

PubMed

Fortelius, Mikael; Geritz, Stefan; Gyllenberg, Mats; Toivonen, Jaakko

2015-07-07

The standard adaptive dynamics framework assumes two timescales, i.e. fast population dynamics and slow evolutionary dynamics. We further assume a third timescale, which is even slower than the evolutionary timescale. We call this the geological timescale and we assume that slow climatic change occurs within this timescale. We study the evolution of our model population over this very slow geological timescale with bifurcation plots of the standard adaptive dynamics framework. The bifurcation parameter being varied describes the abiotic environment that changes over the geological timescale. We construct evolutionary trees over the geological timescale and observe both gradual phenotypic evolution and punctuated branching events. We concur with the established notion that branching of a monomorphic population on an environmental gradient only happens when the gradient is not too shallow and not too steep. However, we show that evolution within the habitat can produce polymorphic populations that inhabit steep gradients. What is necessary is that the environmental gradient at some point in time is such that the initial branching of the monomorphic population can occur. We also find that phenotypes adapted to environments in the middle of the existing environmental range are more likely to branch than phenotypes adapted to extreme environments. Copyright © 2015 Elsevier Ltd. All rights reserved.

Differential Adhesion between Moving Particles as a Mechanism for the Evolution of Social Groups

PubMed Central

Garcia, Thomas; Brunnet, Leonardo Gregory; De Monte, Silvia

2014-01-01

The evolutionary stability of cooperative traits, that are beneficial to other individuals but costly to their carrier, is considered possible only through the establishment of a sufficient degree of assortment between cooperators. Chimeric microbial populations, characterized by simple interactions between unrelated individuals, restrain the applicability of standard mechanisms generating such assortment, in particular when cells disperse between successive reproductive events such as happens in Dicyostelids and Myxobacteria. In this paper, we address the evolutionary dynamics of a costly trait that enhances attachment to others as well as group cohesion. By modeling cells as self-propelled particles moving on a plane according to local interaction forces and undergoing cycles of aggregation, reproduction and dispersal, we show that blind differential adhesion provides a basis for assortment in the process of group formation. When reproductive performance depends on the social context of players, evolution by natural selection can lead to the success of the social trait, and to the concomitant emergence of sizeable groups. We point out the conditions on the microscopic properties of motion and interaction that make such evolutionary outcome possible, stressing that the advent of sociality by differential adhesion is restricted to specific ecological contexts. Moreover, we show that the aggregation process naturally implies the existence of non-aggregated particles, and highlight their crucial evolutionary role despite being largely neglected in theoretical models for the evolution of sociality. PMID:24586133

Rate heterogeneity across Squamata, misleading ancestral state reconstruction and the importance of proper null model specification.

PubMed

Harrington, S; Reeder, T W

2017-02-01

The binary-state speciation and extinction (BiSSE) model has been used in many instances to identify state-dependent diversification and reconstruct ancestral states. However, recent studies have shown that the standard procedure of comparing the fit of the BiSSE model to constant-rate birth-death models often inappropriately favours the BiSSE model when diversification rates vary in a state-independent fashion. The newly developed HiSSE model enables researchers to identify state-dependent diversification rates while accounting for state-independent diversification at the same time. The HiSSE model also allows researchers to test state-dependent models against appropriate state-independent null models that have the same number of parameters as the state-dependent models being tested. We reanalyse two data sets that originally used BiSSE to reconstruct ancestral states within squamate reptiles and reached surprising conclusions regarding the evolution of toepads within Gekkota and viviparity across Squamata. We used this new method to demonstrate that there are many shifts in diversification rates across squamates. We then fit various HiSSE submodels and null models to the state and phylogenetic data and reconstructed states under these models. We found that there is no single, consistent signal for state-dependent diversification associated with toepads in gekkotans or viviparity across all squamates. Our reconstructions show limited support for the recently proposed hypotheses that toepads evolved multiple times independently in Gekkota and that transitions from viviparity to oviparity are common in Squamata. Our results highlight the importance of considering an adequate pool of models and null models when estimating diversification rate parameters and reconstructing ancestral states. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Light curves for bump Cepheids computed with a dynamically zoned pulsation code

NASA Technical Reports Server (NTRS)

Adams, T. F.; Castor, J. I.; Davis, C. G.

1980-01-01

The dynamically zoned pulsation code developed by Castor, Davis, and Davison was used to recalculate the Goddard model and to calculate three other Cepheid models with the same period (9.8 days). This family of models shows how the bumps and other features of the light and velocity curves change as the mass is varied at constant period. The use of a code that is capable of producing reliable light curves demonstrates that the light and velocity curves for 9.8 day Cepheid models with standard homogeneous compositions do not show bumps like those that are observed unless the mass is significantly lower than the 'evolutionary mass.' The light and velocity curves for the Goddard model presented here are similar to those computed independently by Fischel, Sparks, and Karp. They should be useful as standards for future investigators.

Bringing Darwin into the social sciences and the humanities: cultural evolution and its philosophical implications.

PubMed

Blancke, Stefaan; Denis, Gilles

2018-04-10

In the field of cultural evolution it is generally assumed that the study of culture and cultural change would benefit enormously from being informed by evolutionary thinking. Recently, however, there has been much debate about what this "being informed" means. According to the standard view, an interesting analogy obtains between cultural and biological evolution. In the literature, however, the analogy is interpreted and used in at least three distinct, but interrelated ways. We provide a taxonomy in order to clarify these different meanings. Subsequently, we discuss the alternatives model of cultural attraction theory and memetics, which both challenge basic assumptions of the standard view. Finally, we briefly summarize the contributions to the special issue on Darwin in the Humanities and the Social Sciences, which is the result of a collaborative project between scholars and scientists from the universities of Lille and Ghent. Furthermore, we explain how they add to the discussions about the integration of evolutionary thinking and the study of culture.

Reassessing the fundamentals: On the evolution, ages and masses of neutron stars

NASA Astrophysics Data System (ADS)

Kiziltan, Bulent

The evolution, ages and masses of neutron stars are the fundamental threads that make pulsars accessible to other sub-disciplines of astronomy and physics. A realistic and accurate determination of these indirectly probed features play an important role in understanding a very broad range of astrophysical processes that are, in many cases, not empirically accessible otherwise. For the majority of pulsars, the only observables are the rotational period (P), and its derivative (P˙) which gives the rate of change in the spin. I start with calculating the joint P-P˙ distributions of millisecond pulsars for the standard evolutionary model in order to assess whether millisecond pulsars are the unequivocal descendants of low mass X-ray binaries. We show that the P-P˙ density implied by the standard evolutionary model is inconsistent with observations, which suggests that it is unlikely that millisecond pulsars have evolved from a single coherent progenitor population. In the absence of constraints from the binary companion or supernova remnant, the standard method for estimating pulsar ages is to infer an age from the rate of spin-down. I parametrically incorporate constraints that arise from binary evolution and limiting physics to derive a "modified spin-down age" for millisecond pulsars. We show that the standard method can be improved by this approach to achieve age estimates closer to the true age. Then, I critically review radio pulsar mass measurements and present a detailed examination through which we are able to put stringent constraints on the underlying neutron star mass distribution. For the first time, we are able to analyze a sizable population of neutron star-white dwarf systems in addition to double neutron star systems with a technique that accounts for systematically different measurement errors. We find that neutron stars that have evolved through different evolutionary paths reflect distinctive signatures through dissimilar distribution peak and mass cutoff values. Neutron stars in double neutron star and neutron star-white dwarf systems show consistent respective peaks at 1.35 M⊙ and 1.50 M⊙ , which suggest significant mass accretion (Deltam ≈ 0.15 M⊙ ) has occurred during the spin up phase. We find a mass cutoff at 2 M⊙ for neutron stars with white dwarf companions which establishes a firm lower bound for the maximum neutron star mass. This rules out the majority of strange quark and soft equation of state models as viable configurations for neutron star matter. The lack of truncation close to the maximum mass cutoff suggests that the 2 M⊙ limit is set by evolutionary constraints rather than nuclear physics or general relativity, and the existence of rare super-massive neutron stars is possible.

A phylogenetic transform enhances analysis of compositional microbiota data.

PubMed

Silverman, Justin D; Washburne, Alex D; Mukherjee, Sayan; David, Lawrence A

2017-02-15

Surveys of microbial communities (microbiota), typically measured as relative abundance of species, have illustrated the importance of these communities in human health and disease. Yet, statistical artifacts commonly plague the analysis of relative abundance data. Here, we introduce the PhILR transform, which incorporates microbial evolutionary models with the isometric log-ratio transform to allow off-the-shelf statistical tools to be safely applied to microbiota surveys. We demonstrate that analyses of community-level structure can be applied to PhILR transformed data with performance on benchmarks rivaling or surpassing standard tools. Additionally, by decomposing distance in the PhILR transformed space, we identified neighboring clades that may have adapted to distinct human body sites. Decomposing variance revealed that covariation of bacterial clades within human body sites increases with phylogenetic relatedness. Together, these findings illustrate how the PhILR transform combines statistical and phylogenetic models to overcome compositional data challenges and enable evolutionary insights relevant to microbial communities.

Evolutionary games with self-questioning adaptive mechanism and the Ising model

NASA Astrophysics Data System (ADS)

Liu, J.; Xu, C.; Hui, P. M.

2017-09-01

A class of evolutionary games using a self-questioning strategy switching mechanism played in a population of connected agents is shown to behave as an Ising model Hamiltonian of spins connected in the same way. The payoff parameters combine to give the coupling between spins and an external magnetic field. The mapping covers the prisoner's dilemma, snowdrift and stag hunt games in structured populations. A well-mixed system is used to illustrate the equivalence. In a chain of agents/spins, the mapping to Ising model leads to an exact solution to the games effortlessly. The accuracy of standard approximations on the games can then be quantified. The site approximation is found to show varied accuracies depending on the payoff parameters, and the link approximation is shown to give the exact result in a chain but not in a closed form. The mapping established here connects two research areas, with each having much to offer to the other.

Minimal-assumption inference from population-genomic data

NASA Astrophysics Data System (ADS)

Weissman, Daniel; Hallatschek, Oskar

Samples of multiple complete genome sequences contain vast amounts of information about the evolutionary history of populations, much of it in the associations among polymorphisms at different loci. Current methods that take advantage of this linkage information rely on models of recombination and coalescence, limiting the sample sizes and populations that they can analyze. We introduce a method, Minimal-Assumption Genomic Inference of Coalescence (MAGIC), that reconstructs key features of the evolutionary history, including the distribution of coalescence times, by integrating information across genomic length scales without using an explicit model of recombination, demography or selection. Using simulated data, we show that MAGIC's performance is comparable to PSMC' on single diploid samples generated with standard coalescent and recombination models. More importantly, MAGIC can also analyze arbitrarily large samples and is robust to changes in the coalescent and recombination processes. Using MAGIC, we show that the inferred coalescence time histories of samples of multiple human genomes exhibit inconsistencies with a description in terms of an effective population size based on single-genome data.

The Evolutionary Basis of Risky Adolescent Behavior: Implications for Science, Policy, and Practice

ERIC Educational Resources Information Center

Ellis, Bruce J.; Del Giudice, Marco; Dishion, Thomas J.; Figueredo, Aurelio Jose; Gray, Peter; Griskevicius, Vladas; Hawley, Patricia H.; Jacobs, W. Jake; James, Jenee; Volk, Anthony A.; Wilson, David Sloan

2012-01-01

This article proposes an evolutionary model of risky behavior in adolescence and contrasts it with the prevailing developmental psychopathology model. The evolutionary model contends that understanding the evolutionary functions of adolescence is critical to explaining why adolescents engage in risky behavior and that successful intervention…

THE NICHE CONSTRUCTION PERSPECTIVE: A CRITICAL APPRAISAL*

PubMed Central

Scott-Phillips, Thomas C; Laland, Kevin N; Shuker, David M; Dickins, Thomas E; West, Stuart A

2014-01-01

Niche construction refers to the activities of organisms that bring about changes in their environments, many of which are evolutionarily and ecologically consequential. Advocates of niche construction theory (NCT) believe that standard evolutionary theory fails to recognize the full importance of niche construction, and consequently propose a novel view of evolution, in which niche construction and its legacy over time (ecological inheritance) are described as evolutionary processes, equivalent in importance to natural selection. Here, we subject NCT to critical evaluation, in the form of a collaboration between one prominent advocate of NCT, and a team of skeptics. We discuss whether niche construction is an evolutionary process, whether NCT obscures or clarifies how natural selection leads to organismal adaptation, and whether niche construction and natural selection are of equivalent explanatory importance. We also consider whether the literature that promotes NCT overstates the significance of niche construction, whether it is internally coherent, and whether it accurately portrays standard evolutionary theory. Our disagreements reflect a wider dispute within evolutionary theory over whether the neo-Darwinian synthesis is in need of reformulation, as well as different usages of some key terms (e.g., evolutionary process). PMID:24325256

Evolving political science. Biological adaptation, rational action, and symbolism.

PubMed

Tingley, Dustin

2006-01-01

Political science, as a discipline, has been reluctant to adopt theories and methodologies developed in fields studying human behavior from an evolutionary standpoint. I ask whether evolutionary concepts are reconcilable with standard political-science theories and whether those concepts help solve puzzles to which these theories classically are applied. I find that evolutionary concepts readily and simultaneously accommodate theories of rational choice, symbolism, interpretation, and acculturation. Moreover, phenomena perennially hard to explain in standard political science become clearer when human interactions are understood in light of natural selection and evolutionary psychology. These phenomena include the political and economic effects of emotion, status, personal attractiveness, and variations in information-processing and decision-making under uncertainty; exemplary is the use of "focal points" in multiple-equilibrium games. I conclude with an overview of recent research by, and ongoing debates among, scholars analyzing politics in evolutionarily sophisticated terms.

Evolutionary dynamics and the phase structure of the minority game

NASA Astrophysics Data System (ADS)

Yuan, Baosheng; Chen, Kan

2004-06-01

We show that a simple evolutionary scheme, when applied to the minority game (MG), changes the phase structure of the game. In this scheme each agent evolves individually whenever his wealth reaches the specified bankruptcy level, in contrast to the evolutionary schemes used in the previous works. We show that evolution greatly suppresses herding behavior, and it leads to better overall performance of the agents. Similar to the standard nonevolutionary MG, the dependence of the standard deviation σ on the number of agents N and the memory length m can be characterized by a universal curve. We suggest a crowd-anticrowd theory for understanding the effect of evolution in the MG.

Why an extended evolutionary synthesis is necessary

PubMed Central

2017-01-01

Since the last major theoretical integration in evolutionary biology—the modern synthesis (MS) of the 1940s—the biosciences have made significant advances. The rise of molecular biology and evolutionary developmental biology, the recognition of ecological development, niche construction and multiple inheritance systems, the ‘-omics’ revolution and the science of systems biology, among other developments, have provided a wealth of new knowledge about the factors responsible for evolutionary change. Some of these results are in agreement with the standard theory and others reveal different properties of the evolutionary process. A renewed and extended theoretical synthesis, advocated by several authors in this issue, aims to unite pertinent concepts that emerge from the novel fields with elements of the standard theory. The resulting theoretical framework differs from the latter in its core logic and predictive capacities. Whereas the MS theory and its various amendments concentrate on genetic and adaptive variation in populations, the extended framework emphasizes the role of constructive processes, ecological interactions and systems dynamics in the evolution of organismal complexity as well as its social and cultural conditions. Single-level and unilinear causation is replaced by multilevel and reciprocal causation. Among other consequences, the extended framework overcomes many of the limitations of traditional gene-centric explanation and entails a revised understanding of the role of natural selection in the evolutionary process. All these features stimulate research into new areas of evolutionary biology. PMID:28839929

On Reciprocal Causation in the Evolutionary Process.

PubMed

Svensson, Erik I

2018-01-01

Recent calls for a revision of standard evolutionary theory (SET) are based partly on arguments about the reciprocal causation. Reciprocal causation means that cause-effect relationships are bi-directional, as a cause could later become an effect and vice versa. Such dynamic cause-effect relationships raise questions about the distinction between proximate and ultimate causes, as originally formulated by Ernst Mayr. They have also motivated some biologists and philosophers to argue for an Extended Evolutionary Synthesis (EES). The EES will supposedly expand the scope of the Modern Synthesis (MS) and SET, which has been characterized as gene-centred, relying primarily on natural selection and largely neglecting reciprocal causation. Here, I critically examine these claims, with a special focus on the last conjecture. I conclude that reciprocal causation has long been recognized as important by naturalists, ecologists and evolutionary biologists working in the in the MS tradition, although it it could be explored even further. Numerous empirical examples of reciprocal causation in the form of positive and negative feedback are now well known from both natural and laboratory systems. Reciprocal causation have also been explicitly incorporated in mathematical models of coevolutionary arms races, frequency-dependent selection, eco-evolutionary dynamics and sexual selection. Such dynamic feedback were already recognized by Richard Levins and Richard Lewontin in their bok The Dialectical Biologist . Reciprocal causation and dynamic feedback might also be one of the few contributions of dialectical thinking and Marxist philosophy in evolutionary theory. I discuss some promising empirical and analytical tools to study reciprocal causation and the implications for the EES. Finally, I briefly discuss how quantitative genetics can be adapated to studies of reciprocal causation, constructive inheritance and phenotypic plasticity and suggest that the flexibility of this approach might have been underestimated by critics of contemporary evolutionary biology.

Tunicate mitogenomics and phylogenetics: peculiarities of the Herdmania momus mitochondrial genome and support for the new chordate phylogeny

PubMed Central

2009-01-01

Background Tunicates represent a key metazoan group as the sister-group of vertebrates within chordates. The six complete mitochondrial genomes available so far for tunicates have revealed distinctive features. Extensive gene rearrangements and particularly high evolutionary rates have been evidenced with regard to other chordates. This peculiar evolutionary dynamics has hampered the reconstruction of tunicate phylogenetic relationships within chordates based on mitogenomic data. Results In order to further understand the atypical evolutionary dynamics of the mitochondrial genome of tunicates, we determined the complete sequence of the solitary ascidian Herdmania momus. This genome from a stolidobranch ascidian presents the typical tunicate gene content with 13 protein-coding genes, 2 rRNAs and 24 tRNAs which are all encoded on the same strand. However, it also presents a novel gene arrangement, highlighting the extreme plasticity of gene order observed in tunicate mitochondrial genomes. Probabilistic phylogenetic inferences were conducted on the concatenation of the 13 mitochondrial protein-coding genes from representatives of major metazoan phyla. We show that whereas standard homogeneous amino acid models support an artefactual sister position of tunicates relative to all other bilaterians, the CAT and CAT+BP site- and time-heterogeneous mixture models place tunicates as the sister-group of vertebrates within monophyletic chordates. Moreover, the reference phylogeny indicates that tunicate mitochondrial genomes have experienced a drastic acceleration in their evolutionary rate that equally affects protein-coding and ribosomal-RNA genes. Conclusion This is the first mitogenomic study supporting the new chordate phylogeny revealed by recent phylogenomic analyses. It illustrates the beneficial effects of an increased taxon sampling coupled with the use of more realistic amino acid substitution models for the reconstruction of animal phylogeny. PMID:19922605

Tunicate mitogenomics and phylogenetics: peculiarities of the Herdmania momus mitochondrial genome and support for the new chordate phylogeny.

PubMed

Singh, Tiratha Raj; Tsagkogeorga, Georgia; Delsuc, Frédéric; Blanquart, Samuel; Shenkar, Noa; Loya, Yossi; Douzery, Emmanuel Jp; Huchon, Dorothée

2009-11-17

Tunicates represent a key metazoan group as the sister-group of vertebrates within chordates. The six complete mitochondrial genomes available so far for tunicates have revealed distinctive features. Extensive gene rearrangements and particularly high evolutionary rates have been evidenced with regard to other chordates. This peculiar evolutionary dynamics has hampered the reconstruction of tunicate phylogenetic relationships within chordates based on mitogenomic data. In order to further understand the atypical evolutionary dynamics of the mitochondrial genome of tunicates, we determined the complete sequence of the solitary ascidian Herdmania momus. This genome from a stolidobranch ascidian presents the typical tunicate gene content with 13 protein-coding genes, 2 rRNAs and 24 tRNAs which are all encoded on the same strand. However, it also presents a novel gene arrangement, highlighting the extreme plasticity of gene order observed in tunicate mitochondrial genomes. Probabilistic phylogenetic inferences were conducted on the concatenation of the 13 mitochondrial protein-coding genes from representatives of major metazoan phyla. We show that whereas standard homogeneous amino acid models support an artefactual sister position of tunicates relative to all other bilaterians, the CAT and CAT+BP site- and time-heterogeneous mixture models place tunicates as the sister-group of vertebrates within monophyletic chordates. Moreover, the reference phylogeny indicates that tunicate mitochondrial genomes have experienced a drastic acceleration in their evolutionary rate that equally affects protein-coding and ribosomal-RNA genes. This is the first mitogenomic study supporting the new chordate phylogeny revealed by recent phylogenomic analyses. It illustrates the beneficial effects of an increased taxon sampling coupled with the use of more realistic amino acid substitution models for the reconstruction of animal phylogeny.

The Experimental Study of Bacterial Evolution and Its Implications for the Modern Synthesis of Evolutionary Biology.

PubMed

O'Malley, Maureen A

2018-06-01

Since the 1940s, microbiologists, biochemists and population geneticists have experimented with the genetic mechanisms of microorganisms in order to investigate evolutionary processes. These evolutionary studies of bacteria and other microorganisms gained some recognition from the standard-bearers of the modern synthesis of evolutionary biology, especially Theodosius Dobzhansky and Ledyard Stebbins. A further period of post-synthesis bacterial evolutionary research occurred between the 1950s and 1980s. These experimental analyses focused on the evolution of population and genetic structure, the adaptive gain of new functions, and the evolutionary consequences of competition dynamics. This large body of research aimed to make evolutionary theory testable and predictive, by giving it mechanistic underpinnings. Although evolutionary microbiologists promoted bacterial experiments as methodologically advantageous and a source of general insight into evolution, they also acknowledged the biological differences of bacteria. My historical overview concludes with reflections on what bacterial evolutionary research achieved in this period, and its implications for the still-developing modern synthesis.

Cancer Evolution: Mathematical Models and Computational Inference

PubMed Central

Beerenwinkel, Niko; Schwarz, Roland F.; Gerstung, Moritz; Markowetz, Florian

2015-01-01

Cancer is a somatic evolutionary process characterized by the accumulation of mutations, which contribute to tumor growth, clinical progression, immune escape, and drug resistance development. Evolutionary theory can be used to analyze the dynamics of tumor cell populations and to make inference about the evolutionary history of a tumor from molecular data. We review recent approaches to modeling the evolution of cancer, including population dynamics models of tumor initiation and progression, phylogenetic methods to model the evolutionary relationship between tumor subclones, and probabilistic graphical models to describe dependencies among mutations. Evolutionary modeling helps to understand how tumors arise and will also play an increasingly important prognostic role in predicting disease progression and the outcome of medical interventions, such as targeted therapy. PMID:25293804

On the Accuracy of Language Trees

PubMed Central

Pompei, Simone; Loreto, Vittorio; Tria, Francesca

2011-01-01

Historical linguistics aims at inferring the most likely language phylogenetic tree starting from information concerning the evolutionary relatedness of languages. The available information are typically lists of homologous (lexical, phonological, syntactic) features or characters for many different languages: a set of parallel corpora whose compilation represents a paramount achievement in linguistics. From this perspective the reconstruction of language trees is an example of inverse problems: starting from present, incomplete and often noisy, information, one aims at inferring the most likely past evolutionary history. A fundamental issue in inverse problems is the evaluation of the inference made. A standard way of dealing with this question is to generate data with artificial models in order to have full access to the evolutionary process one is going to infer. This procedure presents an intrinsic limitation: when dealing with real data sets, one typically does not know which model of evolution is the most suitable for them. A possible way out is to compare algorithmic inference with expert classifications. This is the point of view we take here by conducting a thorough survey of the accuracy of reconstruction methods as compared with the Ethnologue expert classifications. We focus in particular on state-of-the-art distance-based methods for phylogeny reconstruction using worldwide linguistic databases. In order to assess the accuracy of the inferred trees we introduce and characterize two generalizations of standard definitions of distances between trees. Based on these scores we quantify the relative performances of the distance-based algorithms considered. Further we quantify how the completeness and the coverage of the available databases affect the accuracy of the reconstruction. Finally we draw some conclusions about where the accuracy of the reconstructions in historical linguistics stands and about the leading directions to improve it. PMID:21674034

The niche construction perspective: a critical appraisal.

PubMed

Scott-Phillips, Thomas C; Laland, Kevin N; Shuker, David M; Dickins, Thomas E; West, Stuart A

2014-05-01

Niche construction refers to the activities of organisms that bring about changes in their environments, many of which are evolutionarily and ecologically consequential. Advocates of niche construction theory (NCT) believe that standard evolutionary theory fails to recognize the full importance of niche construction, and consequently propose a novel view of evolution, in which niche construction and its legacy over time (ecological inheritance) are described as evolutionary processes, equivalent in importance to natural selection. Here, we subject NCT to critical evaluation, in the form of a collaboration between one prominent advocate of NCT, and a team of skeptics. We discuss whether niche construction is an evolutionary process, whether NCT obscures or clarifies how natural selection leads to organismal adaptation, and whether niche construction and natural selection are of equivalent explanatory importance. We also consider whether the literature that promotes NCT overstates the significance of niche construction, whether it is internally coherent, and whether it accurately portrays standard evolutionary theory. Our disagreements reflect a wider dispute within evolutionary theory over whether the neo-Darwinian synthesis is in need of reformulation, as well as different usages of some key terms (e.g., evolutionary process). © 2013 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.

Computational evolution: taking liberties.

PubMed

Correia, Luís

2010-09-01

Evolution has, for a long time, inspired computer scientists to produce computer models mimicking its behavior. Evolutionary algorithm (EA) is one of the areas where this approach has flourished. EAs have been used to model and study evolution, but they have been especially developed for their aptitude as optimization tools for engineering. Developed models are quite simple in comparison with their natural sources of inspiration. However, since EAs run on computers, we have the freedom, especially in optimization models, to test approaches both realistic and outright speculative, from the biological point of view. In this article, we discuss different common evolutionary algorithm models, and then present some alternatives of interest. These include biologically inspired models, such as co-evolution and, in particular, symbiogenetics and outright artificial operators and representations. In each case, the advantages of the modifications to the standard model are identified. The other area of computational evolution, which has allowed us to study basic principles of evolution and ecology dynamics, is the development of artificial life platforms for open-ended evolution of artificial organisms. With these platforms, biologists can test theories by directly manipulating individuals and operators, observing the resulting effects in a realistic way. An overview of the most prominent of such environments is also presented. If instead of artificial platforms we use the real world for evolving artificial life, then we are dealing with evolutionary robotics (ERs). A brief description of this area is presented, analyzing its relations to biology. Finally, we present the conclusions and identify future research avenues in the frontier of computation and biology. Hopefully, this will help to draw the attention of more biologists and computer scientists to the benefits of such interdisciplinary research.

Time-Dependent Rate Phenomenon in Viruses

PubMed Central

Aiewsakun, Pakorn

2016-01-01

ABSTRACT Among the most fundamental questions in viral evolutionary biology are how fast viruses evolve and how evolutionary rates differ among viruses and fluctuate through time. Traditionally, viruses are loosely classed into two groups: slow-evolving DNA viruses and fast-evolving RNA viruses. As viral evolutionary rate estimates become more available, it appears that the rates are negatively correlated with the measurement timescales and that the boundary between the rates of DNA and RNA viruses might not be as clear as previously thought. In this study, we collected 396 viral evolutionary rate estimates across almost all viral genome types and replication strategies, and we examined their rate dynamics. We showed that the time-dependent rate phenomenon exists across multiple levels of viral taxonomy, from the Baltimore classification viral groups to genera. We also showed that, by taking the rate decay dynamics into account, a clear division between the rates of DNA and RNA viruses as well as reverse-transcribing viruses could be recovered. Surprisingly, despite large differences in their biology, our analyses suggested that the rate decay speed is independent of viral types and thus might be useful for better estimation of the evolutionary time scale of any virus. To illustrate this, we used our model to reestimate the evolutionary timescales of extant lentiviruses, which were previously suggested to be very young by standard phylogenetic analyses. Our analyses suggested that these viruses are millions of years old, in agreement with paleovirological evidence, and therefore, for the first time, reconciled molecular analyses of ancient and extant viruses. IMPORTANCE This work provides direct evidence that viral evolutionary rate estimates decay with their measurement timescales and that the rate decay speeds do not differ significantly among viruses despite the vast differences in their molecular features. After adjustment for the rate decay dynamics, the division between the rates of double-stranded DNA (dsDNA), single-stranded RNA (ssRNA), and ssDNA/reverse-transcribing viruses could be seen more clearly than before. Our results provide a guideline for further improvement of the molecular clock. As a demonstration of this, we used our model to reestimate the timescales of modern lentiviruses, which were previously thought to be very young, and concluded that they are millions of years old. This result matches the estimate from paleovirological analyses, thus bridging the gap between ancient and extant viral evolutionary studies. PMID:27252529

Strengths and weaknesses of McNamara's evolutionary psychological model of dreaming.

PubMed

Olliges, Sandra

2010-10-07

This article includes a brief overview of McNamara's (2004) evolutionary model of dreaming. The strengths and weaknesses of this model are then evaluated in terms of its consonance with measurable neurological and biological properties of dreaming, its fit within the tenets of evolutionary theories of dreams, and its alignment with evolutionary concepts of cooperation and spirituality. McNamara's model focuses primarily on dreaming that occurs during rapid eye movement (REM) sleep; therefore this article also focuses on REM dreaming.

Evaluation of liquefaction potential of soil based on standard penetration test using multi-gene genetic programming model

NASA Astrophysics Data System (ADS)

Muduli, Pradyut; Das, Sarat

2014-06-01

This paper discusses the evaluation of liquefaction potential of soil based on standard penetration test (SPT) dataset using evolutionary artificial intelligence technique, multi-gene genetic programming (MGGP). The liquefaction classification accuracy (94.19%) of the developed liquefaction index (LI) model is found to be better than that of available artificial neural network (ANN) model (88.37%) and at par with the available support vector machine (SVM) model (94.19%) on the basis of the testing data. Further, an empirical equation is presented using MGGP to approximate the unknown limit state function representing the cyclic resistance ratio (CRR) of soil based on developed LI model. Using an independent database of 227 cases, the overall rates of successful prediction of occurrence of liquefaction and non-liquefaction are found to be 87, 86, and 84% by the developed MGGP based model, available ANN and the statistical models, respectively, on the basis of calculated factor of safety (F s) against the liquefaction occurrence.

Eco-Evo PVAs: Incorporating Eco-Evolutionary Processes into Population Viability Models

EPA Science Inventory

We synthesize how advances in computational methods and population genomics can be combined within an Ecological-Evolutionary (Eco-Evo) PVA model. Eco-Evo PVA models are powerful new tools for understanding the influence of evolutionary processes on plant and animal population pe...

Phylogenics & Tree-Thinking

ERIC Educational Resources Information Center

Baum, David A.; Offner, Susan

2008-01-01

Phylogenetic trees, which are depictions of the inferred evolutionary relationships among a set of species, now permeate almost all branches of biology and are appearing in increasing numbers in biology textbooks. While few state standards explicitly require knowledge of phylogenetics, most require some knowledge of evolutionary biology, and many…

A phylogenetic transform enhances analysis of compositional microbiota data

PubMed Central

Silverman, Justin D; Washburne, Alex D; Mukherjee, Sayan; David, Lawrence A

2017-01-01

Surveys of microbial communities (microbiota), typically measured as relative abundance of species, have illustrated the importance of these communities in human health and disease. Yet, statistical artifacts commonly plague the analysis of relative abundance data. Here, we introduce the PhILR transform, which incorporates microbial evolutionary models with the isometric log-ratio transform to allow off-the-shelf statistical tools to be safely applied to microbiota surveys. We demonstrate that analyses of community-level structure can be applied to PhILR transformed data with performance on benchmarks rivaling or surpassing standard tools. Additionally, by decomposing distance in the PhILR transformed space, we identified neighboring clades that may have adapted to distinct human body sites. Decomposing variance revealed that covariation of bacterial clades within human body sites increases with phylogenetic relatedness. Together, these findings illustrate how the PhILR transform combines statistical and phylogenetic models to overcome compositional data challenges and enable evolutionary insights relevant to microbial communities. DOI: http://dx.doi.org/10.7554/eLife.21887.001 PMID:28198697

Evolutionary construction by staying together and coming together.

PubMed

Tarnita, Corina E; Taubes, Clifford H; Nowak, Martin A

2013-03-07

The evolutionary trajectory of life on earth is one of increasing size and complexity. Yet the standard equations of evolutionary dynamics describe mutation and selection among similar organisms that compete on the same level of organization. Here we begin to outline a mathematical theory that might help to explore how evolution can be constructive, how natural selection can lead from lower to higher levels of organization. We distinguish two fundamental operations, which we call 'staying together' and 'coming together'. Staying together means that individuals form larger units by not separating after reproduction, while coming together means that independent individuals form aggregates. Staying together can lead to specialization and division of labor, but the developmental program must evolve in the basic unit. Coming together can be creative by combining units with different properties. Both operations have been identified in the context of multicellularity, but they have been treated very similarly. Here we point out that staying together and coming together can be found at every level of biological construction and moreover that they face different evolutionary problems. The distinction is particularly clear in the context of cooperation and defection. For staying together the stability of cooperation takes the form of a developmental error threshold, while coming together leads to evolutionary games and requires a mechanism for the evolution of cooperation. We use our models to discuss simple aspects of the evolution of protocells, eukarya, multi-cellularity and animal societies. Copyright © 2012 Elsevier Ltd. All rights reserved.

Cancer evolution: mathematical models and computational inference.

PubMed

Beerenwinkel, Niko; Schwarz, Roland F; Gerstung, Moritz; Markowetz, Florian

2015-01-01

Cancer is a somatic evolutionary process characterized by the accumulation of mutations, which contribute to tumor growth, clinical progression, immune escape, and drug resistance development. Evolutionary theory can be used to analyze the dynamics of tumor cell populations and to make inference about the evolutionary history of a tumor from molecular data. We review recent approaches to modeling the evolution of cancer, including population dynamics models of tumor initiation and progression, phylogenetic methods to model the evolutionary relationship between tumor subclones, and probabilistic graphical models to describe dependencies among mutations. Evolutionary modeling helps to understand how tumors arise and will also play an increasingly important prognostic role in predicting disease progression and the outcome of medical interventions, such as targeted therapy. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society of Systematic Biologists.

Dynamic multipopulation and density dependent evolutionary games related to replicator dynamics. A metasimplex concept.

PubMed

Argasinski, Krzysztof

2006-07-01

This paper contains the basic extensions of classical evolutionary games (multipopulation and density dependent models). It is shown that classical bimatrix approach is inconsistent with other approaches because it does not depend on proportion between populations. The main conclusion is that interspecific proportion parameter is important and must be considered in multipopulation models. The paper provides a synthesis of both extensions (a metasimplex concept) which solves the problem intrinsic in the bimatrix model. It allows us to model interactions among any number of subpopulations including density dependence effects. We prove that all modern approaches to evolutionary games are closely related. All evolutionary models (except classical bimatrix approaches) can be reduced to a single population general model by a simple change of variables. Differences between classic bimatrix evolutionary games and a new model which is dependent on interspecific proportion are shown by examples.

Open Issues in Evolutionary Robotics.

PubMed

Silva, Fernando; Duarte, Miguel; Correia, Luís; Oliveira, Sancho Moura; Christensen, Anders Lyhne

2016-01-01

One of the long-term goals in evolutionary robotics is to be able to automatically synthesize controllers for real autonomous robots based only on a task specification. While a number of studies have shown the applicability of evolutionary robotics techniques for the synthesis of behavioral control, researchers have consistently been faced with a number of issues preventing the widespread adoption of evolutionary robotics for engineering purposes. In this article, we review and discuss the open issues in evolutionary robotics. First, we analyze the benefits and challenges of simulation-based evolution and subsequent deployment of controllers versus evolution on real robotic hardware. Second, we discuss specific evolutionary computation issues that have plagued evolutionary robotics: (1) the bootstrap problem, (2) deception, and (3) the role of genomic encoding and genotype-phenotype mapping in the evolution of controllers for complex tasks. Finally, we address the absence of standard research practices in the field. We also discuss promising avenues of research. Our underlying motivation is the reduction of the current gap between evolutionary robotics and mainstream robotics, and the establishment of evolutionary robotics as a canonical approach for the engineering of autonomous robots.

Theoretical Approaches in Evolutionary Ecology: Environmental Feedback as a Unifying Perspective.

PubMed

Lion, Sébastien

2018-01-01

Evolutionary biology and ecology have a strong theoretical underpinning, and this has fostered a variety of modeling approaches. A major challenge of this theoretical work has been to unravel the tangled feedback loop between ecology and evolution. This has prompted the development of two main classes of models. While quantitative genetics models jointly consider the ecological and evolutionary dynamics of a focal population, a separation of timescales between ecology and evolution is assumed by evolutionary game theory, adaptive dynamics, and inclusive fitness theory. As a result, theoretical evolutionary ecology tends to be divided among different schools of thought, with different toolboxes and motivations. My aim in this synthesis is to highlight the connections between these different approaches and clarify the current state of theory in evolutionary ecology. Central to this approach is to make explicit the dependence on environmental dynamics of the population and evolutionary dynamics, thereby materializing the eco-evolutionary feedback loop. This perspective sheds light on the interplay between environmental feedback and the timescales of ecological and evolutionary processes. I conclude by discussing some potential extensions and challenges to our current theoretical understanding of eco-evolutionary dynamics.

Comparing Evolutionary Programs and Evolutionary Pattern Search Algorithms: A Drug Docking Application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, W.E.

1999-02-10

Evolutionary programs (EPs) and evolutionary pattern search algorithms (EPSAS) are two general classes of evolutionary methods for optimizing on continuous domains. The relative performance of these methods has been evaluated on standard global optimization test functions, and these results suggest that EPSAs more robustly converge to near-optimal solutions than EPs. In this paper we evaluate the relative performance of EPSAs and EPs on a real-world application: flexible ligand binding in the Autodock docking software. We compare the performance of these methods on a suite of docking test problems. Our results confirm that EPSAs and EPs have comparable performance, and theymore » suggest that EPSAs may be more robust on larger, more complex problems.« less

On the evolutionary origins of the egalitarian syndrome

PubMed Central

Gavrilets, Sergey

2012-01-01

The evolutionary emergence of the egalitarian syndrome is one of the most intriguing unsolved puzzles related to the origins of modern humans. Standard explanations and models for cooperation and altruism—reciprocity, kin and group selection, and punishment—are not directly applicable to the emergence of egalitarian behavior in hierarchically organized groups that characterized the social life of our ancestors. Here I study an evolutionary model of group-living individuals competing for resources and reproductive success. In the model, the differences in fighting abilities lead to the emergence of hierarchies where stronger individuals take away resources from weaker individuals and, as a result, have higher reproductive success. First, I show that the logic of within-group competition implies under rather general conditions that each individual benefits if the transfer of the resource from a weaker group member to a stronger one is prevented. This effect is especially strong in small groups. Then I demonstrate that this effect can result in the evolution of a particular, genetically controlled psychology causing individuals to interfere in a bully–victim conflict on the side of the victim. A necessary condition is a high efficiency of coalitions in conflicts against the bullies. The egalitarian drive leads to a dramatic reduction in within-group inequality. Simultaneously it creates the conditions for the emergence of inequity aversion, empathy, compassion, and egalitarian moral values via the internalization of behavioral rules imposed by natural selection. It also promotes widespread cooperation via coalition formation. PMID:22891349

Controlled recovery of phylogenetic communities from an evolutionary model using a network approach

NASA Astrophysics Data System (ADS)

Sousa, Arthur M. Y. R.; Vieira, André P.; Prado, Carmen P. C.; Andrade, Roberto F. S.

2016-04-01

This works reports the use of a complex network approach to produce a phylogenetic classification tree of a simple evolutionary model. This approach has already been used to treat proteomic data of actual extant organisms, but an investigation of its reliability to retrieve a traceable evolutionary history is missing. The used evolutionary model includes key ingredients for the emergence of groups of related organisms by differentiation through random mutations and population growth, but purposefully omits other realistic ingredients that are not strictly necessary to originate an evolutionary history. This choice causes the model to depend only on a small set of parameters, controlling the mutation probability and the population of different species. Our results indicate that for a set of parameter values, the phylogenetic classification produced by the used framework reproduces the actual evolutionary history with a very high average degree of accuracy. This includes parameter values where the species originated by the evolutionary dynamics have modular structures. In the more general context of community identification in complex networks, our model offers a simple setting for evaluating the effects, on the efficiency of community formation and identification, of the underlying dynamics generating the network itself.

Modeling the Personal Health Ecosystem.

PubMed

Blobel, Bernd; Brochhausen, Mathias; Ruotsalainen, Pekka

2018-01-01

Complex ecosystems like the pHealth one combine different domains represented by a huge variety of different actors (human beings, organizations, devices, applications, components) belonging to different policy domains, coming from different disciplines, deploying different methodologies, terminologies, and ontologies, offering different levels of knowledge, skills, and experiences, acting in different scenarios and accommodating different business cases to meet the intended business objectives. For correctly modeling such systems, a system-oriented, architecture-centric, ontology-based, policy-driven approach is inevitable, thereby following established Good Modeling Best Practices. However, most of the existing standards, specifications and tools for describing, representing, implementing and managing health (information) systems reflect the advancement of information and communication technology (ICT) represented by different evolutionary levels of data modeling. The paper presents a methodology for integrating, adopting and advancing models, standards, specifications as well as implemented systems and components on the way towards the aforementioned ultimate approach, so meeting the challenge we face when transforming health systems towards ubiquitous, personalized, predictive, preventive, participative, and cognitive health and social care.

Stellar evolution with turbulent diffusion. I. A new formalism of mixing.

NASA Astrophysics Data System (ADS)

Deng, L.; Bressan, A.; Chiosi, C.

1996-09-01

In this paper we present a new formulation of diffusive mixing in stellar interiors aimed at casting light on the kind of mixing that should take place in the so-called overshoot regions surrounding fully convective zones. Key points of the analysis are the inclusion the concept of scale length most effective for mixing, by means of which the diffusion coefficient is formulated, and the inclusion of intermittence and stirring, two properties of turbulence known from laboratory fluid dynamics. The formalism is applied to follow the evolution of a 20Msun_ star with composition Z=0.008 and Y=0.25. Depending on the value of the diffusion coefficient holding in the overshoot region, the evolutionary behaviour of the test stars goes from the case of virtually no mixing (semiconvective like structures) to that of full mixing over there (standard overshoot models). Indeed, the efficiency of mixing in this region drives the extension of the intermediate fully convective shell developing at the onset of the the shell H-burning, and in turn the path in the HR Diagram (HRD). Models with low efficiency of mixing burn helium in the core at high effective temperatures, models with intermediate efficiency perform extended loops in the HRD, finally models with high efficiency spend the whole core He-burning phase at low effective temperatures. In order to cast light on this important point of stellar structure, we test whether or not in the regions of the H-burning shell a convective layer can develop. More precisely, we examine whether the Schwarzschild or the Ledoux criterion ought to be adopted in this region. Furthermore, we test the response of stellar models to the kind of mixing supposed to occur in the H-burning shell regions. Finally, comparing the time scale of thermal dissipation to the evolutionary time scale, we get the conclusion that no mixing in this region should occur. The models with intermediate efficiency of mixing and no mixing at all in the shell H-burning regions are of particular interest as they possess at the same time evolutionary characteristics that are separately typical of models calculated with different schemes of mixing. In other words, the new models share the same properties of models with standard overshoot, namely a wider main sequence band, higher luminosity, and longer lifetimes than classical models, but they also possess extended loops that are the main signature of the classical (semiconvective) description of convection at the border of the core.

Incorporating evolution of transcription factor binding sites into annotated alignments.

PubMed

Bais, Abha S; Grossmann, Stefen; Vingron, Martin

2007-08-01

Identifying transcription factor binding sites (TFBSs) is essential to elucidate putative regulatory mechanisms. A common strategy is to combine cross-species conservation with single sequence TFBS annotation to yield "conserved TFBSs". Most current methods in this field adopt a multi-step approach that segregates the two aspects. Again, it is widely accepted that the evolutionary dynamics of binding sites differ from those of the surrounding sequence. Hence, it is desirable to have an approach that explicitly takes this factor into account. Although a plethora of approaches have been proposed for the prediction of conserved TFBSs, very few explicitly model TFBS evolutionary properties, while additionally being multi-step. Recently, we introduced a novel approach to simultaneously align and annotate conserved TFBSs in a pair of sequences. Building upon the standard Smith-Waterman algorithm for local alignments, SimAnn introduces additional states for profiles to output extended alignments or annotated alignments. That is, alignments with parts annotated as gaplessly aligned TFBSs (pair-profile hits)are generated. Moreover,the pair- profile related parameters are derived in a sound statistical framework. In this article, we extend this approach to explicitly incorporate evolution of binding sites in the SimAnn framework. We demonstrate the extension in the theoretical derivations through two position-specific evolutionary models, previously used for modelling TFBS evolution. In a simulated setting, we provide a proof of concept that the approach works given the underlying assumptions,as compared to the original work. Finally, using a real dataset of experimentally verified binding sites in human-mouse sequence pairs,we compare the new approach (eSimAnn) to an existing multi-step tool that also considers TFBS evolution. Although it is widely accepted that binding sites evolve differently from the surrounding sequences, most comparative TFBS identification methods do not explicitly consider this.Additionally, prediction of conserved binding sites is carried out in a multi-step approach that segregates alignment from TFBS annotation. In this paper, we demonstrate how the simultaneous alignment and annotation approach of SimAnn can be further extended to incorporate TFBS evolutionary relationships. We study how alignments and binding site predictions interplay at varying evolutionary distances and for various profile qualities.

Evolutionary model selection and parameter estimation for protein-protein interaction network based on differential evolution algorithm

PubMed Central

Huang, Lei; Liao, Li; Wu, Cathy H.

2016-01-01

Revealing the underlying evolutionary mechanism plays an important role in understanding protein interaction networks in the cell. While many evolutionary models have been proposed, the problem about applying these models to real network data, especially for differentiating which model can better describe evolutionary process for the observed network urgently remains as a challenge. The traditional way is to use a model with presumed parameters to generate a network, and then evaluate the fitness by summary statistics, which however cannot capture the complete network structures information and estimate parameter distribution. In this work we developed a novel method based on Approximate Bayesian Computation and modified Differential Evolution (ABC-DEP) that is capable of conducting model selection and parameter estimation simultaneously and detecting the underlying evolutionary mechanisms more accurately. We tested our method for its power in differentiating models and estimating parameters on the simulated data and found significant improvement in performance benchmark, as compared with a previous method. We further applied our method to real data of protein interaction networks in human and yeast. Our results show Duplication Attachment model as the predominant evolutionary mechanism for human PPI networks and Scale-Free model as the predominant mechanism for yeast PPI networks. PMID:26357273

A Python Calculator for Supernova Remnant Evolution

NASA Astrophysics Data System (ADS)

Leahy, D. A.; Williams, J. E.

2017-05-01

A freely available Python code for modeling supernova remnant (SNR) evolution has been created. This software is intended for two purposes: to understand SNR evolution and to use in modeling observations of SNR for obtaining good estimates of SNR properties. It includes all phases for the standard path of evolution for spherically symmetric SNRs. In addition, alternate evolutionary models are available, including evolution in a cloudy ISM, the fractional energy-loss model, and evolution in a hot low-density ISM. The graphical interface takes in various parameters and produces outputs such as shock radius and velocity versus time, as well as SNR surface brightness profile and spectrum. Some interesting properties of SNR evolution are demonstrated using the program.

Forced evolution in silico by artificial transposons and their genetic operators: The ant navigation problem.

PubMed

Zamdborg, Leonid; Holloway, David M; Merelo, Juan J; Levchenko, Vladimir F; Spirov, Alexander V

2015-06-10

Modern evolutionary computation utilizes heuristic optimizations based upon concepts borrowed from the Darwinian theory of natural selection. Their demonstrated efficacy has reawakened an interest in other aspects of contemporary biology as an inspiration for new algorithms. However, amongst the many excellent candidates for study, contemporary models of biological macroevolution attract special attention. We believe that a vital direction in this field must be algorithms that model the activity of "genomic parasites", such as transposons, in biological evolution. Many evolutionary biologists posit that it is the co-evolution of populations with their genomic parasites that permits the high efficiency of evolutionary searches found in the living world. This publication is our first step in the direction of developing a minimal assortment of algorithms that simulate the role of genomic parasites. Specifically, we started in the domain of genetic algorithms (GA) and selected the Artificial Ant Problem as a test case. This navigation problem is widely known as a classical benchmark test and possesses a large body of literature. We add new objects to the standard toolkit of GA - artificial transposons and a collection of operators that operate on them. We define these artificial transposons as a fragment of an ant's code with properties that cause it to stand apart from the rest. The minimal set of operators for transposons is a transposon mutation operator, and a transposon reproduction operator that causes a transposon to multiply within the population of hosts. An analysis of the population dynamics of transposons within the course of ant evolution showed that transposons are involved in the processes of propagation and selection of blocks of ant navigation programs. During this time, the speed of evolutionary search increases significantly. We concluded that artificial transposons, analogous to real transposons, are truly capable of acting as intelligent mutators that adapt in response to an evolutionary problem in the course of co-evolution with their hosts.

Forced evolution in silico by artificial transposons and their genetic operators: The ant navigation problem

PubMed Central

Zamdborg, Leonid; Holloway, David M.; Merelo, Juan J.; Levchenko, Vladimir F.; Spirov, Alexander V.

2015-01-01

Modern evolutionary computation utilizes heuristic optimizations based upon concepts borrowed from the Darwinian theory of natural selection. Their demonstrated efficacy has reawakened an interest in other aspects of contemporary biology as an inspiration for new algorithms. However, amongst the many excellent candidates for study, contemporary models of biological macroevolution attract special attention. We believe that a vital direction in this field must be algorithms that model the activity of “genomic parasites”, such as transposons, in biological evolution. Many evolutionary biologists posit that it is the co-evolution of populations with their genomic parasites that permits the high efficiency of evolutionary searches found in the living world. This publication is our first step in the direction of developing a minimal assortment of algorithms that simulate the role of genomic parasites. Specifically, we started in the domain of genetic algorithms (GA) and selected the Artificial Ant Problem as a test case. This navigation problem is widely known as a classical benchmark test and possesses a large body of literature. We add new objects to the standard toolkit of GA - artificial transposons and a collection of operators that operate on them. We define these artificial transposons as a fragment of an ant's code with properties that cause it to stand apart from the rest. The minimal set of operators for transposons is a transposon mutation operator, and a transposon reproduction operator that causes a transposon to multiply within the population of hosts. An analysis of the population dynamics of transposons within the course of ant evolution showed that transposons are involved in the processes of propagation and selection of blocks of ant navigation programs. During this time, the speed of evolutionary search increases significantly. We concluded that artificial transposons, analogous to real transposons, are truly capable of acting as intelligent mutators that adapt in response to an evolutionary problem in the course of co-evolution with their hosts. PMID:25767296

Simulating natural selection in landscape genetics

Treesearch

E. L. Landguth; S. A. Cushman; N. Johnson

2012-01-01

Linking landscape effects to key evolutionary processes through individual organism movement and natural selection is essential to provide a foundation for evolutionary landscape genetics. Of particular importance is determining how spatially- explicit, individual-based models differ from classic population genetics and evolutionary ecology models based on ideal...

Evolutionary models of interstellar chemistry

NASA Technical Reports Server (NTRS)

Prasad, Sheo S.

1987-01-01

The goal of evolutionary models of interstellar chemistry is to understand how interstellar clouds came to be the way they are, how they will change with time, and to place them in an evolutionary sequence with other celestial objects such as stars. An improved Mark II version of an earlier model of chemistry in dynamically evolving clouds is presented. The Mark II model suggests that the conventional elemental C/O ratio less than one can explain the observed abundances of CI and the nondetection of O2 in dense clouds. Coupled chemical-dynamical models seem to have the potential to generate many observable discriminators of the evolutionary tracks. This is exciting, because, in general, purely dynamical models do not yield enough verifiable discriminators of the predicted tracks.

Evaluation of Generation Alternation Models in Evolutionary Robotics

NASA Astrophysics Data System (ADS)

Oiso, Masashi; Matsumura, Yoshiyuki; Yasuda, Toshiyuki; Ohkura, Kazuhiro

For efficient implementation of Evolutionary Algorithms (EA) to a desktop grid computing environment, we propose a new generation alternation model called Grid-Oriented-Deletion (GOD) based on comparison with the conventional techniques. In previous research, generation alternation models are generally evaluated by using test functions. However, their exploration performance on the real problems such as Evolutionary Robotics (ER) has not been made very clear yet. Therefore we investigate the relationship between the exploration performance of EA on an ER problem and its generation alternation model. We applied four generation alternation models to the Evolutionary Multi-Robotics (EMR), which is the package-pushing problem to investigate their exploration performance. The results show that GOD is more effective than the other conventional models.

Ecological theatre and the evolutionary game: how environmental and demographic factors determine payoffs in evolutionary games.

PubMed

Argasinski, K; Broom, M

2013-10-01

In the standard approach to evolutionary games and replicator dynamics, differences in fitness can be interpreted as an excess from the mean Malthusian growth rate in the population. In the underlying reasoning, related to an analysis of "costs" and "benefits", there is a silent assumption that fitness can be described in some type of units. However, in most cases these units of measure are not explicitly specified. Then the question arises: are these theories testable? How can we measure "benefit" or "cost"? A natural language, useful for describing and justifying comparisons of strategic "cost" versus "benefits", is the terminology of demography, because the basic events that shape the outcome of natural selection are births and deaths. In this paper, we present the consequences of an explicit analysis of births and deaths in an evolutionary game theoretic framework. We will investigate different types of mortality pressures, their combinations and the possibility of trade-offs between mortality and fertility. We will show that within this new approach it is possible to model how strictly ecological factors such as density dependence and additive background fitness, which seem neutral in classical theory, can affect the outcomes of the game. We consider the example of the Hawk-Dove game, and show that when reformulated in terms of our new approach new details and new biological predictions are produced.

A standard deviation selection in evolutionary algorithm for grouper fish feed formulation

NASA Astrophysics Data System (ADS)

Cai-Juan, Soong; Ramli, Razamin; Rahman, Rosshairy Abdul

2016-10-01

Malaysia is one of the major producer countries for fishery production due to its location in the equatorial environment. Grouper fish is one of the potential markets in contributing to the income of the country due to its desirable taste, high demand and high price. However, the demand of grouper fish is still insufficient from the wild catch. Therefore, there is a need to farm grouper fish to cater to the market demand. In order to farm grouper fish, there is a need to have prior knowledge of the proper nutrients needed because there is no exact data available. Therefore, in this study, primary data and secondary data are collected even though there is a limitation of related papers and 30 samples are investigated by using standard deviation selection in Evolutionary algorithm. Thus, this study would unlock frontiers for an extensive research in respect of grouper fish feed formulation. Results shown that the fitness of standard deviation selection in evolutionary algorithm is applicable. The feasible and low fitness, quick solution can be obtained. These fitness can be further predicted to minimize cost in farming grouper fish.

[The history of development of evolutionary methods in St. Petersburg school of computer simulation in biology].

PubMed

Menshutkin, V V; Kazanskiĭ, A B; Levchenko, V F

2010-01-01

The history of rise and development of evolutionary methods in Saint Petersburg school of biological modelling is traced and analyzed. Some pioneering works in simulation of ecological and evolutionary processes, performed in St.-Petersburg school became an exemplary ones for many followers in Russia and abroad. The individual-based approach became the crucial point in the history of the school as an adequate instrument for construction of models of biological evolution. This approach is natural for simulation of the evolution of life-history parameters and adaptive processes in populations and communities. In some cases simulated evolutionary process was used for solving a reverse problem, i. e., for estimation of uncertain life-history parameters of population. Evolutionary computations is one more aspect of this approach application in great many fields. The problems and vistas of ecological and evolutionary modelling in general are discussed.

Integrated pipeline for inferring the evolutionary history of a gene family embedded in the species tree: a case study on the STIMATE gene family.

PubMed

Song, Jia; Zheng, Sisi; Nguyen, Nhung; Wang, Youjun; Zhou, Yubin; Lin, Kui

2017-10-03

Because phylogenetic inference is an important basis for answering many evolutionary problems, a large number of algorithms have been developed. Some of these algorithms have been improved by integrating gene evolution models with the expectation of accommodating the hierarchy of evolutionary processes. To the best of our knowledge, however, there still is no single unifying model or algorithm that can take all evolutionary processes into account through a stepwise or simultaneous method. On the basis of three existing phylogenetic inference algorithms, we built an integrated pipeline for inferring the evolutionary history of a given gene family; this pipeline can model gene sequence evolution, gene duplication-loss, gene transfer and multispecies coalescent processes. As a case study, we applied this pipeline to the STIMATE (TMEM110) gene family, which has recently been reported to play an important role in store-operated Ca 2+ entry (SOCE) mediated by ORAI and STIM proteins. We inferred their phylogenetic trees in 69 sequenced chordate genomes. By integrating three tree reconstruction algorithms with diverse evolutionary models, a pipeline for inferring the evolutionary history of a gene family was developed, and its application was demonstrated.

An Ontology-Based Archive Information Model for the Planetary Science Community

NASA Technical Reports Server (NTRS)

Hughes, J. Steven; Crichton, Daniel J.; Mattmann, Chris

2008-01-01

The Planetary Data System (PDS) information model is a mature but complex model that has been used to capture over 30 years of planetary science data for the PDS archive. As the de-facto information model for the planetary science data archive, it is being adopted by the International Planetary Data Alliance (IPDA) as their archive data standard. However, after seventeen years of evolutionary change the model needs refinement. First a formal specification is needed to explicitly capture the model in a commonly accepted data engineering notation. Second, the core and essential elements of the model need to be identified to help simplify the overall archive process. A team of PDS technical staff members have captured the PDS information model in an ontology modeling tool. Using the resulting knowledge-base, work continues to identify the core elements, identify problems and issues, and then test proposed modifications to the model. The final deliverables of this work will include specifications for the next generation PDS information model and the initial set of IPDA archive data standards. Having the information model captured in an ontology modeling tool also makes the model suitable for use by Semantic Web applications.

Evolutionary Establishment of Moral and Double Moral Standards through Spatial Interactions

PubMed Central

Helbing, Dirk; Szolnoki, Attila; Perc, Matjaž; Szabó, György

2010-01-01

Situations where individuals have to contribute to joint efforts or share scarce resources are ubiquitous. Yet, without proper mechanisms to ensure cooperation, the evolutionary pressure to maximize individual success tends to create a tragedy of the commons (such as over-fishing or the destruction of our environment). This contribution addresses a number of related puzzles of human behavior with an evolutionary game theoretical approach as it has been successfully used to explain the behavior of other biological species many times, from bacteria to vertebrates. Our agent-based model distinguishes individuals applying four different behavioral strategies: non-cooperative individuals (“defectors”), cooperative individuals abstaining from punishment efforts (called “cooperators” or “second-order free-riders”), cooperators who punish non-cooperative behavior (“moralists”), and defectors, who punish other defectors despite being non-cooperative themselves (“immoralists”). By considering spatial interactions with neighboring individuals, our model reveals several interesting effects: First, moralists can fully eliminate cooperators. This spreading of punishing behavior requires a segregation of behavioral strategies and solves the “second-order free-rider problem”. Second, the system behavior changes its character significantly even after very long times (“who laughs last laughs best effect”). Third, the presence of a number of defectors can largely accelerate the victory of moralists over non-punishing cooperators. Fourth, in order to succeed, moralists may profit from immoralists in a way that appears like an “unholy collaboration”. Our findings suggest that the consideration of punishment strategies allows one to understand the establishment and spreading of “moral behavior” by means of game-theoretical concepts. This demonstrates that quantitative biological modeling approaches are powerful even in domains that have been addressed with non-mathematical concepts so far. The complex dynamics of certain social behaviors become understandable as the result of an evolutionary competition between different behavioral strategies. PMID:20454464

Toll-like receptor variation in the bottlenecked population of the Seychelles warbler: computer simulations see the 'ghost of selection past' and quantify the 'drift debt'.

PubMed

Gilroy, D L; Phillips, K P; Richardson, D S; van Oosterhout, C

2017-07-01

Balancing selection can maintain immunogenetic variation within host populations, but detecting its signal in a postbottlenecked population is challenging due to the potentially overriding effects of drift. Toll-like receptor genes (TLRs) play a fundamental role in vertebrate immune defence and are predicted to be under balancing selection. We previously characterized variation at TLR loci in the Seychelles warbler (Acrocephalus sechellensis), an endemic passerine that has undergone a historical bottleneck. Five of seven TLR loci were polymorphic, which is in sharp contrast to the low genomewide variation observed. However, standard population genetic statistical methods failed to detect a contemporary signature of selection at any TLR locus. We examined whether the observed TLR polymorphism could be explained by neutral evolution, simulating the population's demography in the software DIYABC. This showed that the posterior distributions of mutation rates had to be unrealistically high to explain the observed genetic variation. We then conducted simulations with an agent-based model using typical values for the mutation rate, which indicated that weak balancing selection has acted on the three TLR genes. The model was able to detect evidence of past selection elevating TLR polymorphism in the prebottleneck populations, but was unable to discern any effects of balancing selection in the contemporary population. Our results show drift is the overriding evolutionary force that has shaped TLR variation in the contemporary Seychelles warbler population, and the observed TLR polymorphisms might be merely the 'ghost of selection past'. Forecast models predict immunogenetic variation in this species will continue to be eroded in the absence of contemporary balancing selection. Such 'drift debt' occurs when a gene pool has not yet reached its new equilibrium level of polymorphism, and this loss could be an important threat to many recently bottlenecked populations. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

On joint subtree distributions under two evolutionary models.

PubMed

Wu, Taoyang; Choi, Kwok Pui

2016-04-01

In population and evolutionary biology, hypotheses about micro-evolutionary and macro-evolutionary processes are commonly tested by comparing the shape indices of empirical evolutionary trees with those predicted by neutral models. A key ingredient in this approach is the ability to compute and quantify distributions of various tree shape indices under random models of interest. As a step to meet this challenge, in this paper we investigate the joint distribution of cherries and pitchforks (that is, subtrees with two and three leaves) under two widely used null models: the Yule-Harding-Kingman (YHK) model and the proportional to distinguishable arrangements (PDA) model. Based on two novel recursive formulae, we propose a dynamic approach to numerically compute the exact joint distribution (and hence the marginal distributions) for trees of any size. We also obtained insights into the statistical properties of trees generated under these two models, including a constant correlation between the cherry and the pitchfork distributions under the YHK model, and the log-concavity and unimodality of the cherry distributions under both models. In addition, we show that there exists a unique change point for the cherry distributions between these two models. Copyright © 2015 Elsevier Inc. All rights reserved.

Using Genotype Abundance to Improve Phylogenetic Inference

PubMed Central

Mesin, Luka; Victora, Gabriel D; Minin, Vladimir N; Matsen, Frederick A

2018-01-01

Abstract Modern biological techniques enable very dense genetic sampling of unfolding evolutionary histories, and thus frequently sample some genotypes multiple times. This motivates strategies to incorporate genotype abundance information in phylogenetic inference. In this article, we synthesize a stochastic process model with standard sequence-based phylogenetic optimality, and show that tree estimation is substantially improved by doing so. Our method is validated with extensive simulations and an experimental single-cell lineage tracing study of germinal center B cell receptor affinity maturation. PMID:29474671

Tests of two convection theories for red giant and red supergiant envelopes

NASA Technical Reports Server (NTRS)

Stothers, Richard B.; Chin, Chao-Wen

1995-01-01

Two theories of stellar envelope convection are considered here in the context of red giants and red supergiants of intermediate to high mass: Boehm-Vitense's standard mixing-length theory (MLT) and Canuto & Mazzitelli's new theory incorporating the full spectrum of turbulence (FST). Both theories assume incompressible convection. Two formulations of the convective mixing length are also evaluated: l proportional to the local pressure scale height (H(sub P)) and l proportional to the distance from the upper boundary of the convection zone (z). Applications to test both theories are made by calculating stellar evolutionary sequences into the red zone (z). Applications to test both theories are made by calculating stellar evolutionary sequences into the red phase of core helium burning. Since the theoretically predicted effective temperatures for cool stars are known to be sensitive to the assigned value of the mixing length, this quantity has been individually calibrated for each evolutionary sequence. The calibration is done in a composite Hertzsprung-Russell diagram for the red giant and red supergiant members of well-observed Galactic open clusters. The MLT model requires the constant of proportionality for the convective mixing length to vary by a small but statistically significant amount with stellar mass, whereas the FST model succeeds in all cases with the mixing lenghth simply set equal to z. The structure of the deep stellar interior, however, remains very nearly unaffected by the choices of convection theory and mixing lenghth. Inside the convective envelope itself, a density inversion always occurs, but is somewhat smaller for the convectively more efficient MLT model. On physical grounds the FST model is preferable, and seems to alleviate the problem of finding the proper mixing length.

Prediction of stock markets by the evolutionary mix-game model

NASA Astrophysics Data System (ADS)

Chen, Fang; Gou, Chengling; Guo, Xiaoqian; Gao, Jieping

2008-06-01

This paper presents the efforts of using the evolutionary mix-game model, which is a modified form of the agent-based mix-game model, to predict financial time series. Here, we have carried out three methods to improve the original mix-game model by adding the abilities of strategy evolution to agents, and then applying the new model referred to as the evolutionary mix-game model to forecast the Shanghai Stock Exchange Composite Index. The results show that these modifications can improve the accuracy of prediction greatly when proper parameters are chosen.

Evolutionary algorithm for vehicle driving cycle generation.

PubMed

Perhinschi, Mario G; Marlowe, Christopher; Tamayo, Sergio; Tu, Jun; Wayne, W Scott

2011-09-01

Modeling transit bus emissions and fuel economy requires a large amount of experimental data over wide ranges of operational conditions. Chassis dynamometer tests are typically performed using representative driving cycles defined based on vehicle instantaneous speed as sequences of "microtrips", which are intervals between consecutive vehicle stops. Overall significant parameters of the driving cycle, such as average speed, stops per mile, kinetic intensity, and others, are used as independent variables in the modeling process. Performing tests at all the necessary combinations of parameters is expensive and time consuming. In this paper, a methodology is proposed for building driving cycles at prescribed independent variable values using experimental data through the concatenation of "microtrips" isolated from a limited number of standard chassis dynamometer test cycles. The selection of the adequate "microtrips" is achieved through a customized evolutionary algorithm. The genetic representation uses microtrip definitions as genes. Specific mutation, crossover, and karyotype alteration operators have been defined. The Roulette-Wheel selection technique with elitist strategy drives the optimization process, which consists of minimizing the errors to desired overall cycle parameters. This utility is part of the Integrated Bus Information System developed at West Virginia University.

Evolutionary disarmament in interspecific competition.

PubMed

Kisdi, E; Geritz, S A

2001-12-22

Competitive asymmetry, which is the advantage of having a larger body or stronger weaponry than a contestant, drives spectacular evolutionary arms races in intraspecific competition. Similar asymmetries are well documented in interspecific competition, yet they seldom lead to exaggerated traits. Here we demonstrate that two species with substantially different size may undergo parallel coevolution towards a smaller size under the same ecological conditions where a single species would exhibit an evolutionary arms race. We show that disarmament occurs for a wide range of parameters in an ecologically explicit model of competition for a single shared resource; disarmament also occurs in a simple Lotka-Volterra competition model. A key property of both models is the interplay between evolutionary dynamics and population density. The mechanism does not rely on very specific features of the model. Thus, evolutionary disarmament may be widespread and may help to explain the lack of interspecific arms races.

Evolutionary disarmament in interspecific competition.

PubMed Central

Kisdi, E.; Geritz, S. A.

2001-01-01

Competitive asymmetry, which is the advantage of having a larger body or stronger weaponry than a contestant, drives spectacular evolutionary arms races in intraspecific competition. Similar asymmetries are well documented in interspecific competition, yet they seldom lead to exaggerated traits. Here we demonstrate that two species with substantially different size may undergo parallel coevolution towards a smaller size under the same ecological conditions where a single species would exhibit an evolutionary arms race. We show that disarmament occurs for a wide range of parameters in an ecologically explicit model of competition for a single shared resource; disarmament also occurs in a simple Lotka-Volterra competition model. A key property of both models is the interplay between evolutionary dynamics and population density. The mechanism does not rely on very specific features of the model. Thus, evolutionary disarmament may be widespread and may help to explain the lack of interspecific arms races. PMID:11749715

LSPM J1314+1320: An Oversized Magnetic Star with Constraints on the Radio Emission Mechanism

DOE Office of Scientific and Technical Information (OSTI.GOV)

MacDonald, James; Mullan, D. J.

LSPM J1314+1320 (=NLTT 33370) is a binary star system consisting of two nearly identical pre-main-sequence stars of spectral type M7. The system is remarkable among ultracool dwarfs for being the most luminous radio emitter over the widest frequency range. Masses and luminosities are at first sight consistent with the system being coeval at age ∼80 Myr according to standard (nonmagnetic) evolutionary models. However, these models predict an average effective temperature of ∼2950 K, which is 180 K hotter than the empirical value. Thus, the empirical radii are oversized relative to the standard models by ≈13%. We demonstrate that magnetic stellarmore » models can quantitatively account for the oversizing. As a check on our models, we note that the radio emission limits the surface magnetic field strengths: the limits depend on identifying the radio emission mechanism. We find that the field strengths required by our magnetic models are too strong to be consistent with gyrosynchrotron emission but are consistent with electron cyclotron maser emission.« less

Unperturbed Schelling Segregation in Two or Three Dimensions

NASA Astrophysics Data System (ADS)

Barmpalias, George; Elwes, Richard; Lewis-Pye, Andrew

2016-09-01

Schelling's models of segregation, first described in 1969 (Am Econ Rev 59:488-493, 1969) are among the best known models of self-organising behaviour. Their original purpose was to identify mechanisms of urban racial segregation. But his models form part of a family which arises in statistical mechanics, neural networks, social science, and beyond, where populations of agents interact on networks. Despite extensive study, unperturbed Schelling models have largely resisted rigorous analysis, prior results generally focusing on variants in which noise is introduced into the dynamics, the resulting system being amenable to standard techniques from statistical mechanics or stochastic evolutionary game theory (Young in Individual strategy and social structure: an evolutionary theory of institutions, Princeton University Press, Princeton, 1998). A series of recent papers (Brandt et al. in: Proceedings of the 44th annual ACM symposium on theory of computing (STOC 2012), 2012); Barmpalias et al. in: 55th annual IEEE symposium on foundations of computer science, Philadelphia, 2014, J Stat Phys 158:806-852, 2015), has seen the first rigorous analyses of 1-dimensional unperturbed Schelling models, in an asymptotic framework largely unknown in statistical mechanics. Here we provide the first such analysis of 2- and 3-dimensional unperturbed models, establishing most of the phase diagram, and answering a challenge from Brandt et al. in: Proceedings of the 44th annual ACM symposium on theory of computing (STOC 2012), 2012).

Toward a unifying framework for evolutionary processes.

PubMed

Paixão, Tiago; Badkobeh, Golnaz; Barton, Nick; Çörüş, Doğan; Dang, Duc-Cuong; Friedrich, Tobias; Lehre, Per Kristian; Sudholt, Dirk; Sutton, Andrew M; Trubenová, Barbora

2015-10-21

The theory of population genetics and evolutionary computation have been evolving separately for nearly 30 years. Many results have been independently obtained in both fields and many others are unique to its respective field. We aim to bridge this gap by developing a unifying framework for evolutionary processes that allows both evolutionary algorithms and population genetics models to be cast in the same formal framework. The framework we present here decomposes the evolutionary process into its several components in order to facilitate the identification of similarities between different models. In particular, we propose a classification of evolutionary operators based on the defining properties of the different components. We cast several commonly used operators from both fields into this common framework. Using this, we map different evolutionary and genetic algorithms to different evolutionary regimes and identify candidates with the most potential for the translation of results between the fields. This provides a unified description of evolutionary processes and represents a stepping stone towards new tools and results to both fields. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

An Interdisciplinary Model for Teaching Evolutionary Ecology.

ERIC Educational Resources Information Center

Coletta, John

1992-01-01

Describes a general systems evolutionary model and demonstrates how a previously established ecological model is a function of its past development based on the evolution of the rock, nutrient, and water cycles. Discusses the applications of the model in environmental education. (MDH)

Modelling the influence of parental effects on gene-network evolution.

PubMed

Odorico, Andreas; Rünneburger, Estelle; Le Rouzic, Arnaud

2018-05-01

Understanding the importance of nongenetic heredity in the evolutionary process is a major topic in modern evolutionary biology. We modified a classical gene-network model by allowing parental transmission of gene expression and studied its evolutionary properties through individual-based simulations. We identified ontogenetic time (i.e. the time gene networks have to stabilize before being submitted to natural selection) as a crucial factor in determining the evolutionary impact of this phenotypic inheritance. Indeed, fast-developing organisms display enhanced adaptation and greater robustness to mutations when evolving in presence of nongenetic inheritance (NGI). In contrast, in our model, long development reduces the influence of the inherited state of the gene network. NGI thus had a negligible effect on the evolution of gene networks when the speed at which transcription levels reach equilibrium is not constrained. Nevertheless, simulations show that intergenerational transmission of the gene-network state negatively affects the evolution of robustness to environmental disturbances for either fast- or slow-developing organisms. Therefore, these results suggest that the evolutionary consequences of NGI might not be sought only in the way species respond to selection, but also on the evolution of emergent properties (such as environmental and genetic canalization) in complex genetic architectures. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Stochastic noncooperative and cooperative evolutionary game strategies of a population of biological networks under natural selection.

PubMed

Chen, Bor-Sen; Yeh, Chin-Hsun

2017-12-01

We review current static and dynamic evolutionary game strategies of biological networks and discuss the lack of random genetic variations and stochastic environmental disturbances in these models. To include these factors, a population of evolving biological networks is modeled as a nonlinear stochastic biological system with Poisson-driven genetic variations and random environmental fluctuations (stimuli). To gain insight into the evolutionary game theory of stochastic biological networks under natural selection, the phenotypic robustness and network evolvability of noncooperative and cooperative evolutionary game strategies are discussed from a stochastic Nash game perspective. The noncooperative strategy can be transformed into an equivalent multi-objective optimization problem and is shown to display significantly improved network robustness to tolerate genetic variations and buffer environmental disturbances, maintaining phenotypic traits for longer than the cooperative strategy. However, the noncooperative case requires greater effort and more compromises between partly conflicting players. Global linearization is used to simplify the problem of solving nonlinear stochastic evolutionary games. Finally, a simple stochastic evolutionary model of a metabolic pathway is simulated to illustrate the procedure of solving for two evolutionary game strategies and to confirm and compare their respective characteristics in the evolutionary process. Copyright © 2017 Elsevier B.V. All rights reserved.

A 3D MRI-based atlas of a lizard brain.

PubMed

Hoops, Daniel; Desfilis, Ester; Ullmann, Jeremy F P; Janke, Andrew L; Stait-Gardner, Timothy; Devenyi, Gabriel A; Price, William S; Medina, Loreta; Whiting, Martin J; Keogh, J Scott

2018-06-22

Magnetic resonance imaging (MRI) is an established technique for neuroanatomical analysis, being particularly useful in the medical sciences. However, the application of MRI to evolutionary neuroscience is still in its infancy. Few magnetic resonance brain atlases exist outside the standard model organisms in neuroscience and no magnetic resonance atlas has been produced for any reptile brain. A detailed understanding of reptilian brain anatomy is necessary to elucidate the evolutionary origin of enigmatic brain structures such as the cerebral cortex. Here, we present a magnetic resonance atlas for the brain of a representative squamate reptile, the Australian tawny dragon (Agamidae: Ctenophorus decresii), which has been the object of numerous ecological and behavioral studies. We used a high-field 11.74T magnet, a paramagnetic contrasting-enhancing agent and minimum-deformation modeling of the brains of thirteen adult male individuals. From this, we created a high-resolution three-dimensional model of a lizard brain . The 3D-MRI model can be freely downloaded and allows a better comprehension of brain areas, nuclei, and fiber tracts, facilitating comparison with other species and setting the basis for future comparative evolution imaging studies. The MRI model of a tawny dragon brain (Ctenophorus decresii) can be viewed online and downloaded using the Wiley Biolucida Server at wiley.biolucida.net. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

Bistability of Evolutionary Stable Vaccination Strategies in the Reinfection SIRI Model.

PubMed

Martins, José; Pinto, Alberto

2017-04-01

We use the reinfection SIRI epidemiological model to analyze the impact of education programs and vaccine scares on individuals decisions to vaccinate or not. The presence of the reinfection provokes the novelty of the existence of three Nash equilibria for the same level of the morbidity relative risk instead of a single Nash equilibrium as occurs in the SIR model studied by Bauch and Earn (PNAS 101:13391-13394, 2004). The existence of three Nash equilibria, with two of them being evolutionary stable, introduces two scenarios with relevant and opposite features for the same level of the morbidity relative risk: the low-vaccination scenario corresponding to the evolutionary stable vaccination strategy, where individuals will vaccinate with a low probability; and the high-vaccination scenario corresponding to the evolutionary stable vaccination strategy, where individuals will vaccinate with a high probability. We introduce the evolutionary vaccination dynamics for the SIRI model and we prove that it is bistable. The bistability of the evolutionary dynamics indicates that the damage provoked by false scares on the vaccination perceived morbidity risks can be much higher and much more persistent than in the SIR model. Furthermore, the vaccination education programs to be efficient they need to implement a mechanism to suddenly increase the vaccination coverage level.

Evolutionary change in physiological phenotypes along the human lineage

PubMed Central

Vining, Alexander Q.; Nunn, Charles L.

2016-01-01

Background and Objectives: Research in evolutionary medicine provides many examples of how evolution has shaped human susceptibility to disease. Traits undergoing rapid evolutionary change may result in associated costs or reduce the energy available to other traits. We hypothesize that humans have experienced more such changes than other primates as a result of major evolutionary change along the human lineage. We investigated 41 physiological traits across 50 primate species to identify traits that have undergone marked evolutionary change along the human lineage. Methodology: We analysed the data using two Bayesian phylogenetic comparative methods. One approach models trait covariation in non-human primates and predicts human phenotypes to identify whether humans are evolutionary outliers. The other approach models adaptive shifts under an Ornstein-Uhlenbeck model of evolution to assess whether inferred shifts are more common on the human branch than on other primate lineages. Results: We identified four traits with strong evidence for an evolutionary increase on the human lineage (amylase, haematocrit, phosphorus and monocytes) and one trait with strong evidence for decrease (neutrophilic bands). Humans exhibited more cases of distinct evolutionary change than other primates. Conclusions and Implications: Human physiology has undergone increased evolutionary change compared to other primates. Long distance running may have contributed to increases in haematocrit and mean corpuscular haemoglobin concentration, while dietary changes are likely related to increases in amylase. In accordance with the pathogen load hypothesis, human monocyte levels were increased, but many other immune-related measures were not. Determining the mechanisms underlying conspicuous evolutionary change in these traits may provide new insights into human disease. PMID:27615376

Evolutionary suicide through a non-catastrophic bifurcation: adaptive dynamics of pathogens with frequency-dependent transmission.

PubMed

Boldin, Barbara; Kisdi, Éva

2016-03-01

Evolutionary suicide is a riveting phenomenon in which adaptive evolution drives a viable population to extinction. Gyllenberg and Parvinen (Bull Math Biol 63(5):981-993, 2001) showed that, in a wide class of deterministic population models, a discontinuous transition to extinction is a necessary condition for evolutionary suicide. An implicit assumption of their proof is that the invasion fitness of a rare strategy is well-defined also in the extinction state of the population. Epidemic models with frequency-dependent incidence, which are often used to model the spread of sexually transmitted infections or the dynamics of infectious diseases within herds, violate this assumption. In these models, evolutionary suicide can occur through a non-catastrophic bifurcation whereby pathogen adaptation leads to a continuous decline of host (and consequently pathogen) population size to zero. Evolutionary suicide of pathogens with frequency-dependent transmission can occur in two ways, with pathogen strains evolving either higher or lower virulence.

A dynamic eco-evolutionary model predicts slow response of alpine plants to climate warming.

PubMed

Cotto, Olivier; Wessely, Johannes; Georges, Damien; Klonner, Günther; Schmid, Max; Dullinger, Stefan; Thuiller, Wilfried; Guillaume, Frédéric

2017-05-05

Withstanding extinction while facing rapid climate change depends on a species' ability to track its ecological niche or to evolve a new one. Current methods that predict climate-driven species' range shifts use ecological modelling without eco-evolutionary dynamics. Here we present an eco-evolutionary forecasting framework that combines niche modelling with individual-based demographic and genetic simulations. Applying our approach to four endemic perennial plant species of the Austrian Alps, we show that accounting for eco-evolutionary dynamics when predicting species' responses to climate change is crucial. Perennial species persist in unsuitable habitats longer than predicted by niche modelling, causing delayed range losses; however, their evolutionary responses are constrained because long-lived adults produce increasingly maladapted offspring. Decreasing population size due to maladaptation occurs faster than the contraction of the species range, especially for the most abundant species. Monitoring of species' local abundance rather than their range may likely better inform on species' extinction risks under climate change.

Stimulating Scientific Reasoning with Drawing-Based Modeling

ERIC Educational Resources Information Center

Heijnes, Dewi; van Joolingen, Wouter; Leenaars, Frank

2018-01-01

We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each…

Evolving cell models for systems and synthetic biology.

PubMed

Cao, Hongqing; Romero-Campero, Francisco J; Heeb, Stephan; Cámara, Miguel; Krasnogor, Natalio

2010-03-01

This paper proposes a new methodology for the automated design of cell models for systems and synthetic biology. Our modelling framework is based on P systems, a discrete, stochastic and modular formal modelling language. The automated design of biological models comprising the optimization of the model structure and its stochastic kinetic constants is performed using an evolutionary algorithm. The evolutionary algorithm evolves model structures by combining different modules taken from a predefined module library and then it fine-tunes the associated stochastic kinetic constants. We investigate four alternative objective functions for the fitness calculation within the evolutionary algorithm: (1) equally weighted sum method, (2) normalization method, (3) randomly weighted sum method, and (4) equally weighted product method. The effectiveness of the methodology is tested on four case studies of increasing complexity including negative and positive autoregulation as well as two gene networks implementing a pulse generator and a bandwidth detector. We provide a systematic analysis of the evolutionary algorithm's results as well as of the resulting evolved cell models.

Adaptive evolution of body size subject to indirect effect in trophic cascade system.

PubMed

Wang, Xin; Fan, Meng; Hao, Lina

2017-09-01

Trophic cascades represent a classic example of indirect effect and are wide-spread in nature. Their ecological impact are well established, but the evolutionary consequences have received even less theoretical attention. We theoretically and numerically investigate the trait (i.e., body size of consumer) evolution in response to indirect effect in a trophic cascade system. By applying the quantitative trait evolutionary theory and the adaptive dynamic theory, we formulate and explore two different types of eco-evolutionary resource-consumer-predator trophic cascade model. First, an eco-evolutionary model incorporating the rapid evolution is formulated to investigate the effect of rapid evolution of the consumer's body size, and to explore the impact of density-mediate indirect effect on the population dynamics and trait dynamics. Next, by employing the adaptive dynamic theory, a long-term evolutionary model of consumer body size is formulated to evaluate the effect of long-term evolution on the population dynamics and the effect of trait-mediate indirect effect. Those models admit rich dynamics that has not been observed yet in empirical studies. It is found that, both in the trait-mediated and density-mediated system, the body size of consumer in predator-consumer-resource interaction (indirect effect) evolves smaller than that in consumer-resource and predator-consumer interaction (direct effect). Moreover, in the density-mediated system, we found that the evolution of consumer body size contributes to avoiding consumer extinction (i.e., evolutionary rescue). The trait-mediate and density-mediate effects may produce opposite evolutionary response. This study suggests that the trophic cascade indirect effect affects consumer evolution, highlights a more comprehensive mechanistic understanding of the intricate interplay between ecological and evolutionary force. The modeling approaches provide avenue for study on indirect effects from an evolutionary perspective. Copyright © 2017 Elsevier B.V. All rights reserved.

A Philosophical Perspective on Evolutionary Systems Biology

PubMed Central

Soyer, Orkun S.; Siegal, Mark L.

2015-01-01

Evolutionary systems biology (ESB) is an emerging hybrid approach that integrates methods, models, and data from evolutionary and systems biology. Drawing on themes that arose at a cross-disciplinary meeting on ESB in 2013, we discuss in detail some of the explanatory friction that arises in the interaction between evolutionary and systems biology. These tensions appear because of different modeling approaches, diverse explanatory aims and strategies, and divergent views about the scope of the evolutionary synthesis. We locate these discussions in the context of long-running philosophical deliberations on explanation, modeling, and theoretical synthesis. We show how many of the issues central to ESB’s progress can be understood as general philosophical problems. The benefits of addressing these philosophical issues feed back into philosophy too, because ESB provides excellent examples of scientific practice for the development of philosophy of science and philosophy of biology. PMID:26085823

Cooperative combinatorial optimization: evolutionary computation case study.

PubMed

Burgin, Mark; Eberbach, Eugene

2008-01-01

This paper presents a formalization of the notion of cooperation and competition of multiple systems that work toward a common optimization goal of the population using evolutionary computation techniques. It is proved that evolutionary algorithms are more expressive than conventional recursive algorithms, such as Turing machines. Three classes of evolutionary computations are introduced and studied: bounded finite, unbounded finite, and infinite computations. Universal evolutionary algorithms are constructed. Such properties of evolutionary algorithms as completeness, optimality, and search decidability are examined. A natural extension of evolutionary Turing machine (ETM) model is proposed to properly reflect phenomena of cooperation and competition in the whole population.

Hidden long evolutionary memory in a model biochemical network

NASA Astrophysics Data System (ADS)

Ali, Md. Zulfikar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

2018-04-01

We introduce a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational algorithm, and apply the model to study neutral drift in networks that yield oscillatory dynamics. Starting with a functional core module, random evolutionary drift increases network complexity even in the absence of specific selective pressures. Surprisingly, we uncover a hidden order in sequence space that gives rise to long-term evolutionary memory, implying strong constraints on network evolution due to the topology of accessible sequence space.

Evolutionary conceptual analysis: faith community nursing.

PubMed

Ziebarth, Deborah

2014-12-01

The aim of the study was to report an evolutionary concept analysis of faith community nursing (FCN). FCN is a source of healthcare delivery in the USA which has grown in comprehensiveness and complexity. With increasing healthcare cost and a focus on access and prevention, FCN has extended beyond the physical walls of the faith community building. Faith communities and healthcare organizations invest in FCN and standardized training programs exist. Using Rodgers' evolutionary analysis, the literature was examined for antecedents, attributes, and consequences of the concept. This design allows for understanding the historical and social nature of the concept and how it changes over time. A search of databases using the keywords FCN, faith community nurse, parish nursing, and parish nurse was done. The concept of FCN was explored using research and theoretical literature. A theoretical definition and model were developed with relevant implications. The search results netted a sample of 124 reports of research and theoretical articles from multiple disciplines: medicine, education, religion and philosophy, international health, and nursing. Theoretical definition: FCN is a method of healthcare delivery that is centered in a relationship between the nurse and client (client as person, family, group, or community). The relationship occurs in an iterative motion over time when the client seeks or is targeted for wholistic health care with the goal of optimal wholistic health functioning. Faith integrating is a continuous occurring attribute. Health promoting, disease managing, coordinating, empowering and accessing health care are other essential attributes. All essential attributes occur with intentionality in a faith community, home, health institution and other community settings with fluidity as part of a community, national, or global health initiative. A new theoretical definition and corresponding conceptual model of FCN provides a basis for future nursing knowledge and model-based applications for evidence-based practice and research.

Evolutionary cognitive therapy versus standard cognitive therapy for depression: a protocol for a blinded, randomized, superiority clinical trial.

PubMed

Giosan, Cezar; Cobeanu, Oana; Mogoase, Cristina; Muresan, Vlad; Malta, Loretta S; Wyka, Katarzyna; Szentagotai, Aurora

2014-03-19

Depression is estimated to become the leading cause of disease burden globally by 2030. Despite existing efficacious treatments (both medical and psychotherapeutic), a large proportion of patients do not respond to therapy. Recent insights from evolutionary psychology suggest that, in addition to targeting the proximal causes of depression (for example, targeting dysfunctional beliefs by cognitive behavioral therapy), the distal or evolutionary causes (for example, inclusive fitness) should also be addressed. A randomized superiority trial is conducted to develop and test an evolutionary-driven cognitive therapy protocol for depression, and to compare its efficacy against standard cognitive therapy for depression. Romanian-speaking adults (18 years or older) with elevated Beck Depression Inventory (BDI) scores (>13), current diagnosis of major depressive disorder or major depressive episode (MDD or MDE), and MDD with comorbid dysthymia, as evaluated by the Structured Clinical Interview for DSM-IV (SCID), are included in the study. Participants are randomized to one of two conditions: 1) evolutionary-driven cognitive therapy (ED-CT) or 2) cognitive therapy (CT). Both groups undergo 12 psychotherapy sessions, and data are collected at baseline, mid-treatment, post-treatment, and the 3-month follow-up. Primary outcomes are depressive symptomatology and a categorical diagnosis of depression post-treatment. This randomized trial compares the newly proposed ED-CT with a classic CT protocol for depression. To our knowledge, this is the first attempt to integrate insights from evolutionary theories of depression into the treatment of this condition in a controlled manner. This study can thus add substantially to the body of knowledge on validated treatments for depression. Current Controlled Trials ISRCTN64664414The trial was registered in June 2013. The first participant was enrolled on October 3, 2012.

USING ECO-EVOLUTIONARY INDIVIDUAL-BASED MODELS TO INVESTIGATE SPATIALLY-DEPENDENT PROCESSES IN CONSERVATION GENETICS

EPA Science Inventory

Eco-evolutionary population simulation models are powerful new forecasting tools for exploring management strategies for climate change and other dynamic disturbance regimes. Additionally, eco-evo individual-based models (IBMs) are useful for investigating theoretical feedbacks ...

Evolutionary dynamics from a variational principle.

PubMed

Klimek, Peter; Thurner, Stefan; Hanel, Rudolf

2010-07-01

We demonstrate with a thought experiment that fitness-based population dynamical approaches to evolution are not able to make quantitative, falsifiable predictions about the long-term behavior of some evolutionary systems. A key characteristic of evolutionary systems is the ongoing endogenous production of new species. These novel entities change the conditions for already existing species. Even Darwin's Demon, a hypothetical entity with exact knowledge of the abundance of all species and their fitness functions at a given time, could not prestate the impact of these novelties on established populations. We argue that fitness is always a posteriori knowledge--it measures but does not explain why a species has reproductive success or not. To overcome these conceptual limitations, a variational principle is proposed in a spin-model-like setup of evolutionary systems. We derive a functional which is minimized under the most general evolutionary formulation of a dynamical system, i.e., evolutionary trajectories causally emerge as a minimization of a functional. This functional allows the derivation of analytic solutions of the asymptotic diversity for stochastic evolutionary systems within a mean-field approximation. We test these approximations by numerical simulations of the corresponding model and find good agreement in the position of phase transitions in diversity curves. The model is further able to reproduce stylized facts of timeseries from several man-made and natural evolutionary systems. Light will be thrown on how species and their fitness landscapes dynamically coevolve.

The current status of REH theory. [Random Evolutionary Hits in biological molecular evolution

NASA Technical Reports Server (NTRS)

Holmquist, R.; Jukes, T. H.

1981-01-01

A response is made to the evaluation of Fitch (1980) of REH (random evolutionary hits) theory for the evolutionary divergence of proteins and nucleic acids. Correct calculations for the beta hemoglobin mRNAs of the human, mouse and rabbit in the absence and presence of selective constraints are summarized, and it is shown that the alternative evolutionary analysis of Fitch underestimates the total fixed mutations. It is further shown that the model used by Fitch to test for the completeness of the count of total base substitutions is in fact a variant of REH theory. Considerations of the variance inherent in evolutionary estimations are also presented which show the REH model to produce no more variance than other evolutionary models. In the reply, it is argued that, despite the objections raised, REH theory applied to proteins gives inaccurate estimates of total gene substitutions. It is further contended that REH theory developed for nucleic sequences suffers from problems relating to the frequency of nucleotide substitutions, the identity of the codons accepting silent and amino acid-changing substitutions, and estimate uncertainties.

Strategic approaches to planetary base development

NASA Technical Reports Server (NTRS)

Roberts, Barney B.

1992-01-01

The evolutionary development of a planetary expansionary outpost is considered in the light of both technical and economic issues. The outline of a partnering taxonomy is set forth which encompasses both institutional and temporal issues related to establishing shared interests and investments. The purely technical issues are discussed in terms of the program components which include nonaerospace technologies such as construction engineering. Five models are proposed in which partnership and autonomy for participants are approached in different ways including: (1) the standard customer/provider relationship; (2) a service-provider scenario; (3) the joint venture; (4) a technology joint-development model; and (5) a redundancy model for reduced costs. Based on the assumed characteristics of planetary surface systems the cooperative private/public models are championed with coordinated design by NASA to facilitate outside cooperation.

Evolutionary molecular medicine.

PubMed

Nesse, Randolph M; Ganten, Detlev; Gregory, T Ryan; Omenn, Gilbert S

2012-05-01

Evolution has long provided a foundation for population genetics, but some major advances in evolutionary biology from the twentieth century that provide foundations for evolutionary medicine are only now being applied in molecular medicine. They include the need for both proximate and evolutionary explanations, kin selection, evolutionary models for cooperation, competition between alleles, co-evolution, and new strategies for tracing phylogenies and identifying signals of selection. Recent advances in genomics are transforming evolutionary biology in ways that create even more opportunities for progress at its interfaces with genetics, medicine, and public health. This article reviews 15 evolutionary principles and their applications in molecular medicine in hopes that readers will use them and related principles to speed the development of evolutionary molecular medicine.

Evolutionary change in physiological phenotypes along the human lineage.

PubMed

Vining, Alexander Q; Nunn, Charles L

2016-01-01

Research in evolutionary medicine provides many examples of how evolution has shaped human susceptibility to disease. Traits undergoing rapid evolutionary change may result in associated costs or reduce the energy available to other traits. We hypothesize that humans have experienced more such changes than other primates as a result of major evolutionary change along the human lineage. We investigated 41 physiological traits across 50 primate species to identify traits that have undergone marked evolutionary change along the human lineage. We analysed the data using two Bayesian phylogenetic comparative methods. One approach models trait covariation in non-human primates and predicts human phenotypes to identify whether humans are evolutionary outliers. The other approach models adaptive shifts under an Ornstein-Uhlenbeck model of evolution to assess whether inferred shifts are more common on the human branch than on other primate lineages. We identified four traits with strong evidence for an evolutionary increase on the human lineage (amylase, haematocrit, phosphorus and monocytes) and one trait with strong evidence for decrease (neutrophilic bands). Humans exhibited more cases of distinct evolutionary change than other primates. Human physiology has undergone increased evolutionary change compared to other primates. Long distance running may have contributed to increases in haematocrit and mean corpuscular haemoglobin concentration, while dietary changes are likely related to increases in amylase. In accordance with the pathogen load hypothesis, human monocyte levels were increased, but many other immune-related measures were not. Determining the mechanisms underlying conspicuous evolutionary change in these traits may provide new insights into human disease. The Author(s) 2016. Published by Oxford University Press on behalf of the Foundation for Evolution, Medicine, and Public Health.

A fully associative, nonisothermal, nonlinear kinematic, unified viscoplastic model for titanium alloys

NASA Astrophysics Data System (ADS)

Arnold, S. M.; Saleeb, A. F.; Castelli, M. G.

1995-05-01

Specific forms for both the Gibb's and complementary dissipation potentials are chosen such that a complete (i.e., fully associative) potential base multiaxial, nonisothermal unified viscoplastic model is obtained. This model possesses one tensorial internal state variable (that is, associated with dislocation substructure) and an evolutionary law that has nonlinear kinematic hardening and both thermal and strain induced recovery mechanisms. A unique aspect of the present model is the inclusion of nonlinear hardening through the use of a compliance operator, derived from the Gibb's potential, in the evolution law for the back stress. This nonlinear tensorial operator is significant in that it allows both the flow and evolutionary laws to be fully associative (and therefore easily integrated), greatly influences the multiaxial response under non-proportional loading paths, and in the case of nonisothermal histories, introduces an instantaneous thermal softening mechanism proportional to the rate of change in temperature. In addition to this nonlinear compliance operator, a new consistent, potential preserving, internal strain unloading criterion has been introduced to prevent abnormalities in the predicted stress-strain curves, which are present with nonlinear hardening formulations, during unloading and reversed loading of the external variables. The specific model proposed is characterized for a representative titanium alloy commonly used as the matrix material in SiC fiber reinforced composites, i.e., TIMETAL 21S. Verification of the proposed model is shown using 'specialized' non-standard isothermal and thermomechanical deformation tests.

A fully associative, nonisothermal, nonlinear kinematic, unified viscoplastic model for titanium alloys

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Saleeb, A. F.; Castelli, M. G.

1995-01-01

Specific forms for both the Gibb's and complementary dissipation potentials are chosen such that a complete (i.e., fully associative) potential base multiaxial, nonisothermal unified viscoplastic model is obtained. This model possesses one tensorial internal state variable (that is, associated with dislocation substructure) and an evolutionary law that has nonlinear kinematic hardening and both thermal and strain induced recovery mechanisms. A unique aspect of the present model is the inclusion of nonlinear hardening through the use of a compliance operator, derived from the Gibb's potential, in the evolution law for the back stress. This nonlinear tensorial operator is significant in that it allows both the flow and evolutionary laws to be fully associative (and therefore easily integrated), greatly influences the multiaxial response under non-proportional loading paths, and in the case of nonisothermal histories, introduces an instantaneous thermal softening mechanism proportional to the rate of change in temperature. In addition to this nonlinear compliance operator, a new consistent, potential preserving, internal strain unloading criterion has been introduced to prevent abnormalities in the predicted stress-strain curves, which are present with nonlinear hardening formulations, during unloading and reversed loading of the external variables. The specific model proposed is characterized for a representative titanium alloy commonly used as the matrix material in SiC fiber reinforced composites, i.e., TIMETAL 21S. Verification of the proposed model is shown using 'specialized' non-standard isothermal and thermomechanical deformation tests.

Genetic evolutionary taboo search for optimal marker placement in infrared patient setup

NASA Astrophysics Data System (ADS)

Riboldi, M.; Baroni, G.; Spadea, M. F.; Tagaste, B.; Garibaldi, C.; Cambria, R.; Orecchia, R.; Pedotti, A.

2007-09-01

In infrared patient setup adequate selection of the external fiducial configuration is required for compensating inner target displacements (target registration error, TRE). Genetic algorithms (GA) and taboo search (TS) were applied in a newly designed approach to optimal marker placement: the genetic evolutionary taboo search (GETS) algorithm. In the GETS paradigm, multiple solutions are simultaneously tested in a stochastic evolutionary scheme, where taboo-based decision making and adaptive memory guide the optimization process. The GETS algorithm was tested on a group of ten prostate patients, to be compared to standard optimization and to randomly selected configurations. The changes in the optimal marker configuration, when TRE is minimized for OARs, were specifically examined. Optimal GETS configurations ensured a 26.5% mean decrease in the TRE value, versus 19.4% for conventional quasi-Newton optimization. Common features in GETS marker configurations were highlighted in the dataset of ten patients, even when multiple runs of the stochastic algorithm were performed. Including OARs in TRE minimization did not considerably affect the spatial distribution of GETS marker configurations. In conclusion, the GETS algorithm proved to be highly effective in solving the optimal marker placement problem. Further work is needed to embed site-specific deformation models in the optimization process.

The law of cooperation: Comment on "Universal scaling for the dilemma strength in evolutionary games" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Ichinose, Genki

2015-09-01

Cooperation is a behavior that benefits others while incurring costs to the actor. Thus, natural selection favors defection (non-cooperation), which unilaterally takes the benefits without paying any costs, rather than cooperation. Despite this logical consequence, reality is the opposite: Cooperation is ubiquitous at any level from genomes to human societies. This contradiction is known as the puzzle of the evolution of cooperation. For a long time, evolutionary game theorists have used the prisoner's dilemma game (PD) and the chicken game (CH) as the standard models to solve this puzzle. For these researchers, it is recognized that a specific mechanism is needed for the evolution of cooperation [1]. Five mechanisms are proposed: kin selection, direct reciprocity, indirect reciprocity, network reciprocity, and group selection. By using the donor and recipient game (D&R), which is one of the particular forms of PD, Nowak theoretically showed that once benefit (b), cost (c), and the other one or two parameters for each mechanism are given, we (evolutionary game theorists) can immediately know whether cooperation evolves [1]. The point here is that he included those unique parameters for each mechanism into PD and then reformulated the payoff matrix. Therefore, we can use this extended PD as the first scaling parameters.

Not just a theory--the utility of mathematical models in evolutionary biology.

PubMed

Servedio, Maria R; Brandvain, Yaniv; Dhole, Sumit; Fitzpatrick, Courtney L; Goldberg, Emma E; Stern, Caitlin A; Van Cleve, Jeremy; Yeh, D Justin

2014-12-01

Progress in science often begins with verbal hypotheses meant to explain why certain biological phenomena exist. An important purpose of mathematical models in evolutionary research, as in many other fields, is to act as “proof-of-concept” tests of the logic in verbal explanations, paralleling the way in which empirical data are used to test hypotheses. Because not all subfields of biology use mathematics for this purpose, misunderstandings of the function of proof-of-concept modeling are common. In the hope of facilitating communication, we discuss the role of proof-of-concept modeling in evolutionary biology.

EVOLUTIONARY FOUNDATIONS FOR MOLECULAR MEDICINE

PubMed Central

Nesse, Randolph M.; Ganten, Detlev; Gregory, T. Ryan; Omenn, Gilbert S.

2015-01-01

Evolution has long provided a foundation for population genetics, but many major advances in evolutionary biology from the 20th century are only now being applied in molecular medicine. They include the distinction between proximate and evolutionary explanations, kin selection, evolutionary models for cooperation, and new strategies for tracing phylogenies and identifying signals of selection. Recent advances in genomics are further transforming evolutionary biology and creating yet more opportunities for progress at the interface of evolution with genetics, medicine, and public health. This article reviews 15 evolutionary principles and their applications in molecular medicine in hopes that readers will use them and others to speed the development of evolutionary molecular medicine. PMID:22544168

Phylogeography Takes a Relaxed Random Walk in Continuous Space and Time

PubMed Central

Lemey, Philippe; Rambaut, Andrew; Welch, John J.; Suchard, Marc A.

2010-01-01

Research aimed at understanding the geographic context of evolutionary histories is burgeoning across biological disciplines. Recent endeavors attempt to interpret contemporaneous genetic variation in the light of increasingly detailed geographical and environmental observations. Such interest has promoted the development of phylogeographic inference techniques that explicitly aim to integrate such heterogeneous data. One promising development involves reconstructing phylogeographic history on a continuous landscape. Here, we present a Bayesian statistical approach to infer continuous phylogeographic diffusion using random walk models while simultaneously reconstructing the evolutionary history in time from molecular sequence data. Moreover, by accommodating branch-specific variation in dispersal rates, we relax the most restrictive assumption of the standard Brownian diffusion process and demonstrate increased statistical efficiency in spatial reconstructions of overdispersed random walks by analyzing both simulated and real viral genetic data. We further illustrate how drawing inference about summary statistics from a fully specified stochastic process over both sequence evolution and spatial movement reveals important characteristics of a rabies epidemic. Together with recent advances in discrete phylogeographic inference, the continuous model developments furnish a flexible statistical framework for biogeographical reconstructions that is easily expanded upon to accommodate various landscape genetic features. PMID:20203288

Cooperation and stability through periodic impulses.

PubMed

Zhang, Bo-Yu; Cressman, Ross; Tao, Yi

2010-03-29

Basic games, where each individual chooses between two strategies, illustrate several issues that immediately emerge from the standard approach that applies strategic reasoning, based on rational decisions, to predict population behavior where no rationality is assumed. These include how mutual cooperation (which corresponds to the best outcome from the population perspective) can evolve when the only individually rational choice is to defect, illustrated by the Prisoner's Dilemma (PD) game, and how individuals can randomize between two strategies when neither is individually rational, illustrated by the Battle of the Sexes (BS) game that models male-female conflict over parental investment in offspring. We examine these questions from an evolutionary perspective where the evolutionary dynamics includes an impulsive effect that models sudden changes in collective population behavior. For the PD game, we show analytically that cooperation can either coexist with defection or completely take over the population, depending on the strength of the impulse. By extending these results for the PD game, we also show that males and females each evolve to a single strategy in the BS game when the impulsive effect is strong and that weak impulses stabilize the randomized strategies of this game.

Physical characteristics and evolutionary trends of continental rifts

NASA Technical Reports Server (NTRS)

Ramberg, I. B.; Morgan, P.

1984-01-01

Rifts may be defined as zones beneath which the entire lithosphere has ruptured in extension. They are widespread and occur in a variety of tectonic settings, and range up to 2,600 m.y. in age. The object of this review is to highlight characteristic features of modern and ancient rifts, to emphasize differences and similarities in order to help characterize evolutionary trends, to identify physical conditions favorable for initiation as well as termination of rifting, and to provide constraints for future modeling studies of rifting. Rifts are characterized on the basis of their structural, geomorphic, magmatic and geophysical features and the diverse character of these features and their evolutionary trends through time are discussed. Mechanisms of rifting are critically examined in terms of the physical characteristics and evolutionary trends of rifts, and it is concluded that while simple models can give valuable insight into specific processes of rifting, individual rifts can rarely, if ever, be characterized by well defined trends predicted by these models. More data are required to clearly define evolutionary trends, and the models require development to incorporate the effects of lithospheric heterogeneities and complex geologic histories.

An evolutionary advantage for extravagant honesty.

PubMed

Bullock, Seth

2012-01-07

A game-theoretic model of handicap signalling over a pair of signalling channels is introduced in order to determine when one channel has an evolutionary advantage over the other. The stability conditions for honest handicap signalling are presented for a single channel and are shown to conform with the results of prior handicap signalling models. Evolutionary simulations are then used to show that, for a two-channel system in which honest signalling is possible on both channels, the channel featuring larger advertisements at equilibrium is favoured by evolution. This result helps to address a significant tension in the handicap principle literature. While the original theory was motivated by the prevalence of extravagant natural signalling, contemporary models have demonstrated that it is the cost associated with deception that stabilises honesty, and that the honest signals exhibited at equilibrium need not be extravagant at all. The current model suggests that while extravagant and wasteful signals are not required to ensure a signalling system's evolutionary stability, extravagant signalling systems may enjoy an advantage in terms of evolutionary attainability. Copyright © 2011 Elsevier Ltd. All rights reserved.

Climate change and evolutionary adaptation.

PubMed

Hoffmann, Ary A; Sgrò, Carla M

2011-02-24

Evolutionary adaptation can be rapid and potentially help species counter stressful conditions or realize ecological opportunities arising from climate change. The challenges are to understand when evolution will occur and to identify potential evolutionary winners as well as losers, such as species lacking adaptive capacity living near physiological limits. Evolutionary processes also need to be incorporated into management programmes designed to minimize biodiversity loss under rapid climate change. These challenges can be met through realistic models of evolutionary change linked to experimental data across a range of taxa.

Lithium-rich very metal-poor stars discovered with LAMOST and Subaru

NASA Astrophysics Data System (ADS)

Aoki, Wako; Li, Haining; Matsuno, Tadafumi; Kumar, Yerra Bharat; Shi, Jianrong; Suda, Takuma; Zhao, Gang

2018-04-01

Lithium is a unique element that is produced in the Big Bang nucleosynthesis but is destroyed by nuclear reactions inside stars. As a result, almost constant lithium abundance is found in unevolved main-sequence metal-poor stars, although the value is systematically lower than that expected from the standard Big Bang nucleosynthesis models, whereas lithium abundances of red giants are more than one order of magnitudes lower than those of unevolved stars. There are, however, a small fraction of metal-poor stars that show extremely high lithium abundances, which is not explained by standard stellar evolution models. We have discovered 12 new very metal-poor stars that have enhancement of lithium by more than 10 times compared with typical metal-poor stars at similar evolutionary stages by the large-scale spectroscopic survey with LAMOST and the follow-up high-resolution spectroscopy with the Subaru Telescope. The sample shows a wide distribution of evolutionary stages from subgiants to red giants with the metallicity of -3.3 <[Fe/H]< -1.6. The chemical abundance ratios of other elements have been obtained by our spectroscopic study, and an estimate of the binary frequency by radial velocity monitoring is ongoing. The observational results provide new constraints on the scenarios to explain lithium-rich metal-poor stars, such as extra mixing during the evolution along the red giant branch, mass-transfer from a companion AGB star, and engulfment of planet-like objects. These explanations are very unlikely for at least some of lithium-rich objects in our sample, suggesting a new mechanism that enhances lithium during the low-mass star evolution.

Clustering Genes of Common Evolutionary History

PubMed Central

Gori, Kevin; Suchan, Tomasz; Alvarez, Nadir; Goldman, Nick; Dessimoz, Christophe

2016-01-01

Phylogenetic inference can potentially result in a more accurate tree using data from multiple loci. However, if the loci are incongruent—due to events such as incomplete lineage sorting or horizontal gene transfer—it can be misleading to infer a single tree. To address this, many previous contributions have taken a mechanistic approach, by modeling specific processes. Alternatively, one can cluster loci without assuming how these incongruencies might arise. Such “process-agnostic” approaches typically infer a tree for each locus and cluster these. There are, however, many possible combinations of tree distance and clustering methods; their comparative performance in the context of tree incongruence is largely unknown. Furthermore, because standard model selection criteria such as AIC cannot be applied to problems with a variable number of topologies, the issue of inferring the optimal number of clusters is poorly understood. Here, we perform a large-scale simulation study of phylogenetic distances and clustering methods to infer loci of common evolutionary history. We observe that the best-performing combinations are distances accounting for branch lengths followed by spectral clustering or Ward’s method. We also introduce two statistical tests to infer the optimal number of clusters and show that they strongly outperform the silhouette criterion, a general-purpose heuristic. We illustrate the usefulness of the approach by 1) identifying errors in a previous phylogenetic analysis of yeast species and 2) identifying topological incongruence among newly sequenced loci of the globeflower fly genus Chiastocheta. We release treeCl, a new program to cluster genes of common evolutionary history (http://git.io/treeCl). PMID:26893301

Evolutionary adaptations: theoretical and practical implications for visual ergonomics.

PubMed

Fostervold, Knut Inge; Watten, Reidulf G; Volden, Frode

2014-01-01

The literature discussing visual ergonomics often mention that human vision is adapted to light emitted by the sun. However, theoretical and practical implications of this viewpoint is seldom discussed or taken into account. The paper discusses some of the main theoretical implications of an evolutionary approach to visual ergonomics. Based on interactional theory and ideas from ecological psychology an evolutionary stress model is proposed as a theoretical framework for future research in ergonomics and human factors. The model stresses the importance of developing work environments that fits with our evolutionary adaptations. In accordance with evolutionary psychology, the environment of evolutionary adaptedness (EEA) and evolutionarily-novel environments (EN) are used as key concepts. Using work with visual display units (VDU) as an example, the paper discusses how this knowledge can be utilized in an ergonomic analysis of risk factors in the work environment. The paper emphasises the importance of incorporating evolutionary theory in the field of ergonomics. Further, the paper encourages scientific practices that further our understanding of any phenomena beyond the borders of traditional proximal explanations.

Incorporating evolutionary processes into population viability models.

PubMed

Pierson, Jennifer C; Beissinger, Steven R; Bragg, Jason G; Coates, David J; Oostermeijer, J Gerard B; Sunnucks, Paul; Schumaker, Nathan H; Trotter, Meredith V; Young, Andrew G

2015-06-01

We examined how ecological and evolutionary (eco-evo) processes in population dynamics could be better integrated into population viability analysis (PVA). Complementary advances in computation and population genomics can be combined into an eco-evo PVA to offer powerful new approaches to understand the influence of evolutionary processes on population persistence. We developed the mechanistic basis of an eco-evo PVA using individual-based models with individual-level genotype tracking and dynamic genotype-phenotype mapping to model emergent population-level effects, such as local adaptation and genetic rescue. We then outline how genomics can allow or improve parameter estimation for PVA models by providing genotypic information at large numbers of loci for neutral and functional genome regions. As climate change and other threatening processes increase in rate and scale, eco-evo PVAs will become essential research tools to evaluate the effects of adaptive potential, evolutionary rescue, and locally adapted traits on persistence. © 2014 Society for Conservation Biology.

On the evolution of specialization with a mechanistic underpinning in structured metapopulations.

PubMed

Nurmi, Tuomas; Parvinen, Kalle

2008-03-01

We analyze the evolution of specialization in resource utilization in a discrete-time metapopulation model using the adaptive dynamics approach. The local dynamics in the metapopulation are based on the Beverton-Holt model with mechanistic underpinnings. The consumer faces a trade-off in the abilities to consume two resources that are spatially heterogeneously distributed to patches that are prone to local catastrophes. We explore the factors favoring the spread of generalist or specialist strategies. Increasing fecundity or decreasing catastrophe probability favors the spread of the generalist strategy and increasing environmental heterogeneity enlarges the parameter domain where the evolutionary branching is possible. When there are no catastrophes, increasing emigration diminishes the parameter domain where the evolutionary branching may occur. Otherwise, the effect of emigration on evolutionary dynamics is non-monotonous: both small and large values of emigration probability favor the spread of the specialist strategies whereas the parameter domain where evolutionary branching may occur is largest when the emigration probability has intermediate values. We compare how different forms of spatial heterogeneity and different models of local growth affect the evolutionary dynamics. We show that even small changes in the resource dynamics may have outstanding evolutionary effects to the consumers.

Modelling galaxy spectra in presence of interstellar dust - III. From nearby galaxies to the distant Universe

NASA Astrophysics Data System (ADS)

Cassarà, L. P.; Piovan, L.; Chiosi, C.

2015-07-01

Improving upon the standard evolutionary population synthesis technique, we present spectrophotometric models of galaxies with morphology going from spherical structures to discs, properly accounting for the effect of dust in the interstellar medium (ISM). The models contain three main physical components: the diffuse ISM made of gas and dust, the complexes of molecular clouds where active star formation occurs, and stars of any age and chemical composition. These models are based on robust evolutionary chemical description providing the total amount of gas and stars present at any age, and matching the properties of galaxies of different morphological types. We have considered the results obtained by Piovan et al. for the properties of the ISM, and those by Cassarà et al. for the spectral energy distribution (SED) of single stellar populations, both in presence of dust, to model the integral SEDs of galaxies of different morphological types, going from pure bulges to discs passing through a number of composite systems with different combinations of the two components. The first part of the paper is devoted to recall the technical details of the method and the basic relations driving the interaction between the physical components of the galaxy. Then, the main parameters are examined and their effects on the SED of three prototype galaxies are highlighted. The theoretical SEDs nicely match the observational ones both for nearby galaxies and those at high redshift.

Genome-wide investigation reveals high evolutionary rates in annual model plants.

PubMed

Yue, Jia-Xing; Li, Jinpeng; Wang, Dan; Araki, Hitoshi; Tian, Dacheng; Yang, Sihai

2010-11-09

Rates of molecular evolution vary widely among species. While significant deviations from molecular clock have been found in many taxa, effects of life histories on molecular evolution are not fully understood. In plants, annual/perennial life history traits have long been suspected to influence the evolutionary rates at the molecular level. To date, however, the number of genes investigated on this subject is limited and the conclusions are mixed. To evaluate the possible heterogeneity in evolutionary rates between annual and perennial plants at the genomic level, we investigated 85 nuclear housekeeping genes, 10 non-housekeeping families, and 34 chloroplast genes using the genomic data from model plants including Arabidopsis thaliana and Medicago truncatula for annuals and grape (Vitis vinifera) and popular (Populus trichocarpa) for perennials. According to the cross-comparisons among the four species, 74-82% of the nuclear genes and 71-97% of the chloroplast genes suggested higher rates of molecular evolution in the two annuals than those in the two perennials. The significant heterogeneity in evolutionary rate between annuals and perennials was consistently found both in nonsynonymous sites and synonymous sites. While a linear correlation of evolutionary rates in orthologous genes between species was observed in nonsynonymous sites, the correlation was weak or invisible in synonymous sites. This tendency was clearer in nuclear genes than in chloroplast genes, in which the overall evolutionary rate was small. The slope of the regression line was consistently lower than unity, further confirming the higher evolutionary rate in annuals at the genomic level. The higher evolutionary rate in annuals than in perennials appears to be a universal phenomenon both in nuclear and chloroplast genomes in the four dicot model plants we investigated. Therefore, such heterogeneity in evolutionary rate should result from factors that have genome-wide influence, most likely those associated with annual/perennial life history. Although we acknowledge current limitations of this kind of study, mainly due to a small sample size available and a distant taxonomic relationship of the model organisms, our results indicate that the genome-wide survey is a promising approach toward further understanding of the mechanism determining the molecular evolutionary rate at the genomic level.

Langley's CSI evolutionary model: Phase O

NASA Technical Reports Server (NTRS)

Belvin, W. Keith; Elliott, Kenny B.; Horta, Lucas G.; Bailey, Jim P.; Bruner, Anne M.; Sulla, Jeffrey L.; Won, John; Ugoletti, Roberto M.

1991-01-01

A testbed for the development of Controls Structures Interaction (CSI) technology to improve space science platform pointing is described. The evolutionary nature of the testbed will permit the study of global line-of-sight pointing in phases 0 and 1, whereas, multipayload pointing systems will be studied beginning with phase 2. The design, capabilities, and typical dynamic behavior of the phase 0 version of the CSI evolutionary model (CEM) is documented for investigator both internal and external to NASA. The model description includes line-of-sight pointing measurement, testbed structure, actuators, sensors, and real time computers, as well as finite element and state space models of major components.

Two-Drug Antimicrobial Chemotherapy: A Mathematical Model and Experiments with Mycobacterium marinum

PubMed Central

Ankomah, Peter; Levin, Bruce R.

2012-01-01

Multi-drug therapy is the standard-of-care treatment for tuberculosis. Despite this, virtually all studies of the pharmacodynamics (PD) of mycobacterial drugs employed for the design of treatment protocols are restricted to single agents. In this report, mathematical models and in vitro experiments with Mycobacterium marinum and five antimycobacterial drugs are used to quantitatively evaluate the pharmaco-, population and evolutionary dynamics of two-drug antimicrobial chemotherapy regimes. Time kill experiments with single and pairs of antibiotics are used to estimate the parameters and evaluate the fit of Hill-function-based PD models. While Hill functions provide excellent fits for the PD of each single antibiotic studied, rifampin, amikacin, clarithromycin, streptomycin and moxifloxacin, two-drug Hill functions with a unique interaction parameter cannot account for the PD of any of the 10 pairs of these drugs. If we assume two antibiotic-concentration dependent functions for the interaction parameter, one for sub-MIC and one for supra-MIC drug concentrations, the modified biphasic Hill function provides a reasonably good fit for the PD of all 10 pairs of antibiotics studied. Monte Carlo simulations of antibiotic treatment based on the experimentally-determined PD functions are used to evaluate the potential microbiological efficacy (rate of clearance) and evolutionary consequences (likelihood of generating multi-drug resistance) of these different drug combinations as well as their sensitivity to different forms of non-adherence to therapy. These two-drug treatment simulations predict varying outcomes for the different pairs of antibiotics with respect to the aforementioned measures of efficacy. In summary, Hill functions with biphasic drug-drug interaction terms provide accurate analogs for the PD of pairs of antibiotics and M. marinum. The models, experimental protocols and computer simulations used in this study can be applied to evaluate the potential microbiological and evolutionary efficacy of two-drug therapy for any bactericidal antibiotics and bacteria that can be cultured in vitro. PMID:22253599

Disruptive selection as a driver of evolutionary branching and caste evolution in social insects.

PubMed

Planqué, R; Powell, S; Franks, N R; van den Berg, J B

2016-11-01

Theory suggests that evolutionary branching via disruptive selection may be a relatively common and powerful force driving phenotypic divergence. Here, we extend this theory to social insects, which have novel social axes of phenotypic diversification. Our model, built around turtle ant (Cephalotes) biology, is used to explore whether disruptive selection can drive the evolutionary branching of divergent colony phenotypes that include a novel soldier caste. Soldier evolution is a recurrent theme in social insect diversification that is exemplified in the turtle ants. We show that phenotypic mutants can gain competitive advantages that induce disruptive selection and subsequent branching. A soldier caste does not generally appear before branching, but can evolve from subsequent competition. The soldier caste then evolves in association with specialized resource preferences that maximize defensive performance. Overall, our model indicates that resource specialization may occur in the absence of morphological specialization, but that when morphological specialization evolves, it is always in association with resource specialization. This evolutionary coupling of ecological and morphological specialization is consistent with recent empirical evidence, but contrary to predictions of classical caste theory. Our model provides a new theoretical understanding of the ecology of caste evolution that explicitly considers the process of adaptive phenotypic divergence and diversification. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Complex Genotype by Environment interactions and changing genetic architectures across thermal environments in the Australian field cricket, Teleogryllus oceanicus

PubMed Central

2011-01-01

Background Biologists studying adaptation under sexual selection have spent considerable effort assessing the relative importance of two groups of models, which hinge on the idea that females gain indirect benefits via mate discrimination. These are the good genes and genetic compatibility models. Quantitative genetic studies have advanced our understanding of these models by enabling assessment of whether the genetic architectures underlying focal phenotypes are congruent with either model. In this context, good genes models require underlying additive genetic variance, while compatibility models require non-additive variance. Currently, we know very little about how the expression of genotypes comprised of distinct parental haplotypes, or how levels and types of genetic variance underlying key phenotypes, change across environments. Such knowledge is important, however, because genotype-environment interactions can have major implications on the potential for evolutionary responses to selection. Results We used a full diallel breeding design to screen for complex genotype-environment interactions, and genetic architectures underlying key morphological traits, across two thermal environments (the lab standard 27°C, and the cooler 23°C) in the Australian field cricket, Teleogryllus oceanicus. In males, complex three-way interactions between sire and dam parental haplotypes and the rearing environment accounted for up to 23 per cent of the scaled phenotypic variance in the traits we measured (body mass, pronotum width and testes mass), and each trait harboured significant additive genetic variance in the standard temperature (27°C) only. In females, these three-way interactions were less important, with interactions between the paternal haplotype and rearing environment accounting for about ten per cent of the phenotypic variance (in body mass, pronotum width and ovary mass). Of the female traits measured, only ovary mass for crickets reared at the cooler temperature (23°C), exhibited significant levels of additive genetic variance. Conclusions Our results show that the genetics underlying phenotypic expression can be complex, context-dependent and different in each of the sexes. We discuss the implications of these results, particularly in terms of the evolutionary processes that hinge on good and compatible genes models. PMID:21791118

On the preservation of cooperation in two-strategy games with nonlocal interactions.

PubMed

Aydogmus, Ozgur; Zhou, Wen; Kang, Yun

2017-03-01

Nonlocal interactions such as spatial interaction are ubiquitous in nature and may alter the equilibrium in evolutionary dynamics. Models including nonlocal spatial interactions can provide a further understanding on the preservation and emergence of cooperation in evolutionary dynamics. In this paper, we consider a variety of two-strategy evolutionary spatial games with nonlocal interactions based on an integro-differential replicator equation. By defining the invasion speed and minimal traveling wave speed for the derived model, we study the effects of the payoffs, the selection pressure and the spatial parameter on the preservation of cooperation. One of our most interesting findings is that, for the Prisoners Dilemma games in which the defection is the only evolutionary stable strategy for unstructured populations, analyses on its asymptotic speed of propagation suggest that, in contrast with spatially homogeneous games, the cooperators can invade the habitat under proper conditions. Other two-strategy evolutionary spatial games are also explored. Both our theoretical and numerical studies show that the nonlocal spatial interaction favors diversity in strategies in a population and is able to preserve cooperation in a competing environment. A real data application in a virus mutation study echoes our theoretical observations. In addition, we compare the results of our model to the partial differential equation approach to demonstrate the importance of including non-local interaction component in evolutionary game models. Copyright © 2016 Elsevier Inc. All rights reserved.

Evolutionary perspectives on clonal reproduction in vertebrate animals

PubMed Central

Avise, John C.

2015-01-01

A synopsis is provided of different expressions of whole-animal vertebrate clonality (asexual organismal-level reproduction), both in the laboratory and in nature. For vertebrate taxa, such clonal phenomena include the following: human-mediated cloning via artificial nuclear transfer; intergenerational clonality in nature via parthenogenesis and gynogenesis; intergenerational hemiclonality via hybridogenesis and kleptogenesis; intragenerational clonality via polyembryony; and what in effect qualifies as clonal replication via self-fertilization and intense inbreeding by simultaneous hermaphrodites. Each of these clonal or quasi-clonal mechanisms is described, and its evolutionary genetic ramifications are addressed. By affording an atypical vantage on standard vertebrate reproduction, clonality offers fresh perspectives on the evolutionary and ecological significance of recombination-derived genetic variety. PMID:26195735

On the evolution of the standard amino-acid alphabet

PubMed Central

Lu, Yi; Freeland, Stephen

2006-01-01

Although one standard amino-acid 'alphabet' is used by most organisms on Earth, the evolutionary cause(s) and significance of this alphabet remain elusive. Fresh insights into the origin of the alphabet are now emerging from disciplines as diverse as astrobiology, biochemical engineering and bioinformatics. PMID:16515719

Incorporating Eco-Evolutionary Processes into Population Models:Design and Applications

EPA Science Inventory

Eco-evolutionary population models are powerful new tools for exploring howevolutionary processes influence plant and animal population dynamics andvice-versa. The need to manage for climate change and other dynamicdisturbance regimes is creating a demand for the incorporation of...

Modeling the stylized facts in finance through simple nonlinear adaptive systems

PubMed Central

Hommes, Cars H.

2002-01-01

Recent work on adaptive systems for modeling financial markets is discussed. Financial markets are viewed as evolutionary systems between different, competing trading strategies. Agents are boundedly rational in the sense that they tend to follow strategies that have performed well, according to realized profits or accumulated wealth, in the recent past. Simple technical trading rules may survive evolutionary competition in a heterogeneous world where prices and beliefs co-evolve over time. Evolutionary models can explain important stylized facts, such as fat tails, clustered volatility, and long memory, of real financial series. PMID:12011401

Neuronal boost to evolutionary dynamics.

PubMed

de Vladar, Harold P; Szathmáry, Eörs

2015-12-06

Standard evolutionary dynamics is limited by the constraints of the genetic system. A central message of evolutionary neurodynamics is that evolutionary dynamics in the brain can happen in a neuronal niche in real time, despite the fact that neurons do not reproduce. We show that Hebbian learning and structural synaptic plasticity broaden the capacity for informational replication and guided variability provided a neuronally plausible mechanism of replication is in place. The synergy between learning and selection is more efficient than the equivalent search by mutation selection. We also consider asymmetric landscapes and show that the learning weights become correlated with the fitness gradient. That is, the neuronal complexes learn the local properties of the fitness landscape, resulting in the generation of variability directed towards the direction of fitness increase, as if mutations in a genetic pool were drawn such that they would increase reproductive success. Evolution might thus be more efficient within evolved brains than among organisms out in the wild.

To Cooperate or Not to Cooperate: Why Behavioural Mechanisms Matter

PubMed Central

2016-01-01

Mutualistic cooperation often requires multiple individuals to behave in a coordinated fashion. Hence, while the evolutionary stability of mutualistic cooperation poses no particular theoretical difficulty, its evolutionary emergence faces a chicken and egg problem: an individual cannot benefit from cooperating unless other individuals already do so. Here, we use evolutionary robotic simulations to study the consequences of this problem for the evolution of cooperation. In contrast with standard game-theoretic results, we find that the transition from solitary to cooperative strategies is very unlikely, whether interacting individuals are genetically related (cooperation evolves in 20% of all simulations) or unrelated (only 3% of all simulations). We also observe that successful cooperation between individuals requires the evolution of a specific and rather complex behaviour. This behavioural complexity creates a large fitness valley between solitary and cooperative strategies, making the evolutionary transition difficult. These results reveal the need for research on biological mechanisms which may facilitate this transition. PMID:27148874

New Holographic Chaplygin Gas Model of Dark Energy

NASA Astrophysics Data System (ADS)

Malekjani, M.; Khodam-Mohammadi, A.

In this work, we investigate the holographic dark energy model with a new infrared cutoff (new HDE model), proposed by Granda and Oliveros. Using this new definition for the infrared cutoff, we establish the correspondence between the new HDE model and the standard Chaplygin gas (SCG), generalized Chaplygin gas (GCG) and modified Chaplygin gas (MCG) scalar field models in a nonflat universe. The potential and dynamics for these scalar field models, which describe the accelerated expansion of the universe, are reconstructed. According to the evolutionary behavior of the new HDE model, we derive the same form of dynamics and potential for the different SCG, GCG and MCG models. We also calculate the squared sound speed of the new HDE model as well as the SCG, GCG and MCG models, and investigate the new HDE Chaplygin gas models from the viewpoint of linear perturbation theory. In addition, all results in the nonflat universe are discussed in the limiting case of the flat universe, i.e. k = 0.

SOME USES OF MODELS OF QUANTITATIVE GENETIC SELECTION IN SOCIAL SCIENCE.

PubMed

Weight, Michael D; Harpending, Henry

2017-01-01

The theory of selection of quantitative traits is widely used in evolutionary biology, agriculture and other related fields. The fundamental model known as the breeder's equation is simple, robust over short time scales, and it is often possible to estimate plausible parameters. In this paper it is suggested that the results of this model provide useful yardsticks for the description of social traits and the evaluation of transmission models. The differences on a standard personality test between samples of Old Order Amish and Indiana rural young men from the same county and the decline of homicide in Medieval Europe are used as illustrative examples of the overall approach. It is shown that the decline of homicide is unremarkable under a threshold model while the differences between rural Amish and non-Amish young men are too large to be a plausible outcome of simple genetic selection in which assortative mating by affiliation is equivalent to truncation selection.

A Generative Angular Model of Protein Structure Evolution

PubMed Central

Golden, Michael; García-Portugués, Eduardo; Sørensen, Michael; Mardia, Kanti V.; Hamelryck, Thomas; Hein, Jotun

2017-01-01

Abstract Recently described stochastic models of protein evolution have demonstrated that the inclusion of structural information in addition to amino acid sequences leads to a more reliable estimation of evolutionary parameters. We present a generative, evolutionary model of protein structure and sequence that is valid on a local length scale. The model concerns the local dependencies between sequence and structure evolution in a pair of homologous proteins. The evolutionary trajectory between the two structures in the protein pair is treated as a random walk in dihedral angle space, which is modeled using a novel angular diffusion process on the two-dimensional torus. Coupling sequence and structure evolution in our model allows for modeling both “smooth” conformational changes and “catastrophic” conformational jumps, conditioned on the amino acid changes. The model has interpretable parameters and is comparatively more realistic than previous stochastic models, providing new insights into the relationship between sequence and structure evolution. For example, using the trained model we were able to identify an apparent sequence–structure evolutionary motif present in a large number of homologous protein pairs. The generative nature of our model enables us to evaluate its validity and its ability to simulate aspects of protein evolution conditioned on an amino acid sequence, a related amino acid sequence, a related structure or any combination thereof. PMID:28453724

Absolute dimensions of eclipsing binaries. XXVI.. Setting a new standard: Masses, radii, and abundances for the F-type systems AD Bootis VZ Hydrae, and WZ Ophiuchi

NASA Astrophysics Data System (ADS)

Clausen, J. V.; Torres, G.; Bruntt, H.; Andersen, J.; Nordström, B.; Stefanik, R. P.; Latham, D. W.; Southworth, J.

2008-09-01

Context: Accurate mass, radius, and abundance determinations from binaries provide important information on stellar evolution, fundamental to central fields in modern astrophysics and cosmology. Aims: We aim to determine absolute dimensions and abundances for the three F-type main-sequence detached eclipsing binaries AD Boo, VZ Hya, and WZ Oph and to perform a detailed comparison with results from recent stellar evolutionary models. Methods: uvby light curves and uvbyβ standard photometry were obtained with the Strömgren Automatic Telescope at ESO, La Silla, radial velocity observations at CfA facilities, and supplementary high-resolution spectra with ESO's FEROS spectrograph. State-of-the-art methods were applied for the analyses: the EBOP and Wilson-Devinney binary models, two-dimensional cross-correlation and disentangling, and the VWA abundance analysis tool. Results: Masses and radii that are precise to 0.5-0.7% and 0.4-0.9%, respectively, have been established for the components, which span the ranges of 1.1 to 1.4 M⊙ and 1.1 to 1.6 R⊙. The [Fe/H] abundances are from -0.27 to +0.10, with uncertainties between 0.07 and 0.15 dex. We find indications of a slight α-element overabundance of [α/Fe] ˜ + 0.1 for WZ Oph. The secondary component of AD Boo and both components of WZ Oph appear to be slightly active. Yale-Yonsai and Victoria-Regina evolutionary models fit the components of AD Boo and VZ Hya almost equally well, assuming coeval formation, at ages of about 1.75/1.50 Gyr (AD Boo) and 1.25/1.00 Gyr (VZ Hya). BaSTI models, however, predict somewhat different ages for the primary and secondary components. For WZ Oph, the models from all three grids are significantly hotter than observed. A low He content, decreased envelope convection coupled with surface activity, and/or higher interstellar absorption would remove the discrepancy, but its cause has not been definitively identified. Conclusions: We have demonstrated the power of testing and comparing recent stellar evolutionary models using eclipsing binaries, provided their abundances are known. The strongest limitations and challenges are set by T_eff and interstellar absorption determinations, and by their effects on and correlation with abundance results. Based on observations carried out at the Strömgren Automatic Telescope (SAT) and the 1.5 m and 2.2 m telescopes at ESO, La Silla, Chile (62.L-0284, 63.H-0080, 71.D-0554); the 1.5 m Wyeth reflector at the Oak Ridge Observatory, Harvard, Massachusetts, USA; the 1.5-m Tillinghast reflector and the Multiple Mirror Telescope at the F. L. Whipple Observatory, Mt. Hopkins, Arizona.

Mouse Models as Predictors of Human Responses: Evolutionary Medicine.

PubMed

Uhl, Elizabeth W; Warner, Natalie J

Mice offer a number of advantages and are extensively used to model human diseases and drug responses. Selective breeding and genetic manipulation of mice have made many different genotypes and phenotypes available for research. However, in many cases, mouse models have failed to be predictive. Important sources of the prediction problem have been the failure to consider the evolutionary basis for species differences, especially in drug metabolism, and disease definitions that do not reflect the complexity of gene expression underlying disease phenotypes. Incorporating evolutionary insights into mouse models allow for unique opportunities to characterize the effects of diet, different gene expression profiles, and microbiomics underlying human drug responses and disease phenotypes.

Evolutionary grinding model for nanometric control of surface roughness for aspheric optical surfaces.

PubMed

Han, Jeong-Yeol; Kim, Sug-Whan; Han, Inwoo; Kim, Geon-Hee

2008-03-17

A new evolutionary grinding process model has been developed for nanometric control of material removal from an aspheric surface of Zerodur substrate. The model incorporates novel control features such as i) a growing database; ii) an evolving, multi-variable regression equation; and iii) an adaptive correction factor for target surface roughness (Ra) for the next machine run. This process model demonstrated a unique evolutionary controllability of machining performance resulting in the final grinding accuracy (i.e. averaged difference between target and measured surface roughness) of -0.2+/-2.3(sigma) nm Ra over seven trial machine runs for the target surface roughness ranging from 115 nm to 64 nm Ra.

ConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromolecules

PubMed Central

Ashkenazy, Haim; Abadi, Shiran; Martz, Eric; Chay, Ofer; Mayrose, Itay; Pupko, Tal; Ben-Tal, Nir

2016-01-01

The degree of evolutionary conservation of an amino acid in a protein or a nucleic acid in DNA/RNA reflects a balance between its natural tendency to mutate and the overall need to retain the structural integrity and function of the macromolecule. The ConSurf web server (http://consurf.tau.ac.il), established over 15 years ago, analyses the evolutionary pattern of the amino/nucleic acids of the macromolecule to reveal regions that are important for structure and/or function. Starting from a query sequence or structure, the server automatically collects homologues, infers their multiple sequence alignment and reconstructs a phylogenetic tree that reflects their evolutionary relations. These data are then used, within a probabilistic framework, to estimate the evolutionary rates of each sequence position. Here we introduce several new features into ConSurf, including automatic selection of the best evolutionary model used to infer the rates, the ability to homology-model query proteins, prediction of the secondary structure of query RNA molecules from sequence, the ability to view the biological assembly of a query (in addition to the single chain), mapping of the conservation grades onto 2D RNA models and an advanced view of the phylogenetic tree that enables interactively rerunning ConSurf with the taxa of a sub-tree. PMID:27166375

Adaptive evolutionary walks require neutral intermediates in RNA fitness landscapes.

PubMed

Rendel, Mark D

2011-01-01

In RNA fitness landscapes with interconnected networks of neutral mutations, neutral precursor mutations can play an important role in facilitating the accessibility of epistatic adaptive mutant combinations. I use an exhaustively surveyed fitness landscape model based on short sequence RNA genotypes (and their secondary structure phenotypes) to calculate the minimum rate at which mutants initially appearing as neutral are incorporated into an adaptive evolutionary walk. I show first, that incorporating neutral mutations significantly increases the number of point mutations in a given evolutionary walk when compared to estimates from previous adaptive walk models. Second, that incorporating neutral mutants into such a walk significantly increases the final fitness encountered on that walk - indeed evolutionary walks including neutral steps often reach the global optimum in this model. Third, and perhaps most importantly, evolutionary paths of this kind are often extremely winding in their nature and have the potential to undergo multiple mutations at a given sequence position within a single walk; the potential of these winding paths to mislead phylogenetic reconstruction is briefly considered. Copyright © 2010 Elsevier Inc. All rights reserved.

Evolutionary genetics of plant adaptation.

PubMed

Anderson, Jill T; Willis, John H; Mitchell-Olds, Thomas

2011-07-01

Plants provide unique opportunities to study the mechanistic basis and evolutionary processes of adaptation to diverse environmental conditions. Complementary laboratory and field experiments are important for testing hypotheses reflecting long-term ecological and evolutionary history. For example, these approaches can infer whether local adaptation results from genetic tradeoffs (antagonistic pleiotropy), where native alleles are best adapted to local conditions, or if local adaptation is caused by conditional neutrality at many loci, where alleles show fitness differences in one environment, but not in a contrasting environment. Ecological genetics in natural populations of perennial or outcrossing plants can also differ substantially from model systems. In this review of the evolutionary genetics of plant adaptation, we emphasize the importance of field studies for understanding the evolutionary dynamics of model and nonmodel systems, highlight a key life history trait (flowering time) and discuss emerging conservation issues. Copyright © 2011 Elsevier Ltd. All rights reserved.

Applying ecological and evolutionary theory to cancer: a long and winding road.

PubMed

Thomas, Frédéric; Fisher, Daniel; Fort, Philippe; Marie, Jean-Pierre; Daoust, Simon; Roche, Benjamin; Grunau, Christoph; Cosseau, Céline; Mitta, Guillaume; Baghdiguian, Stephen; Rousset, François; Lassus, Patrice; Assenat, Eric; Grégoire, Damien; Missé, Dorothée; Lorz, Alexander; Billy, Frédérique; Vainchenker, William; Delhommeau, François; Koscielny, Serge; Itzykson, Raphael; Tang, Ruoping; Fava, Fanny; Ballesta, Annabelle; Lepoutre, Thomas; Krasinska, Liliana; Dulic, Vjekoslav; Raynaud, Peggy; Blache, Philippe; Quittau-Prevostel, Corinne; Vignal, Emmanuel; Trauchessec, Hélène; Perthame, Benoit; Clairambault, Jean; Volpert, Vitali; Solary, Eric; Hibner, Urszula; Hochberg, Michael E

2013-01-01

Since the mid 1970s, cancer has been described as a process of Darwinian evolution, with somatic cellular selection and evolution being the fundamental processes leading to malignancy and its many manifestations (neoangiogenesis, evasion of the immune system, metastasis, and resistance to therapies). Historically, little attention has been placed on applications of evolutionary biology to understanding and controlling neoplastic progression and to prevent therapeutic failures. This is now beginning to change, and there is a growing international interest in the interface between cancer and evolutionary biology. The objective of this introduction is first to describe the basic ideas and concepts linking evolutionary biology to cancer. We then present four major fronts where the evolutionary perspective is most developed, namely laboratory and clinical models, mathematical models, databases, and techniques and assays. Finally, we discuss several of the most promising challenges and future prospects in this interdisciplinary research direction in the war against cancer.

Computational intelligence approaches for pattern discovery in biological systems.

PubMed

Fogel, Gary B

2008-07-01

Biology, chemistry and medicine are faced by tremendous challenges caused by an overwhelming amount of data and the need for rapid interpretation. Computational intelligence (CI) approaches such as artificial neural networks, fuzzy systems and evolutionary computation are being used with increasing frequency to contend with this problem, in light of noise, non-linearity and temporal dynamics in the data. Such methods can be used to develop robust models of processes either on their own or in combination with standard statistical approaches. This is especially true for database mining, where modeling is a key component of scientific understanding. This review provides an introduction to current CI methods, their application to biological problems, and concludes with a commentary about the anticipated impact of these approaches in bioinformatics.

Evolutionary Maps: A New Model for the Analysis of Conceptual Development, with Application to the Diurnal Cycle

ERIC Educational Resources Information Center

Navarro, Manuel

2014-01-01

This paper presents a model of how children generate concrete concepts from perception through processes of differentiation and integration. The model informs the design of a novel methodology ("evolutionary maps" or "emaps"), whose implementation on certain domains unfolds the web of itineraries that children may follow in the…

An alternative approach for neural network evolution with a genetic algorithm: crossover by combinatorial optimization.

PubMed

García-Pedrajas, Nicolás; Ortiz-Boyer, Domingo; Hervás-Martínez, César

2006-05-01

In this work we present a new approach to crossover operator in the genetic evolution of neural networks. The most widely used evolutionary computation paradigm for neural network evolution is evolutionary programming. This paradigm is usually preferred due to the problems caused by the application of crossover to neural network evolution. However, crossover is the most innovative operator within the field of evolutionary computation. One of the most notorious problems with the application of crossover to neural networks is known as the permutation problem. This problem occurs due to the fact that the same network can be represented in a genetic coding by many different codifications. Our approach modifies the standard crossover operator taking into account the special features of the individuals to be mated. We present a new model for mating individuals that considers the structure of the hidden layer and redefines the crossover operator. As each hidden node represents a non-linear projection of the input variables, we approach the crossover as a problem on combinatorial optimization. We can formulate the problem as the extraction of a subset of near-optimal projections to create the hidden layer of the new network. This new approach is compared to a classical crossover in 25 real-world problems with an excellent performance. Moreover, the networks obtained are much smaller than those obtained with classical crossover operator.

Y fuse? Sex chromosome fusions in fishes and reptiles.

PubMed

Pennell, Matthew W; Kirkpatrick, Mark; Otto, Sarah P; Vamosi, Jana C; Peichel, Catherine L; Valenzuela, Nicole; Kitano, Jun

2015-05-01

Chromosomal fusion plays a recurring role in the evolution of adaptations and reproductive isolation among species, yet little is known of the evolutionary drivers of chromosomal fusions. Because sex chromosomes (X and Y in male heterogametic systems, Z and W in female heterogametic systems) differ in their selective, mutational, and demographic environments, those differences provide a unique opportunity to dissect the evolutionary forces that drive chromosomal fusions. We estimate the rate at which fusions between sex chromosomes and autosomes become established across the phylogenies of both fishes and squamate reptiles. Both the incidence among extant species and the establishment rate of Y-autosome fusions is much higher than for X-autosome, Z-autosome, or W-autosome fusions. Using population genetic models, we show that this pattern cannot be reconciled with many standard explanations for the spread of fusions. In particular, direct selection acting on fusions or sexually antagonistic selection cannot, on their own, account for the predominance of Y-autosome fusions. The most plausible explanation for the observed data seems to be (a) that fusions are slightly deleterious, and (b) that the mutation rate is male-biased or the reproductive sex ratio is female-biased. We identify other combinations of evolutionary forces that might in principle account for the data although they appear less likely. Our results shed light on the processes that drive structural changes throughout the genome.

Y Fuse? Sex Chromosome Fusions in Fishes and Reptiles

PubMed Central

Vamosi, Jana C.; Peichel, Catherine L.; Valenzuela, Nicole; Kitano, Jun

2015-01-01

Chromosomal fusion plays a recurring role in the evolution of adaptations and reproductive isolation among species, yet little is known of the evolutionary drivers of chromosomal fusions. Because sex chromosomes (X and Y in male heterogametic systems, Z and W in female heterogametic systems) differ in their selective, mutational, and demographic environments, those differences provide a unique opportunity to dissect the evolutionary forces that drive chromosomal fusions. We estimate the rate at which fusions between sex chromosomes and autosomes become established across the phylogenies of both fishes and squamate reptiles. Both the incidence among extant species and the establishment rate of Y-autosome fusions is much higher than for X-autosome, Z-autosome, or W-autosome fusions. Using population genetic models, we show that this pattern cannot be reconciled with many standard explanations for the spread of fusions. In particular, direct selection acting on fusions or sexually antagonistic selection cannot, on their own, account for the predominance of Y-autosome fusions. The most plausible explanation for the observed data seems to be (a) that fusions are slightly deleterious, and (b) that the mutation rate is male-biased or the reproductive sex ratio is female-biased. We identify other combinations of evolutionary forces that might in principle account for the data although they appear less likely. Our results shed light on the processes that drive structural changes throughout the genome. PMID:25993542

Asymmetric Evolutionary Games.

PubMed

McAvoy, Alex; Hauert, Christoph

2015-08-01

Evolutionary game theory is a powerful framework for studying evolution in populations of interacting individuals. A common assumption in evolutionary game theory is that interactions are symmetric, which means that the players are distinguished by only their strategies. In nature, however, the microscopic interactions between players are nearly always asymmetric due to environmental effects, differing baseline characteristics, and other possible sources of heterogeneity. To model these phenomena, we introduce into evolutionary game theory two broad classes of asymmetric interactions: ecological and genotypic. Ecological asymmetry results from variation in the environments of the players, while genotypic asymmetry is a consequence of the players having differing baseline genotypes. We develop a theory of these forms of asymmetry for games in structured populations and use the classical social dilemmas, the Prisoner's Dilemma and the Snowdrift Game, for illustrations. Interestingly, asymmetric games reveal essential differences between models of genetic evolution based on reproduction and models of cultural evolution based on imitation that are not apparent in symmetric games.

Individual-based modeling of ecological and evolutionary processes

USGS Publications Warehouse

DeAngelis, Donald L.; Mooij, Wolf M.

2005-01-01

Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential-equation and difference-equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis for IBMs by describing five major types of individual variation in IBMs: spatial, ontogenetic, phenotypic, cognitive, and genetic. IBMs are now used in almost all subfields of ecology and evolutionary biology. We map those subfields and look more closely at selected key papers on fish recruitment, forest dynamics, sympatric speciation, metapopulation dynamics, maintenance of diversity, and species conservation. Theorists are currently divided on whether IBMs represent only a practical tool for extending classical theory to more complex situations, or whether individual-based theory represents a radically new research program. We feel that the tension between these two poles of thinking can be a source of creativity in ecology and evolutionary theory.

Evolutionary Creation: Moving beyond the Evolution versus Creation Debate

ERIC Educational Resources Information Center

Lamoureux, Denis O.

2010-01-01

Evolutionary creation offers a conservative Christian approach to evolution. It explores biblical faith and evolutionary science through a Two Divine Books model and proposes a complementary relationship between Scripture and science. The Book of God's Words discloses the spiritual character of the world, while the Book of God's Works reveals the…

Scheduling Earth Observing Fleets Using Evolutionary Algorithms: Problem Description and Approach

NASA Technical Reports Server (NTRS)

Globus, Al; Crawford, James; Lohn, Jason; Morris, Robert; Clancy, Daniel (Technical Monitor)

2002-01-01

We describe work in progress concerning multi-instrument, multi-satellite scheduling. Most, although not all, Earth observing instruments currently in orbit are unique. In the relatively near future, however, we expect to see fleets of Earth observing spacecraft, many carrying nearly identical instruments. This presents a substantially new scheduling challenge. Inspired by successful commercial applications of evolutionary algorithms in scheduling domains, this paper presents work in progress regarding the use of evolutionary algorithms to solve a set of Earth observing related model problems. Both the model problems and the software are described. Since the larger problems will require substantial computation and evolutionary algorithms are embarrassingly parallel, we discuss our parallelization techniques using dedicated and cycle-scavenged workstations.

Evolution and literary theory.

PubMed

Carroll, J

1995-06-01

Presupposing that all knowledge is the study of a unitary order of nature, the author maintains that the study of literature should be included within the larger field of evolutionary theory. He outlines four elementary concepts in evolutionary theory, and he argues that these concepts should regulate our understanding of literature. On the basis of these concepts, he repudiates the antirealist and irrationalist views that, under the aegis of "poststructuralism," have dominated academic literary studies for the past two decades. He examines the linkage between poststructuralism and standard social science, and he speculates about the ideological and disciplinary motives that have hitherto impeded evolutionary study in both the social sciences and the humanities. Finally, he distinguishes literature from science and argues that literary criticism integrates elements of both.

Evolutionary Connectionism: Algorithmic Principles Underlying the Evolution of Biological Organisation in Evo-Devo, Evo-Eco and Evolutionary Transitions.

PubMed

Watson, Richard A; Mills, Rob; Buckley, C L; Kouvaris, Kostas; Jackson, Adam; Powers, Simon T; Cox, Chris; Tudge, Simon; Davies, Adam; Kounios, Loizos; Power, Daniel

2016-01-01

The mechanisms of variation, selection and inheritance, on which evolution by natural selection depends, are not fixed over evolutionary time. Current evolutionary biology is increasingly focussed on understanding how the evolution of developmental organisations modifies the distribution of phenotypic variation, the evolution of ecological relationships modifies the selective environment, and the evolution of reproductive relationships modifies the heritability of the evolutionary unit. The major transitions in evolution, in particular, involve radical changes in developmental, ecological and reproductive organisations that instantiate variation, selection and inheritance at a higher level of biological organisation. However, current evolutionary theory is poorly equipped to describe how these organisations change over evolutionary time and especially how that results in adaptive complexes at successive scales of organisation (the key problem is that evolution is self-referential, i.e. the products of evolution change the parameters of the evolutionary process). Here we first reinterpret the central open questions in these domains from a perspective that emphasises the common underlying themes. We then synthesise the findings from a developing body of work that is building a new theoretical approach to these questions by converting well-understood theory and results from models of cognitive learning. Specifically, connectionist models of memory and learning demonstrate how simple incremental mechanisms, adjusting the relationships between individually-simple components, can produce organisations that exhibit complex system-level behaviours and improve the adaptive capabilities of the system. We use the term "evolutionary connectionism" to recognise that, by functionally equivalent processes, natural selection acting on the relationships within and between evolutionary entities can result in organisations that produce complex system-level behaviours in evolutionary systems and modify the adaptive capabilities of natural selection over time. We review the evidence supporting the functional equivalences between the domains of learning and of evolution, and discuss the potential for this to resolve conceptual problems in our understanding of the evolution of developmental, ecological and reproductive organisations and, in particular, the major evolutionary transitions.

What does convergent evolution mean? The interpretation of convergence and its implications in the search for limits to evolution

PubMed Central

Stayton, C. Tristan

2015-01-01

Convergent evolution is central to the study of life's evolutionary history. Researchers have documented the ubiquity of convergence and have used this ubiquity to make inferences about the nature of limits on evolution. However, these inferences are compromised by unrecognized inconsistencies in the definitions, measures, significance tests and inferred causes of convergent evolution. I review these inconsistencies and provide recommendations for standardizing studies of convergence. A fundamental dichotomy exists between definitions that describe convergence as a pattern and those that describe it as a pattern caused by a particular process. When this distinction is not acknowledged it becomes easy to assume that a pattern of convergence indicates that a particular process has been active, leading researchers away from alternative explanations. Convergence is not necessarily caused by limits to evolution, either adaptation or constraint; even substantial amounts of convergent evolution can be generated by a purely stochastic process. In the absence of null models, long lists of examples of convergent events do not necessarily indicate that convergence or any evolutionary process is ubiquitous throughout the history of life. Pattern-based definitions of convergence, coupled with quantitative measures and null models, must be applied before drawing inferences regarding large-scale limits to evolution. PMID:26640646

Multivariate Phylogenetic Comparative Methods: Evaluations, Comparisons, and Recommendations.

PubMed

Adams, Dean C; Collyer, Michael L

2018-01-01

Recent years have seen increased interest in phylogenetic comparative analyses of multivariate data sets, but to date the varied proposed approaches have not been extensively examined. Here we review the mathematical properties required of any multivariate method, and specifically evaluate existing multivariate phylogenetic comparative methods in this context. Phylogenetic comparative methods based on the full multivariate likelihood are robust to levels of covariation among trait dimensions and are insensitive to the orientation of the data set, but display increasing model misspecification as the number of trait dimensions increases. This is because the expected evolutionary covariance matrix (V) used in the likelihood calculations becomes more ill-conditioned as trait dimensionality increases, and as evolutionary models become more complex. Thus, these approaches are only appropriate for data sets with few traits and many species. Methods that summarize patterns across trait dimensions treated separately (e.g., SURFACE) incorrectly assume independence among trait dimensions, resulting in nearly a 100% model misspecification rate. Methods using pairwise composite likelihood are highly sensitive to levels of trait covariation, the orientation of the data set, and the number of trait dimensions. The consequences of these debilitating deficiencies are that a user can arrive at differing statistical conclusions, and therefore biological inferences, simply from a dataspace rotation, like principal component analysis. By contrast, algebraic generalizations of the standard phylogenetic comparative toolkit that use the trace of covariance matrices are insensitive to levels of trait covariation, the number of trait dimensions, and the orientation of the data set. Further, when appropriate permutation tests are used, these approaches display acceptable Type I error and statistical power. We conclude that methods summarizing information across trait dimensions, as well as pairwise composite likelihood methods should be avoided, whereas algebraic generalizations of the phylogenetic comparative toolkit provide a useful means of assessing macroevolutionary patterns in multivariate data. Finally, we discuss areas in which multivariate phylogenetic comparative methods are still in need of future development; namely highly multivariate Ornstein-Uhlenbeck models and approaches for multivariate evolutionary model comparisons. © The Author(s) 2017. Published by Oxford University Press on behalf of the Systematic Biology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Determining Selection across Heterogeneous Landscapes: A Perturbation-Based Method and Its Application to Modeling Evolution in Space.

PubMed

Wickman, Jonas; Diehl, Sebastian; Blasius, Bernd; Klausmeier, Christopher A; Ryabov, Alexey B; Brännström, Åke

2017-04-01

Spatial structure can decisively influence the way evolutionary processes unfold. To date, several methods have been used to study evolution in spatial systems, including population genetics, quantitative genetics, moment-closure approximations, and individual-based models. Here we extend the study of spatial evolutionary dynamics to eco-evolutionary models based on reaction-diffusion equations and adaptive dynamics. Specifically, we derive expressions for the strength of directional and stabilizing/disruptive selection that apply both in continuous space and to metacommunities with symmetrical dispersal between patches. For directional selection on a quantitative trait, this yields a way to integrate local directional selection across space and determine whether the trait value will increase or decrease. The robustness of this prediction is validated against quantitative genetics. For stabilizing/disruptive selection, we show that spatial heterogeneity always contributes to disruptive selection and hence always promotes evolutionary branching. The expression for directional selection is numerically very efficient and hence lends itself to simulation studies of evolutionary community assembly. We illustrate the application and utility of the expressions for this purpose with two examples of the evolution of resource utilization. Finally, we outline the domain of applicability of reaction-diffusion equations as a modeling framework and discuss their limitations.

Estimating true evolutionary distances under the DCJ model.

PubMed

Lin, Yu; Moret, Bernard M E

2008-07-01

Modern techniques can yield the ordering and strandedness of genes on each chromosome of a genome; such data already exists for hundreds of organisms. The evolutionary mechanisms through which the set of the genes of an organism is altered and reordered are of great interest to systematists, evolutionary biologists, comparative genomicists and biomedical researchers. Perhaps the most basic concept in this area is that of evolutionary distance between two genomes: under a given model of genomic evolution, how many events most likely took place to account for the difference between the two genomes? We present a method to estimate the true evolutionary distance between two genomes under the 'double-cut-and-join' (DCJ) model of genome rearrangement, a model under which a single multichromosomal operation accounts for all genomic rearrangement events: inversion, transposition, translocation, block interchange and chromosomal fusion and fission. Our method relies on a simple structural characterization of a genome pair and is both analytically and computationally tractable. We provide analytical results to describe the asymptotic behavior of genomes under the DCJ model, as well as experimental results on a wide variety of genome structures to exemplify the very high accuracy (and low variance) of our estimator. Our results provide a tool for accurate phylogenetic reconstruction from multichromosomal gene rearrangement data as well as a theoretical basis for refinements of the DCJ model to account for biological constraints. All of our software is available in source form under GPL at http://lcbb.epfl.ch.

Emergence of evolutionary cycles in size-structured food webs.

PubMed

Ritterskamp, Daniel; Bearup, Daniel; Blasius, Bernd

2016-11-07

The interplay of population dynamics and evolution within ecological communities has been of long-standing interest for ecologists and can give rise to evolutionary cycles, e.g. taxon cycles. Evolutionary cycling was intensely studied in small communities with asymmetric competition; the latter drives the evolutionary processes. Here we demonstrate that evolutionary cycling arises naturally in larger communities if trophic interactions are present, since these are intrinsically asymmetric. To investigate the evolutionary dynamics of a trophic community, we use an allometric food web model. We find that evolutionary cycles emerge naturally for a large parameter ranges. The origin of the evolutionary dynamics is an intrinsic asymmetry in the feeding kernel which creates an evolutionary ratchet, driving species towards larger bodysize. We reveal different kinds of cycles: single morph cycles, and coevolutionary and mixed cycling of complete food webs. The latter refers to the case where each trophic level can have different evolutionary dynamics. We discuss the generality of our findings and conclude that ongoing evolution in food webs may be more frequent than commonly believed. Copyright © 2016 Elsevier Ltd. All rights reserved.

An improved approximate-Bayesian model-choice method for estimating shared evolutionary history

PubMed Central

2014-01-01

Background To understand biological diversification, it is important to account for large-scale processes that affect the evolutionary history of groups of co-distributed populations of organisms. Such events predict temporally clustered divergences times, a pattern that can be estimated using genetic data from co-distributed species. I introduce a new approximate-Bayesian method for comparative phylogeographical model-choice that estimates the temporal distribution of divergences across taxa from multi-locus DNA sequence data. The model is an extension of that implemented in msBayes. Results By reparameterizing the model, introducing more flexible priors on demographic and divergence-time parameters, and implementing a non-parametric Dirichlet-process prior over divergence models, I improved the robustness, accuracy, and power of the method for estimating shared evolutionary history across taxa. Conclusions The results demonstrate the improved performance of the new method is due to (1) more appropriate priors on divergence-time and demographic parameters that avoid prohibitively small marginal likelihoods for models with more divergence events, and (2) the Dirichlet-process providing a flexible prior on divergence histories that does not strongly disfavor models with intermediate numbers of divergence events. The new method yields more robust estimates of posterior uncertainty, and thus greatly reduces the tendency to incorrectly estimate models of shared evolutionary history with strong support. PMID:24992937

A constraint-based evolutionary learning approach to the expectation maximization for optimal estimation of the hidden Markov model for speech signal modeling.

PubMed

Huda, Shamsul; Yearwood, John; Togneri, Roberto

2009-02-01

This paper attempts to overcome the tendency of the expectation-maximization (EM) algorithm to locate a local rather than global maximum when applied to estimate the hidden Markov model (HMM) parameters in speech signal modeling. We propose a hybrid algorithm for estimation of the HMM in automatic speech recognition (ASR) using a constraint-based evolutionary algorithm (EA) and EM, the CEL-EM. The novelty of our hybrid algorithm (CEL-EM) is that it is applicable for estimation of the constraint-based models with many constraints and large numbers of parameters (which use EM) like HMM. Two constraint-based versions of the CEL-EM with different fusion strategies have been proposed using a constraint-based EA and the EM for better estimation of HMM in ASR. The first one uses a traditional constraint-handling mechanism of EA. The other version transforms a constrained optimization problem into an unconstrained problem using Lagrange multipliers. Fusion strategies for the CEL-EM use a staged-fusion approach where EM has been plugged with the EA periodically after the execution of EA for a specific period of time to maintain the global sampling capabilities of EA in the hybrid algorithm. A variable initialization approach (VIA) has been proposed using a variable segmentation to provide a better initialization for EA in the CEL-EM. Experimental results on the TIMIT speech corpus show that CEL-EM obtains higher recognition accuracies than the traditional EM algorithm as well as a top-standard EM (VIA-EM, constructed by applying the VIA to EM).

Determination of Fundamental Properties of an M31 Globular Cluster from Main-Sequence Photometry

NASA Astrophysics Data System (ADS)

Ma, Jun; Wu, Zhenyu; Wang, Song; Fan, Zhou; Zhou, Xu; Wu, Jianghua; Jiang, Zhaoji; Chen, Jiansheng

2010-10-01

M31 globular cluster B379 is the first extragalactic cluster whose age was determined by main-sequence photometry. In the main-sequence photometric method, the age of a cluster is obtained by fitting its color-magnitude diagram (CMD) with stellar evolutionary models. However, different stellar evolutionary models use different parameters of stellar evolution, such as range of stellar masses, different opacities and equations of state, and different recipes, and so on. So, it is interesting to check whether different stellar evolutionary models can give consistent results for the same cluster. Brown et al. constrained the age of B379 by comparing its CMD with isochrones of the 2006 VandenBerg models. Using SSP models of Bruzual & Charlot and its multiphotometry, ZMa et al. independently determined the age of B379, which is in good agreement with the determination of Brown et al. The models of Bruzual & Charlot are calculated based on the Padova evolutionary tracks. It is necessary to check whether the age of B379 as determined based on the Padova evolutionary tracks is in agreement with the determination of Brown et al.. In this article, we redetermine the age of B379 using isochrones of the Padova stellar evolutionary models. In addition, the metal abundance, the distance modulus, and the reddening value for B379 are reported. The results obtained are consistent with the previous determinations, which include the age obtained by Brown et al. This article thus confirms the consistency of the age scale of B379 between the Padova isochrones and the 2006 VandenBerg isochrones; i.e., the comparison between the results of Brown et al. and Ma et al. is meaningful. The results reported in this article of values found for B379 are: metallicity [M/H] = log(Z/Z ⊙) = -0.325, age τ = 11.0 ± 1.5 Gyr, reddening E(B - V) = 0.08, and distance modulus (m - M)0 = 24.44 ± 0.10.

More efficient evolutionary strategies for model calibration with watershed model for demonstration

NASA Astrophysics Data System (ADS)

Baggett, J. S.; Skahill, B. E.

2008-12-01

Evolutionary strategies allow automatic calibration of more complex models than traditional gradient based approaches, but they are more computationally intensive. We present several efficiency enhancements for evolution strategies, many of which are not new, but when combined have been shown to dramatically decrease the number of model runs required for calibration of synthetic problems. To reduce the number of expensive model runs we employ a surrogate objective function for an adaptively determined fraction of the population at each generation (Kern et al., 2006). We demonstrate improvements to the adaptive ranking strategy that increase its efficiency while sacrificing little reliability and further reduce the number of model runs required in densely sampled parts of parameter space. Furthermore, we include a gradient individual in each generation that is usually not selected when the search is in a global phase or when the derivatives are poorly approximated, but when selected near a smooth local minimum can dramatically increase convergence speed (Tahk et al., 2007). Finally, the selection of the gradient individual is used to adapt the size of the population near local minima. We show, by incorporating these enhancements into the Covariance Matrix Adaption Evolution Strategy (CMAES; Hansen, 2006), that their synergetic effect is greater than their individual parts. This hybrid evolutionary strategy exploits smooth structure when it is present but degrades to an ordinary evolutionary strategy, at worst, if smoothness is not present. Calibration of 2D-3D synthetic models with the modified CMAES requires approximately 10%-25% of the model runs of ordinary CMAES. Preliminary demonstration of this hybrid strategy will be shown for watershed model calibration problems. Hansen, N. (2006). The CMA Evolution Strategy: A Comparing Review. In J.A. Lozano, P. Larrañga, I. Inza and E. Bengoetxea (Eds.). Towards a new evolutionary computation. Advances in estimation of distribution algorithms. pp. 75-102, Springer Kern, S., N. Hansen and P. Koumoutsakos (2006). Local Meta-Models for Optimization Using Evolution Strategies. In Ninth International Conference on Parallel Problem Solving from Nature PPSN IX, Proceedings, pp.939-948, Berlin: Springer. Tahk, M., Woo, H., and Park. M, (2007). A hybrid optimization of evolutionary and gradient search. Engineering Optimization, (39), 87-104.

A Critical Assessment of Ages Derived Using Pre-Main-Sequence Isochrones in Colour-Magnitude Diagrams

NASA Astrophysics Data System (ADS)

Bell, Cameron P. M.

2012-11-01

In this thesis a critical assessment of the ages derived using theoretical pre-main-sequence (pre-MS) stellar evolutionary models is presented by comparing the predictions to the low-mass pre-MS population of 14 young star-forming regions (SFRs) in colour-magnitude diagrams (CMDs). Deriving pre-MS ages requires precise distances and estimates of the reddening. Therefore, the main-sequence (MS) members of the SFRs have been used to derive a self-consistent set of statistically robust ages, distances and reddenings with associated uncertainties using a maximum-likelihood fitting statistic and MS evolutionary models. A photometric method for de-reddening individual stars - known as the Q-method - in regions where the extinction is spatially variable has been updated and is presented. The effects of both the model dependency and the SFR composition on these derived parameters are also discussed. The problem of calibrating photometric observations of red pre-MS stars is examined and it is shown that using observations of MS stars to transform the data into a standard photometric system can introduce significant errors in the position of the pre-MS locus in CMD space. Hence, it is crucial that precise photometric studies - especially of pre-MS objects - be carried out in the natural photometric system of the observations. This therefore requires a robust model of the system responses for the instrument used, and thus the calculated responses for the Wide-Field Camera on the Isaac Newton Telescope are presented. These system responses have been tested using standard star observations and have been shown to be a good representation of the photometric system. A benchmark test for the pre-MS evolutionary models is performed by comparing them to a set of well-calibrated CMDs of the Pleiades in the wavelength regime 0.4-2.5 μm. The masses predicted by these models are also tested against dynamical masses using a sample of MS binaries by calculating the system magnitude in a given photometric bandpass. This analysis shows that for Teff ≤ 4000 K the models systematically overestimate the flux by a factor of 2 at 0.5 μm, though this decreases with wavelength, becoming negligible at 2.2 μm. Thus before the pre-MS models are used to derive ages, a recalibration of the models is performed by incorporating an empirical colour-Teff relation and bolometric corrections based on the Ks-band luminosity of Pleiades members, with theoretical corrections for the dependence on the surface gravity (log g). The recalibrated pre-MS model isochrones are used to derive ages from the pre-MS populations of the SFRs. These ages are then compared with the MS derivations, thus providing a powerful diagnostic tool with which to discriminate between the different pre-MS age scales that arise from a much stronger model dependency in the pre-MS regime. The revised ages assigned to each of the 14 SFRs are up to a factor two older than previous derivations, a result with wide-ranging implications, including that circumstellar discs survive longer and that the average Class II lifetime is greater than currently believed.

Philosophy and Sociology of Science Evolution and History

NASA Astrophysics Data System (ADS)

Rosen, Joe

The following sections are included: * Concrete Versus Abstract Theoretical Models * Introduction: concrete and abstract in kepler's contribution * Einstein's theory of gravitation and mach's principle * Unitary symmetry and the structure of hadrons * Conclusion * Dedication * Symmetry, Entropy and Complexity * Introduction * Symmetry Implies Abstraction and Loss of Information * Broken Symmetries - Imposed or Spontaneous * Symmetry, Order and Information * References * Cosmological Surrealism: More Than "Eternal Reality" Is Needed * Pythagoreanism in atomic, nuclear and particle physics * Introduction: Pythagoreanism as part of the Greek scientific world view — and the three questions I will tackle * Point 1: the impact of Gersonides and Crescas, two scientific anti-Aristotelian rebels * Point 2: Kepler's spheres to Bohr's orbits — Pythagoreanisms at last! * Point 3: Aristotle to Maupertuis, Emmy Noether, Schwinger * References * Paradigm Completion For Generalized Evolutionary Theory With Application To Epistemology * Evolution Fully Generalized * Entropy: Gravity as Model * Evolution and Entropy: Measures of Complexity * Extinctions and a Balanced Evolutionary Paradigm * The Evolution of Human Society - the Age of Information as example * High-Energy Physics and the World Wide Web * Twentieth Century Epistemology has Strong (de facto) Evolutionary Elements * The discoveries towards the beginning of the XXth Century * Summary and Conclusions * References * Evolutionary Epistemology and Invalidation * Introduction * Extinctions and A New Evolutionary Paradigm * Evolutionary Epistemology - Active Mutations * Evolutionary Epistemology: Invalidation as An Extinction * References

Ecological and evolutionary consequences of niche construction for its agent.

PubMed

Kylafis, Grigoris; Loreau, Michel

2008-10-01

Niche construction can generate ecological and evolutionary feedbacks that have been underinvestigated so far. We present an eco-evolutionary model that incorporates the process of niche construction to reveal its effects on the ecology and evolution of the niche-constructing agent. We consider a simple plant-soil nutrient ecosystem in which plants have the ability to increase the input of inorganic nutrient as an example of positive niche construction. On an ecological time scale, the model shows that niche construction allows the persistence of plants under infertile soil conditions that would otherwise lead to their extinction. This expansion of plants' niche, however, requires a high enough rate of niche construction and a high enough initial plant biomass to fuel the positive ecological feedback between plants and their soil environment. On an evolutionary time scale, we consider that the rates of niche construction and nutrient uptake coevolve in plants while a trade-off constrains their values. Different evolutionary outcomes are possible depending on the shape of the trade-off. We show that niche construction results in an evolutionary feedback between plants and their soil environment such that plants partially regulate soil nutrient content. The direct benefit accruing to plants, however, plays a crucial role in the evolutionary advantage of niche construction.

Evolución de estrellas de varias masas: Cálculo de los pulsos térmicos

NASA Astrophysics Data System (ADS)

Panei, J. A.; Althaus, L. G.; Benvenuto, O. G.; Serenelli, A. M.

We present stellar evolutionary calculations for models with stellar masses ranging from 1.2 to 20 Msolar. We follow the calculations from the Main Sequence up to the phase of thermal pulses. The emphasis is placed mainly on the analysis of the behaviour of a 5 Msolar model. The evolutionary code is based on the Kippenhahn, Weigert, & Hofmeister (1967) method to compute stellar evolution. The structure and stellar evolution equations for the stellar interior are integrated using the standard Henyey method. The degree of superadiabaticity is computed from the mixing length theory of convection (Böhm - Vitense 1958). The equation of state we employed takes into account partial ionization, radiation pressure and relativistic degeneracy for electrons at finite temperature. Radiative opacities with metallicity Z=0.02 are taken from Rogers & Iglesias (1996). Conductive opacities for the low - density regime are from the fits of Iben (1975) to the calculations of Hubbard & Lampe (1969). For higher densities we use the results of Itoh et. al (1983). The molecular opacities are those of Alexander & Ferguson (1994). The different mechanisms of neutrino emission are also taken account. In particular, photo and pair neutrinos are from Itoh et al. (1989); plasma neutrinos from Itoh et al. (1989) and Bremsstrahlung from Itoh et al. (1992). Because the aim in this work has been to calculate the stages corresponding to the thermal pulses, particular attention has been devoted to the treatment of the numerical difficulties appearing in this kind of calculation. To this end, we solve the equations describing the structure and evolution of a star in terms of differences with respect to time, instead of iterating the value of the physical variables directly. This change has allowed us to calculate advanced evolutionary stages such as the thermal pulses. In this regard, we find that our models experiencies up to 10 thermal flashes.

Experimental evidence for the evolution of indirect genetic effects: changes in the interaction effect coefficient, psi (Psi), due to sexual selection.

PubMed

Chenoweth, Stephen F; Rundle, Howard D; Blows, Mark W

2010-06-01

Indirect genetics effects (IGEs)--when the genotype of one individual affects the phenotypic expression of a trait in another--may alter evolutionary trajectories beyond that predicted by standard quantitative genetic theory as a consequence of genotypic evolution of the social environment. For IGEs to occur, the trait of interest must respond to one or more indicator traits in interacting conspecifics. In quantitative genetic models of IGEs, these responses (reaction norms) are termed interaction effect coefficients and are represented by the parameter psi (Psi). The extent to which Psi exhibits genetic variation within a population, and may therefore itself evolve, is unknown. Using an experimental evolution approach, we provide evidence for a genetic basis to the phenotypic response caused by IGEs on sexual display traits in Drosophila serrata. We show that evolution of the response is affected by sexual but not natural selection when flies adapt to a novel environment. Our results indicate a further mechanism by which IGEs can alter evolutionary trajectories--the evolution of interaction effects themselves.

SLiM 2: Flexible, Interactive Forward Genetic Simulations.

PubMed

Haller, Benjamin C; Messer, Philipp W

2017-01-01

Modern population genomic datasets hold immense promise for revealing the evolutionary processes operating in natural populations, but a crucial prerequisite for this goal is the ability to model realistic evolutionary scenarios and predict their expected patterns in genomic data. To that end, we present SLiM 2: an evolutionary simulation framework that combines a powerful, fast engine for forward population genetic simulations with the capability of modeling a wide variety of complex evolutionary scenarios. SLiM achieves this flexibility through scriptability, which provides control over most aspects of the simulated evolutionary scenarios with a simple R-like scripting language called Eidos. An example SLiM simulation is presented to illustrate the power of this approach. SLiM 2 also includes a graphical user interface for simulation construction, interactive runtime control, and dynamic visualization of simulation output, facilitating easy and fast model development with quick prototyping and visual debugging. We conclude with a performance comparison between SLiM and two other popular forward genetic simulation packages. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A Tale of Four Stories: Soil Ecology, Theory, Evolution and the Publication System

PubMed Central

Barot, Sébastien; Blouin, Manuel; Fontaine, Sébastien; Jouquet, Pascal; Lata, Jean-Christophe; Mathieu, Jérôme

2007-01-01

Background Soil ecology has produced a huge corpus of results on relations between soil organisms, ecosystem processes controlled by these organisms and links between belowground and aboveground processes. However, some soil scientists think that soil ecology is short of modelling and evolutionary approaches and has developed too independently from general ecology. We have tested quantitatively these hypotheses through a bibliographic study (about 23000 articles) comparing soil ecology journals, generalist ecology journals, evolutionary ecology journals and theoretical ecology journals. Findings We have shown that soil ecology is not well represented in generalist ecology journals and that soil ecologists poorly use modelling and evolutionary approaches. Moreover, the articles published by a typical soil ecology journal (Soil Biology and Biochemistry) are cited by and cite low percentages of articles published in generalist ecology journals, evolutionary ecology journals and theoretical ecology journals. Conclusion This confirms our hypotheses and suggests that soil ecology would benefit from an effort towards modelling and evolutionary approaches. This effort should promote the building of a general conceptual framework for soil ecology and bridges between soil ecology and general ecology. We give some historical reasons for the parsimonious use of modelling and evolutionary approaches by soil ecologists. We finally suggest that a publication system that classifies journals according to their Impact Factors and their level of generality is probably inadequate to integrate “particularity” (empirical observations) and “generality” (general theories), which is the goal of all natural sciences. Such a system might also be particularly detrimental to the development of a science such as ecology that is intrinsically multidisciplinary. PMID:18043755

Adaptive landscape and functional diversity of Neotropical cichlids: implications for the ecology and evolution of Cichlinae (Cichlidae; Cichliformes).

PubMed

Arbour, J H; López-Fernández, H

2014-11-01

Morphological, lineage and ecological diversity can vary substantially even among closely related lineages. Factors that influence morphological diversification, especially in functionally relevant traits, can help to explain the modern distribution of disparity across phylogenies and communities. Multivariate axes of feeding functional morphology from 75 species of Neotropical cichlid and a stepwise-AIC algorithm were used to estimate the adaptive landscape of functional morphospace in Cichlinae. Adaptive landscape complexity and convergence, as well as the functional diversity of Cichlinae, were compared with expectations under null evolutionary models. Neotropical cichlid feeding function varied primarily between traits associated with ram feeding vs. suction feeding/biting and secondarily with oral jaw muscle size and pharyngeal crushing capacity. The number of changes in selective regimes and the amount of convergence between lineages was higher than expected under a null model of evolution, but convergence was not higher than expected under a similarly complex adaptive landscape. Functional disparity was compatible with an adaptive landscape model, whereas the distribution of evolutionary change through morphospace corresponded with a process of evolution towards a single adaptive peak. The continentally distributed Neotropical cichlids have evolved relatively rapidly towards a number of adaptive peaks in functional trait space. Selection in Cichlinae functional morphospace is more complex than expected under null evolutionary models. The complexity of selective constraints in feeding morphology has likely been a significant contributor to the diversity of feeding ecology in this clade. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Accurate quantification of within- and between-host HBV evolutionary rates requires explicit transmission chain modelling.

PubMed

Vrancken, Bram; Suchard, Marc A; Lemey, Philippe

2017-07-01

Analyses of virus evolution in known transmission chains have the potential to elucidate the impact of transmission dynamics on the viral evolutionary rate and its difference within and between hosts. Lin et al. (2015, Journal of Virology , 89/7: 3512-22) recently investigated the evolutionary history of hepatitis B virus in a transmission chain and postulated that the 'colonization-adaptation-transmission' model can explain the differential impact of transmission on synonymous and non-synonymous substitution rates. Here, we revisit this dataset using a full probabilistic Bayesian phylogenetic framework that adequately accounts for the non-independence of sequence data when estimating evolutionary parameters. Examination of the transmission chain data under a flexible coalescent prior reveals a general inconsistency between the estimated timings and clustering patterns and the known transmission history, highlighting the need to incorporate host transmission information in the analysis. Using an explicit genealogical transmission chain model, we find strong support for a transmission-associated decrease of the overall evolutionary rate. However, in contrast to the initially reported larger transmission effect on non-synonymous substitution rate, we find a similar decrease in both non-synonymous and synonymous substitution rates that cannot be adequately explained by the colonization-adaptation-transmission model. An alternative explanation may involve a transmission/establishment advantage of hepatitis B virus variants that have accumulated fewer within-host substitutions, perhaps by spending more time in the covalently closed circular DNA state between each round of viral replication. More generally, this study illustrates that ignoring phylogenetic relationships can lead to misleading evolutionary estimates.

Advances in computer simulation of genome evolution: toward more realistic evolutionary genomics analysis by approximate bayesian computation.

PubMed

Arenas, Miguel

2015-04-01

NGS technologies present a fast and cheap generation of genomic data. Nevertheless, ancestral genome inference is not so straightforward due to complex evolutionary processes acting on this material such as inversions, translocations, and other genome rearrangements that, in addition to their implicit complexity, can co-occur and confound ancestral inferences. Recently, models of genome evolution that accommodate such complex genomic events are emerging. This letter explores these novel evolutionary models and proposes their incorporation into robust statistical approaches based on computer simulations, such as approximate Bayesian computation, that may produce a more realistic evolutionary analysis of genomic data. Advantages and pitfalls in using these analytical methods are discussed. Potential applications of these ancestral genomic inferences are also pointed out.

How much can history constrain adaptive evolution? A real-time evolutionary approach of inversion polymorphisms in Drosophila subobscura.

PubMed

Fragata, I; Lopes-Cunha, M; Bárbaro, M; Kellen, B; Lima, M; Santos, M A; Faria, G S; Santos, M; Matos, M; Simões, P

2014-12-01

Chromosomal inversions are present in a wide range of animals and plants, having an important role in adaptation and speciation. Although empirical evidence of their adaptive value is abundant, the role of different processes underlying evolution of chromosomal polymorphisms is not fully understood. History and selection are likely to shape inversion polymorphism variation to an extent yet largely unknown. Here, we perform a real-time evolution study addressing the role of historical constraints and selection in the evolution of these polymorphisms. We founded laboratory populations of Drosophila subobscura derived from three locations along the European cline and followed the evolutionary dynamics of inversion polymorphisms throughout the first 40 generations. At the beginning, populations were highly differentiated and remained so throughout generations. We report evidence of positive selection for some inversions, variable between foundations. Signs of negative selection were more frequent, in particular for most cold-climate standard inversions across the three foundations. We found that previously observed convergence at the phenotypic level in these populations was not associated with convergence in inversion frequencies. In conclusion, our study shows that selection has shaped the evolutionary dynamics of inversion frequencies, but doing so within the constraints imposed by previous history. Both history and selection are therefore fundamental to predict the evolutionary potential of different populations to respond to global environmental changes. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

An Effective Hybrid Evolutionary Algorithm for Solving the Numerical Optimization Problems

NASA Astrophysics Data System (ADS)

Qian, Xiaohong; Wang, Xumei; Su, Yonghong; He, Liu

2018-04-01

There are many different algorithms for solving complex optimization problems. Each algorithm has been applied successfully in solving some optimization problems, but not efficiently in other problems. In this paper the Cauchy mutation and the multi-parent hybrid operator are combined to propose a hybrid evolutionary algorithm based on the communication (Mixed Evolutionary Algorithm based on Communication), hereinafter referred to as CMEA. The basic idea of the CMEA algorithm is that the initial population is divided into two subpopulations. Cauchy mutation operators and multiple paternal crossover operators are used to perform two subpopulations parallelly to evolve recursively until the downtime conditions are met. While subpopulation is reorganized, the individual is exchanged together with information. The algorithm flow is given and the performance of the algorithm is compared using a number of standard test functions. Simulation results have shown that this algorithm converges significantly faster than FEP (Fast Evolutionary Programming) algorithm, has good performance in global convergence and stability and is superior to other compared algorithms.

Neuronal boost to evolutionary dynamics

PubMed Central

de Vladar, Harold P.; Szathmáry, Eörs

2015-01-01

Standard evolutionary dynamics is limited by the constraints of the genetic system. A central message of evolutionary neurodynamics is that evolutionary dynamics in the brain can happen in a neuronal niche in real time, despite the fact that neurons do not reproduce. We show that Hebbian learning and structural synaptic plasticity broaden the capacity for informational replication and guided variability provided a neuronally plausible mechanism of replication is in place. The synergy between learning and selection is more efficient than the equivalent search by mutation selection. We also consider asymmetric landscapes and show that the learning weights become correlated with the fitness gradient. That is, the neuronal complexes learn the local properties of the fitness landscape, resulting in the generation of variability directed towards the direction of fitness increase, as if mutations in a genetic pool were drawn such that they would increase reproductive success. Evolution might thus be more efficient within evolved brains than among organisms out in the wild. PMID:26640653

The ConSurf-DB: pre-calculated evolutionary conservation profiles of protein structures.

PubMed

Goldenberg, Ofir; Erez, Elana; Nimrod, Guy; Ben-Tal, Nir

2009-01-01

ConSurf-DB is a repository for evolutionary conservation analysis of the proteins of known structures in the Protein Data Bank (PDB). Sequence homologues of each of the PDB entries were collected and aligned using standard methods. The evolutionary conservation of each amino acid position in the alignment was calculated using the Rate4Site algorithm, implemented in the ConSurf web server. The algorithm takes into account the phylogenetic relations between the aligned proteins and the stochastic nature of the evolutionary process explicitly. Rate4Site assigns a conservation level for each position in the multiple sequence alignment using an empirical Bayesian inference. Visual inspection of the conservation patterns on the 3D structure often enables the identification of key residues that comprise the functionally important regions of the protein. The repository is updated with the latest PDB entries on a monthly basis and will be rebuilt annually. ConSurf-DB is available online at http://consurfdb.tau.ac.il/

The ConSurf-DB: pre-calculated evolutionary conservation profiles of protein structures

PubMed Central

Goldenberg, Ofir; Erez, Elana; Nimrod, Guy; Ben-Tal, Nir

2009-01-01

ConSurf-DB is a repository for evolutionary conservation analysis of the proteins of known structures in the Protein Data Bank (PDB). Sequence homologues of each of the PDB entries were collected and aligned using standard methods. The evolutionary conservation of each amino acid position in the alignment was calculated using the Rate4Site algorithm, implemented in the ConSurf web server. The algorithm takes into account the phylogenetic relations between the aligned proteins and the stochastic nature of the evolutionary process explicitly. Rate4Site assigns a conservation level for each position in the multiple sequence alignment using an empirical Bayesian inference. Visual inspection of the conservation patterns on the 3D structure often enables the identification of key residues that comprise the functionally important regions of the protein. The repository is updated with the latest PDB entries on a monthly basis and will be rebuilt annually. ConSurf-DB is available online at http://consurfdb.tau.ac.il/ PMID:18971256

Evolution of dispersal and life history interact to drive accelerating spread of an invasive species.

PubMed

Perkins, T Alex; Phillips, Benjamin L; Baskett, Marissa L; Hastings, Alan

2013-08-01

Populations on the edge of an expanding range are subject to unique evolutionary pressures acting on their life-history and dispersal traits. Empirical evidence and theory suggest that traits there can evolve rapidly enough to interact with ecological dynamics, potentially giving rise to accelerating spread. Nevertheless, which of several evolutionary mechanisms drive this interaction between evolution and spread remains an open question. We propose an integrated theoretical framework for partitioning the contributions of different evolutionary mechanisms to accelerating spread, and we apply this model to invasive cane toads in northern Australia. In doing so, we identify a previously unrecognised evolutionary process that involves an interaction between life-history and dispersal evolution during range shift. In roughly equal parts, life-history evolution, dispersal evolution and their interaction led to a doubling of distance spread by cane toads in our model, highlighting the potential importance of multiple evolutionary processes in the dynamics of range expansion. © 2013 John Wiley & Sons Ltd/CNRS.

Mathematics and evolutionary biology make bioinformatics education comprehensible.

PubMed

Jungck, John R; Weisstein, Anton E

2013-09-01

The patterns of variation within a molecular sequence data set result from the interplay between population genetic, molecular evolutionary and macroevolutionary processes-the standard purview of evolutionary biologists. Elucidating these patterns, particularly for large data sets, requires an understanding of the structure, assumptions and limitations of the algorithms used by bioinformatics software-the domain of mathematicians and computer scientists. As a result, bioinformatics often suffers a 'two-culture' problem because of the lack of broad overlapping expertise between these two groups. Collaboration among specialists in different fields has greatly mitigated this problem among active bioinformaticians. However, science education researchers report that much of bioinformatics education does little to bridge the cultural divide, the curriculum too focused on solving narrow problems (e.g. interpreting pre-built phylogenetic trees) rather than on exploring broader ones (e.g. exploring alternative phylogenetic strategies for different kinds of data sets). Herein, we present an introduction to the mathematics of tree enumeration, tree construction, split decomposition and sequence alignment. We also introduce off-line downloadable software tools developed by the BioQUEST Curriculum Consortium to help students learn how to interpret and critically evaluate the results of standard bioinformatics analyses.

Mathematics and evolutionary biology make bioinformatics education comprehensible

PubMed Central

Weisstein, Anton E.

2013-01-01

The patterns of variation within a molecular sequence data set result from the interplay between population genetic, molecular evolutionary and macroevolutionary processes—the standard purview of evolutionary biologists. Elucidating these patterns, particularly for large data sets, requires an understanding of the structure, assumptions and limitations of the algorithms used by bioinformatics software—the domain of mathematicians and computer scientists. As a result, bioinformatics often suffers a ‘two-culture’ problem because of the lack of broad overlapping expertise between these two groups. Collaboration among specialists in different fields has greatly mitigated this problem among active bioinformaticians. However, science education researchers report that much of bioinformatics education does little to bridge the cultural divide, the curriculum too focused on solving narrow problems (e.g. interpreting pre-built phylogenetic trees) rather than on exploring broader ones (e.g. exploring alternative phylogenetic strategies for different kinds of data sets). Herein, we present an introduction to the mathematics of tree enumeration, tree construction, split decomposition and sequence alignment. We also introduce off-line downloadable software tools developed by the BioQUEST Curriculum Consortium to help students learn how to interpret and critically evaluate the results of standard bioinformatics analyses. PMID:23821621

Agency, Values, and Well-Being: A Human Development Model

ERIC Educational Resources Information Center

Welzel, Christian; Inglehart, Ronald

2010-01-01

This paper argues that feelings of agency are linked to human well-being through a sequence of adaptive mechanisms that promote human development, once existential conditions become permissive. In the first part, we elaborate on the evolutionary logic of this model and outline why an evolutionary perspective is helpful to understand changes in…

An Examination of the Impact of Harsh Parenting Contexts on Children's Adaptation within an Evolutionary Framework

ERIC Educational Resources Information Center

Sturge-Apple, Melissa L.; Davies, Patrick T.; Martin, Meredith J.; Cicchetti, Dante; Hentges, Rochelle F.

2012-01-01

The current study tests whether propositions set forth in an evolutionary model of temperament (Korte, Koolhaas, Wingfield, & McEwen, 2005) may enhance our understanding of children's differential susceptibility to unsupportive and harsh caregiving practices. Guided by this model, we examined whether children's behavioral strategies for coping…

Understanding of evolutionary genomics of invasive species of rice

USDA-ARS?s Scientific Manuscript database

Red rice is an aggressive, weedy form of cultivated rice (Oryza sativa) that infests crop fields and is a primary factor limiting rice productivity in the U.S. and worldwide. As the weedy relative of a genomic model species, red rice is a model for understanding the genetic and evolutionary mechani...

When should we expect early bursts of trait evolution in comparative data? Predictions from an evolutionary food web model.

PubMed

Ingram, T; Harmon, L J; Shurin, J B

2012-09-01

Conceptual models of adaptive radiation predict that competitive interactions among species will result in an early burst of speciation and trait evolution followed by a slowdown in diversification rates. Empirical studies often show early accumulation of lineages in phylogenetic trees, but usually fail to detect early bursts of phenotypic evolution. We use an evolutionary simulation model to assemble food webs through adaptive radiation, and examine patterns in the resulting phylogenetic trees and species' traits (body size and trophic position). We find that when foraging trade-offs result in food webs where all species occupy integer trophic levels, lineage diversity and trait disparity are concentrated early in the tree, consistent with the early burst model. In contrast, in food webs in which many omnivorous species feed at multiple trophic levels, high levels of turnover of species' identities and traits tend to eliminate the early burst signal. These results suggest testable predictions about how the niche structure of ecological communities may be reflected by macroevolutionary patterns. © 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.

The evolutionary language game: an orthogonal approach.

PubMed

Lenaerts, Tom; Jansen, Bart; Tuyls, Karl; De Vylder, Bart

2005-08-21

Evolutionary game dynamics have been proposed as a mathematical framework for the cultural evolution of language and more specifically the evolution of vocabulary. This article discusses a model that is mutually exclusive in its underlying principals with some previously suggested models. The model describes how individuals in a population culturally acquire a vocabulary by actively participating in the acquisition process instead of passively observing and communicate through peer-to-peer interactions instead of vertical parent-offspring relations. Concretely, a notion of social/cultural learning called the naming game is first abstracted using learning theory. This abstraction defines the required cultural transmission mechanism for an evolutionary process. Second, the derived transmission system is expressed in terms of the well-known selection-mutation model defined in the context of evolutionary dynamics. In this way, the analogy between social learning and evolution at the level of meaning-word associations is made explicit. Although only horizontal and oblique transmission structures will be considered, extensions to vertical structures over different genetic generations can easily be incorporated. We provide a number of simplified experiments to clarify our reasoning.

Evolutionary systems biology: historical and philosophical perspectives on an emerging synthesis.

PubMed

O'Malley, Maureen A

2012-01-01

Systems biology (SB) is at least a decade old now and maturing rapidly. A more recent field, evolutionary systems biology (ESB), is in the process of further developing system-level approaches through the expansion of their explanatory and potentially predictive scope. This chapter will outline the varieties of ESB existing today by tracing the diverse roots and fusions that make up this integrative project. My approach is philosophical and historical. As well as examining the recent origins of ESB, I will reflect on its central features and the different clusters of research it comprises. In its broadest interpretation, ESB consists of five overlapping approaches: comparative and correlational ESB; network architecture ESB; network property ESB; population genetics ESB; and finally, standard evolutionary questions answered with SB methods. After outlining each approach with examples, I will examine some strong general claims about ESB, particularly that it can be viewed as the next step toward a fuller modern synthesis of evolutionary biology (EB), and that it is also the way forward for evolutionary and systems medicine. I will conclude with a discussion of whether the emerging field of ESB has the capacity to combine an even broader scope of research aims and efforts than it presently does.

Evolutionary and plastic responses to climate change in terrestrial plant populations

PubMed Central

Franks, Steven J; Weber, Jennifer J; Aitken, Sally N

2014-01-01

As climate change progresses, we are observing widespread changes in phenotypes in many plant populations. Whether these phenotypic changes are directly caused by climate change, and whether they result from phenotypic plasticity or evolution, are active areas of investigation. Here, we review terrestrial plant studies addressing these questions. Plastic and evolutionary responses to climate change are clearly occurring. Of the 38 studies that met our criteria for inclusion, all found plastic or evolutionary responses, with 26 studies showing both. These responses, however, may be insufficient to keep pace with climate change, as indicated by eight of 12 studies that examined this directly. There is also mixed evidence for whether evolutionary responses are adaptive, and whether they are directly caused by contemporary climatic changes. We discuss factors that will likely influence the extent of plastic and evolutionary responses, including patterns of environmental changes, species’ life history characteristics including generation time and breeding system, and degree and direction of gene flow. Future studies with standardized methodologies, especially those that use direct approaches assessing responses to climate change over time, and sharing of data through public databases, will facilitate better predictions of the capacity for plant populations to respond to rapid climate change. PMID:24454552

Cooperation and age structure in spatial games

NASA Astrophysics Data System (ADS)

Wang, Zhen; Wang, Zhen; Zhu, Xiaodan; Arenzon, Jeferson J.

2012-01-01

We study the evolution of cooperation in evolutionary spatial games when the payoff correlates with the increasing age of players (the level of correlation is set through a single parameter, α). The demographic heterogeneous age distribution, directly affecting the outcome of the game, is thus shown to be responsible for enhancing the cooperative behavior in the population. In particular, moderate values of α allow cooperators not only to survive but to outcompete defectors, even when the temptation to defect is large and the ageless, standard α=0 model does not sustain cooperation. The interplay between age structure and noise is also considered, and we obtain the conditions for optimal levels of cooperation.

Low-metallicity (sub-SMC) massive stars

NASA Astrophysics Data System (ADS)

Garcia, Miriam; Herrero, Artemio; Najarro, Francisco; Camacho, Inés; Lennon, Daniel J.; Urbaneja, Miguel A.; Castro, Norberto

2017-11-01

The double distance and metallicity frontier marked by the SMC has been finally broken with the aid of powerful multi-object spectrographs installed at 8-10m class telescopes. VLT, GTC and Keck have enabled studies of massive stars in dwarf irregular galaxies of the Local Group with poorer metal-content than the SMC. The community is working to test the predictions of evolutionary models in the low-metallicity regime, set the new standard for the metal-poor high-redshift Universe, and test the extrapolation of the physics of massive stars to environments of decreasing metallicity. In this paper, we review current knowledge on this topic.

Evolutionary model of the growth and size of firms

NASA Astrophysics Data System (ADS)

Kaldasch, Joachim

2012-07-01

The key idea of this model is that firms are the result of an evolutionary process. Based on demand and supply considerations the evolutionary model presented here derives explicitly Gibrat's law of proportionate effects as the result of the competition between products. Applying a preferential attachment mechanism for firms, the theory allows to establish the size distribution of products and firms. Also established are the growth rate and price distribution of consumer goods. Taking into account the characteristic property of human activities to occur in bursts, the model allows also an explanation of the size-variance relationship of the growth rate distribution of products and firms. Further the product life cycle, the learning (experience) curve and the market size in terms of the mean number of firms that can survive in a market are derived. The model also suggests the existence of an invariant of a market as the ratio of total profit to total revenue. The relationship between a neo-classic and an evolutionary view of a market is discussed. The comparison with empirical investigations suggests that the theory is able to describe the main stylized facts concerning the size and growth of firms.

Grand challenges in evolutionary and population genetics: The importance of integrating epigenetics, genomics, modeling, and experimentation

Treesearch

Samuel A. Cushman

2014-01-01

This is a time of explosive growth in the fields of evolutionary and population genetics, with whole genome sequencing and bioinformatics driving a transformative paradigm shift (Morozova and Marra, 2008). At the same time, advances in epigenetics are thoroughly transforming our understanding of evolutionary processes and their implications for populations, species and...

An evolutionary perspective on gradual formation of superego in the primal horde

PubMed Central

Pulcu, Erdem

2014-01-01

Freud proposed that the processes which occurred in the primal horde are essential for understanding superego formation and therefore, the successful dissolution of the Oedipus complex. However, Freud theorized superego formation in the primal horde as if it is an instant, all-or-none achievement. The present paper proposes an alternative model aiming to explain gradual development of superego in the primitive man. The proposed model is built on knowledge from evolutionary and neural sciences as well as anthropology, and it particularly focuses on the evolutionary significance of the acquisition of fire by hominids in the Pleistocene period in the light of up-to-date archaeological findings. Acquisition of fire is discussed as a form of sublimation which might have helped Prehistoric man to maximize the utility of limited evolutionary biological resources, potentially contributing to the rate and extent of bodily evolution. The limitations of both Freud's original conceptualization and the present model are discussed accordingly in an interdisciplinary framework. PMID:24478740

Asymmetric Evolutionary Games

PubMed Central

McAvoy, Alex; Hauert, Christoph

2015-01-01

Evolutionary game theory is a powerful framework for studying evolution in populations of interacting individuals. A common assumption in evolutionary game theory is that interactions are symmetric, which means that the players are distinguished by only their strategies. In nature, however, the microscopic interactions between players are nearly always asymmetric due to environmental effects, differing baseline characteristics, and other possible sources of heterogeneity. To model these phenomena, we introduce into evolutionary game theory two broad classes of asymmetric interactions: ecological and genotypic. Ecological asymmetry results from variation in the environments of the players, while genotypic asymmetry is a consequence of the players having differing baseline genotypes. We develop a theory of these forms of asymmetry for games in structured populations and use the classical social dilemmas, the Prisoner’s Dilemma and the Snowdrift Game, for illustrations. Interestingly, asymmetric games reveal essential differences between models of genetic evolution based on reproduction and models of cultural evolution based on imitation that are not apparent in symmetric games. PMID:26308326

Are there laws of genome evolution?

PubMed

Koonin, Eugene V

2011-08-01

Research in quantitative evolutionary genomics and systems biology led to the discovery of several universal regularities connecting genomic and molecular phenomic variables. These universals include the log-normal distribution of the evolutionary rates of orthologous genes; the power law-like distributions of paralogous family size and node degree in various biological networks; the negative correlation between a gene's sequence evolution rate and expression level; and differential scaling of functional classes of genes with genome size. The universals of genome evolution can be accounted for by simple mathematical models similar to those used in statistical physics, such as the birth-death-innovation model. These models do not explicitly incorporate selection; therefore, the observed universal regularities do not appear to be shaped by selection but rather are emergent properties of gene ensembles. Although a complete physical theory of evolutionary biology is inconceivable, the universals of genome evolution might qualify as "laws of evolutionary genomics" in the same sense "law" is understood in modern physics.

Observing Clonal Dynamics across Spatiotemporal Axes: A Prelude to Quantitative Fitness Models for Cancer.

PubMed

McPherson, Andrew W; Chan, Fong Chun; Shah, Sohrab P

2018-02-01

The ability to accurately model evolutionary dynamics in cancer would allow for prediction of progression and response to therapy. As a prelude to quantitative understanding of evolutionary dynamics, researchers must gather observations of in vivo tumor evolution. High-throughput genome sequencing now provides the means to profile the mutational content of evolving tumor clones from patient biopsies. Together with the development of models of tumor evolution, reconstructing evolutionary histories of individual tumors generates hypotheses about the dynamics of evolution that produced the observed clones. In this review, we provide a brief overview of the concepts involved in predicting evolutionary histories, and provide a workflow based on bulk and targeted-genome sequencing. We then describe the application of this workflow to time series data obtained for transformed and progressed follicular lymphomas (FL), and contrast the observed evolutionary dynamics between these two subtypes. We next describe results from a spatial sampling study of high-grade serous (HGS) ovarian cancer, propose mechanisms of disease spread based on the observed clonal mixtures, and provide examples of diversification through subclonal acquisition of driver mutations and convergent evolution. Finally, we state implications of the techniques discussed in this review as a necessary but insufficient step on the path to predictive modelling of disease dynamics. Copyright © 2018 Cold Spring Harbor Laboratory Press; all rights reserved.

Cultural and climatic changes shape the evolutionary history of the Uralic languages.

PubMed

Honkola, T; Vesakoski, O; Korhonen, K; Lehtinen, J; Syrjänen, K; Wahlberg, N

2013-06-01

Quantitative phylogenetic methods have been used to study the evolutionary relationships and divergence times of biological species, and recently, these have also been applied to linguistic data to elucidate the evolutionary history of language families. In biology, the factors driving macroevolutionary processes are assumed to be either mainly biotic (the Red Queen model) or mainly abiotic (the Court Jester model) or a combination of both. The applicability of these models is assumed to depend on the temporal and spatial scale observed as biotic factors act on species divergence faster and in smaller spatial scale than the abiotic factors. Here, we used the Uralic language family to investigate whether both 'biotic' interactions (i.e. cultural interactions) and abiotic changes (i.e. climatic fluctuations) are also connected to language diversification. We estimated the times of divergence using Bayesian phylogenetics with a relaxed-clock method and related our results to climatic, historical and archaeological information. Our timing results paralleled the previous linguistic studies but suggested a later divergence of Finno-Ugric, Finnic and Saami languages. Some of the divergences co-occurred with climatic fluctuation and some with cultural interaction and migrations of populations. Thus, we suggest that both 'biotic' and abiotic factors contribute either directly or indirectly to the diversification of languages and that both models can be applied when studying language evolution. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

VizieR Online Data Catalog: Comparison of evolutionary tracks (Martins+, 2013)

NASA Astrophysics Data System (ADS)

Martins, F.; Palacios, A.

2013-11-01

Tables of evolutionary models for massive stars. The files m*_stol.dat correspond to models computed with the code STAREVOL. The files m*_mesa.dat correspond to models computed with the code MESA. For each code, models with initial masses equal to 7, 9, 15, 20, 25, 40 and 60M⊙ are provided. No rotation is included. The overshooting parameter f is equal to 0.01. The metallicity is solar. (14 data files).

Epigenetic game theory and its application in plants. Comment on: ;Epigenetic game theory: How to compute the epigenetic control of maternal-to-zygotic transition; by Qian Wang et al.

NASA Astrophysics Data System (ADS)

Zhang, Yuan-Ming; Zhang, Yinghao; Guo, Mingyue

2017-03-01

Wang's et al. article [1] is the first to integrate game theory (especially evolutionary game theory) with epigenetic modification of zygotic genomes. They described and assessed a modeling framework based on evolutionary game theory to quantify, how sperms and oocytes interact through epigenetic processes, to determine embryo development. They also studied the internal mechanisms for normal embryo development: 1) evolutionary interactions between DNA methylation of the paternal and maternal genomes, and 2) the application of game theory to formulate and quantify how different genes compete or cooperate to regulate embryogenesis through methylation. Although it is not very comprehensive and profound regarding game theory modeling, this article bridges the gap between evolutionary game theory and the epigenetic control of embryo development by powerful ordinary differential equations (ODEs). The epiGame framework includes four aspects: 1) characterizing how epigenetic game theory works by the strategy matrix, in which the pattern and relative magnitude of the methylation effects on embryogenesis, are described by the cooperation and competition mechanisms, 2) quantifying the game that the direction and degree of P-M interactions over embryo development can be explained by the sign and magnitude of interaction parameters in model (2), 3) modeling epigenetic interactions within the morula, especially for two coupled nonlinear ODEs, with explicit functions in model (4), which provide a good fit to the observed data for the two sexes (adjusted R2 = 0.956), and 4) revealing multifactorial interactions in embryogenesis from the coupled ODEs in model (2) to triplet ODEs in model (6). Clearly, this article extends game theory from evolutionary game theory to epigenetic game theory.

The long-term evolution of multilocus traits under frequency-dependent disruptive selection.

PubMed

van Doorn, G Sander; Dieckmann, Ulf

2006-11-01

Frequency-dependent disruptive selection is widely recognized as an important source of genetic variation. Its evolutionary consequences have been extensively studied using phenotypic evolutionary models, based on quantitative genetics, game theory, or adaptive dynamics. However, the genetic assumptions underlying these approaches are highly idealized and, even worse, predict different consequences of frequency-dependent disruptive selection. Population genetic models, by contrast, enable genotypic evolutionary models, but traditionally assume constant fitness values. Only a minority of these models thus addresses frequency-dependent selection, and only a few of these do so in a multilocus context. An inherent limitation of these remaining studies is that they only investigate the short-term maintenance of genetic variation. Consequently, the long-term evolution of multilocus characters under frequency-dependent disruptive selection remains poorly understood. We aim to bridge this gap between phenotypic and genotypic models by studying a multilocus version of Levene's soft-selection model. Individual-based simulations and deterministic approximations based on adaptive dynamics theory provide insights into the underlying evolutionary dynamics. Our analysis uncovers a general pattern of polymorphism formation and collapse, likely to apply to a wide variety of genetic systems: after convergence to a fitness minimum and the subsequent establishment of genetic polymorphism at multiple loci, genetic variation becomes increasingly concentrated on a few loci, until eventually only a single polymorphic locus remains. This evolutionary process combines features observed in quantitative genetics and adaptive dynamics models, and it can be explained as a consequence of changes in the selection regime that are inherent to frequency-dependent disruptive selection. Our findings demonstrate that the potential of frequency-dependent disruptive selection to maintain polygenic variation is considerably smaller than previously expected.

A Penalized Likelihood Framework For High-Dimensional Phylogenetic Comparative Methods And An Application To New-World Monkeys Brain Evolution.

PubMed

Julien, Clavel; Leandro, Aristide; Hélène, Morlon

2018-06-19

Working with high-dimensional phylogenetic comparative datasets is challenging because likelihood-based multivariate methods suffer from low statistical performances as the number of traits p approaches the number of species n and because some computational complications occur when p exceeds n. Alternative phylogenetic comparative methods have recently been proposed to deal with the large p small n scenario but their use and performances are limited. Here we develop a penalized likelihood framework to deal with high-dimensional comparative datasets. We propose various penalizations and methods for selecting the intensity of the penalties. We apply this general framework to the estimation of parameters (the evolutionary trait covariance matrix and parameters of the evolutionary model) and model comparison for the high-dimensional multivariate Brownian (BM), Early-burst (EB), Ornstein-Uhlenbeck (OU) and Pagel's lambda models. We show using simulations that our penalized likelihood approach dramatically improves the estimation of evolutionary trait covariance matrices and model parameters when p approaches n, and allows for their accurate estimation when p equals or exceeds n. In addition, we show that penalized likelihood models can be efficiently compared using Generalized Information Criterion (GIC). We implement these methods, as well as the related estimation of ancestral states and the computation of phylogenetic PCA in the R package RPANDA and mvMORPH. Finally, we illustrate the utility of the new proposed framework by evaluating evolutionary models fit, analyzing integration patterns, and reconstructing evolutionary trajectories for a high-dimensional 3-D dataset of brain shape in the New World monkeys. We find a clear support for an Early-burst model suggesting an early diversification of brain morphology during the ecological radiation of the clade. Penalized likelihood offers an efficient way to deal with high-dimensional multivariate comparative data.

Cooperation in two-person evolutionary games with complex personality profiles.

PubMed

Płatkowski, Tadeusz

2010-10-21

We propose a theory of evolution of social systems which generalizes the standard proportional fitness rule of the evolutionary game theory. The formalism is applied to describe the dynamics of two-person one-shot population games. In particular it predicts the non-zero level of cooperation in the long run for the Prisoner's Dilemma games, the increase of the fraction of cooperators for general classes of the Snow-Drift game, and stable nonzero cooperation level for coordination games. Copyright © 2010 Elsevier Ltd. All rights reserved.

The Unusual Binary Pulsar PSR J1744-3922: Radio Flux Variability, Near-Infrared Observation, and Evolution

NASA Astrophysics Data System (ADS)

Breton, R. P.; Roberts, M. S. E.; Ransom, S. M.; Kaspi, V. M.; Durant, M.; Bergeron, P.; Faulkner, A. J.

2007-06-01

PSR J1744-3922 is a binary pulsar exhibiting highly variable pulsed radio emission. We report on a statistical multifrequency study of the pulsed radio flux variability which suggests that this phenomenon is extrinsic to the pulsar and possibly tied to the companion, although not strongly correlated with orbital phase. The pulsar has an unusual combination of characteristics compared to typical recycled pulsars: a long spin period (172 ms); a relatively high magnetic field strength (1.7×1010 G); a very circular, compact orbit of 4.6 hr; and a low-mass companion (0.08 Msolar). These spin and orbital properties are likely inconsistent with standard evolutionary models. We find similarities between the properties of the PSR J1744-3922 system and those of several other known binary pulsar systems, motivating the identification of a new class of binary pulsars. We suggest that this new class could result from: a standard accretion scenario of a magnetar or a high magnetic field pulsar; common envelope evolution with a low-mass star and a neutron star, similar to what is expected for ultracompact X-ray binaries; or accretion induced collapse of a white dwarf. We also report the detection of a possible K'=19.30(15) infrared counterpart at the position of the pulsar, which is relatively bright if the companion is a helium white dwarf at the nominal distance, and discuss its implications for the pulsar's companion and evolutionary history.

Equilibria, information and frustration in heterogeneous network games with conflicting preferences

NASA Astrophysics Data System (ADS)

Mazzoli, M.; Sánchez, A.

2017-11-01

Interactions between people are the basis on which the structure of our society arises as a complex system and, at the same time, are the starting point of any physical description of it. In the last few years, much theoretical research has addressed this issue by combining the physics of complex networks with a description of interactions in terms of evolutionary game theory. We here take this research a step further by introducing a most salient societal factor such as the individuals’ preferences, a characteristic that is key to understanding much of the social phenomenology these days. We consider a heterogeneous, agent-based model in which agents interact strategically with their neighbors, but their preferences and payoffs for the possible actions differ. We study how such a heterogeneous network behaves under evolutionary dynamics and different strategic interactions, namely coordination games and best shot games. With this model we study the emergence of the equilibria predicted analytically in random graphs under best response dynamics, and we extend this test to unexplored contexts like proportional imitation and scale free networks. We show that some theoretically predicted equilibria do not arise in simulations with incomplete information, and we demonstrate the importance of the graph topology and the payoff function parameters for some games. Finally, we discuss our results with the available experimental evidence on coordination games, showing that our model agrees better with the experiment than standard economic theories, and draw hints as to how to maximize social efficiency in situations of conflicting preferences.

Fear and Loving in Las Vegas: Evolution, Emotion, and Persuasion.

PubMed

Griskevicius, Vladas; Goldstein, Noah J; Mortensen, Chad R; Sundie, Jill M; Cialdini, Robert B; Kenrick, Douglas T

2009-06-01

How do arousal-inducing contexts, such as frightening or romantic television programs, influence the effectiveness of basic persuasion heuristics? Different predictions are made by three theoretical models: A general arousal model predicts that arousal should increase effectiveness of heuristics; an affective valence model predicts that effectiveness should depend on whether the context elicits positive or negative affect; an evolutionary model predicts that persuasiveness should depend on both the specific emotion that is elicited and the content of the particular heuristic. Three experiments examined how fear-inducing versus romantic contexts influenced the effectiveness of two widely used heuristics-social proof (e.g., "most popular") and scarcity (e.g., "limited edition"). Results supported predictions from an evolutionary model, showing that fear can lead scarcity appeals to be counter-persuasive, and that romantic desire can lead social proof appeals to be counter-persuasive. The findings highlight how an evolutionary theoretical approach can lead to novel theoretical and practical marketing insights.

Two-phase vesicles: a study on evolutionary and stationary models.

PubMed

Sahebifard, MohammadMahdi; Shahidi, Alireza; Ziaei-Rad, Saeed

2017-05-01

In the current article, the dynamic evolution of two-phase vesicles is presented as an extension to a previous stationary model and based on an equilibrium of local forces. In the simplified model, ignoring the effects of membrane inertia, a dynamic equilibrium between the membrane bending potential and local fluid friction is considered in each phase. The equilibrium equations at the domain borders are completed by extended introduction of membrane section reactions. We show that in some cases, the results of stationary and evolutionary models are in agreement with each other and also with experimental observations, while in others the two models differ markedly. The value of our approach is that we can account for unresponsive points of uncertainty using our equations with the local velocity of the lipid membranes and calculating the intermediate states (shapes) in the consequent evolutionary, or response, path.

A framework for evolutionary systems biology

PubMed Central

Loewe, Laurence

2009-01-01

Background Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects. Results Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions in silico. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism. Conclusion EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications. PMID:19239699

Emerging Concepts of Data Integration in Pathogen Phylodynamics.

PubMed

Baele, Guy; Suchard, Marc A; Rambaut, Andrew; Lemey, Philippe

2017-01-01

Phylodynamics has become an increasingly popular statistical framework to extract evolutionary and epidemiological information from pathogen genomes. By harnessing such information, epidemiologists aim to shed light on the spatio-temporal patterns of spread and to test hypotheses about the underlying interaction of evolutionary and ecological dynamics in pathogen populations. Although the field has witnessed a rich development of statistical inference tools with increasing levels of sophistication, these tools initially focused on sequences as their sole primary data source. Integrating various sources of information, however, promises to deliver more precise insights in infectious diseases and to increase opportunities for statistical hypothesis testing. Here, we review how the emerging concept of data integration is stimulating new advances in Bayesian evolutionary inference methodology which formalize a marriage of statistical thinking and evolutionary biology. These approaches include connecting sequence to trait evolution, such as for host, phenotypic and geographic sampling information, but also the incorporation of covariates of evolutionary and epidemic processes in the reconstruction procedures. We highlight how a full Bayesian approach to covariate modeling and testing can generate further insights into sequence evolution, trait evolution, and population dynamics in pathogen populations. Specific examples demonstrate how such approaches can be used to test the impact of host on rabies and HIV evolutionary rates, to identify the drivers of influenza dispersal as well as the determinants of rabies cross-species transmissions, and to quantify the evolutionary dynamics of influenza antigenicity. Finally, we briefly discuss how data integration is now also permeating through the inference of transmission dynamics, leading to novel insights into tree-generative processes and detailed reconstructions of transmission trees. [Bayesian inference; birth–death models; coalescent models; continuous trait evolution; covariates; data integration; discrete trait evolution; pathogen phylodynamics.

Emerging Concepts of Data Integration in Pathogen Phylodynamics

PubMed Central

Baele, Guy; Suchard, Marc A.; Rambaut, Andrew; Lemey, Philippe

2017-01-01

Phylodynamics has become an increasingly popular statistical framework to extract evolutionary and epidemiological information from pathogen genomes. By harnessing such information, epidemiologists aim to shed light on the spatio-temporal patterns of spread and to test hypotheses about the underlying interaction of evolutionary and ecological dynamics in pathogen populations. Although the field has witnessed a rich development of statistical inference tools with increasing levels of sophistication, these tools initially focused on sequences as their sole primary data source. Integrating various sources of information, however, promises to deliver more precise insights in infectious diseases and to increase opportunities for statistical hypothesis testing. Here, we review how the emerging concept of data integration is stimulating new advances in Bayesian evolutionary inference methodology which formalize a marriage of statistical thinking and evolutionary biology. These approaches include connecting sequence to trait evolution, such as for host, phenotypic and geographic sampling information, but also the incorporation of covariates of evolutionary and epidemic processes in the reconstruction procedures. We highlight how a full Bayesian approach to covariate modeling and testing can generate further insights into sequence evolution, trait evolution, and population dynamics in pathogen populations. Specific examples demonstrate how such approaches can be used to test the impact of host on rabies and HIV evolutionary rates, to identify the drivers of influenza dispersal as well as the determinants of rabies cross-species transmissions, and to quantify the evolutionary dynamics of influenza antigenicity. Finally, we briefly discuss how data integration is now also permeating through the inference of transmission dynamics, leading to novel insights into tree-generative processes and detailed reconstructions of transmission trees. [Bayesian inference; birth–death models; coalescent models; continuous trait evolution; covariates; data integration; discrete trait evolution; pathogen phylodynamics. PMID:28173504

Evolution in the Caribbean Classroom: A Critical Analysis of the Role of Biology Teachers and Science Standards in Shaping Evolution Instruction in Belize

ERIC Educational Resources Information Center

Nunez, Elvis Enrique; Pringle, Rose M.; Showalter, Kevin Tyler

2012-01-01

A survey of the literature on evolution instruction provides evidence that teachers' personal views and understandings can shape instructional approaches and content delivered in science classrooms regardless of established science standards. This study is the first to quantify evolutionary worldviews of in-service teachers in the Caribbean,…

Evolutionary Games with Randomly Changing Payoff Matrices

NASA Astrophysics Data System (ADS)

Yakushkina, Tatiana; Saakian, David B.; Bratus, Alexander; Hu, Chin-Kun

2015-06-01

Evolutionary games are used in various fields stretching from economics to biology. In most of these games a constant payoff matrix is assumed, although some works also consider dynamic payoff matrices. In this article we assume a possibility of switching the system between two regimes with different sets of payoff matrices. Potentially such a model can qualitatively describe the development of bacterial or cancer cells with a mutator gene present. A finite population evolutionary game is studied. The model describes the simplest version of annealed disorder in the payoff matrix and is exactly solvable at the large population limit. We analyze the dynamics of the model, and derive the equations for both the maximum and the variance of the distribution using the Hamilton-Jacobi equation formalism.

Evolutionary considerations on complex emotions and music-induced emotions. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

NASA Astrophysics Data System (ADS)

Gingras, Bruno; Marin, Manuela M.

2015-06-01

Recent efforts to uncover the neural underpinnings of emotional experiences have provided a foundation for novel neurophysiological theories of emotions, adding to the existing body of psychophysiological, motivational, and evolutionary theories. Besides explicitly modeling human-specific emotions and considering the interactions between emotions and language, Koelsch et al.'s original contribution to this challenging endeavor is to identify four brain areas as distinct "affect systems" which differ in terms of emotional qualia and evolutionary pathways [1]. Here, we comment on some features of this promising Quartet Theory of Emotions, focusing particularly on evolutionary and biological aspects related to the four affect systems and their relation to prevailing emotion theories, as well as on the role of music-induced emotions.

An Evolutionary Cascade Model for Sauropod Dinosaur Gigantism - Overview, Update and Tests

PubMed Central

Sander, P. Martin

2013-01-01

Sauropod dinosaurs are a group of herbivorous dinosaurs which exceeded all other terrestrial vertebrates in mean and maximal body size. Sauropod dinosaurs were also the most successful and long-lived herbivorous tetrapod clade, but no abiological factors such as global environmental parameters conducive to their gigantism can be identified. These facts justify major efforts by evolutionary biologists and paleontologists to understand sauropods as living animals and to explain their evolutionary success and uniquely gigantic body size. Contributions to this research program have come from many fields and can be synthesized into a biological evolutionary cascade model of sauropod dinosaur gigantism (sauropod gigantism ECM). This review focuses on the sauropod gigantism ECM, providing an updated version based on the contributions to the PLoS ONE sauropod gigantism collection and on other very recent published evidence. The model consist of five separate evolutionary cascades (“Reproduction”, “Feeding”, “Head and neck”, “Avian-style lung”, and “Metabolism”). Each cascade starts with observed or inferred basal traits that either may be plesiomorphic or derived at the level of Sauropoda. Each trait confers hypothetical selective advantages which permit the evolution of the next trait. Feedback loops in the ECM consist of selective advantages originating from traits higher in the cascades but affecting lower traits. All cascades end in the trait “Very high body mass”. Each cascade is linked to at least one other cascade. Important plesiomorphic traits of sauropod dinosaurs that entered the model were ovipary as well as no mastication of food. Important evolutionary innovations (derived traits) were an avian-style respiratory system and an elevated basal metabolic rate. Comparison with other tetrapod lineages identifies factors limiting body size. PMID:24205267

An evolutionary cascade model for sauropod dinosaur gigantism--overview, update and tests.

PubMed

Sander, P Martin

2013-01-01

Sauropod dinosaurs are a group of herbivorous dinosaurs which exceeded all other terrestrial vertebrates in mean and maximal body size. Sauropod dinosaurs were also the most successful and long-lived herbivorous tetrapod clade, but no abiological factors such as global environmental parameters conducive to their gigantism can be identified. These facts justify major efforts by evolutionary biologists and paleontologists to understand sauropods as living animals and to explain their evolutionary success and uniquely gigantic body size. Contributions to this research program have come from many fields and can be synthesized into a biological evolutionary cascade model of sauropod dinosaur gigantism (sauropod gigantism ECM). This review focuses on the sauropod gigantism ECM, providing an updated version based on the contributions to the PLoS ONE sauropod gigantism collection and on other very recent published evidence. The model consist of five separate evolutionary cascades ("Reproduction", "Feeding", "Head and neck", "Avian-style lung", and "Metabolism"). Each cascade starts with observed or inferred basal traits that either may be plesiomorphic or derived at the level of Sauropoda. Each trait confers hypothetical selective advantages which permit the evolution of the next trait. Feedback loops in the ECM consist of selective advantages originating from traits higher in the cascades but affecting lower traits. All cascades end in the trait "Very high body mass". Each cascade is linked to at least one other cascade. Important plesiomorphic traits of sauropod dinosaurs that entered the model were ovipary as well as no mastication of food. Important evolutionary innovations (derived traits) were an avian-style respiratory system and an elevated basal metabolic rate. Comparison with other tetrapod lineages identifies factors limiting body size.

Diversity Arrays Technology (DArT) for Pan-Genomic Evolutionary Studies of Non-Model Organisms

PubMed Central

James, Karen E.; Schneider, Harald; Ansell, Stephen W.; Evers, Margaret; Robba, Lavinia; Uszynski, Grzegorz; Pedersen, Niklas; Newton, Angela E.; Russell, Stephen J.; Vogel, Johannes C.; Kilian, Andrzej

2008-01-01

Background High-throughput tools for pan-genomic study, especially the DNA microarray platform, have sparked a remarkable increase in data production and enabled a shift in the scale at which biological investigation is possible. The use of microarrays to examine evolutionary relationships and processes, however, is predominantly restricted to model or near-model organisms. Methodology/Principal Findings This study explores the utility of Diversity Arrays Technology (DArT) in evolutionary studies of non-model organisms. DArT is a hybridization-based genotyping method that uses microarray technology to identify and type DNA polymorphism. Theoretically applicable to any organism (even one for which no prior genetic data are available), DArT has not yet been explored in exclusively wild sample sets, nor extensively examined in a phylogenetic framework. DArT recovered 1349 markers of largely low copy-number loci in two lineages of seed-free land plants: the diploid fern Asplenium viride and the haploid moss Garovaglia elegans. Direct sequencing of 148 of these DArT markers identified 30 putative loci including four routinely sequenced for evolutionary studies in plants. Phylogenetic analyses of DArT genotypes reveal phylogeographic and substrate specificity patterns in A. viride, a lack of phylogeographic pattern in Australian G. elegans, and additive variation in hybrid or mixed samples. Conclusions/Significance These results enable methodological recommendations including procedures for detecting and analysing DArT markers tailored specifically to evolutionary investigations and practical factors informing the decision to use DArT, and raise evolutionary hypotheses concerning substrate specificity and biogeographic patterns. Thus DArT is a demonstrably valuable addition to the set of existing molecular approaches used to infer biological phenomena such as adaptive radiations, population dynamics, hybridization, introgression, ecological differentiation and phylogeography. PMID:18301759

Influences of Agents with a Self-Reputation Awareness Component in an Evolutionary Spatial IPD Game

PubMed Central

Huang, Chung-Yuan; Lee, Chun-Liang

2014-01-01

Iterated prisoner’s dilemma (IPD) researchers have shown that strong positive reputations plus an efficient reputation evaluation system encourages both sides to pursue long-term collaboration and to avoid falling into mutual defection cycles. In agent-based environments with reliable reputation rating systems, agents interested in maximizing their private interests must show concern for other agents as well as their own self-reputations–an important capability that standard IPD game agents lack. Here we present a novel learning agent model possessing self-reputation awareness. Agents in our proposed model are capable of evaluating self-behaviors based on a mix of public and private interest considerations, and of testing various solutions aimed at meeting social standards. Simulation results indicate multiple outcomes from the addition of a small percentage of self-reputation awareness agents: faster cooperation, faster movement toward stability in an agent society, a higher level of public interest in the agent society, the resolution of common conflicts between public and private interests, and a lower potential for rational individual behavior to transform into irrational group behavior. PMID:24945966

An evolutionary game model for behavioral gambit of loyalists: Global awareness and risk-aversion

NASA Astrophysics Data System (ADS)

Alfinito, E.; Barra, A.; Beccaria, M.; Fachechi, A.; Macorini, G.

2018-02-01

We study the phase diagram of a minority game where three classes of agents are present. Two types of agents play a risk-loving game that we model by the standard Snowdrift Game. The behaviour of the third type of agents is coded by indifference with respect to the game at all: their dynamics is designed to account for risk-aversion as an innovative behavioral gambit. From this point of view, the choice of this solitary strategy is enhanced when innovation starts, while is depressed when it becomes the majority option. This implies that the payoff matrix of the game becomes dependent on the global awareness of the agents measured by the relevance of the population of the indifferent players. The resulting dynamics is nontrivial with different kinds of phase transition depending on a few model parameters. The phase diagram is studied on regular as well as complex networks.

The Proposal of a Evolutionary Strategy Generating the Data Structures Based on a Horizontal Tree for the Tests

NASA Astrophysics Data System (ADS)

Żukowicz, Marek; Markiewicz, Michał

2016-09-01

The aim of the article is to present a mathematical definition of the object model, that is known in computer science as TreeList and to show application of this model for design evolutionary algorithm, that purpose is to generate structures based on this object. The first chapter introduces the reader to the problem of presenting data using the TreeList object. The second chapter describes the problem of testing data structures based on TreeList. The third one shows a mathematical model of the object TreeList and the parameters, used in determining the utility of structures created through this model and in evolutionary strategy, that generates these structures for testing purposes. The last chapter provides a brief summary and plans for future research related to the algorithm presented in the article.

Evolutionary model of stock markets

NASA Astrophysics Data System (ADS)

Kaldasch, Joachim

2014-12-01

The paper presents an evolutionary economic model for the price evolution of stocks. Treating a stock market as a self-organized system governed by a fast purchase process and slow variations of demand and supply the model suggests that the short term price distribution has the form a logistic (Laplace) distribution. The long term return can be described by Laplace-Gaussian mixture distributions. The long term mean price evolution is governed by a Walrus equation, which can be transformed into a replicator equation. This allows quantifying the evolutionary price competition between stocks. The theory suggests that stock prices scaled by the price over all stocks can be used to investigate long-term trends in a Fisher-Pry plot. The price competition that follows from the model is illustrated by examining the empirical long-term price trends of two stocks.

Parametric Sensitivity Analysis of Oscillatory Delay Systems with an Application to Gene Regulation.

PubMed

Ingalls, Brian; Mincheva, Maya; Roussel, Marc R

2017-07-01

A parametric sensitivity analysis for periodic solutions of delay-differential equations is developed. Because phase shifts cause the sensitivity coefficients of a periodic orbit to diverge, we focus on sensitivities of the extrema, from which amplitude sensitivities are computed, and of the period. Delay-differential equations are often used to model gene expression networks. In these models, the parametric sensitivities of a particular genotype define the local geometry of the evolutionary landscape. Thus, sensitivities can be used to investigate directions of gradual evolutionary change. An oscillatory protein synthesis model whose properties are modulated by RNA interference is used as an example. This model consists of a set of coupled delay-differential equations involving three delays. Sensitivity analyses are carried out at several operating points. Comments on the evolutionary implications of the results are offered.

Comparative modeling of coevolution in communities of unicellular organisms: adaptability and biodiversity.

PubMed

Lashin, Sergey A; Suslov, Valentin V; Matushkin, Yuri G

2010-06-01

We propose an original program "Evolutionary constructor" that is capable of computationally efficient modeling of both population-genetic and ecological problems, combining these directions in one model of required detail level. We also present results of comparative modeling of stability, adaptability and biodiversity dynamics in populations of unicellular haploid organisms which form symbiotic ecosystems. The advantages and disadvantages of two evolutionary strategies of biota formation--a few generalists' taxa-based biota formation and biodiversity-based biota formation--are discussed.

Informations in Models of Evolutionary Dynamics

NASA Astrophysics Data System (ADS)

Rivoire, Olivier

2016-03-01

Biological organisms adapt to changes by processing informations from different sources, most notably from their ancestors and from their environment. We review an approach to quantify these informations by analyzing mathematical models of evolutionary dynamics and show how explicit results are obtained for a solvable subclass of these models. In several limits, the results coincide with those obtained in studies of information processing for communication, gambling or thermodynamics. In the most general case, however, information processing by biological populations shows unique features that motivate the analysis of specific models.

Evolutionary Thinking in Microeconomic Models: Prestige Bias and Market Bubbles

PubMed Central

Bell, Adrian Viliami

2013-01-01

Evolutionary models broadly support a number of social learning strategies likely important in economic behavior. Using a simple model of price dynamics, I show how prestige bias, or copying of famed (and likely successful) individuals, influences price equilibria and investor disposition in a way that exacerbates or creates market bubbles. I discuss how integrating the social learning and demographic forces important in cultural evolution with economic models provides a fruitful line of inquiry into real-world behavior. PMID:23544100

Construction of multiple trade-offs to obtain arbitrary singularities of adaptive dynamics.

PubMed

Kisdi, Éva

2015-04-01

Evolutionary singularities are central to the adaptive dynamics of evolving traits. The evolutionary singularities are strongly affected by the shape of any trade-off functions a model assumes, yet the trade-off functions are often chosen in an ad hoc manner, which may unjustifiably constrain the evolutionary dynamics exhibited by the model. To avoid this problem, critical function analysis has been used to find a trade-off function that yields a certain evolutionary singularity such as an evolutionary branching point. Here I extend this method to multiple trade-offs parameterized with a scalar strategy. I show that the trade-off functions can be chosen such that an arbitrary point in the viability domain of the trait space is a singularity of an arbitrary type, provided (next to certain non-degeneracy conditions) that the model has at least two environmental feedback variables and at least as many trade-offs as feedback variables. The proof is constructive, i.e., it provides an algorithm to find trade-off functions that yield the desired singularity. I illustrate the construction of trade-offs with an example where the virulence of a pathogen evolves in a small ecosystem of a host, its pathogen, a predator that attacks the host and an alternative prey of the predator.

Evolutionary theory of ageing and the problem of correlated Gompertz parameters.

PubMed

Burger, Oskar; Missov, Trifon I

2016-11-07

The Gompertz mortality model is often used to evaluate evolutionary theories of ageing, such as the Medawar-Williams' hypothesis that high extrinsic mortality leads to faster ageing. However, fits of the Gompertz mortality model to data often find the opposite result that mortality is negatively correlated with the rate of ageing. This negative correlation has been independently discovered in several taxa and is known in actuarial studies of ageing as the Strehler-Mildvan correlation. We examine the role of mortality selection in determining late-life variation in susceptibility to death, which has been suggested to be the cause of this negative correlation. We demonstrate that fixed-frailty models that account for heterogeneity in frailty do not remove the correlation and that the correlation is an inherent statistical property of the Gompertz distribution. Linking actuarial and biological rates of ageing will continue to be a pressing challenge, but the Strehler-Mildvan correlation itself should not be used to diagnose any biological, physiological, or evolutionary process. These findings resolve some key tensions between theory and data that affect evolutionary and biological studies of ageing and mortality. Tests of evolutionary theories of ageing should include direct measures of physiological performance or condition. Copyright © 2016 Elsevier Ltd. All rights reserved.

Individual heterogeneity in life histories and eco-evolutionary dynamics

PubMed Central

Vindenes, Yngvild; Langangen, Øystein

2015-01-01

Individual heterogeneity in life history shapes eco-evolutionary processes, and unobserved heterogeneity can affect demographic outputs characterising life history and population dynamical properties. Demographic frameworks like matrix models or integral projection models represent powerful approaches to disentangle mechanisms linking individual life histories and population-level processes. Recent developments have provided important steps towards their application to study eco-evolutionary dynamics, but so far individual heterogeneity has largely been ignored. Here, we present a general demographic framework that incorporates individual heterogeneity in a flexible way, by separating static and dynamic traits (discrete or continuous). First, we apply the framework to derive the consequences of ignoring heterogeneity for a range of widely used demographic outputs. A general conclusion is that besides the long-term growth rate lambda, all parameters can be affected. Second, we discuss how the framework can help advance current demographic models of eco-evolutionary dynamics, by incorporating individual heterogeneity. For both applications numerical examples are provided, including an empirical example for pike. For instance, we demonstrate that predicted demographic responses to climate warming can be reversed by increased heritability. We discuss how applications of this demographic framework incorporating individual heterogeneity can help answer key biological questions that require a detailed understanding of eco-evolutionary dynamics. PMID:25807980

Evolution of spatially structured host-parasite interactions.

PubMed

Lion, S; Gandon, S

2015-01-01

Spatial structure has dramatic effects on the demography and the evolution of species. A large variety of theoretical models have attempted to understand how local dispersal may shape the coevolution of interacting species such as host-parasite interactions. The lack of a unifying framework is a serious impediment for anyone willing to understand current theory. Here, we review previous theoretical studies in the light of a single epidemiological model that allows us to explore the effects of both host and parasite migration rates on the evolution and coevolution of various life-history traits. We discuss the impact of local dispersal on parasite virulence, various host defence strategies and local adaptation. Our analysis shows that evolutionary and coevolutionary outcomes crucially depend on the details of the host-parasite life cycle and on which life-history trait is involved in the interaction. We also discuss experimental studies that support the effects of spatial structure on the evolution of host-parasite interactions. This review highlights major similarities between some theoretical results, but it also reveals an important gap between evolutionary and coevolutionary models. We discuss possible ways to bridge this gap within a more unified framework that would reconcile spatial epidemiology, evolution and coevolution. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Ecological and evolutionary consequences of explicit spatial structure in exploiter-victim systems

NASA Astrophysics Data System (ADS)

Klopfer, Eric David

One class of spatial model which has been widely used in ecology has been termed "pseudo-spatial models" and classically employs various types of aggregation in studying the coexistence of competing parasitoids. Yet, little is known about the relative effects of each of these aggregation behaviors. Thus, in Chapter 1 I chose to examine three types of aggregation and explore their relative strengths in promoting coexistence of two competing parasitoids. A striking shortcoming of spatial models in ecology to date is that there is a relative lack of use of spatial models to investigate problems on the evolutionary as opposed to ecological time scale. Consequently, in Chapter 2 I chose to start with a classic problem of evolutionary time scale--the evolution of virulence and predation rates. Debate about this problem has continued through several decades, yet many instances are not adequately explained by current models. In this study I explored the effect of explicit spatial structure on exploitation rates by comparing a cellular automata (CA) exploiter-victim model which incorporates local dynamics to a metapopulation model which does not include such dynamics. One advantage of CA models is that they are defined by simple rules rather than the often complex equations of other types of spatial models. This is an extremely useful attribute when one wants to convey results of models to an audience with an applied bent that is often uncomfortable with hard-to-understand equations. Thus, in Chapter 3, through the use of CA models I show that there are spatial phenomena which alter the impact of introduced predators and that these phenomena are potentially important in the implementation of biocontrol programs. The relatively recent incorporation of spatial models into the ecological literature has left most ecologists and evolutionary biologists without the ability to understand, let alone employ, spatial models in evolutionary problems. In order to give the next generation of potential ecologists a better understanding of these models, in Chapter 4 I present an interactive tutorial in which students are able to explore the most well studied of these models (the evolution of cooperation in a spatial environment).

Cosmological constraints from a joint analysis of cosmic growth and expansion

NASA Astrophysics Data System (ADS)

Moresco, M.; Marulli, F.

2017-10-01

Combining measurements on the expansion history of the Universe and on the growth rate of cosmic structures is key to discriminate between alternative cosmological frameworks and to test gravity. Recently, Linder proposed a new diagram to investigate the joint evolutionary track of these two quantities. In this letter, we collect the most recent cosmic growth and expansion rate data sets to provide the state-of-the-art observational constraints on this diagram. By performing a joint statistical analysis of both probes, we test the standard Λcold dark matter model, confirming a mild tension between cosmic microwave background predictions from Planck mission and cosmic growth measurements at low redshift (z < 2). Then we test alternative models allowing the variation of one single cosmological parameter at a time. In particular, we find a larger growth index than the one predicted by general relativity γ =0.65^{+0.05}_{-0.04}. However, also a standard model with total neutrino mass of 0.26 ± 0.10 eV provides a similarly accurate description of the current data. By simulating an additional data set consistent with next-generation dark-energy mission forecasts, we show that growth rate constraints at z > 1 will be crucial to discriminate between alternative models.

Building v/s Exploring Models: Comparing Learning of Evolutionary Processes through Agent-based Modeling

NASA Astrophysics Data System (ADS)

Wagh, Aditi

Two strands of work motivate the three studies in this dissertation. Evolutionary change can be viewed as a computational complex system in which a small set of rules operating at the individual level result in different population level outcomes under different conditions. Extensive research has documented students' difficulties with learning about evolutionary change (Rosengren et al., 2012), particularly in terms of levels slippage (Wilensky & Resnick, 1999). Second, though building and using computational models is becoming increasingly common in K-12 science education, we know little about how these two modalities compare. This dissertation adopts agent-based modeling as a representational system to compare these modalities in the conceptual context of micro-evolutionary processes. Drawing on interviews, Study 1 examines middle-school students' productive ways of reasoning about micro-evolutionary processes to find that the specific framing of traits plays a key role in whether slippage explanations are cued. Study 2, which was conducted in 2 schools with about 150 students, forms the crux of the dissertation. It compares learning processes and outcomes when students build their own models or explore a pre-built model. Analysis of Camtasia videos of student pairs reveals that builders' and explorers' ways of accessing rules, and sense-making of observed trends are of a different character. Builders notice rules through available blocks-based primitives, often bypassing their enactment while explorers attend to rules primarily through the enactment. Moreover, builders' sense-making of observed trends is more rule-driven while explorers' is more enactment-driven. Pre and posttests reveal that builders manifest a greater facility with accessing rules, providing explanations manifesting targeted assembly. Explorers use rules to construct explanations manifesting non-targeted assembly. Interviews reveal varying degrees of shifts away from slippage in both modalities, with students who built models not incorporating slippage explanations in responses. Study 3 compares these modalities with a control using traditional activities. Pre and posttests reveal that the two modalities manifested greater facility with accessing and assembling rules than the control. The dissertation offers implications for the design of learning environments for evolutionary change, design of the two modalities based on their strengths and weaknesses, and teacher training for the same.

Spatial Structure of Evolutionary Models of Dialects in Contact

PubMed Central

Murawaki, Yugo

2015-01-01

Phylogenetic models, originally developed to demonstrate evolutionary biology, have been applied to a wide range of cultural data including natural language lexicons, manuscripts, folktales, material cultures, and religions. A fundamental question regarding the application of phylogenetic inference is whether trees are an appropriate approximation of cultural evolutionary history. Their validity in cultural applications has been scrutinized, particularly with respect to the lexicons of dialects in contact. Phylogenetic models organize evolutionary data into a series of branching events through time. However, branching events are typically not included in dialectological studies to interpret the distributions of lexical terms. Instead, dialectologists have offered spatial interpretations to represent lexical data. For example, new lexical items that emerge in a politico-cultural center are likely to spread to peripheries, but not vice versa. To explore the question of the tree model’s validity, we present a simple simulation model in which dialects form a spatial network and share lexical items through contact rather than through common ancestors. We input several network topologies to the model to generate synthetic data. We then analyze the synthesized data using conventional phylogenetic techniques. We found that a group of dialects can be considered tree-like even if it has not evolved in a temporally tree-like manner but has a temporally invariant, spatially tree-like structure. In addition, the simulation experiments appear to reproduce unnatural results observed in reconstructed trees for real data. These results motivate further investigation into the spatial structure of the evolutionary history of dialect lexicons as well as other cultural characteristics. PMID:26221958

MultiSeq: unifying sequence and structure data for evolutionary analysis

PubMed Central

Roberts, Elijah; Eargle, John; Wright, Dan; Luthey-Schulten, Zaida

2006-01-01

Background Since the publication of the first draft of the human genome in 2000, bioinformatic data have been accumulating at an overwhelming pace. Currently, more than 3 million sequences and 35 thousand structures of proteins and nucleic acids are available in public databases. Finding correlations in and between these data to answer critical research questions is extremely challenging. This problem needs to be approached from several directions: information science to organize and search the data; information visualization to assist in recognizing correlations; mathematics to formulate statistical inferences; and biology to analyze chemical and physical properties in terms of sequence and structure changes. Results Here we present MultiSeq, a unified bioinformatics analysis environment that allows one to organize, display, align and analyze both sequence and structure data for proteins and nucleic acids. While special emphasis is placed on analyzing the data within the framework of evolutionary biology, the environment is also flexible enough to accommodate other usage patterns. The evolutionary approach is supported by the use of predefined metadata, adherence to standard ontological mappings, and the ability for the user to adjust these classifications using an electronic notebook. MultiSeq contains a new algorithm to generate complete evolutionary profiles that represent the topology of the molecular phylogenetic tree of a homologous group of distantly related proteins. The method, based on the multidimensional QR factorization of multiple sequence and structure alignments, removes redundancy from the alignments and orders the protein sequences by increasing linear dependence, resulting in the identification of a minimal basis set of sequences that spans the evolutionary space of the homologous group of proteins. Conclusion MultiSeq is a major extension of the Multiple Alignment tool that is provided as part of VMD, a structural visualization program for analyzing molecular dynamics simulations. Both are freely distributed by the NIH Resource for Macromolecular Modeling and Bioinformatics and MultiSeq is included with VMD starting with version 1.8.5. The MultiSeq website has details on how to download and use the software: PMID:16914055

Research on Duplication Dynamics and Evolutionary Stable of Reverse Supply Chain

NASA Astrophysics Data System (ADS)

Huizhong, Dong; Hongli, Song

An evolutionary game model of Reverse Supply Chain(RSC) is established based on duplication dynamics function and evolutionary stable strategy. Using the model framework, this paper provides insights into a deeper understanding on how each supplier make strategic decision independently in reverse supply chain to determine their performance. The main conclusion is as follow: Under the market mechanism, not unless the extra income derived from the implementation of RSC exceeds zero point would the suppliers implement RSC strategy. When those suppliers are passive to RSC, the effective solution is that the government takes macro-control measures, for example, to force those suppliers implement RSC through punishment mechanism.

The locus of sexual selection: moving sexual selection studies into the post-genomics era.

PubMed

Wilkinson, G S; Breden, F; Mank, J E; Ritchie, M G; Higginson, A D; Radwan, J; Jaquiery, J; Salzburger, W; Arriero, E; Barribeau, S M; Phillips, P C; Renn, S C P; Rowe, L

2015-04-01

Sexual selection drives fundamental evolutionary processes such as trait elaboration and speciation. Despite this importance, there are surprisingly few examples of genes unequivocally responsible for variation in sexually selected phenotypes. This lack of information inhibits our ability to predict phenotypic change due to universal behaviours, such as fighting over mates and mate choice. Here, we discuss reasons for this apparent gap and provide recommendations for how it can be overcome by adopting contemporary genomic methods, exploiting underutilized taxa that may be ideal for detecting the effects of sexual selection and adopting appropriate experimental paradigms. Identifying genes that determine variation in sexually selected traits has the potential to improve theoretical models and reveal whether the genetic changes underlying phenotypic novelty utilize common or unique molecular mechanisms. Such a genomic approach to sexual selection will help answer questions in the evolution of sexually selected phenotypes that were first asked by Darwin and can furthermore serve as a model for the application of genomics in all areas of evolutionary biology. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

Limited evolutionary rescue of locally adapted populations facing climate change.

PubMed

Schiffers, Katja; Bourne, Elizabeth C; Lavergne, Sébastien; Thuiller, Wilfried; Travis, Justin M J

2013-01-19

Dispersal is a key determinant of a population's evolutionary potential. It facilitates the propagation of beneficial alleles throughout the distributional range of spatially outspread populations and increases the speed of adaptation. However, when habitat is heterogeneous and individuals are locally adapted, dispersal may, at the same time, reduce fitness through increasing maladaptation. Here, we use a spatially explicit, allelic simulation model to quantify how these equivocal effects of dispersal affect a population's evolutionary response to changing climate. Individuals carry a diploid set of chromosomes, with alleles coding for adaptation to non-climatic environmental conditions and climatic conditions, respectively. Our model results demonstrate that the interplay between gene flow and habitat heterogeneity may decrease effective dispersal and population size to such an extent that substantially reduces the likelihood of evolutionary rescue. Importantly, even when evolutionary rescue saves a population from extinction, its spatial range following climate change may be strongly narrowed, that is, the rescue is only partial. These findings emphasize that neglecting the impact of non-climatic, local adaptation might lead to a considerable overestimation of a population's evolvability under rapid environmental change.

Metapopulation dynamics and the evolution of dispersal

NASA Astrophysics Data System (ADS)

Parvinen, Kalle

A metapopulation consists of local populations living in habitat patches. In this chapter metapopulation dynamics and the evolution of dispersal is studied in two metapopulation models defined in discrete time. In the first model there are finitely many patches, and in the other one there are infinitely many patches, which allows to incorporate catastrophes into the model. In the first model, cyclic local population dynamics can be either synchronized or not, and increasing dispersal both synchronizes and stabilizes metapopulation dynamics. On the other hand, the type of dynamics has a strong effect on the evolution of dispersal. In case of non-synchronized metapopulation dynamics, dispersal is much more beneficial than in the case of synchronized metapopulation dynamics. Local dynamics has a substantial effect also on the possibility of evolutionary branching in both models. Furthermore, with an Allee effect in the local dynamics of the second model, even evolutionary suicide can occur. It is an evolutionary process in which a viable population adapts in such a way that it can no longer persist.

Using Evolutionary Theory to Guide Mental Health Research.

PubMed

Durisko, Zachary; Mulsant, Benoit H; McKenzie, Kwame; Andrews, Paul W

2016-03-01

Evolutionary approaches to medicine can shed light on the origins and etiology of disease. Such an approach may be especially useful in psychiatry, which frequently addresses conditions with heterogeneous presentation and unknown causes. We review several previous applications of evolutionary theory that highlight the ways in which psychiatric conditions may persist despite and because of natural selection. One lesson from the evolutionary approach is that some conditions currently classified as disorders (because they cause distress and impairment) may actually be caused by functioning adaptations operating "normally" (as designed by natural selection). Such conditions suggest an alternative illness model that may generate alternative intervention strategies. Thus, the evolutionary approach suggests that psychiatry should sometimes think differently about distress and impairment. The complexity of the human brain, including normal functioning and potential for dysfunctions, has developed over evolutionary time and has been shaped by natural selection. Understanding the evolutionary origins of psychiatric conditions is therefore a crucial component to a complete understanding of etiology. © The Author(s) 2016.

Using Evolutionary Theory to Guide Mental Health Research

PubMed Central

Mulsant, Benoit H.; McKenzie, Kwame; Andrews, Paul W.

2016-01-01

Evolutionary approaches to medicine can shed light on the origins and etiology of disease. Such an approach may be especially useful in psychiatry, which frequently addresses conditions with heterogeneous presentation and unknown causes. We review several previous applications of evolutionary theory that highlight the ways in which psychiatric conditions may persist despite and because of natural selection. One lesson from the evolutionary approach is that some conditions currently classified as disorders (because they cause distress and impairment) may actually be caused by functioning adaptations operating “normally” (as designed by natural selection). Such conditions suggest an alternative illness model that may generate alternative intervention strategies. Thus, the evolutionary approach suggests that psychiatry should sometimes think differently about distress and impairment. The complexity of the human brain, including normal functioning and potential for dysfunctions, has developed over evolutionary time and has been shaped by natural selection. Understanding the evolutionary origins of psychiatric conditions is therefore a crucial component to a complete understanding of etiology. PMID:27254091

A piecewise smooth model of evolutionary game for residential mobility and segregation

NASA Astrophysics Data System (ADS)

Radi, D.; Gardini, L.

2018-05-01

The paper proposes an evolutionary version of a Schelling-type dynamic system to model the patterns of residential segregation when two groups of people are involved. The payoff functions of agents are the individual preferences for integration which are empirically grounded. Differently from Schelling's model, where the limited levels of tolerance are the driving force of segregation, in the current setup agents benefit from integration. Despite the differences, the evolutionary model shows a dynamics of segregation that is qualitatively similar to the one of the classical Schelling's model: segregation is always a stable equilibrium, while equilibria of integration exist only for peculiar configurations of the payoff functions and their asymptotic stability is highly sensitive to parameter variations. Moreover, a rich variety of integrated dynamic behaviors can be observed. In particular, the dynamics of the evolutionary game is regulated by a one-dimensional piecewise smooth map with two kink points that is rigorously analyzed using techniques recently developed for piecewise smooth dynamical systems. The investigation reveals that when a stable internal equilibrium exists, the bimodal shape of the map leads to several different kinds of bifurcations, smooth, and border collision, in a complicated interplay. Our global analysis can give intuitions to be used by a social planner to maximize integration through social policies that manipulate people's preferences for integration.

Evolution of sparsity and modularity in a model of protein allostery

NASA Astrophysics Data System (ADS)

Hemery, Mathieu; Rivoire, Olivier

2015-04-01

The sequence of a protein is not only constrained by its physical and biochemical properties under current selection, but also by features of its past evolutionary history. Understanding the extent and the form that these evolutionary constraints may take is important to interpret the information in protein sequences. To study this problem, we introduce a simple but physical model of protein evolution where selection targets allostery, the functional coupling of distal sites on protein surfaces. This model shows how the geometrical organization of couplings between amino acids within a protein structure can depend crucially on its evolutionary history. In particular, two scenarios are found to generate a spatial concentration of functional constraints: high mutation rates and fluctuating selective pressures. This second scenario offers a plausible explanation for the high tolerance of natural proteins to mutations and for the spatial organization of their least tolerant amino acids, as revealed by sequence analysis and mutagenesis experiments. It also implies a faculty to adapt to new selective pressures that is consistent with observations. The model illustrates how several independent functional modules may emerge within the same protein structure, depending on the nature of past environmental fluctuations. Our model thus relates the evolutionary history of proteins to the geometry of their functional constraints, with implications for decoding and engineering protein sequences.

The Neural Systems of Forgiveness: An Evolutionary Psychological Perspective

PubMed Central

Billingsley, Joseph; Losin, Elizabeth A. R.

2017-01-01

Evolution-minded researchers posit that the suite of human cognitive adaptations may include forgiveness systems. According to these researchers, forgiveness systems regulate interpersonal motivation toward a transgressor in the wake of harm by weighing multiple factors that influence both the potential gains of future interaction with the transgressor and the likelihood of future harm. Although behavioral research generally supports this evolutionary model of forgiveness, the model’s claims have not been examined with available neuroscience specifically in mind, nor has recent neuroscientific research on forgiveness generally considered the evolutionary literature. The current review aims to help bridge this gap by using evolutionary psychology and cognitive neuroscience to mutually inform and interrogate one another. We briefly summarize the evolutionary research on forgiveness, then review recent neuroscientific findings on forgiveness in light of the evolutionary model. We emphasize neuroscientific research that links desire for vengeance to reward-based areas of the brain, that singles out prefrontal areas likely associated with inhibition of vengeful feelings, and that correlates the activity of a theory-of-mind network with assessments of the intentions and blameworthiness of those who commit harm. In addition, we identify gaps in the existing neuroscientific literature, and propose future research directions that might address them, at least in part. PMID:28539904

Applying Evolutionary Genetics to Developmental Toxicology and Risk Assessment

PubMed Central

Leung, Maxwell C. K.; Procter, Andrew C.; Goldstone, Jared V.; Foox, Jonathan; DeSalle, Robert; Mattingly, Carolyn J.; Siddall, Mark E.; Timme-Laragy, Alicia R.

2018-01-01

Evolutionary thinking continues to challenge our views on health and disease. Yet, there is a communication gap between evolutionary biologists and toxicologists in recognizing the connections among developmental pathways, high-throughput screening, and birth defects in humans. To increase our capability in identifying potential developmental toxicants in humans, we propose to apply evolutionary genetics to improve the experimental design and data interpretation with various in vitro and whole-organism models. We review five molecular systems of stress response and update 18 consensual cell-cell signaling pathways that are the hallmark for early development, organogenesis, and differentiation; and revisit the principles of teratology in light of recent advances in high-throughput screening, big data techniques, and systems toxicology. Multiscale systems modeling plays an integral role in the evolutionary approach to cross-species extrapolation. Phylogenetic analysis and comparative bioinformatics are both valuable tools in identifying and validating the molecular initiating events that account for adverse developmental outcomes in humans. The discordance of susceptibility between test species and humans (ontogeny) reflects their differences in evolutionary history (phylogeny). This synthesis not only can lead to novel applications in developmental toxicity and risk assessment, but also can pave the way for applying an evo-devo perspective to the study of developmental origins of health and disease. PMID:28267574

Enzyme sequence similarity improves the reaction alignment method for cross-species pathway comparison

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ovacik, Meric A.; Androulakis, Ioannis P., E-mail: yannis@rci.rutgers.edu; Biomedical Engineering Department, Rutgers University, Piscataway, NJ 08854

2013-09-15

Pathway-based information has become an important source of information for both establishing evolutionary relationships and understanding the mode of action of a chemical or pharmaceutical among species. Cross-species comparison of pathways can address two broad questions: comparison in order to inform evolutionary relationships and to extrapolate species differences used in a number of different applications including drug and toxicity testing. Cross-species comparison of metabolic pathways is complex as there are multiple features of a pathway that can be modeled and compared. Among the various methods that have been proposed, reaction alignment has emerged as the most successful at predicting phylogeneticmore » relationships based on NCBI taxonomy. We propose an improvement of the reaction alignment method by accounting for sequence similarity in addition to reaction alignment method. Using nine species, including human and some model organisms and test species, we evaluate the standard and improved comparison methods by analyzing glycolysis and citrate cycle pathways conservation. In addition, we demonstrate how organism comparison can be conducted by accounting for the cumulative information retrieved from nine pathways in central metabolism as well as a more complete study involving 36 pathways common in all nine species. Our results indicate that reaction alignment with enzyme sequence similarity results in a more accurate representation of pathway specific cross-species similarities and differences based on NCBI taxonomy.« less

Colour spaces in ecology and evolutionary biology.

PubMed

Renoult, Julien P; Kelber, Almut; Schaefer, H Martin

2017-02-01

The recognition that animals sense the world in a different way than we do has unlocked important lines of research in ecology and evolutionary biology. In practice, the subjective study of natural stimuli has been permitted by perceptual spaces, which are graphical models of how stimuli are perceived by a given animal. Because colour vision is arguably the best-known sensory modality in most animals, a diversity of colour spaces are now available to visual ecologists, ranging from generalist and basic models allowing rough but robust predictions on colour perception, to species-specific, more complex models giving accurate but context-dependent predictions. Selecting among these models is most often influenced by historical contingencies that have associated models to specific questions and organisms; however, these associations are not always optimal. The aim of this review is to provide visual ecologists with a critical perspective on how models of colour space are built, how well they perform and where their main limitations are with regard to their most frequent uses in ecology and evolutionary biology. We propose a classification of models based on their complexity, defined as whether and how they model the mechanisms of chromatic adaptation and receptor opponency, the nonlinear association between the stimulus and its perception, and whether or not models have been fitted to experimental data. Then, we review the effect of modelling these mechanisms on predictions of colour detection and discrimination, colour conspicuousness, colour diversity and diversification, and for comparing the perception of colour traits between distinct perceivers. While a few rules emerge (e.g. opponent log-linear models should be preferred when analysing very distinct colours), in general model parameters still have poorly known effects. Colour spaces have nonetheless permitted significant advances in ecology and evolutionary biology, and more progress is expected if ecologists compare results between models and perform behavioural experiments more routinely. Such an approach would further contribute to a better understanding of colour vision and its links to the behavioural ecology of animals. While visual ecology is essentially a transfer of knowledge from visual sciences to evolutionary ecology, we hope that the discipline will benefit both fields more evenly in the future. © 2015 Cambridge Philosophical Society.

Evolutionary stability concepts in a stochastic environment

NASA Astrophysics Data System (ADS)

Zheng, Xiu-Deng; Li, Cong; Lessard, Sabin; Tao, Yi

2017-09-01

Over the past 30 years, evolutionary game theory and the concept of an evolutionarily stable strategy have been not only extensively developed and successfully applied to explain the evolution of animal behaviors, but also widely used in economics and social sciences. Nonetheless, the stochastic dynamical properties of evolutionary games in randomly fluctuating environments are still unclear. In this study, we investigate conditions for stochastic local stability of fixation states and constant interior equilibria in a two-phenotype model with random payoffs following pairwise interactions. Based on this model, we develop the concepts of stochastic evolutionary stability (SES) and stochastic convergence stability (SCS). We show that the condition for a pure strategy to be SES and SCS is more stringent than in a constant environment, while the condition for a constant mixed strategy to be SES is less stringent than the condition to be SCS, which is less stringent than the condition in a constant environment.

Selection on Network Dynamics Drives Differential Rates of Protein Domain Evolution

PubMed Central

Mannakee, Brian K.; Gutenkunst, Ryan N.

2016-01-01

The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein’s rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical perturbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate within networks in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces. PMID:27380265

Evolutionary transitions towards eusociality in snapping shrimps.

PubMed

Chak, Solomon Tin Chi; Duffy, J Emmett; Hultgren, Kristin M; Rubenstein, Dustin R

2017-03-20

Animal social organization varies from complex societies where reproduction is dominated by a single individual (eusociality) to those where reproduction is more evenly distributed among group members (communal breeding). Yet, how simple groups transition evolutionarily to more complex societies remains unclear. Competing hypotheses suggest that eusociality and communal breeding are alternative evolutionary endpoints, or that communal breeding is an intermediate stage in the transition towards eusociality. We tested these alternative hypotheses in sponge-dwelling shrimps, Synalpheus spp. Although species varied continuously in reproductive skew, they clustered into pair-forming, communal and eusocial categories based on several demographic traits. Evolutionary transition models suggested that eusocial and communal species are discrete evolutionary endpoints that evolved independently from pair-forming ancestors along alternative paths. This 'family-centred' origin of eusociality parallels observations in insects and vertebrates, reinforcing the role of kin selection in the evolution of eusociality and suggesting a general model of animal social evolution.

Development of X-TOOLSS: Preliminary Design of Space Systems Using Evolutionary Computation

NASA Technical Reports Server (NTRS)

Schnell, Andrew R.; Hull, Patrick V.; Turner, Mike L.; Dozier, Gerry; Alverson, Lauren; Garrett, Aaron; Reneau, Jarred

2008-01-01

Evolutionary computational (EC) techniques such as genetic algorithms (GA) have been identified as promising methods to explore the design space of mechanical and electrical systems at the earliest stages of design. In this paper the authors summarize their research in the use of evolutionary computation to develop preliminary designs for various space systems. An evolutionary computational solver developed over the course of the research, X-TOOLSS (Exploration Toolset for the Optimization of Launch and Space Systems) is discussed. With the success of early, low-fidelity example problems, an outline of work involving more computationally complex models is discussed.

New paradigms in clonal evolution: punctuated equilibrium in cancer.

PubMed

Cross, William Ch; Graham, Trevor A; Wright, Nicholas A

2016-10-01

Evolutionary theories are themselves subject to evolution. Clonal evolution - the model that describes the initiation and progression of cancer - is entering a period of profound change, brought about largely by technological developments in genome analysis. A flurry of recent publications, using modern mathematical and bioinformatics techniques, have revealed both punctuated and neutral evolution phenomena that are poorly explained by the conventional graduated perspectives. In this review, we propose that a hybrid model, inspired by the evolutionary model of punctuated equilibrium, could better explain these recent observations. We also discuss the conceptual changes and clinical implications of variable evolutionary tempos. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Effects of anisotropy on interacting ghost dark energy in Brans-Dicke theories

NASA Astrophysics Data System (ADS)

Hossienkhani, H.; Fayaz, V.; Azimi, N.

2017-03-01

In this work we concentrate on the ghost dark energy model within the framework of the Brans-Dicke theory in an anisotropic Universe. Within this framework we discuss the behavior of equation of state, deceleration and dark energy density parameters of the model. We consider the squared sound speed and quest for signs of stability of the model. We also probe observational constraints by using the latest observational data on the ghost dark energy models as the unification of dark matter and dark energy. In order to do so, we focus on observational determinations of the Hubble expansion rate (namely, the expansion history) H(z). Then we evaluate the evolution of the growth of perturbations in the linear regime for both ghost DE and Brans-Dicke theory and compare the results with standard FRW and ΛCDM models. We display the effects of the anisotropy on the evolutionary behavior the ghost DE models where the growth rate is higher in this models. Eventually the growth factor for the ΛCDM Universe will always fall behind the ghost DE models in an anisotropic Universe.

A new bio-inspired, population-level approach to the socioeconomic evolution of dynamic spectrum access services

NASA Astrophysics Data System (ADS)

Horvath, Denis; Gazda, Juraj; Brutovsky, Branislav

Evolutionary species and quasispecies models provide the universal and flexible basis for a large-scale description of the dynamics of evolutionary systems, which can be built conceived as a constraint satisfaction dynamics. It represents a general framework to design and study many novel, technologically contemporary models and their variants. Here, we apply the classical quasispecies concept to model the emerging dynamic spectrum access (DSA) markets. The theory describes the mechanisms of mimetic transfer, competitive interactions between socioeconomic strata of the end-users, their perception of the utility and inter-operator switching in the variable technological environments of the operators offering the wireless spectrum services. The algorithmization and numerical modeling demonstrate the long-term evolutionary socioeconomic changes which reflect the end-user preferences and results of the majorization of their irrational decisions in the same manner as the prevailing tendencies which are embodied in the efficient market hypothesis.

LS³: A Method for Improving Phylogenomic Inferences When Evolutionary Rates Are Heterogeneous among Taxa

PubMed Central

Rivera-Rivera, Carlos J.; Montoya-Burgos, Juan I.

2016-01-01

Phylogenetic inference artifacts can occur when sequence evolution deviates from assumptions made by the models used to analyze them. The combination of strong model assumption violations and highly heterogeneous lineage evolutionary rates can become problematic in phylogenetic inference, and lead to the well-described long-branch attraction (LBA) artifact. Here, we define an objective criterion for assessing lineage evolutionary rate heterogeneity among predefined lineages: the result of a likelihood ratio test between a model in which the lineages evolve at the same rate (homogeneous model) and a model in which different lineage rates are allowed (heterogeneous model). We implement this criterion in the algorithm Locus Specific Sequence Subsampling (LS³), aimed at reducing the effects of LBA in multi-gene datasets. For each gene, LS³ sequentially removes the fastest-evolving taxon of the ingroup and tests for lineage rate homogeneity until all lineages have uniform evolutionary rates. The sequences excluded from the homogeneously evolving taxon subset are flagged as potentially problematic. The software implementation provides the user with the possibility to remove the flagged sequences for generating a new concatenated alignment. We tested LS³ with simulations and two real datasets containing LBA artifacts: a nucleotide dataset regarding the position of Glires within mammals and an amino-acid dataset concerning the position of nematodes within bilaterians. The initially incorrect phylogenies were corrected in all cases upon removing data flagged by LS³. PMID:26912812

Polymorphic Evolutionary Games.

PubMed

Fishman, Michael A

2016-06-07

In this paper, I present an analytical framework for polymorphic evolutionary games suitable for explicitly modeling evolutionary processes in diploid populations with sexual reproduction. The principal aspect of the proposed approach is adding diploid genetics cum sexual recombination to a traditional evolutionary game, and switching from phenotypes to haplotypes as the new game׳s pure strategies. Here, the relevant pure strategy׳s payoffs derived by summing the payoffs of all the phenotypes capable of producing gametes containing that particular haplotype weighted by the pertinent probabilities. The resulting game is structurally identical to the familiar Evolutionary Games with non-linear pure strategy payoffs (Hofbauer and Sigmund, 1998. Cambridge University Press), and can be analyzed in terms of an established analytical framework for such games. And these results can be translated into the terms of genotypic, and whence, phenotypic evolutionary stability pertinent to the original game. Copyright © 2016 Elsevier Ltd. All rights reserved.

Phylogenetic Analysis Supports the Aerobic-Capacity Model for the Evolution of Endothermy.

PubMed

Nespolo, Roberto F; Solano-Iguaran, Jaiber J; Bozinovic, Francisco

2017-01-01

The evolution of endothermy is a controversial topic in evolutionary biology, although several hypotheses have been proposed to explain it. To a great extent, the debate has centered on the aerobic-capacity model (AC model), an adaptive hypothesis involving maximum and resting rates of metabolism (MMR and RMR, respectively; hereafter "metabolic traits"). The AC model posits that MMR, a proxy of aerobic capacity and sustained activity, is the target of directional selection and that RMR is also influenced as a correlated response. Associated with this reasoning are the assumptions that (1) factorial aerobic scope (FAS; MMR/RMR) and net aerobic scope (NAS; MMR - RMR), two commonly used indexes of aerobic capacity, show different evolutionary optima and (2) the functional link between MMR and RMR is a basic design feature of vertebrates. To test these assumptions, we performed a comparative phylogenetic analysis in 176 vertebrate species, ranging from fish and amphibians to birds and mammals. Using disparity-through-time analysis, we also explored trait diversification and fitted different evolutionary models to study the evolution of metabolic traits. As predicted, we found (1) a positive phylogenetic correlation between RMR and MMR, (2) diversification of metabolic traits exceeding that of random-walk expectations, (3) that a model assuming selection fits the data better than alternative models, and (4) that a single evolutionary optimum best fits FAS data, whereas a model involving two optima (one for ectotherms and another for endotherms) is the best explanatory model for NAS. These results support the AC model and give novel information concerning the mode and tempo of physiological evolution of vertebrates.

Spatial evolutionary epidemiology of spreading epidemics

PubMed Central

2016-01-01

Most spatial models of host–parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation. PMID:27798295

Spatial evolutionary epidemiology of spreading epidemics.

PubMed

Lion, S; Gandon, S

2016-10-26

Most spatial models of host-parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation. © 2016 The Author(s).

Evolutionary contributions to solving the "matrilineal puzzle": a test of Holden, Sear, and Mace's model.

PubMed

Mattison, Siobhán M

2011-07-01

Matriliny has long been debated by anthropologists positing either its primitive or its puzzling nature. More recently, evolutionary anthropologists have attempted to recast matriliny as an adaptive solution to modern social and ecological environments, tying together much of what was known to be associated with matriliny. This paper briefly reviews the major anthropological currents in studies of matriliny and discusses the contribution of evolutionary anthropology to this body of literature. It discusses the utility of an evolutionary framework in the context of the first independent test of Holden et al.'s 2003 model of matriliny as daughter-biased investment. It finds that historical daughter-biased transmission of land among the Mosuo is consistent with the model, whereas current income transmission is not. In both cases, resources had equivalent impacts on male and female reproduction, a result which predicts daughter-biased resource transmission given any nonzero level of paternity uncertainty. However, whereas land was transmitted traditionally to daughters, income today is invested in both sexes. Possible reasons for this discrepancy are discussed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neugent, Kathryn F.; Massey, Philip; Skiff, Brian

Due to their transitionary nature, yellow supergiants (YSGs) provide a critical challenge for evolutionary modeling. Previous studies within M31 and the Small Magellanic Cloud show that the Geneva evolutionary models do a poor job at predicting the lifetimes of these short-lived stars. Here, we extend this study to the Large Magellanic Cloud (LMC) while also investigating the galaxy's red supergiant (RSG) content. This task is complicated by contamination by Galactic foreground stars that color and magnitude criteria alone cannot weed out. Therefore, we use proper-motions and the LMC's large systemic radial velocity ({approx}278 km s{sup -1}) to separate out thesemore » foreground dwarfs. After observing nearly 2000 stars, we identified 317 probable YSGs, 6 possible YSGs, and 505 probable RSGs. Foreground contamination of our YSG sample was {approx}80%, while that of the RSG sample was only 3%. By placing the YSGs on the Hertzsprung-Russell diagram and comparing them against the evolutionary tracks, we find that new Geneva evolutionary models do an exemplary job at predicting both the locations and the lifetimes of these transitory objects.« less

Estimating the ratios of the stationary distribution values for Markov chains modeling evolutionary algorithms.

PubMed

Mitavskiy, Boris; Cannings, Chris

2009-01-01

The evolutionary algorithm stochastic process is well-known to be Markovian. These have been under investigation in much of the theoretical evolutionary computing research. When the mutation rate is positive, the Markov chain modeling of an evolutionary algorithm is irreducible and, therefore, has a unique stationary distribution. Rather little is known about the stationary distribution. In fact, the only quantitative facts established so far tell us that the stationary distributions of Markov chains modeling evolutionary algorithms concentrate on uniform populations (i.e., those populations consisting of a repeated copy of the same individual). At the same time, knowing the stationary distribution may provide some information about the expected time it takes for the algorithm to reach a certain solution, assessment of the biases due to recombination and selection, and is of importance in population genetics to assess what is called a "genetic load" (see the introduction for more details). In the recent joint works of the first author, some bounds have been established on the rates at which the stationary distribution concentrates on the uniform populations. The primary tool used in these papers is the "quotient construction" method. It turns out that the quotient construction method can be exploited to derive much more informative bounds on ratios of the stationary distribution values of various subsets of the state space. In fact, some of the bounds obtained in the current work are expressed in terms of the parameters involved in all the three main stages of an evolutionary algorithm: namely, selection, recombination, and mutation.

Time Series Expression Analyses Using RNA-seq: A Statistical Approach

PubMed Central

Oh, Sunghee; Song, Seongho; Grabowski, Gregory; Zhao, Hongyu; Noonan, James P.

2013-01-01

RNA-seq is becoming the de facto standard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis. PMID:23586021

Time series expression analyses using RNA-seq: a statistical approach.

PubMed

Oh, Sunghee; Song, Seongho; Grabowski, Gregory; Zhao, Hongyu; Noonan, James P

2013-01-01

RNA-seq is becoming the de facto standard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis.

NeXML: rich, extensible, and verifiable representation of comparative data and metadata.

PubMed

Vos, Rutger A; Balhoff, James P; Caravas, Jason A; Holder, Mark T; Lapp, Hilmar; Maddison, Wayne P; Midford, Peter E; Priyam, Anurag; Sukumaran, Jeet; Xia, Xuhua; Stoltzfus, Arlin

2012-07-01

In scientific research, integration and synthesis require a common understanding of where data come from, how much they can be trusted, and what they may be used for. To make such an understanding computer-accessible requires standards for exchanging richly annotated data. The challenges of conveying reusable data are particularly acute in regard to evolutionary comparative analysis, which comprises an ever-expanding list of data types, methods, research aims, and subdisciplines. To facilitate interoperability in evolutionary comparative analysis, we present NeXML, an XML standard (inspired by the current standard, NEXUS) that supports exchange of richly annotated comparative data. NeXML defines syntax for operational taxonomic units, character-state matrices, and phylogenetic trees and networks. Documents can be validated unambiguously. Importantly, any data element can be annotated, to an arbitrary degree of richness, using a system that is both flexible and rigorous. We describe how the use of NeXML by the TreeBASE and Phenoscape projects satisfies user needs that cannot be satisfied with other available file formats. By relying on XML Schema Definition, the design of NeXML facilitates the development and deployment of software for processing, transforming, and querying documents. The adoption of NeXML for practical use is facilitated by the availability of (1) an online manual with code samples and a reference to all defined elements and attributes, (2) programming toolkits in most of the languages used commonly in evolutionary informatics, and (3) input-output support in several widely used software applications. An active, open, community-based development process enables future revision and expansion of NeXML.

NeXML: Rich, Extensible, and Verifiable Representation of Comparative Data and Metadata

PubMed Central

Vos, Rutger A.; Balhoff, James P.; Caravas, Jason A.; Holder, Mark T.; Lapp, Hilmar; Maddison, Wayne P.; Midford, Peter E.; Priyam, Anurag; Sukumaran, Jeet; Xia, Xuhua; Stoltzfus, Arlin

2012-01-01

Abstract In scientific research, integration and synthesis require a common understanding of where data come from, how much they can be trusted, and what they may be used for. To make such an understanding computer-accessible requires standards for exchanging richly annotated data. The challenges of conveying reusable data are particularly acute in regard to evolutionary comparative analysis, which comprises an ever-expanding list of data types, methods, research aims, and subdisciplines. To facilitate interoperability in evolutionary comparative analysis, we present NeXML, an XML standard (inspired by the current standard, NEXUS) that supports exchange of richly annotated comparative data. NeXML defines syntax for operational taxonomic units, character-state matrices, and phylogenetic trees and networks. Documents can be validated unambiguously. Importantly, any data element can be annotated, to an arbitrary degree of richness, using a system that is both flexible and rigorous. We describe how the use of NeXML by the TreeBASE and Phenoscape projects satisfies user needs that cannot be satisfied with other available file formats. By relying on XML Schema Definition, the design of NeXML facilitates the development and deployment of software for processing, transforming, and querying documents. The adoption of NeXML for practical use is facilitated by the availability of (1) an online manual with code samples and a reference to all defined elements and attributes, (2) programming toolkits in most of the languages used commonly in evolutionary informatics, and (3) input–output support in several widely used software applications. An active, open, community-based development process enables future revision and expansion of NeXML. PMID:22357728

phyloXML: XML for evolutionary biology and comparative genomics

PubMed Central

Han, Mira V; Zmasek, Christian M

2009-01-01

Background Evolutionary trees are central to a wide range of biological studies. In many of these studies, tree nodes and branches need to be associated (or annotated) with various attributes. For example, in studies concerned with organismal relationships, tree nodes are associated with taxonomic names, whereas tree branches have lengths and oftentimes support values. Gene trees used in comparative genomics or phylogenomics are usually annotated with taxonomic information, genome-related data, such as gene names and functional annotations, as well as events such as gene duplications, speciations, or exon shufflings, combined with information related to the evolutionary tree itself. The data standards currently used for evolutionary trees have limited capacities to incorporate such annotations of different data types. Results We developed a XML language, named phyloXML, for describing evolutionary trees, as well as various associated data items. PhyloXML provides elements for commonly used items, such as branch lengths, support values, taxonomic names, and gene names and identifiers. By using "property" elements, phyloXML can be adapted to novel and unforeseen use cases. We also developed various software tools for reading, writing, conversion, and visualization of phyloXML formatted data. Conclusion PhyloXML is an XML language defined by a complete schema in XSD that allows storing and exchanging the structures of evolutionary trees as well as associated data. More information about phyloXML itself, the XSD schema, as well as tools implementing and supporting phyloXML, is available at . PMID:19860910

Evolution of complex life cycles in trophically transmitted helminths. I. Host incorporation and trophic ascent.

PubMed

Parker, G A; Ball, M A; Chubb, J C

2015-02-01

Links between parasites and food webs are evolutionarily ancient but dynamic: life history theory provides insights into helminth complex life cycle origins. Most adult helminths benefit by sexual reproduction in vertebrates, often high up food chains, but direct infection is commonly constrained by a trophic vacuum between free-living propagules and definitive hosts. Intermediate hosts fill this vacuum, facilitating transmission to definitive hosts. The central question concerns why sexual reproduction, and sometimes even larval growth, is suppressed in intermediate hosts, favouring growth arrest at larval maturity in intermediate hosts and reproductive suppression until transmission to definitive hosts? Increased longevity and higher growth in definitive hosts can generate selection for larger parasite body size and higher fecundity at sexual maturity. Life cycle length is increased by two evolutionary mechanisms, upward and downward incorporation, allowing simple (one-host) cycles to become complex (multihost). In downward incorporation, an intermediate host is added below the definitive host: models suggest that downward incorporation probably evolves only after ecological or evolutionary perturbations create a trophic vacuum. In upward incorporation, a new definitive host is added above the original definitive host, which subsequently becomes an intermediate host, again maintained by the trophic vacuum: theory suggests that this is plausible even under constant ecological/evolutionary conditions. The final cycle is similar irrespective of its origin (upward or downward). Insights about host incorporation are best gained by linking comparative phylogenetic analyses (describing evolutionary history) with evolutionary models (examining selective forces). Ascent of host trophic levels and evolution of optimal host taxa ranges are discussed. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

The sociobiology of genes: the gene's eye view as a unifying behavioural-ecological framework for biological evolution.

PubMed

De Tiège, Alexis; Van de Peer, Yves; Braeckman, Johan; Tanghe, Koen B

2017-11-22

Although classical evolutionary theory, i.e., population genetics and the Modern Synthesis, was already implicitly 'gene-centred', the organism was, in practice, still generally regarded as the individual unit of which a population is composed. The gene-centred approach to evolution only reached a logical conclusion with the advent of the gene-selectionist or gene's eye view in the 1960s and 1970s. Whereas classical evolutionary theory can only work with (genotypically represented) fitness differences between individual organisms, gene-selectionism is capable of working with fitness differences among genes within the same organism and genome. Here, we explore the explanatory potential of 'intra-organismic' and 'intra-genomic' gene-selectionism, i.e., of a behavioural-ecological 'gene's eye view' on genetic, genomic and organismal evolution. First, we give a general outline of the framework and how it complements the-to some extent-still 'organism-centred' approach of classical evolutionary theory. Secondly, we give a more in-depth assessment of its explanatory potential for biological evolution, i.e., for Darwin's 'common descent with modification' or, more specifically, for 'historical continuity or homology with modular evolutionary change' as it has been studied by evolutionary developmental biology (evo-devo) during the last few decades. In contrast with classical evolutionary theory, evo-devo focuses on 'within-organism' developmental processes. Given the capacity of gene-selectionism to adopt an intra-organismal gene's eye view, we outline the relevance of the latter model for evo-devo. Overall, we aim for the conceptual integration between the gene's eye view on the one hand, and more organism-centred evolutionary models (both classical evolutionary theory and evo-devo) on the other.

The Simulation and Analysis of an Evolutionary Model of Deoxyribonucleic Acid (DNA).

DTIC Science & Technology

1983-09-01

current interest in evolutionary biology . This section identifies the organization of the remainder of the paper. The second chapter reports the...the field of evolutionary biology . 77 APPENDIX 78 APPENDIX A PROGRAM SOURCE LISTING -79 PROGRAM SOURCE LISTING 00005 PROGRAM (COMPUTERANDOM MUTATIONS...34Some Theoretical Aspects of the Problem of Life Origin," Journal 2f Theoreical Biology : 13-23, 1975. 27. Chirpich, Thomas P. "Rates of Protein

Sex-Specific Pathways to Early Puberty, Sexual Debut, and Sexual Risk Taking: Tests of an Integrated Evolutionary-Developmental Model

ERIC Educational Resources Information Center

James, Jenee; Ellis, Bruce J.; Schlomer, Gabriel L.; Garber, Judy

2012-01-01

The current study tested sex-specific pathways to early puberty, sexual debut, and sexual risk taking, as specified by an integrated evolutionary-developmental model of adolescent sexual development and behavior. In a prospective study of 238 adolescents (n = 129 girls and n = 109 boys) followed from approximately 12-18 years of age, we tested for…

Binaries, cluster dynamics and population studies of stars and stellar phenomena

NASA Astrophysics Data System (ADS)

Vanbeveren, Dany

2005-10-01

The effects of binaries on population studies of stars and stellar phenomena have been investigated over the past 3 decades by many research groups. Here we will focus mainly on the work that has been done recently in Brussels and we will consider the following topics: the effect of binaries on overall galactic chemical evolutionary models and on the rates of different types of supernova, the population of point-like X-ray sources where we distinguish the standard high mass X-ray binaries and the ULXs, a UFO-scenario for the formation of WR+OB binaries in dense star systems. Finally we critically discuss the possible effect of rotation on population studies.

Using Nonlinear Stochastic Evolutionary Game Strategy to Model an Evolutionary Biological Network of Organ Carcinogenesis Under a Natural Selection Scheme

PubMed Central

Chen, Bor-Sen; Tsai, Kun-Wei; Li, Cheng-Wei

2015-01-01

Molecular biologists have long recognized carcinogenesis as an evolutionary process that involves natural selection. Cancer is driven by the somatic evolution of cell lineages. In this study, the evolution of somatic cancer cell lineages during carcinogenesis was modeled as an equilibrium point (ie, phenotype of attractor) shifting, the process of a nonlinear stochastic evolutionary biological network. This process is subject to intrinsic random fluctuations because of somatic genetic and epigenetic variations, as well as extrinsic disturbances because of carcinogens and stressors. In order to maintain the normal function (ie, phenotype) of an evolutionary biological network subjected to random intrinsic fluctuations and extrinsic disturbances, a network robustness scheme that incorporates natural selection needs to be developed. This can be accomplished by selecting certain genetic and epigenetic variations to modify the network structure to attenuate intrinsic fluctuations efficiently and to resist extrinsic disturbances in order to maintain the phenotype of the evolutionary biological network at an equilibrium point (attractor). However, during carcinogenesis, the remaining (or neutral) genetic and epigenetic variations accumulate, and the extrinsic disturbances become too large to maintain the normal phenotype at the desired equilibrium point for the nonlinear evolutionary biological network. Thus, the network is shifted to a cancer phenotype at a new equilibrium point that begins a new evolutionary process. In this study, the natural selection scheme of an evolutionary biological network of carcinogenesis was derived from a robust negative feedback scheme based on the nonlinear stochastic Nash game strategy. The evolvability and phenotypic robustness criteria of the evolutionary cancer network were also estimated by solving a Hamilton–Jacobi inequality – constrained optimization problem. The simulation revealed that the phenotypic shift of the lung cancer-associated cell network takes 54.5 years from a normal state to stage I cancer, 1.5 years from stage I to stage II cancer, and 2.5 years from stage II to stage III cancer, with a reasonable match for the statistical result of the average age of lung cancer. These results suggest that a robust negative feedback scheme, based on a stochastic evolutionary game strategy, plays a critical role in an evolutionary biological network of carcinogenesis under a natural selection scheme. PMID:26244004

DOE Office of Scientific and Technical Information (OSTI.GOV)

MacDonald, James; Mullan, D. J.

KIC 7177553 is a quadruple system containing two binaries of orbital periods 16.5 and 18 days. All components have comparable masses and are slowly rotating with spectral types of ∼G2V. The longer period binary is eclipsing with component masses and radii M {sub 1} = 1.043 ± 0.014 M {sub ⊙}, R {sub 1} = 0.940 ± 0.005 R {sub ⊙} and M {sub 2} = 0.986 ± 0.015 M {sub ⊙}, R {sub 2} = 0.941 ± 0.005 R {sub ⊙}. The essentially equal radii measurements are inconsistent with the two stars being on the man sequence at themore » same age using standard nonmagnetic stellar evolution models. Instead a consistent scenario is found if the stars are in their pre-main-sequence phase of evolution and have an age of 32–36 Myr. We have also computed evolutionary models of magnetic stars, but we find that our nonmagnetic models fit the empirical radii and effective temperatures better than the magnetic models.« less

Mutation-selection balance in mixed mating populations.

PubMed

Kelly, John K

2007-05-21

An approximation to the average number of deleterious mutations per gamete, Q, is derived from a model allowing selection on both zygotes and male gametes. Progeny are produced by either outcrossing or self-fertilization with fixed probabilities. The genetic model is a standard in evolutionary biology: mutations occur at unlinked loci, have equivalent effects, and combine multiplicatively to determine fitness. The approximation developed here treats individual mutation counts with a generalized Poisson model conditioned on the distribution of selfing histories in the population. The approximation is accurate across the range of parameter sets considered and provides both analytical insights and greatly increased computational speed. Model predictions are discussed in relation to several outstanding problems, including the estimation of the genomic deleterious mutation rates (U), the generality of "selective interference" among loci, and the consequences of gametic selection for the joint distribution of inbreeding depression and mating system across species. Finally, conflicting results from previous analytical treatments of mutation-selection balance are resolved to assumptions about the life-cycle and the initial fate of mutations.

Fear and Loving in Las Vegas: Evolution, Emotion, and Persuasion

PubMed Central

Griskevicius, Vladas; Goldstein, Noah J.; Mortensen, Chad R.; Sundie, Jill M.; Cialdini, Robert B.; Kenrick, Douglas T.

2009-01-01

How do arousal-inducing contexts, such as frightening or romantic television programs, influence the effectiveness of basic persuasion heuristics? Different predictions are made by three theoretical models: A general arousal model predicts that arousal should increase effectiveness of heuristics; an affective valence model predicts that effectiveness should depend on whether the context elicits positive or negative affect; an evolutionary model predicts that persuasiveness should depend on both the specific emotion that is elicited and the content of the particular heuristic. Three experiments examined how fear-inducing versus romantic contexts influenced the effectiveness of two widely used heuristics—social proof (e.g., “most popular”) and scarcity (e.g., “limited edition”). Results supported predictions from an evolutionary model, showing that fear can lead scarcity appeals to be counter-persuasive, and that romantic desire can lead social proof appeals to be counter-persuasive. The findings highlight how an evolutionary theoretical approach can lead to novel theoretical and practical marketing insights. PMID:19727416

An improved shuffled frog leaping algorithm based evolutionary framework for currency exchange rate prediction

NASA Astrophysics Data System (ADS)

Dash, Rajashree

2017-11-01

Forecasting purchasing power of one currency with respect to another currency is always an interesting topic in the field of financial time series prediction. Despite the existence of several traditional and computational models for currency exchange rate forecasting, there is always a need for developing simpler and more efficient model, which will produce better prediction capability. In this paper, an evolutionary framework is proposed by using an improved shuffled frog leaping (ISFL) algorithm with a computationally efficient functional link artificial neural network (CEFLANN) for prediction of currency exchange rate. The model is validated by observing the monthly prediction measures obtained for three currency exchange data sets such as USD/CAD, USD/CHF, and USD/JPY accumulated within same period of time. The model performance is also compared with two other evolutionary learning techniques such as Shuffled frog leaping algorithm and Particle Swarm optimization algorithm. Practical analysis of results suggest that, the proposed model developed using the ISFL algorithm with CEFLANN network is a promising predictor model for currency exchange rate prediction compared to other models included in the study.

Phylotranscriptomic consolidation of the jawed vertebrate timetree.

PubMed

Irisarri, Iker; Baurain, Denis; Brinkmann, Henner; Delsuc, Frédéric; Sire, Jean-Yves; Kupfer, Alexander; Petersen, Jörn; Jarek, Michael; Meyer, Axel; Vences, Miguel; Philippe, Hervé

2017-09-01

Phylogenomics is extremely powerful but introduces new challenges as no agreement exists on "standards" for data selection, curation and tree inference. We use jawed vertebrates (Gnathostomata) as model to address these issues. Despite considerable efforts in resolving their evolutionary history and macroevolution, few studies have included a full phylogenetic diversity of gnathostomes and some relationships remain controversial. We tested a novel bioinformatic pipeline to assemble large and accurate phylogenomic datasets from RNA sequencing and find this phylotranscriptomic approach successful and highly cost-effective. Increased sequencing effort up to ca. 10Gbp allows recovering more genes, but shallower sequencing (1.5Gbp) is sufficient to obtain thousands of full-length orthologous transcripts. We reconstruct a robust and strongly supported timetree of jawed vertebrates using 7,189 nuclear genes from 100 taxa, including 23 new transcriptomes from previously unsampled key species. Gene jackknifing of genomic data corroborates the robustness of our tree and allows calculating genome-wide divergence times by overcoming gene sampling bias. Mitochondrial genomes prove insufficient to resolve the deepest relationships because of limited signal and among-lineage rate heterogeneity. Our analyses emphasize the importance of large curated nuclear datasets to increase the accuracy of phylogenomics and provide a reference framework for the evolutionary history of jawed vertebrates.

PGDD: a database of gene and genome duplication in plants

PubMed Central

Lee, Tae-Ho; Tang, Haibao; Wang, Xiyin; Paterson, Andrew H.

2013-01-01

Genome duplication (GD) has permanently shaped the architecture and function of many higher eukaryotic genomes. The angiosperms (flowering plants) are outstanding models in which to elucidate consequences of GD for higher eukaryotes, owing to their propensity for chromosomal duplication or even triplication in a few cases. Duplicated genome structures often require both intra- and inter-genome alignments to unravel their evolutionary history, also providing the means to deduce both obvious and otherwise-cryptic orthology, paralogy and other relationships among genes. The burgeoning sets of angiosperm genome sequences provide the foundation for a host of investigations into the functional and evolutionary consequences of gene and GD. To provide genome alignments from a single resource based on uniform standards that have been validated by empirical studies, we built the Plant Genome Duplication Database (PGDD; freely available at http://chibba.agtec.uga.edu/duplication/), a web service providing synteny information in terms of colinearity between chromosomes. At present, PGDD contains data for 26 plants including bryophytes and chlorophyta, as well as angiosperms with draft genome sequences. In addition to the inclusion of new genomes as they become available, we are preparing new functions to enhance PGDD. PMID:23180799

Fast and asymptotic computation of the fixation probability for Moran processes on graphs.

PubMed

Alcalde Cuesta, F; González Sequeiros, P; Lozano Rojo, Á

2015-03-01

Evolutionary dynamics has been classically studied for homogeneous populations, but now there is a growing interest in the non-homogeneous case. One of the most important models has been proposed in Lieberman et al. (2005), adapting to a weighted directed graph the process described in Moran (1958). The Markov chain associated with the graph can be modified by erasing all non-trivial loops in its state space, obtaining the so-called Embedded Markov chain (EMC). The fixation probability remains unchanged, but the expected time to absorption (fixation or extinction) is reduced. In this paper, we shall use this idea to compute asymptotically the average fixation probability for complete bipartite graphs K(n,m). To this end, we firstly review some recent results on evolutionary dynamics on graphs trying to clarify some points. We also revisit the 'Star Theorem' proved in Lieberman et al. (2005) for the star graphs K(1,m). Theoretically, EMC techniques allow fast computation of the fixation probability, but in practice this is not always true. Thus, in the last part of the paper, we compare this algorithm with the standard Monte Carlo method for some kind of complex networks. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Differences in boldness are repeatable and heritable in a long-lived marine predator

PubMed Central

Patrick, Samantha C; Charmantier, Anne; Weimerskirch, Henri

2013-01-01

Animal personalities, composed of axes of consistent individual behaviors, are widely reported and can have important fitness consequences. However, despite theoretical predictions that life-history trade-offs may cause and maintain personality differences, our understanding of the evolutionary ecology of personality remains poor, especially in long-lived species where trade-offs and senescence have been shown to be stronger. Furthermore, although much theoretical and empirical work assumes selection shapes variation in personalities, studies exploring the genetic underpinnings of personality traits are rare. Here we study one standard axis of personality, the shy–bold continuum, in a long-lived marine species, the wandering albatross from Possession Island, Crozet, by measuring the behavioral response to a human approach. Using generalized linear mixed models in a Bayesian framework, we show that boldness is highly repeatable and heritable. We also find strong differences in boldness between breeding colonies, which vary in size and density, suggesting birds are shyer in more dense colonies. These results demonstrate that in this seabird population, boldness is both heritable and repeatable and highlights the potential for ecological and evolutionary processes to shape personality traits in species with varying life-history strategies. PMID:24340172

Differences in boldness are repeatable and heritable in a long-lived marine predator.

PubMed

Patrick, Samantha C; Charmantier, Anne; Weimerskirch, Henri

2013-11-01

Animal personalities, composed of axes of consistent individual behaviors, are widely reported and can have important fitness consequences. However, despite theoretical predictions that life-history trade-offs may cause and maintain personality differences, our understanding of the evolutionary ecology of personality remains poor, especially in long-lived species where trade-offs and senescence have been shown to be stronger. Furthermore, although much theoretical and empirical work assumes selection shapes variation in personalities, studies exploring the genetic underpinnings of personality traits are rare. Here we study one standard axis of personality, the shy-bold continuum, in a long-lived marine species, the wandering albatross from Possession Island, Crozet, by measuring the behavioral response to a human approach. Using generalized linear mixed models in a Bayesian framework, we show that boldness is highly repeatable and heritable. We also find strong differences in boldness between breeding colonies, which vary in size and density, suggesting birds are shyer in more dense colonies. These results demonstrate that in this seabird population, boldness is both heritable and repeatable and highlights the potential for ecological and evolutionary processes to shape personality traits in species with varying life-history strategies.

Scientific Change as AN Evolutionary, Information Process: its Structural, Conceptual and Cultural Elements.

NASA Astrophysics Data System (ADS)

Al-Bustany, Fatin Khalil Ismail

1989-09-01

My aim in this dissertation is to develop an evolutionary conception of science based on recent studies in evolution theory, the thermodynamics of non-equilibrium and information theory, as exemplified in the works of Prigogine, Jantsch, Wicken and Gatlin. The nature of scientific change is of interest to philosophers and historians of science. Some construe it after a revolutionary model (e.g. Kuhn), others adopt an evolutionary view (e.g. Toulmin). It appears to me that it is possible to construct an evolutionary model encompassing the revolutionary mode as well. The following strategies are employed: (1) A distinction is made between two types of growth: one represents gradual change, the other designates radical transformations, and two principles underlying the process of change, one of conservation, the other of innovation. (2) Science in general, and scientific theories in particular, are looked upon as dissipative structures. These are characterised by openness, irreversibility and self-organisation. In terms of these, one may identify a state of "normal" growth and another of violent fluctuations leading to a new order (revolutionary phase). These fluctuations are generated by the flow of information coming from the observable world. The chief merits of this evolutionary model of the development of science lie in the emphasis it puts on the relation of science to its environment, in the description of scientific change as a process of interaction between internal and external elements (structural, conceptual, and cultural), in the enhancement of our understanding progress and rationality in science, and in the post Neo -Darwinian conception of evolution, stressing self-organisation, the innovativeness of the evolutionary process and the trend toward complexification. These features are also manifested in the process of discovery, which is a fundamental part of the scientific enterprise. In addition, a distinction is made between two types of discovery which serves as a criterion for delineating various episodes in the development of science. The evolutionary model further displays a complementarity mode of description on several levels: between science and its milieu, stability and instability, discovery and confirmation.

A dynamic parking charge optimal control model under perspective of commuters' evolutionary game behavior

NASA Astrophysics Data System (ADS)

Lin, XuXun; Yuan, PengCheng

2018-01-01

In this research we consider commuters' dynamic learning effect by modeling the trip mode choice behavior from a new perspective of dynamic evolutionary game theory. We explore the behavior pattern of different types of commuters and study the evolution path and equilibrium properties under different traffic conditions. We further establish a dynamic parking charge optimal control (referred to as DPCOC) model to alter commuters' trip mode choice while minimizing the total social cost. Numerical tests show. (1) Under fixed parking fee policy, the evolutionary results are completely decided by the travel time and the only method for public transit induction is to increase the parking charge price. (2) Compared with fixed parking fee policy, DPCOC policy proposed in this research has several advantages. Firstly, it can effectively turn the evolutionary path and evolutionary stable strategy to a better situation while minimizing the total social cost. Secondly, it can reduce the sensitivity of trip mode choice behavior to traffic congestion and improve the ability to resist interferences and emergencies. Thirdly, it is able to control the private car proportion to a stable state and make the trip behavior more predictable for the transportation management department. The research results can provide theoretical basis and decision-making references for commuters' mode choice prediction, dynamic setting of urban parking charge prices and public transit induction.

A test of genetic models for the evolutionary maintenance of same-sex sexual behaviour.

PubMed

Hoskins, Jessica L; Ritchie, Michael G; Bailey, Nathan W

2015-06-22

The evolutionary maintenance of same-sex sexual behaviour (SSB) has received increasing attention because it is perceived to be an evolutionary paradox. The genetic basis of SSB is almost wholly unknown in non-human animals, though this is key to understanding its persistence. Recent theoretical work has yielded broadly applicable predictions centred on two genetic models for SSB: overdominance and sexual antagonism. Using Drosophila melanogaster, we assayed natural genetic variation for male SSB and empirically tested predictions about the mode of inheritance and fitness consequences of alleles influencing its expression. We screened 50 inbred lines derived from a wild population for male-male courtship and copulation behaviour, and examined crosses between the lines for evidence of overdominance and antagonistic fecundity selection. Consistent variation among lines revealed heritable genetic variation for SSB, but the nature of the genetic variation was complex. Phenotypic and fitness variation was consistent with expectations under overdominance, although predictions of the sexual antagonism model were also supported. We found an unexpected and strong paternal effect on the expression of SSB, suggesting possible Y-linkage of the trait. Our results inform evolutionary genetic mechanisms that might maintain low but persistently observed levels of male SSB in D. melanogaster, but highlight a need for broader taxonomic representation in studies of its evolutionary causes. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Common evolutionary trends underlie the four-bar linkage systems of sunfish and mantis shrimp.

PubMed

Hu, Yinan; Nelson-Maney, Nathan; Anderson, Philip S L

2017-05-01

Comparative biomechanics offers an opportunity to explore the evolution of disparate biological systems that share common underlying mechanics. Four-bar linkage modeling has been applied to various biological systems such as fish jaws and crustacean appendages to explore the relationship between biomechanics and evolutionary diversification. Mechanical sensitivity states that the functional output of a mechanical system will show differential sensitivity to changes in specific morphological components. We document similar patterns of mechanical sensitivity in two disparate four-bar systems from different phyla: the opercular four-bar system in centrarchid fishes and the raptorial appendage of stomatopods. We built dynamic linkage models of 19 centrarchid and 36 stomatopod species and used phylogenetic generalized least squares regression (PGLS) to compare evolutionary shifts in linkage morphology and mechanical outputs derived from the models. In both systems, the kinematics of the four-bar mechanism show significant evolutionary correlation with the output link, while travel distance of the output arm is correlated with the coupler link. This common evolutionary pattern seen in both fish and crustacean taxa is a potential consequence of the mechanical principles underlying four-bar systems. Our results illustrate the potential influence of physical principles on morphological evolution across biological systems with different structures, behaviors, and ecologies. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

The Evolution of Different Forms of Sociality: Behavioral Mechanisms and Eco-Evolutionary Feedback

PubMed Central

van der Post, Daniel J.; Verbrugge, Rineke; Hemelrijk, Charlotte K.

2015-01-01

Different forms of sociality have evolved via unique evolutionary trajectories. However, it remains unknown to what extent trajectories of social evolution depend on the specific characteristics of different species. Our approach to studying such trajectories is to use evolutionary case-studies, so that we can investigate how grouping co-evolves with a multitude of individual characteristics. Here we focus on anti-predator vigilance and foraging. We use an individual-based model, where behavioral mechanisms are specified, and costs and benefits are not predefined. We show that evolutionary changes in grouping alter selection pressures on vigilance, and vice versa. This eco-evolutionary feedback generates an evolutionary progression from “leader-follower” societies to “fission-fusion” societies, where cooperative vigilance in groups is maintained via a balance between within- and between-group selection. Group-level selection is generated from an assortment that arises spontaneously when vigilant and non-vigilant foragers have different grouping tendencies. The evolutionary maintenance of small groups, and cooperative vigilance in those groups, is therefore achieved simultaneously. The evolutionary phases, and the transitions between them, depend strongly on behavioral mechanisms. Thus, integrating behavioral mechanisms and eco-evolutionary feedback is critical for understanding what kinds of intermediate stages are involved during the evolution of particular forms of sociality. PMID:25629313

The evolution of different forms of sociality: behavioral mechanisms and eco-evolutionary feedback.

PubMed

van der Post, Daniel J; Verbrugge, Rineke; Hemelrijk, Charlotte K

2015-01-01

Different forms of sociality have evolved via unique evolutionary trajectories. However, it remains unknown to what extent trajectories of social evolution depend on the specific characteristics of different species. Our approach to studying such trajectories is to use evolutionary case-studies, so that we can investigate how grouping co-evolves with a multitude of individual characteristics. Here we focus on anti-predator vigilance and foraging. We use an individual-based model, where behavioral mechanisms are specified, and costs and benefits are not predefined. We show that evolutionary changes in grouping alter selection pressures on vigilance, and vice versa. This eco-evolutionary feedback generates an evolutionary progression from "leader-follower" societies to "fission-fusion" societies, where cooperative vigilance in groups is maintained via a balance between within- and between-group selection. Group-level selection is generated from an assortment that arises spontaneously when vigilant and non-vigilant foragers have different grouping tendencies. The evolutionary maintenance of small groups, and cooperative vigilance in those groups, is therefore achieved simultaneously. The evolutionary phases, and the transitions between them, depend strongly on behavioral mechanisms. Thus, integrating behavioral mechanisms and eco-evolutionary feedback is critical for understanding what kinds of intermediate stages are involved during the evolution of particular forms of sociality.

NexGen PVAs: Incorporating Eco-Evolutionary Processes into Population Viability Models

EPA Science Inventory

We examine how the integration of evolutionary and ecological processes in population dynamics – an emerging framework in ecology – could be incorporated into population viability analysis (PVA). Driven by parallel, complementary advances in population genomics and computational ...

A case study of bats and white-nose syndrome demonstrating how to model population viability with evolutionary effects.

PubMed

Maslo, Brooke; Fefferman, Nina H

2015-08-01

Ecological factors generally affect population viability on rapid time scales. Traditional population viability analyses (PVA) therefore focus on alleviating ecological pressures, discounting potential evolutionary impacts on individual phenotypes. Recent studies of evolutionary rescue (ER) focus on cases in which severe, environmentally induced population bottlenecks trigger a rapid evolutionary response that can potentially reverse demographic threats. ER models have focused on shifting genetics and resulting population recovery, but no one has explored how to incorporate those findings into PVA. We integrated ER into PVA to identify the critical decision interval for evolutionary rescue (DIER) under which targeted conservation action should be applied to buffer populations undergoing ER against extinction from stochastic events and to determine the most appropriate vital rate to target to promote population recovery. We applied this model to little brown bats (Myotis lucifugus) affected by white-nose syndrome (WNS), a fungal disease causing massive declines in several North American bat populations. Under the ER scenario, the model predicted that the DIER period for little brown bats was within 11 years of initial WNS emergence, after which they stabilized at a positive growth rate (λ = 1.05). By comparing our model results with population trajectories of multiple infected hibernacula across the WNS range, we concluded that ER is a potential explanation of observed little brown bat population trajectories across multiple hibernacula within the affected range. Our approach provides a tool that can be used by all managers to provide testable hypotheses regarding the occurrence of ER in declining populations, suggest empirical studies to better parameterize the population genetics and conservation-relevant vital rates, and identify the DIER period during which management strategies will be most effective for species conservation. © 2015 Society for Conservation Biology.

The Ancient Evolutionary History of Polyomaviruses

PubMed Central

Buck, Christopher B.; Van Doorslaer, Koenraad; Peretti, Alberto; Geoghegan, Eileen M.; Tisza, Michael J.; An, Ping; Katz, Joshua P.; Pipas, James M.; McBride, Alison A.; Camus, Alvin C.; McDermott, Alexa J.; Dill, Jennifer A.; Delwart, Eric; Ng, Terry F. F.; Farkas, Kata; Austin, Charlotte; Kraberger, Simona; Davison, William; Pastrana, Diana V.; Varsani, Arvind

2016-01-01

Polyomaviruses are a family of DNA tumor viruses that are known to infect mammals and birds. To investigate the deeper evolutionary history of the family, we used a combination of viral metagenomics, bioinformatics, and structural modeling approaches to identify and characterize polyomavirus sequences associated with fish and arthropods. Analyses drawing upon the divergent new sequences indicate that polyomaviruses have been gradually co-evolving with their animal hosts for at least half a billion years. Phylogenetic analyses of individual polyomavirus genes suggest that some modern polyomavirus species arose after ancient recombination events involving distantly related polyomavirus lineages. The improved evolutionary model provides a useful platform for developing a more accurate taxonomic classification system for the viral family Polyomaviridae. PMID:27093155

Evolutionary and mechanistic theories of aging.

PubMed

Hughes, Kimberly A; Reynolds, Rose M

2005-01-01

Senescence (aging) is defined as a decline in performance and fitness with advancing age. Senescence is a nearly universal feature of multicellular organisms, and understanding why it occurs is a long-standing problem in biology. Here we present a concise review of both evolutionary and mechanistic theories of aging. We describe the development of the general evolutionary theory, along with the mutation accumulation, antagonistic pleiotropy, and disposable soma versions of the evolutionary model. The review of the mechanistic theories focuses on the oxidative stress resistance, cellular signaling, and dietary control mechanisms of life span extension. We close with a discussion of how an approach that makes use of both evolutionary and molecular analyses can address a critical question: Which of the mechanisms that can cause variation in aging actually do cause variation in natural populations?

Is specialization an evolutionary dead end? Testing for differences in speciation, extinction and trait transition rates across diverse phylogenies of specialists and generalists.

PubMed

Day, E H; Hua, X; Bromham, L

2016-06-01

Specialization has often been claimed to be an evolutionary dead end, with specialist lineages having a reduced capacity to persist or diversify. In a phylogenetic comparative framework, an evolutionary dead end may be detectable from the phylogenetic distribution of specialists, if specialists rarely give rise to large, diverse clades. Previous phylogenetic studies of the influence of specialization on macroevolutionary processes have demonstrated a range of patterns, including examples where specialists have both higher and lower diversification rates than generalists, as well as examples where the rates of evolutionary transitions from generalists to specialists are higher, lower or equal to transitions from specialists to generalists. Here, we wish to ask whether these varied answers are due to the differences in macroevolutionary processes in different clades, or partly due to differences in methodology. We analysed ten phylogenies containing multiple independent origins of specialization and quantified the phylogenetic distribution of specialists by applying a common set of metrics to all datasets. We compared the tip branch lengths of specialists to generalists, the size of specialist clades arising from each evolutionary origin of a specialized trait and whether specialists tend to be clustered or scattered on phylogenies. For each of these measures, we compared the observed values to expectations under null models of trait evolution and expected outcomes under alternative macroevolutionary scenarios. We found that specialization is sometimes an evolutionary dead end: in two of the ten case studies (pollinator-specific plants and host-specific flies), specialization is associated with a reduced rate of diversification or trait persistence. However, in the majority of studies, we could not distinguish the observed phylogenetic distribution of specialists from null models in which specialization has no effect on diversification or trait persistence. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

From computers to cultivation: reconceptualizing evolutionary psychology.

PubMed

Barrett, Louise; Pollet, Thomas V; Stulp, Gert

2014-01-01

Does evolutionary theorizing have a role in psychology? This is a more contentious issue than one might imagine, given that, as evolved creatures, the answer must surely be yes. The contested nature of evolutionary psychology lies not in our status as evolved beings, but in the extent to which evolutionary ideas add value to studies of human behavior, and the rigor with which these ideas are tested. This, in turn, is linked to the framework in which particular evolutionary ideas are situated. While the framing of the current research topic places the brain-as-computer metaphor in opposition to evolutionary psychology, the most prominent school of thought in this field (born out of cognitive psychology, and often known as the Santa Barbara school) is entirely wedded to the computational theory of mind as an explanatory framework. Its unique aspect is to argue that the mind consists of a large number of functionally specialized (i.e., domain-specific) computational mechanisms, or modules (the massive modularity hypothesis). Far from offering an alternative to, or an improvement on, the current perspective, we argue that evolutionary psychology is a mainstream computational theory, and that its arguments for domain-specificity often rest on shaky premises. We then go on to suggest that the various forms of e-cognition (i.e., embodied, embedded, enactive) represent a true alternative to standard computational approaches, with an emphasis on "cognitive integration" or the "extended mind hypothesis" in particular. We feel this offers the most promise for human psychology because it incorporates the social and historical processes that are crucial to human "mind-making" within an evolutionarily informed framework. In addition to linking to other research areas in psychology, this approach is more likely to form productive links to other disciplines within the social sciences, not least by encouraging a healthy pluralism in approach.

Viruses and mobile elements as drivers of evolutionary transitions

PubMed Central

2016-01-01

The history of life is punctuated by evolutionary transitions which engender emergence of new levels of biological organization that involves selection acting at increasingly complex ensembles of biological entities. Major evolutionary transitions include the origin of prokaryotic and then eukaryotic cells, multicellular organisms and eusocial animals. All or nearly all cellular life forms are hosts to diverse selfish genetic elements with various levels of autonomy including plasmids, transposons and viruses. I present evidence that, at least up to and including the origin of multicellularity, evolutionary transitions are driven by the coevolution of hosts with these genetic parasites along with sharing of ‘public goods’. Selfish elements drive evolutionary transitions at two distinct levels. First, mathematical modelling of evolutionary processes, such as evolution of primitive replicator populations or unicellular organisms, indicates that only increasing organizational complexity, e.g. emergence of multicellular aggregates, can prevent the collapse of the host–parasite system under the pressure of parasites. Second, comparative genomic analysis reveals numerous cases of recruitment of genes with essential functions in cellular life forms, including those that enable evolutionary transitions. This article is part of the themed issue ‘The major synthetic evolutionary transitions’. PMID:27431520

Viruses and mobile elements as drivers of evolutionary transitions.

PubMed

Koonin, Eugene V

2016-08-19

The history of life is punctuated by evolutionary transitions which engender emergence of new levels of biological organization that involves selection acting at increasingly complex ensembles of biological entities. Major evolutionary transitions include the origin of prokaryotic and then eukaryotic cells, multicellular organisms and eusocial animals. All or nearly all cellular life forms are hosts to diverse selfish genetic elements with various levels of autonomy including plasmids, transposons and viruses. I present evidence that, at least up to and including the origin of multicellularity, evolutionary transitions are driven by the coevolution of hosts with these genetic parasites along with sharing of 'public goods'. Selfish elements drive evolutionary transitions at two distinct levels. First, mathematical modelling of evolutionary processes, such as evolution of primitive replicator populations or unicellular organisms, indicates that only increasing organizational complexity, e.g. emergence of multicellular aggregates, can prevent the collapse of the host-parasite system under the pressure of parasites. Second, comparative genomic analysis reveals numerous cases of recruitment of genes with essential functions in cellular life forms, including those that enable evolutionary transitions.This article is part of the themed issue 'The major synthetic evolutionary transitions'. © 2016 The Authors.

Indirect evolutionary rescue: prey adapts, predator avoids extinction

PubMed Central

Yamamichi, Masato; Miner, Brooks E

2015-01-01

Recent studies have increasingly recognized evolutionary rescue (adaptive evolution that prevents extinction following environmental change) as an important process in evolutionary biology and conservation science. Researchers have concentrated on single species living in isolation, but populations in nature exist within communities of interacting species, so evolutionary rescue should also be investigated in a multispecies context. We argue that the persistence or extinction of a focal species can be determined solely by evolutionary change in an interacting species. We demonstrate that prey adaptive evolution can prevent predator extinction in two-species predator–prey models, and we derive the conditions under which this indirect evolutionary interaction is essential to prevent extinction following environmental change. A nonevolving predator can be rescued from extinction by adaptive evolution of its prey due to a trade-off for the prey between defense against predation and population growth rate. As prey typically have larger populations and shorter generations than their predators, prey evolution can be rapid and have profound effects on predator population dynamics. We suggest that this process, which we term ‘indirect evolutionary rescue’, has the potential to be critically important to the ecological and evolutionary responses of populations and communities to dramatic environmental change. PMID:26366196

A survey on evolutionary algorithm based hybrid intelligence in bioinformatics.

PubMed

Li, Shan; Kang, Liying; Zhao, Xing-Ming

2014-01-01

With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency. Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs) are widely used in various fields due to the efficiency and robustness of EAs. In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics. In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks.

An evolutionary morphological approach for software development cost estimation.

PubMed

Araújo, Ricardo de A; Oliveira, Adriano L I; Soares, Sergio; Meira, Silvio

2012-08-01

In this work we present an evolutionary morphological approach to solve the software development cost estimation (SDCE) problem. The proposed approach consists of a hybrid artificial neuron based on framework of mathematical morphology (MM) with algebraic foundations in the complete lattice theory (CLT), referred to as dilation-erosion perceptron (DEP). Also, we present an evolutionary learning process, called DEP(MGA), using a modified genetic algorithm (MGA) to design the DEP model, because a drawback arises from the gradient estimation of morphological operators in the classical learning process of the DEP, since they are not differentiable in the usual way. Furthermore, an experimental analysis is conducted with the proposed model using five complex SDCE problems and three well-known performance metrics, demonstrating good performance of the DEP model to solve SDCE problems. Copyright © 2012 Elsevier Ltd. All rights reserved.

The effect of climatic forcing on population synchrony and genetic structuring of the Canadian lynx

PubMed Central

Stenseth, Nils Chr.; Ehrich, Dorothee; Rueness, Eli Knispel; Lingjærde, Ole Chr.; Chan, Kung-Sik; Boutin, Stan; O'Donoghue, Mark; Robinson, David A.; Viljugrein, Hildegunn; Jakobsen, Kjetill S.

2004-01-01

The abundance of Canadian lynx follows 10-year density fluctuations across the Canadian subcontinent. These cyclic fluctuations have earlier been shown to be geographically structured into three climatic regions: the Atlantic, Continental, and Pacific zones. Recent genetic evidence revealed an essentially similar spatial structuring. Introducing a new population model, the “climate forcing of ecological and evolutionary patterns” model, we link the observed ecological and evolutionary patterns. Specifically, we demonstrate that there is greater phase synchrony within climatic zones than between them and show that external climatic forcing may act as a synchronizer. We simulated genetic drift by using data on population dynamics generated by the climate forcing of ecological and evolutionary patterns model, and we demonstrate that the observed genetic structuring can be seen as an emerging property of the spatiotemporal ecological dynamics. PMID:15067131

Advanced Targeting Cost Function Design for Evolutionary Optimization of Control of Logistic Equation

NASA Astrophysics Data System (ADS)

Senkerik, Roman; Zelinka, Ivan; Davendra, Donald; Oplatkova, Zuzana

2010-06-01

This research deals with the optimization of the control of chaos by means of evolutionary algorithms. This work is aimed on an explanation of how to use evolutionary algorithms (EAs) and how to properly define the advanced targeting cost function (CF) securing very fast and precise stabilization of desired state for any initial conditions. As a model of deterministic chaotic system, the one dimensional Logistic equation was used. The evolutionary algorithm Self-Organizing Migrating Algorithm (SOMA) was used in four versions. For each version, repeated simulations were conducted to outline the effectiveness and robustness of used method and targeting CF.

A general relativistic rotating evolutionary universe—Part II

NASA Astrophysics Data System (ADS)

Berman, Marcelo Samuel

2008-06-01

As a sequel to Berman (Astrophys. Space Sci., 2008b), we show that the rotation of the Universe can be dealt by generalised Gaussian metrics, defined in this paper. Robertson-Walker’s metric has been employed with proper-time, in its standard applications; the generalised Gaussian metric implies in the use of a non-constant temporal metric coefficient modifying Robertson-Walker’s standard form. Experimental predictions are made.

Assessing variation in life-history tactics within a population using mixture regression models: a practical guide for evolutionary ecologists.

PubMed

Hamel, Sandra; Yoccoz, Nigel G; Gaillard, Jean-Michel

2017-05-01

Mixed models are now well-established methods in ecology and evolution because they allow accounting for and quantifying within- and between-individual variation. However, the required normal distribution of the random effects can often be violated by the presence of clusters among subjects, which leads to multi-modal distributions. In such cases, using what is known as mixture regression models might offer a more appropriate approach. These models are widely used in psychology, sociology, and medicine to describe the diversity of trajectories occurring within a population over time (e.g. psychological development, growth). In ecology and evolution, however, these models are seldom used even though understanding changes in individual trajectories is an active area of research in life-history studies. Our aim is to demonstrate the value of using mixture models to describe variation in individual life-history tactics within a population, and hence to promote the use of these models by ecologists and evolutionary ecologists. We first ran a set of simulations to determine whether and when a mixture model allows teasing apart latent clustering, and to contrast the precision and accuracy of estimates obtained from mixture models versus mixed models under a wide range of ecological contexts. We then used empirical data from long-term studies of large mammals to illustrate the potential of using mixture models for assessing within-population variation in life-history tactics. Mixture models performed well in most cases, except for variables following a Bernoulli distribution and when sample size was small. The four selection criteria we evaluated [Akaike information criterion (AIC), Bayesian information criterion (BIC), and two bootstrap methods] performed similarly well, selecting the right number of clusters in most ecological situations. We then showed that the normality of random effects implicitly assumed by evolutionary ecologists when using mixed models was often violated in life-history data. Mixed models were quite robust to this violation in the sense that fixed effects were unbiased at the population level. However, fixed effects at the cluster level and random effects were better estimated using mixture models. Our empirical analyses demonstrated that using mixture models facilitates the identification of the diversity of growth and reproductive tactics occurring within a population. Therefore, using this modelling framework allows testing for the presence of clusters and, when clusters occur, provides reliable estimates of fixed and random effects for each cluster of the population. In the presence or expectation of clusters, using mixture models offers a suitable extension of mixed models, particularly when evolutionary ecologists aim at identifying how ecological and evolutionary processes change within a population. Mixture regression models therefore provide a valuable addition to the statistical toolbox of evolutionary ecologists. As these models are complex and have their own limitations, we provide recommendations to guide future users. © 2016 Cambridge Philosophical Society.

Using evolutionary computations to understand the design and evolution of gene and cell regulatory networks.

PubMed

Spirov, Alexander; Holloway, David

2013-07-15

This paper surveys modeling approaches for studying the evolution of gene regulatory networks (GRNs). Modeling of the design or 'wiring' of GRNs has become increasingly common in developmental and medical biology, as a means of quantifying gene-gene interactions, the response to perturbations, and the overall dynamic motifs of networks. Drawing from developments in GRN 'design' modeling, a number of groups are now using simulations to study how GRNs evolve, both for comparative genomics and to uncover general principles of evolutionary processes. Such work can generally be termed evolution in silico. Complementary to these biologically-focused approaches, a now well-established field of computer science is Evolutionary Computations (ECs), in which highly efficient optimization techniques are inspired from evolutionary principles. In surveying biological simulation approaches, we discuss the considerations that must be taken with respect to: (a) the precision and completeness of the data (e.g. are the simulations for very close matches to anatomical data, or are they for more general exploration of evolutionary principles); (b) the level of detail to model (we proceed from 'coarse-grained' evolution of simple gene-gene interactions to 'fine-grained' evolution at the DNA sequence level); (c) to what degree is it important to include the genome's cellular context; and (d) the efficiency of computation. With respect to the latter, we argue that developments in computer science EC offer the means to perform more complete simulation searches, and will lead to more comprehensive biological predictions. Copyright © 2013 Elsevier Inc. All rights reserved.

The Betelgeuse Project: Constraints from Rotation

NASA Astrophysics Data System (ADS)

Diaz, Manuel; Nance, Sarafina; Sullivan, James; Wheeler, J. Craig

2017-01-01

In order to constrain the evolutionary state of the red supergiant Betelgeuse, we have produced a suite of models with ZAMS masses from 15 to 25 Msun in intervals of 1 Msun including the effects of rotation computed with the stellar evolutionary code MESA. For non--rotating models we find results that are similar to other work. It is somewhat difficult to find models that agree within 1 σ of the observed values of R, Teff and L, but modestly easy within 3 σ uncertainty. Incorporating the nominal observed rotational velocity, ~15 km/s, yields significantly different, and challenging, constraints. This velocity constraint is only matched when the models first approach the base of the red supergiant branch (RSB), having crossed the Hertzsprung gap, but not yet having ascended the RSB and most violate even generous error bars on R, Teff and L. Models at the tip of the RSB typically rotate at only ~0.1 km/s, independent of any reasonable choice of initial rotation. We discuss the possible uncertainties in our modeling and the observations, including the distance to Betelgeuse, the rotation velocity, and model parameters. We summarize various options to account for the rotational velocity and suggest that one possibility is that Betelgeuse merged with a companion star of about 1 Msun as it ascended the RSB, in the process producing the ring structure observed at about 7' away. A past coalescence would complicate attempts to understand the evolutionary history and future of Betelgeuse. To that end, we also present asteroseismology models with acoustic waves driven by inner convective regions that could elucidate the inner structure and evolutionary state.

Reconstructing evolutionary trees in parallel for massive sequences.

PubMed

Zou, Quan; Wan, Shixiang; Zeng, Xiangxiang; Ma, Zhanshan Sam

2017-12-14

Building the evolutionary trees for massive unaligned DNA sequences is challenging and crucial. However, reconstructing evolutionary tree for ultra-large sequences is hard. Massive multiple sequence alignment is also challenging and time/space consuming. Hadoop and Spark are developed recently, which bring spring light for the classical computational biology problems. In this paper, we tried to solve the multiple sequence alignment and evolutionary reconstruction in parallel. HPTree, which is developed in this paper, can deal with big DNA sequence files quickly. It works well on the >1GB files, and gets better performance than other evolutionary reconstruction tools. Users could use HPTree for reonstructing evolutioanry trees on the computer clusters or cloud platform (eg. Amazon Cloud). HPTree could help on population evolution research and metagenomics analysis. In this paper, we employ the Hadoop and Spark platform and design an evolutionary tree reconstruction software tool for unaligned massive DNA sequences. Clustering and multiple sequence alignment are done in parallel. Neighbour-joining model was employed for the evolutionary tree building. We opened our software together with source codes via http://lab.malab.cn/soft/HPtree/ .

The painted turtle, Chrysemys picta: a model system for vertebrate evolution, ecology, and human health.

PubMed

Valenzuela, Nicole

2009-07-01

Painted turtles (Chrysemys picta) are representatives of a vertebrate clade whose biology and phylogenetic position hold a key to our understanding of fundamental aspects of vertebrate evolution. These features make them an ideal emerging model system. Extensive ecological and physiological research provide the context in which to place new research advances in evolutionary genetics, genomics, evolutionary developmental biology, and ecological developmental biology which are enabled by current resources, such as a bacterial artificial chromosome (BAC) library of C. picta, and the imminent development of additional ones such as genome sequences and cDNA and expressed sequence tag (EST) libraries. This integrative approach will allow the research community to continue making advances to provide functional and evolutionary explanations for the lability of biological traits found not only among reptiles but vertebrates in general. Moreover, because humans and reptiles share a common ancestor, and given the ease of using nonplacental vertebrates in experimental biology compared with mammalian embryos, painted turtles are also an emerging model system for biomedical research. For example, painted turtles have been studied to understand many biological responses to overwintering and anoxia, as potential sentinels for environmental xenobiotics, and as a model to decipher the ecology and evolution of sexual development and reproduction. Thus, painted turtles are an excellent reptilian model system for studies with human health, environmental, ecological, and evolutionary significance.

When everything is not everywhere but species evolve: an alternative method to model adaptive properties of marine ecosystems

PubMed Central

Sauterey, Boris; Ward, Ben A.; Follows, Michael J.; Bowler, Chris; Claessen, David

2015-01-01

The functional and taxonomic biogeography of marine microbial systems reflects the current state of an evolving system. Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle. Here, we investigate the evolutionary adaptive potential of marine microbial systems under environmental change and introduce explicit Darwinian adaptation into an ocean modelling framework, simulating evolving phytoplankton communities in space and time. To this end, we adopt tools from adaptive dynamics theory, evaluating the fitness of invading mutants over annual timescales, replacing the resident if a fitter mutant arises. Using the evolutionary framework, we examine how community assembly, specifically the emergence of phytoplankton cell size diversity, reflects the combined effects of bottom-up and top-down controls. When compared with a species-selection approach, based on the paradigm that “Everything is everywhere, but the environment selects”, we show that (i) the selected optimal trait values are similar; (ii) the patterns emerging from the adaptive model are more robust, but (iii) the two methods lead to different predictions in terms of emergent diversity. We demonstrate that explicitly evolutionary approaches to modelling marine microbial populations and functionality are feasible and practical in time-varying, space-resolving settings and provide a new tool for exploring evolutionary interactions on a range of timescales in the ocean. PMID:25852217

When everything is not everywhere but species evolve: an alternative method to model adaptive properties of marine ecosystems.

PubMed

Sauterey, Boris; Ward, Ben A; Follows, Michael J; Bowler, Chris; Claessen, David

2015-01-01

The functional and taxonomic biogeography of marine microbial systems reflects the current state of an evolving system. Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle. Here, we investigate the evolutionary adaptive potential of marine microbial systems under environmental change and introduce explicit Darwinian adaptation into an ocean modelling framework, simulating evolving phytoplankton communities in space and time. To this end, we adopt tools from adaptive dynamics theory, evaluating the fitness of invading mutants over annual timescales, replacing the resident if a fitter mutant arises. Using the evolutionary framework, we examine how community assembly, specifically the emergence of phytoplankton cell size diversity, reflects the combined effects of bottom-up and top-down controls. When compared with a species-selection approach, based on the paradigm that "Everything is everywhere, but the environment selects", we show that (i) the selected optimal trait values are similar; (ii) the patterns emerging from the adaptive model are more robust, but (iii) the two methods lead to different predictions in terms of emergent diversity. We demonstrate that explicitly evolutionary approaches to modelling marine microbial populations and functionality are feasible and practical in time-varying, space-resolving settings and provide a new tool for exploring evolutionary interactions on a range of timescales in the ocean.

Application of network methods for understanding evolutionary dynamics in discrete habitats.

PubMed

Greenbaum, Gili; Fefferman, Nina H

2017-06-01

In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene-flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population-genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene-flow patterns. In the last decades, network theory - a branch of discrete mathematics concerned with complex interactions between discrete elements - has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population-genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology. © 2017 John Wiley & Sons Ltd.

Transgressive Hybrids as Hopeful Monsters.

PubMed

Dittrich-Reed, Dylan R; Fitzpatrick, Benjamin M

2013-06-01

The origin of novelty is a critical subject for evolutionary biologists. Early geneticists speculated about the sudden appearance of new species via special macromutations, epitomized by Goldschmidt's infamous "hopeful monster". Although these ideas were easily dismissed by the insights of the Modern Synthesis, a lingering fascination with the possibility of sudden, dramatic change has persisted. Recent work on hybridization and gene exchange suggests an underappreciated mechanism for the sudden appearance of evolutionary novelty that is entirely consistent with the principles of modern population genetics. Genetic recombination in hybrids can produce transgressive phenotypes, "monstrous" phenotypes beyond the range of parental populations. Transgressive phenotypes can be products of epistatic interactions or additive effects of multiple recombined loci. We compare several epistatic and additive models of transgressive segregation in hybrids and find that they are special cases of a general, classic quantitative genetic model. The Dobzhansky-Muller model predicts "hopeless" monsters, sterile and inviable transgressive phenotypes. The Bateson model predicts "hopeful" monsters with fitness greater than either parental population. The complementation model predicts both. Transgressive segregation after hybridization can rapidly produce novel phenotypes by recombining multiple loci simultaneously. Admixed populations will also produce many similar recombinant phenotypes at the same time, increasing the probability that recombinant "hopeful monsters" will establish true-breeding evolutionary lineages. Recombination is not the only (or even most common) process generating evolutionary novelty, but might be the most credible mechanism for sudden appearance of new forms.

InterEvDock: a docking server to predict the structure of protein–protein interactions using evolutionary information

PubMed Central

Yu, Jinchao; Vavrusa, Marek; Andreani, Jessica; Rey, Julien; Tufféry, Pierre; Guerois, Raphaël

2016-01-01

The structural modeling of protein–protein interactions is key in understanding how cell machineries cross-talk with each other. Molecular docking simulations provide efficient means to explore how two unbound protein structures interact. InterEvDock is a server for protein docking based on a free rigid-body docking strategy. A systematic rigid-body docking search is performed using the FRODOCK program and the resulting models are re-scored with InterEvScore and SOAP-PP statistical potentials. The InterEvScore potential was specifically designed to integrate co-evolutionary information in the docking process. InterEvDock server is thus particularly well suited in case homologous sequences are available for both binding partners. The server returns 10 structures of the most likely consensus models together with 10 predicted residues most likely involved in the interface. In 91% of all complexes tested in the benchmark, at least one residue out of the 10 predicted is involved in the interface, providing useful guidelines for mutagenesis. InterEvDock is able to identify a correct model among the top10 models for 49% of the rigid-body cases with evolutionary information, making it a unique and efficient tool to explore structural interactomes under an evolutionary perspective. The InterEvDock web interface is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/InterEvDock/. PMID:27131368

Development of antibiotic regimens using graph based evolutionary algorithms.

PubMed

Corns, Steven M; Ashlock, Daniel A; Bryden, Kenneth M

2013-12-01

This paper examines the use of evolutionary algorithms in the development of antibiotic regimens given to production animals. A model is constructed that combines the lifespan of the animal and the bacteria living in the animal's gastro-intestinal tract from the early finishing stage until the animal reaches market weight. This model is used as the fitness evaluation for a set of graph based evolutionary algorithms to assess the impact of diversity control on the evolving antibiotic regimens. The graph based evolutionary algorithms have two objectives: to find an antibiotic treatment regimen that maintains the weight gain and health benefits of antibiotic use and to reduce the risk of spreading antibiotic resistant bacteria. This study examines different regimens of tylosin phosphate use on bacteria populations divided into Gram positive and Gram negative types, with a focus on Campylobacter spp. Treatment regimens were found that provided decreased antibiotic resistance relative to conventional methods while providing nearly the same benefits as conventional antibiotic regimes. By using a graph to control the information flow in the evolutionary algorithm, a variety of solutions along the Pareto front can be found automatically for this and other multi-objective problems. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Spatial Selection and Local Adaptation Jointly Shape Life-History Evolution during Range Expansion.

PubMed

Van Petegem, Katrien H P; Boeye, Jeroen; Stoks, Robby; Bonte, Dries

2016-11-01

In the context of climate change and species invasions, range shifts increasingly gain attention because the rates at which they occur in the Anthropocene induce rapid changes in biological assemblages. During range shifts, species experience multiple selection pressures. For poleward expansions in particular, it is difficult to interpret observed evolutionary dynamics because of the joint action of evolutionary processes related to spatial selection and to adaptation toward local climatic conditions. To disentangle the effects of these two processes, we integrated stochastic modeling and data from a common garden experiment, using the spider mite Tetranychus urticae as a model species. By linking the empirical data with those derived form a highly parameterized individual-based model, we infer that both spatial selection and local adaptation contributed to the observed latitudinal life-history divergence. Spatial selection best described variation in dispersal behavior, while variation in development was best explained by adaptation to the local climate. Divergence in life-history traits in species shifting poleward could consequently be jointly determined by contemporary evolutionary dynamics resulting from adaptation to the environmental gradient and from spatial selection. The integration of modeling with common garden experiments provides a powerful tool to study the contribution of these evolutionary processes on life-history evolution during range expansion.

The amazing evolutionary dynamics of non-linear optical systems with feedback

NASA Astrophysics Data System (ADS)

Yaroslavsky, Leonid

2013-09-01

Optical systems with feedback are, generally, non-linear dynamic systems. As such, they exhibit evolutionary behavior. In the paper we present results of experimental investigation of evolutionary dynamics of several models of such systems. The models are modifications of the famous mathematical "Game of Life". The modifications are two-fold: "Game of Life" rules are made stochastic and mutual influence of cells is made spatially non-uniform. A number of new phenomena in the evolutionary dynamics of the models are revealed: - "Ordering of chaos". Formation, from seed patterns, of stable maze-like patterns with chaotic "dislocations" that resemble natural patterns, such as skin patterns of some animals and fishes, see shell, fingerprints, magnetic domain patterns and alike, which one can frequently find in the nature. These patterns and their fragments exhibit a remarkable capability of unlimited growth. - "Self-controlled growth" of chaotic "live" formations into "communities" bounded, depending on the model, by a square, hexagon or octagon, until they reach a certain critical size, after which the growth stops. - "Eternal life in a bounded space" of "communities" after reaching a certain size and shape. - "Coherent shrinkage" of "mature", after reaching a certain size, "communities" into one of stable or oscillating patterns preserving in this process isomorphism of their bounding shapes until the very end.

Is `Learning' Science Enough? - A Cultural Model of Religious Students of Science in an Australian Government School

NASA Astrophysics Data System (ADS)

Ferguson, Joseph Paul; Kameniar, Barbara

2014-10-01

This paper investigates the cognitive experiences of four religious students studying evolutionary biology in an inner city government secondary school in Melbourne, Australia. The participants in the study were identified using the Religious Background and Behaviours questionnaire (Connors, Tonigan, & Miller, 1996). Participants were interviewed and asked to respond to questions about their cognitive experiences of studying evolutionary biology. Students' responses were analysed using cultural analysis of discourse to construct a cultural model of religious students of science. This cultural model suggests that these students employ a human schema and a non-human schema, which assert that humans are fundamentally different from non-humans in terms of origins and that humans have a transcendental purpose in life. For these students, these maxims seem to be challenged by their belief that evolutionary biology is dictated by metaphysical naturalism. The model suggests that because the existential foundation of these students is challenged, they employ a believing schema to classify their religious explanations and a learning schema to classify evolutionary biology. These schemas are then hierarchically arranged with the learning schema being made subordinate to the believing schema. Importantly, these students are thus able to maintain their existential foundation while fulfilling the requirements of school science. However, the quality of this "learning" is questionable.

Safe Science: Be Protected!

ERIC Educational Resources Information Center

Roy, Ken

2006-01-01

Science education is a changing landscape. Changes over the past ten years alone have been both evolutionary and revolutionary--Science Education Standards, new required assessments, science teacher certification issues, science teacher shortages and retirements, molecular approach to Biology, etc. These changes and issues range from…

Links between Evolution, Development, Human Anatomy, Pathology, and Medicine, with A Proposition of A Re-defined Anatomical Position and Notes on Constraints and Morphological "Imperfections".

PubMed

Diogo, Rui; Molnar, Julia

2016-06-01

Surprisingly the oldest formal discipline in medicine (anatomy) has not yet felt the full impact of evolutionary developmental biology. In medical anatomy courses and textbooks, the human body is still too often described as though it is a "perfect machine." In fact, the study of human anatomy predates evolutionary theory; therefore, many of its conventions continue to be outdated, making it difficult to study, understand, and treat the human body, and to compare it with that of other, nonbipedal animals, including other primates. Moreover, such an erroneous view of our anatomy as "perfect" can be used to fuel nonevolutionary ideologies such as intelligent design. In the section An Evolutionary and Developmental Approach to Human Anatomical Position of this paper, we propose the redefinition of the "human standard anatomical position" used in textbooks to be consistent with human evolutionary and developmental history. This redefined position also simplifies, for students and practitioners of the health professions, the study and learning of embryonic muscle groups (each group including muscles derived from the same/ontogenetically closely related primordium/primordia) and joint movements and highlights the topological correspondence between the upper and lower limbs. Section Evolutionary and Developmental Constraints, "Imperfections" and Sports Pathologies continues the theme by describing examples of apparently "illogical" characteristics of the human body that only make sense when one understands the developmental and evolutionary constraints that have accumulated over millions of years. We focus, in particular, on musculoskeletal functional problems and sports pathologies to emphasize the links with pathology and medicine. These examples demonstrate how incorporating evolutionary theory into anatomy education can be helpful for medical students, teachers, researchers, and physicians, as well as for anatomists, functional morphologists, and evolutionary and developmental biologists. © 2016 Wiley Periodicals, Inc.

The environmental zero-point problem in evolutionary reaction norm modeling.

PubMed

Ergon, Rolf

2018-04-01

There is a potential problem in present quantitative genetics evolutionary modeling based on reaction norms. Such models are state-space models, where the multivariate breeder's equation in some form is used as the state equation that propagates the population state forward in time. These models use the implicit assumption of a constant reference environment, in many cases set to zero. This zero-point is often the environment a population is adapted to, that is, where the expected geometric mean fitness is maximized. Such environmental reference values follow from the state of the population system, and they are thus population properties. The environment the population is adapted to, is, in other words, an internal population property, independent of the external environment. It is only when the external environment coincides with the internal reference environment, or vice versa, that the population is adapted to the current environment. This is formally a result of state-space modeling theory, which is an important theoretical basis for evolutionary modeling. The potential zero-point problem is present in all types of reaction norm models, parametrized as well as function-valued, and the problem does not disappear when the reference environment is set to zero. As the environmental reference values are population characteristics, they ought to be modeled as such. Whether such characteristics are evolvable is an open question, but considering the complexity of evolutionary processes, such evolvability cannot be excluded without good arguments. As a straightforward solution, I propose to model the reference values as evolvable mean traits in their own right, in addition to other reaction norm traits. However, solutions based on an evolvable G matrix are also possible.

EvoBuild: A Quickstart Toolkit for Programming Agent-Based Models of Evolutionary Processes

NASA Astrophysics Data System (ADS)

Wagh, Aditi; Wilensky, Uri

2018-04-01

Extensive research has shown that one of the benefits of programming to learn about scientific phenomena is that it facilitates learning about mechanisms underlying the phenomenon. However, using programming activities in classrooms is associated with costs such as requiring additional time to learn to program or students needing prior experience with programming. This paper presents a class of programming environments that we call quickstart: Environments with a negligible threshold for entry into programming and a modest ceiling. We posit that such environments can provide benefits of programming for learning without incurring associated costs for novice programmers. To make this claim, we present a design-based research study conducted to compare programming models of evolutionary processes with a quickstart toolkit with exploring pre-built models of the same processes. The study was conducted in six seventh grade science classes in two schools. Students in the programming condition used EvoBuild, a quickstart toolkit for programming agent-based models of evolutionary processes, to build their NetLogo models. Students in the exploration condition used pre-built NetLogo models. We demonstrate that although students came from a range of academic backgrounds without prior programming experience, and all students spent the same number of class periods on the activities including the time students took to learn programming in this environment, EvoBuild students showed greater learning about evolutionary mechanisms. We discuss the implications of this work for design research on programming environments in K-12 science education.

LS³: A Method for Improving Phylogenomic Inferences When Evolutionary Rates Are Heterogeneous among Taxa.

PubMed

Rivera-Rivera, Carlos J; Montoya-Burgos, Juan I

2016-06-01

Phylogenetic inference artifacts can occur when sequence evolution deviates from assumptions made by the models used to analyze them. The combination of strong model assumption violations and highly heterogeneous lineage evolutionary rates can become problematic in phylogenetic inference, and lead to the well-described long-branch attraction (LBA) artifact. Here, we define an objective criterion for assessing lineage evolutionary rate heterogeneity among predefined lineages: the result of a likelihood ratio test between a model in which the lineages evolve at the same rate (homogeneous model) and a model in which different lineage rates are allowed (heterogeneous model). We implement this criterion in the algorithm Locus Specific Sequence Subsampling (LS³), aimed at reducing the effects of LBA in multi-gene datasets. For each gene, LS³ sequentially removes the fastest-evolving taxon of the ingroup and tests for lineage rate homogeneity until all lineages have uniform evolutionary rates. The sequences excluded from the homogeneously evolving taxon subset are flagged as potentially problematic. The software implementation provides the user with the possibility to remove the flagged sequences for generating a new concatenated alignment. We tested LS³ with simulations and two real datasets containing LBA artifacts: a nucleotide dataset regarding the position of Glires within mammals and an amino-acid dataset concerning the position of nematodes within bilaterians. The initially incorrect phylogenies were corrected in all cases upon removing data flagged by LS³. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Individual Development and Evolution: Experiential Canalization of Self-Regulation

ERIC Educational Resources Information Center

Blair, Clancy; Raver, C. Cybele

2012-01-01

In this article, we contrast evolutionary and psychobiological models of individual development to address the idea that individual development occurring in prototypically risky and unsupportive environments can be understood as adaptation. We question traditional evolutionary explanations of individual development, calling on the principle of…

Howling about Trophic Cascades

ERIC Educational Resources Information Center

Kowalewski, David

2012-01-01

Following evolutionary theory and an agriculture model, ecosystem research has stressed bottom-up dynamics, implying that top wild predators are epiphenomenal effects of more basic causes. As such, they are assumed expendable. A more modern co-evolutionary and wilderness approach--trophic cascades--instead suggests that top predators, whose…

EvoDB: a database of evolutionary rate profiles, associated protein domains and phylogenetic trees for PFAM-A

PubMed Central

Ndhlovu, Andrew; Durand, Pierre M.; Hazelhurst, Scott

2015-01-01

The evolutionary rate at codon sites across protein-coding nucleotide sequences represents a valuable tier of information for aligning sequences, inferring homology and constructing phylogenetic profiles. However, a comprehensive resource for cataloguing the evolutionary rate at codon sites and their corresponding nucleotide and protein domain sequence alignments has not been developed. To address this gap in knowledge, EvoDB (an Evolutionary rates DataBase) was compiled. Nucleotide sequences and their corresponding protein domain data including the associated seed alignments from the PFAM-A (protein family) database were used to estimate evolutionary rate (ω = dN/dS) profiles at codon sites for each entry. EvoDB contains 98.83% of the gapped nucleotide sequence alignments and 97.1% of the evolutionary rate profiles for the corresponding information in PFAM-A. As the identification of codon sites under positive selection and their position in a sequence profile is usually the most sought after information for molecular evolutionary biologists, evolutionary rate profiles were determined under the M2a model using the CODEML algorithm in the PAML (Phylogenetic Analysis by Maximum Likelihood) suite of software. Validation of nucleotide sequences against amino acid data was implemented to ensure high data quality. EvoDB is a catalogue of the evolutionary rate profiles and provides the corresponding phylogenetic trees, PFAM-A alignments and annotated accession identifier data. In addition, the database can be explored and queried using known evolutionary rate profiles to identify domains under similar evolutionary constraints and pressures. EvoDB is a resource for evolutionary, phylogenetic studies and presents a tier of information untapped by current databases. Database URL: http://www.bioinf.wits.ac.za/software/fire/evodb PMID:26140928

EvoDB: a database of evolutionary rate profiles, associated protein domains and phylogenetic trees for PFAM-A.

PubMed

Ndhlovu, Andrew; Durand, Pierre M; Hazelhurst, Scott

2015-01-01

The evolutionary rate at codon sites across protein-coding nucleotide sequences represents a valuable tier of information for aligning sequences, inferring homology and constructing phylogenetic profiles. However, a comprehensive resource for cataloguing the evolutionary rate at codon sites and their corresponding nucleotide and protein domain sequence alignments has not been developed. To address this gap in knowledge, EvoDB (an Evolutionary rates DataBase) was compiled. Nucleotide sequences and their corresponding protein domain data including the associated seed alignments from the PFAM-A (protein family) database were used to estimate evolutionary rate (ω = dN/dS) profiles at codon sites for each entry. EvoDB contains 98.83% of the gapped nucleotide sequence alignments and 97.1% of the evolutionary rate profiles for the corresponding information in PFAM-A. As the identification of codon sites under positive selection and their position in a sequence profile is usually the most sought after information for molecular evolutionary biologists, evolutionary rate profiles were determined under the M2a model using the CODEML algorithm in the PAML (Phylogenetic Analysis by Maximum Likelihood) suite of software. Validation of nucleotide sequences against amino acid data was implemented to ensure high data quality. EvoDB is a catalogue of the evolutionary rate profiles and provides the corresponding phylogenetic trees, PFAM-A alignments and annotated accession identifier data. In addition, the database can be explored and queried using known evolutionary rate profiles to identify domains under similar evolutionary constraints and pressures. EvoDB is a resource for evolutionary, phylogenetic studies and presents a tier of information untapped by current databases. © The Author(s) 2015. Published by Oxford University Press.

On evolutionary spatial heterogeneous games

NASA Astrophysics Data System (ADS)

Fort, H.

2008-03-01

How cooperation between self-interested individuals evolve is a crucial problem, both in biology and in social sciences, that is far from being well understood. Evolutionary game theory is a useful approach to this issue. The simplest model to take into account the spatial dimension in evolutionary games is in terms of cellular automata with just a one-parameter payoff matrix. Here, the effects of spatial heterogeneities of the environment and/or asymmetries in the interactions among the individuals are analysed through different extensions of this model. Instead of using the same universal payoff matrix, bimatrix games in which each cell at site ( i, j) has its own different ‘temptation to defect’ parameter T(i,j) are considered. First, the case in which these individual payoffs are constant in time is studied. Second, an evolving evolutionary spatial game such that T=T(i,j;t), i.e. besides depending on the position evolves (by natural selection), is used to explore the combination of spatial heterogeneity and natural selection of payoff matrices.

A transmission-virulence evolutionary trade-off explains attenuation of HIV-1 in Uganda

PubMed Central

Blanquart, François; Grabowski, Mary Kate; Herbeck, Joshua; Nalugoda, Fred; Serwadda, David; Eller, Michael A; Robb, Merlin L; Gray, Ronald; Kigozi, Godfrey; Laeyendecker, Oliver; Lythgoe, Katrina A; Nakigozi, Gertrude; Quinn, Thomas C; Reynolds, Steven J; Wawer, Maria J; Fraser, Christophe

2016-01-01

Evolutionary theory hypothesizes that intermediate virulence maximizes pathogen fitness as a result of a trade-off between virulence and transmission, but empirical evidence remains scarce. We bridge this gap using data from a large and long-standing HIV-1 prospective cohort, in Uganda. We use an epidemiological-evolutionary model parameterised with this data to derive evolutionary predictions based on analysis and detailed individual-based simulations. We robustly predict stabilising selection towards a low level of virulence, and rapid attenuation of the virus. Accordingly, set-point viral load, the most common measure of virulence, has declined in the last 20 years. Our model also predicts that subtype A is slowly outcompeting subtype D, with both subtypes becoming less virulent, as observed in the data. Reduction of set-point viral loads should have resulted in a 20% reduction in incidence, and a three years extension of untreated asymptomatic infection, increasing opportunities for timely treatment of infected individuals. DOI: http://dx.doi.org/10.7554/eLife.20492.001 PMID:27815945

Test of Von Baer's law of the conservation of early development.

PubMed

Poe, Steven

2006-11-01

One of the oldest and most pervasive ideas in comparative embryology is the perceived evolutionary conservation of early ontogeny relative to late ontogeny. Karl Von Baer first noted the similarity of early ontogeny across taxa, and Ernst Haeckel and Charles Darwin gave evolutionary interpretation to this phenomenon. In spite of a resurgence of interest in comparative embryology and the development of mechanistic explanations for Von Baer's law, the pattern itself has been largely untested. Here, I use statistical phylogenetic approaches to show that Von Baer's law is an unnecessarily complex explanation of the patterns of ontogenetic timing in several clades of vertebrates. Von Baer's law suggests a positive correlation between ontogenetic time and amount of evolutionary change. I compare ranked position in ontogeny to frequency of evolutionary change in rank for developmental events and find that these measures are not correlated, thus failing to support Von Baer's model. An alternative model that postulates that small changes in ontogenetic rank are evolutionarily easier than large changes is tentatively supported.

Modelling and strategy optimisation for a kind of networked evolutionary games with memories under the bankruptcy mechanism

NASA Astrophysics Data System (ADS)

Fu, Shihua; Li, Haitao; Zhao, Guodong

2018-05-01

This paper investigates the evolutionary dynamic and strategy optimisation for a kind of networked evolutionary games whose strategy updating rules incorporate 'bankruptcy' mechanism, and the situation that each player's bankruptcy is due to the previous continuous low profits gaining from the game is considered. First, by using semi-tensor product of matrices method, the evolutionary dynamic of this kind of games is expressed as a higher order logical dynamic system and then converted into its algebraic form, based on which, the evolutionary dynamic of the given games can be discussed. Second, the strategy optimisation problem is investigated, and some free-type control sequences are designed to maximise the total payoff of the whole game. Finally, an illustrative example is given to show that our new results are very effective.

Invisible hand effect in an evolutionary minority game model

NASA Astrophysics Data System (ADS)

Sysi-Aho, Marko; Saramäki, Jari; Kaski, Kimmo

2005-03-01

In this paper, we study the properties of a minority game with evolution realized by using genetic crossover to modify fixed-length decision-making strategies of agents. Although the agents in this evolutionary game act selfishly by trying to maximize their own performances only, it turns out that the whole society will eventually be rewarded optimally. This “invisible hand” effect is what Adam Smith over two centuries ago expected to take place in the context of free market mechanism. However, this behaviour of the society of agents is realized only under idealized conditions, where all agents are utilizing the same efficient evolutionary mechanism. If on the other hand part of the agents are adaptive, but not evolutionary, the system does not reach optimum performance, which is also the case if part of the evolutionary agents form a uniformly acting “cartel”.

How mutation affects evolutionary games on graphs

PubMed Central

Allen, Benjamin; Traulsen, Arne; Tarnita, Corina E.; Nowak, Martin A.

2011-01-01

Evolutionary dynamics are affected by population structure, mutation rates and update rules. Spatial or network structure facilitates the clustering of strategies, which represents a mechanism for the evolution of cooperation. Mutation dilutes this effect. Here we analyze how mutation influences evolutionary clustering on graphs. We introduce new mathematical methods to evolutionary game theory, specifically the analysis of coalescing random walks via generating functions. These techniques allow us to derive exact identity-by-descent (IBD) probabilities, which characterize spatial assortment on lattices and Cayley trees. From these IBD probabilities we obtain exact conditions for the evolution of cooperation and other game strategies, showing the dual effects of graph topology and mutation rate. High mutation rates diminish the clustering of cooperators, hindering their evolutionary success. Our model can represent either genetic evolution with mutation, or social imitation processes with random strategy exploration. PMID:21473871

An evolutionary model of cooperation, fairness and altruistic punishment in public good games.

PubMed

Hetzer, Moritz; Sornette, Didier

2013-01-01

We identify and explain the mechanisms that account for the emergence of fairness preferences and altruistic punishment in voluntary contribution mechanisms by combining an evolutionary perspective together with an expected utility model. We aim at filling a gap between the literature on the theory of evolution applied to cooperation and punishment, and the empirical findings from experimental economics. The approach is motivated by previous findings on other-regarding behavior, the co-evolution of culture, genes and social norms, as well as bounded rationality. Our first result reveals the emergence of two distinct evolutionary regimes that force agents to converge either to a defection state or to a state of coordination, depending on the predominant set of self- or other-regarding preferences. Our second result indicates that subjects in laboratory experiments of public goods games with punishment coordinate and punish defectors as a result of an aversion against disadvantageous inequitable outcomes. Our third finding identifies disadvantageous inequity aversion as evolutionary dominant and stable in a heterogeneous population of agents endowed initially only with purely self-regarding preferences. We validate our model using previously obtained results from three independently conducted experiments of public goods games with punishment.

An Evolutionary Model of Cooperation, Fairness and Altruistic Punishment in Public Good Games

PubMed Central

Hetzer, Moritz; Sornette, Didier

2013-01-01

We identify and explain the mechanisms that account for the emergence of fairness preferences and altruistic punishment in voluntary contribution mechanisms by combining an evolutionary perspective together with an expected utility model. We aim at filling a gap between the literature on the theory of evolution applied to cooperation and punishment, and the empirical findings from experimental economics. The approach is motivated by previous findings on other-regarding behavior, the co-evolution of culture, genes and social norms, as well as bounded rationality. Our first result reveals the emergence of two distinct evolutionary regimes that force agents to converge either to a defection state or to a state of coordination, depending on the predominant set of self- or other-regarding preferences. Our second result indicates that subjects in laboratory experiments of public goods games with punishment coordinate and punish defectors as a result of an aversion against disadvantageous inequitable outcomes. Our third finding identifies disadvantageous inequity aversion as evolutionary dominant and stable in a heterogeneous population of agents endowed initially only with purely self-regarding preferences. We validate our model using previously obtained results from three independently conducted experiments of public goods games with punishment. PMID:24260101

Evolution of Swarming Behavior Is Shaped by How Predators Attack.

PubMed

Olson, Randal S; Knoester, David B; Adami, Christoph

2016-01-01

Animal grouping behaviors have been widely studied due to their implications for understanding social intelligence, collective cognition, and potential applications in engineering, artificial intelligence, and robotics. An important biological aspect of these studies is discerning which selection pressures favor the evolution of grouping behavior. In the past decade, researchers have begun using evolutionary computation to study the evolutionary effects of these selection pressures in predator-prey models. The selfish herd hypothesis states that concentrated groups arise because prey selfishly attempt to place their conspecifics between themselves and the predator, thus causing an endless cycle of movement toward the center of the group. Using an evolutionary model of a predator-prey system, we show that how predators attack is critical to the evolution of the selfish herd. Following this discovery, we show that density-dependent predation provides an abstraction of Hamilton's original formulation of domains of danger. Finally, we verify that density-dependent predation provides a sufficient selective advantage for prey to evolve the selfish herd in response to predation by coevolving predators. Thus, our work corroborates Hamilton's selfish herd hypothesis in a digital evolutionary model, refines the assumptions of the selfish herd hypothesis, and generalizes the domain of danger concept to density-dependent predation.

A model of ecological and evolutionary consequences of color polymorphism.

PubMed

Forsman, Anders; Ahnesjö, Jonas; Caesar, Sofia; Karlsson, Magnus

2008-01-01

We summarize direct and indirect effects on fitness components of animal color pattern and present a synthesis of theories concerning the ecological and evolutionary dynamics of chromatic multiple niche polymorphisms. Previous endeavors have aimed primarily at identifying conditions that promote the evolution and maintenance of polymorphisms. We consider in a conceptual model also the reciprocal influence of color polymorphism on population processes and propose that polymorphism entails selective advantages that may promote the ecological success of polymorphic species. The model begins with an evolutionary branching event from mono- to polymorphic condition that, under the influence of correlational selection, is predicted to promote the evolution of physical integration of coloration and other traits (cf. multi-trait coevolution and complex phenotypes). We propose that the coexistence within a population of alternative ecomorphs with coadapted gene complexes promotes utilization of diverse environmental resources, population stability and persistence, colonization success, and range expansions, and enhances the evolutionary potential and speciation. Conversely, we predict polymorphic populations to be less vulnerable to environmental change and at lower risk of range contractions and extinctions compared with monomorphic populations. We offer brief suggestions as to how these falsifiable predictions may be tested.

VizieR Online Data Catalog: Low-mass helium white dwarfs evolutionary models (Istrate+, 2016)

NASA Astrophysics Data System (ADS)

Istrate, A.; Marchant, P.; Tauris, T. M.; Langer, N.; Stancliffe, R. J.; Grassitelli, L.

2016-07-01

Evolutionary models of low-mass helium white dwarfs including element diffusion and rotational mixing. The WDs are produced considering binary evolution through the LMXB channel, with final WDs masses between ~0.16-~0.44. The models are computed using MESA, for different metallicities: Z=0.02, 0.01, 0.001 and 0.0002. For each metallicity, the models are divided in three categories: (1) basic (no diffusion nor rotation are considered) (2) diffusion (element diffusion is considered) (3) rotation+diffusion (both element diffusion and rotational mixing are considered) (4 data files).

Non-Evolutionary Algorithms for Scheduling Dependent Tasks in Distributed Heterogeneous Computing Environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wayne F. Boyer; Gurdeep S. Hura

2005-09-01

The Problem of obtaining an optimal matching and scheduling of interdependent tasks in distributed heterogeneous computing (DHC) environments is well known to be an NP-hard problem. In a DHC system, task execution time is dependent on the machine to which it is assigned and task precedence constraints are represented by a directed acyclic graph. Recent research in evolutionary techniques has shown that genetic algorithms usually obtain more efficient schedules that other known algorithms. We propose a non-evolutionary random scheduling (RS) algorithm for efficient matching and scheduling of inter-dependent tasks in a DHC system. RS is a succession of randomized taskmore » orderings and a heuristic mapping from task order to schedule. Randomized task ordering is effectively a topological sort where the outcome may be any possible task order for which the task precedent constraints are maintained. A detailed comparison to existing evolutionary techniques (GA and PSGA) shows the proposed algorithm is less complex than evolutionary techniques, computes schedules in less time, requires less memory and fewer tuning parameters. Simulation results show that the average schedules produced by RS are approximately as efficient as PSGA schedules for all cases studied and clearly more efficient than PSGA for certain cases. The standard formulation for the scheduling problem addressed in this paper is Rm|prec|Cmax.,« less

Evolutionary Software Development (Developpement Evolutionnaire de Logiciels)

DTIC Science & Technology

2008-08-01

development processes. While this may be true, frequently it is not. MIL-STD-498 was explicitly introduced to encourage iterative development; ISO /IEC... 12207 was carefully worded not to prohibit iterative development. Yet both standards were widely interpreted as requiring waterfall development, as

Evolutionary Software Development (Developpement evolutionnaire de logiciels)

DTIC Science & Technology

2008-08-01

development processes. While this may be true, frequently it is not. MIL-STD-498 was explicitly introduced to encourage iterative development; ISO /IEC... 12207 was carefully worded not to prohibit iterative development. Yet both standards were widely interpreted as requiring waterfall development, as

Phylogenetic tree and community structure from a Tangled Nature model.

PubMed

Canko, Osman; Taşkın, Ferhat; Argın, Kamil

2015-10-07

In evolutionary biology, the taxonomy and origination of species are widely studied subjects. An estimation of the evolutionary tree can be done via available DNA sequence data. The calculation of the tree is made by well-known and frequently used methods such as maximum likelihood and neighbor-joining. In order to examine the results of these methods, an evolutionary tree is pursued computationally by a mathematical model, called Tangled Nature. A relatively small genome space is investigated due to computational burden and it is found that the actual and predicted trees are in reasonably good agreement in terms of shape. Moreover, the speciation and the resulting community structure of the food-web are investigated by modularity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evolutionary Development of the Simulation by Logical Modeling System (SIBYL)

NASA Technical Reports Server (NTRS)

Wu, Helen

1995-01-01

Through the evolutionary development of the Simulation by Logical Modeling System (SIBYL) we have re-engineered the expensive and complex IBM mainframe based Long-term Hardware Projection Model (LHPM) to a robust cost-effective computer based mode that is easy to use. We achieved significant cost reductions and improved productivity in preparing long-term forecasts of Space Shuttle Main Engine (SSME) hardware. The LHPM for the SSME is a stochastic simulation model that projects the hardware requirements over 10 years. SIBYL is now the primary modeling tool for developing SSME logistics proposals and Program Operating Plan (POP) for NASA and divisional marketing studies.

The evolution of ecosystem ascendency in a complex systems based model.

PubMed

Brinck, Katharina; Jensen, Henrik Jeldtoft

2017-09-07

General patterns in ecosystem development can shed light on driving forces behind ecosystem formation and recovery and have been of long interest. In recent years, the need for integrative and process oriented approaches to capture ecosystem growth, development and organisation, as well as the scope of information theory as a descriptive tool has been addressed from various sides. However data collection of ecological network flows is difficult and tedious and comprehensive models are lacking. We use a hierarchical version of the Tangled Nature Model of evolutionary ecology to study the relationship between structure, flow and organisation in model ecosystems, their development over evolutionary time scales and their relation to ecosystem stability. Our findings support the validity of ecosystem ascendency as a meaningful measure of ecosystem organisation, which increases over evolutionary time scales and significantly drops during periods of disturbance. The results suggest a general trend towards both higher integrity and increased stability driven by functional and structural ecosystem coadaptation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Adaptive Topographies and Equilibrium Selection in an Evolutionary Game

PubMed Central

Osinga, Hinke M.; Marshall, James A. R.

2015-01-01

It has long been known in the field of population genetics that adaptive topographies, in which population equilibria maximise mean population fitness for a trait regardless of its genetic bases, do not exist. Whether one chooses to model selection acting on a single locus or multiple loci does matter. In evolutionary game theory, analysis of a simple and general game involving distinct roles for the two players has shown that whether strategies are modelled using a single ‘locus’ or one ‘locus’ for each role, the stable population equilibria are unchanged and correspond to the fitness-maximising evolutionary stable strategies of the game. This is curious given the aforementioned population genetical results on the importance of the genetic bases of traits. Here we present a dynamical systems analysis of the game with roles detailing how, while the stable equilibria in this game are unchanged by the number of ‘loci’ modelled, equilibrium selection may differ under the two modelling approaches. PMID:25706762

Using New Technologies: A Technology Transfer Guidebook. Version 02.00. 08

DTIC Science & Technology

1993-12-01

Barton (1990) and Pressman (1992), depend on the concept that improving your overall technology transfer process decreases the amount of time it takes to...Evolutionary Spiral Process Any enactment of the evolutionary spiral model (ESP) which is an adaptation of the basic spiral model pro- posed by Barry Boehm...Innovations in Organizations, 1989 CMU/SEI-89-TR-17, (also NTIS ADA211573). Pittsburgh, Pennsylvania: Software Engineering Institute. Boehm, Barry A

Darwin without borders? Looking at 'generalised Darwinism' through the prism of the 'hourglass model'.

PubMed

Levit, Georgy S; Hossfeld, Uwe

2011-12-01

This article critically analyzes the arguments of the 'generalized Darwinism' recently proposed for the analysis of social-economical systems. We argue that 'generalized Darwinism' is both restrictive and empty. It is restrictive because it excludes alternative (non-selectionist) evolutionary mechanisms such as orthogenesis, saltationism and mutationism without any examination of their suitability for modeling socio-economic processes and ignoring their important roles in the development of contemporary evolutionary theory. It is empty, because it reduces Darwinism to an abstract triple-principle scheme (variation, selection and inheritance) thus ignoring the actual structure of Darwinism as a complex and dynamic theoretical structure inseparable from a very detailed system of theoretical constraints. Arguing against 'generalised Darwinism' we present our vision of the history of evolutionary biology with the help of the 'hourglass model' reflecting the internal dynamic of competing theories of evolution.

Evolutionary fuzzy modeling human diagnostic decisions.

PubMed

Peña-Reyes, Carlos Andrés

2004-05-01

Fuzzy CoCo is a methodology, combining fuzzy logic and evolutionary computation, for constructing systems able to accurately predict the outcome of a human decision-making process, while providing an understandable explanation of the underlying reasoning. Fuzzy logic provides a formal framework for constructing systems exhibiting both good numeric performance (accuracy) and linguistic representation (interpretability). However, fuzzy modeling--meaning the construction of fuzzy systems--is an arduous task, demanding the identification of many parameters. To solve it, we use evolutionary computation techniques (specifically cooperative coevolution), which are widely used to search for adequate solutions in complex spaces. We have successfully applied the algorithm to model the decision processes involved in two breast cancer diagnostic problems, the WBCD problem and the Catalonia mammography interpretation problem, obtaining systems both of high performance and high interpretability. For the Catalonia problem, an evolved system was embedded within a Web-based tool-called COBRA-for aiding radiologists in mammography interpretation.

A Genetic Representation for Evolutionary Fault Recovery in Virtex FPGAs

NASA Technical Reports Server (NTRS)

Lohn, Jason; Larchev, Greg; DeMara, Ronald; Korsmeyer, David (Technical Monitor)

2003-01-01

Most evolutionary approaches to fault recovery in FPGAs focus on evolving alternative logic configurations as opposed to evolving the intra-cell routing. Since the majority of transistors in a typical FPGA are dedicated to interconnect, nearly 80% according to one estimate, evolutionary fault-recovery systems should benefit hy accommodating routing. In this paper, we propose an evolutionary fault-recovery system employing a genetic representation that takes into account both logic and routing configurations. Experiments were run using a software model of the Xilinx Virtex FPGA. We report that using four Virtex combinational logic blocks, we were able to evolve a 100% accurate quadrature decoder finite state machine in the presence of a stuck-at-zero fault.

[Sex differences in sexual versus emotional jealousy: evolutionary approach and recent discussions].

PubMed

Demirtaş Madran, H Andaç

2008-01-01

Sex differences in jealousy have been reported widely in the social psychological, clinical psychological, psychiatric, and anthropological literature. Many of the studies conducted on jealousy have focused on the sex differences in the level of reported jealousy. Most research has reported that there is no difference between men and women regarding the level of reported jealousy, but there are some sex differences between sexual and emotional jealousy. Evolutionary psychologists divide jealousy into 2 dimensions based on their observations and empirical research findings: Sexual jealousy and emotional jealousy. Sexual jealousy is knowing or suspecting that one's partners has had sexual relationship with a third person, whereas emotional jealousy is triggered by partner's emotional involvement with and/or love for another person. The parental investment model, which extended Darwin's explanations of sexual selection, provides a useful theoretical framework for studying sexual and emotional jealousy. According to this model sexual selection is driven by differential parental investment by men and women; men should experience more sexual jealousy than women and women should experience more emotional jealousy than men. Considerable research has focused on testing this hypothesis and, with a few exceptions, the results are generally consistent with the evolutionary account. In this study, firstly, a brief definition of the sexual and emotional jealousy will be given. Then, sex differences in sexual and emotional jealousy will be explained according to the evolutionary theory. Finally, the results of empirical studies and critiques of the evolutionary model will be given.

Identifying predictors of time-inhomogeneous viral evolutionary processes.

PubMed

Bielejec, Filip; Baele, Guy; Rodrigo, Allen G; Suchard, Marc A; Lemey, Philippe

2016-07-01

Various factors determine the rate at which mutations are generated and fixed in viral genomes. Viral evolutionary rates may vary over the course of a single persistent infection and can reflect changes in replication rates and selective dynamics. Dedicated statistical inference approaches are required to understand how the complex interplay of these processes shapes the genetic diversity and divergence in viral populations. Although evolutionary models accommodating a high degree of complexity can now be formalized, adequately informing these models by potentially sparse data, and assessing the association of the resulting estimates with external predictors, remains a major challenge. In this article, we present a novel Bayesian evolutionary inference method, which integrates multiple potential predictors and tests their association with variation in the absolute rates of synonymous and non-synonymous substitutions along the evolutionary history. We consider clinical and virological measures as predictors, but also changes in population size trajectories that are simultaneously inferred using coalescent modelling. We demonstrate the potential of our method in an application to within-host HIV-1 sequence data sampled throughout the infection of multiple patients. While analyses of individual patient populations lack statistical power, we detect significant evidence for an abrupt drop in non-synonymous rates in late stage infection and a more gradual increase in synonymous rates over the course of infection in a joint analysis across all patients. The former is predicted by the immune relaxation hypothesis while the latter may be in line with increasing replicative fitness during the asymptomatic stage.

Group-level traits can be studied with standard evolutionary theory.

PubMed

Scott-Phillips, Thomas C; Dickins, Thomas E

2014-06-01

Smaldino's target article draws on and seeks to add to a literature that has partially rejected orthodox, gene-centric evolutionary theory. However, orthodox theory has much to say about group-level traits. The target article does not reference or refute these views, and provides no explicit arguments for this narrow approach. In this commentary we: (i) give two examples of topics that the target article might and probably should have discussed (cultural epidemiology and the psychology of individual differences); and (ii) argue that the orthodox approach has much more to say about the emergence of group-level traits than the target article recognises, or gives credit for.

Multidimensional scaling for evolutionary algorithms--visualization of the path through search space and solution space using Sammon mapping.

PubMed

Pohlheim, Hartmut

2006-01-01

Multidimensional scaling as a technique for the presentation of high-dimensional data with standard visualization techniques is presented. The technique used is often known as Sammon mapping. We explain the mathematical foundations of multidimensional scaling and its robust calculation. We also demonstrate the use of this technique in the area of evolutionary algorithms. First, we present the visualization of the path through the search space of the best individuals during an optimization run. We then apply multidimensional scaling to the comparison of multiple runs regarding the variables of individuals and multi-criteria objective values (path through the solution space).

Modeling Tumor Clonal Evolution for Drug Combinations Design.

PubMed

Zhao, Boyang; Hemann, Michael T; Lauffenburger, Douglas A

2016-03-01

Cancer is a clonal evolutionary process. This presents challenges for effective therapeutic intervention, given the constant selective pressure towards drug resistance. Mathematical modeling from population genetics, evolutionary dynamics, and engineering perspectives are being increasingly employed to study tumor progression, intratumoral heterogeneity, drug resistance, and rational drug scheduling and combinations design. In this review, we discuss promising opportunities these inter-disciplinary approaches hold for advances in cancer biology and treatment. We propose that quantitative modeling perspectives can complement emerging experimental technologies to facilitate enhanced understanding of disease progression and improved capabilities for therapeutic drug regimen designs.

Multidimensional extended spatial evolutionary games.

PubMed

Krześlak, Michał; Świerniak, Andrzej

2016-02-01

The goal of this paper is to study the classical hawk-dove model using mixed spatial evolutionary games (MSEG). In these games, played on a lattice, an additional spatial layer is introduced for dependence on more complex parameters and simulation of changes in the environment. Furthermore, diverse polymorphic equilibrium points dependent on cell reproduction, model parameters, and their simulation are discussed. Our analysis demonstrates the sensitivity properties of MSEGs and possibilities for further development. We discuss applications of MSEGs, particularly algorithms for modelling cell interactions during the development of tumours. Copyright © 2015 Elsevier Ltd. All rights reserved.

Field Guide to Plant Model Systems

PubMed Central

Chang, Caren; Bowman, John L.; Meyerowitz, Elliot M.

2016-01-01

For the past several decades, advances in plant development, physiology, cell biology, and genetics have relied heavily on the model (or reference) plant Arabidopsis thaliana. Arabidopsis resembles other plants, including crop plants, in many but by no means all respects. Study of Arabidopsis alone provides little information on the evolutionary history of plants, evolutionary differences between species, plants that survive in different environments, or plants that access nutrients and photosynthesize differently. Empowered by the availability of large-scale sequencing and new technologies for investigating gene function, many new plant models are being proposed and studied. PMID:27716506

Inference of Evolutionary Jumps in Large Phylogenies using Lévy Processes

PubMed Central

Duchen, Pablo; Leuenberger, Christoph; Szilágyi, Sándor M.; Harmon, Luke; Eastman, Jonathan; Schweizer, Manuel

2017-01-01

Abstract Although it is now widely accepted that the rate of phenotypic evolution may not necessarily be constant across large phylogenies, the frequency and phylogenetic position of periods of rapid evolution remain unclear. In his highly influential view of evolution, G. G. Simpson supposed that such evolutionary jumps occur when organisms transition into so-called new adaptive zones, for instance after dispersal into a new geographic area, after rapid climatic changes, or following the appearance of an evolutionary novelty. Only recently, large, accurate and well calibrated phylogenies have become available that allow testing this hypothesis directly, yet inferring evolutionary jumps remains computationally very challenging. Here, we develop a computationally highly efficient algorithm to accurately infer the rate and strength of evolutionary jumps as well as their phylogenetic location. Following previous work we model evolutionary jumps as a compound process, but introduce a novel approach to sample jump configurations that does not require matrix inversions and thus naturally scales to large trees. We then make use of this development to infer evolutionary jumps in Anolis lizards and Loriinii parrots where we find strong signal for such jumps at the basis of clades that transitioned into new adaptive zones, just as postulated by Simpson’s hypothesis. [evolutionary jump; Lévy process; phenotypic evolution; punctuated equilibrium; quantitative traits. PMID:28204787

Cosmic archaeology with gravitational waves from cosmic strings

NASA Astrophysics Data System (ADS)

Cui, Yanou; Lewicki, Marek; Morrissey, David E.; Wells, James D.

2018-06-01

Cosmic strings are generic cosmological predictions of many extensions of the standard model of particle physics, such as a U (1 )' symmetry-breaking phase transition in the early Universe or remnants of superstring theory. Unlike other topological defects, cosmic strings can reach a scaling regime that maintains a small fixed fraction of the total energy density of the Universe from a very early epoch until today. If present, they will oscillate and generate gravitational waves with a frequency spectrum that imprints the dominant sources of total cosmic energy density throughout the history of the Universe. We demonstrate that current and future gravitational wave detectors, such as LIGO and LISA, could be capable of measuring the frequency spectrum of gravitational waves from cosmic strings and discerning the energy composition of the Universe at times well before primordial nucleosynthesis and the cosmic microwave background where standard cosmology has yet to be tested. This work establishes a benchmark case that gravitational waves may provide an unprecedented, powerful tool for probing the evolutionary history of the very early Universe.

Co-niche construction between hosts and symbionts: ideas and evidence.

PubMed

Borges, Renee M

2017-07-01

Symbiosis is a process that can generate evolutionary novelties and can extend the phenotypic niche space of organisms. Symbionts can act together with their hosts to co-construct host organs, within which symbionts are housed. Once established within hosts, symbionts can also influence various aspects of host phenotype, such as resource acquisition, protection from predation by acquisition of toxicity, as well as behaviour. Once symbiosis is established, its fidelity between generations must be ensured. Hosts evolve various mechanisms to screen unwanted symbionts and to facilitate faithful transmission of mutualistic partners between generations. Microbes are the most important symbionts that have influenced plant and animal phenotypes; multicellular organisms engage in developmental symbioses with microbes at many stages in ontogeny. The co-construction of niches may result in composite organisms that are physically nested within each other. While it has been advocated that these composite organisms need new evolutionary theories and perspectives to describe their properties and evolutionary trajectories, it appears that standard evolutionary theories are adequate to explore selection pressures on their composite or individual traits. Recent advances in our understanding of composite organisms open up many important questions regarding the stability and transmission of these units.

A modified Wright-Fisher model that incorporates Ne: A variant of the standard model with increased biological realism and reduced computational complexity.

PubMed

Zhao, Lei; Gossmann, Toni I; Waxman, David

2016-03-21

The Wright-Fisher model is an important model in evolutionary biology and population genetics. It has been applied in numerous analyses of finite populations with discrete generations. It is recognised that real populations can behave, in some key aspects, as though their size that is not the census size, N, but rather a smaller size, namely the effective population size, Ne. However, in the Wright-Fisher model, there is no distinction between the effective and census population sizes. Equivalently, we can say that in this model, Ne coincides with N. The Wright-Fisher model therefore lacks an important aspect of biological realism. Here, we present a method that allows Ne to be directly incorporated into the Wright-Fisher model. The modified model involves matrices whose size is determined by Ne. Thus apart from increased biological realism, the modified model also has reduced computational complexity, particularly so when Ne⪡N. For complex problems, it may be hard or impossible to numerically analyse the most commonly-used approximation of the Wright-Fisher model that incorporates Ne, namely the diffusion approximation. An alternative approach is simulation. However, the simulations need to be sufficiently detailed that they yield an effective size that is different to the census size. Simulations may also be time consuming and have attendant statistical errors. The method presented in this work may then be the only alternative to simulations, when Ne differs from N. We illustrate the straightforward application of the method to some problems involving allele fixation and the determination of the equilibrium site frequency spectrum. We then apply the method to the problem of fixation when three alleles are segregating in a population. This latter problem is significantly more complex than a two allele problem and since the diffusion equation cannot be numerically solved, the only other way Ne can be incorporated into the analysis is by simulation. We have achieved good accuracy in all cases considered. In summary, the present work extends the realism and tractability of an important model of evolutionary biology and population genetics. Copyright © 2016 Elsevier Ltd. All rights reserved.

A theory of pragmatic information and its application to the quasi-species model of biological evolution.

PubMed

Weinberger, Edward D

2002-01-01

'Standard' information theory says nothing about the semantic content of information. Nevertheless, applications such as evolutionary theory demand consideration of precisely this aspect of information, a need that has motivated a largely unsuccessful search for a suitable measure of an 'amount of meaning'. This paper represents an attempt to move beyond this impasse, based on the observation that the meaning of a message can only be understood relative to its receiver. Positing that the semantic value of information is its usefulness in making an informed decision, we define pragmatic information as the information gain in the probability distributions of the receiver's actions, both before and after receipt of a message in some pre-defined ensemble. We then prove rigorously that our definition is the only one that satisfies obvious desiderata, such as the additivity of information from logically independent messages. This definition, when applied to the information 'learned' by the time evolution of a process, defies the intuitions of the few previous researchers thinking along these lines by being monotonic in the uncertainty that remains after receipt of the message, but non-monotonic in the Shannon entropy of the input ensemble. It also follows that the pragmatic information of the genetic 'messages' in an evolving population is a global Lyapunov function for Eigen's quasi-species model of biological evolution. A concluding section argues that a theory such as ours must explicitly acknowledge purposeful action, or 'agency', in such diverse fields as evolutionary theory and finance.

Evolution of Collective Behaviour in an Artificial World Using Linguistic Fuzzy Rule-Based Systems

PubMed Central

Lebar Bajec, Iztok

2017-01-01

Collective behaviour is a fascinating and easily observable phenomenon, attractive to a wide range of researchers. In biology, computational models have been extensively used to investigate various properties of collective behaviour, such as: transfer of information across the group, benefits of grouping (defence against predation, foraging), group decision-making process, and group behaviour types. The question ‘why,’ however remains largely unanswered. Here the interest goes into which pressures led to the evolution of such behaviour, and evolutionary computational models have already been used to test various biological hypotheses. Most of these models use genetic algorithms to tune the parameters of previously presented non-evolutionary models, but very few attempt to evolve collective behaviour from scratch. Of these last, the successful attempts display clumping or swarming behaviour. Empirical evidence suggests that in fish schools there exist three classes of behaviour; swarming, milling and polarized. In this paper we present a novel, artificial life-like evolutionary model, where individual agents are governed by linguistic fuzzy rule-based systems, which is capable of evolving all three classes of behaviour. PMID:28045964

Evolution of Collective Behaviour in an Artificial World Using Linguistic Fuzzy Rule-Based Systems.

PubMed

Demšar, Jure; Lebar Bajec, Iztok

2017-01-01

Collective behaviour is a fascinating and easily observable phenomenon, attractive to a wide range of researchers. In biology, computational models have been extensively used to investigate various properties of collective behaviour, such as: transfer of information across the group, benefits of grouping (defence against predation, foraging), group decision-making process, and group behaviour types. The question 'why,' however remains largely unanswered. Here the interest goes into which pressures led to the evolution of such behaviour, and evolutionary computational models have already been used to test various biological hypotheses. Most of these models use genetic algorithms to tune the parameters of previously presented non-evolutionary models, but very few attempt to evolve collective behaviour from scratch. Of these last, the successful attempts display clumping or swarming behaviour. Empirical evidence suggests that in fish schools there exist three classes of behaviour; swarming, milling and polarized. In this paper we present a novel, artificial life-like evolutionary model, where individual agents are governed by linguistic fuzzy rule-based systems, which is capable of evolving all three classes of behaviour.

An evolutionary firefly algorithm for the estimation of nonlinear biological model parameters.

PubMed

Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N V

2013-01-01

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.

An Evolutionary Firefly Algorithm for the Estimation of Nonlinear Biological Model Parameters

PubMed Central

Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N. V.

2013-01-01

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test. PMID:23469172

Vibration attenuation of the NASA Langley evolutionary structure experiment using H(sub infinity) and structured singular value (micron) robust multivariable control techniques

NASA Technical Reports Server (NTRS)

Balas, Gary J.

1992-01-01

The use is studied of active control to attenuate structural vibrations of the NASA Langley Phase Zero Evolutionary Structure due to external disturbance excitations. H sub infinity and structured singular value (mu) based control techniques are used to analyze and synthesize control laws for the NASA Langley Controls Structures Interaction (CSI) Evolutionary Model (CEM). The CEM structure experiment provides an excellent test bed to address control design issues for large space structures. Specifically, control design for structures with numerous lightly damped, coupled flexible modes, collocated and noncollocated sensors and actuators and stringent performance specifications. The performance objectives are to attenuate the vibration of the structure due to external disturbances, and minimize the actuator control force. The control design problem formulation for the CEM Structure uses a mathematical model developed with finite element techniques. A reduced order state space model for the control design is formulated from the finite element model. It is noted that there are significant variations between the design model and the experimentally derived transfer function data.

Breeding novel solutions in the brain: a model of Darwinian neurodynamics.

PubMed

Szilágyi, András; Zachar, István; Fedor, Anna; de Vladar, Harold P; Szathmáry, Eörs

2016-01-01

Background : The fact that surplus connections and neurons are pruned during development is well established. We complement this selectionist picture by a proof-of-principle model of evolutionary search in the brain, that accounts for new variations in theory space. We present a model for Darwinian evolutionary search for candidate solutions in the brain. Methods : We combine known components of the brain - recurrent neural networks (acting as attractors), the action selection loop and implicit working memory - to provide the appropriate Darwinian architecture. We employ a population of attractor networks with palimpsest memory. The action selection loop is employed with winners-share-all dynamics to select for candidate solutions that are transiently stored in implicit working memory. Results : We document two processes: selection of stored solutions and evolutionary search for novel solutions. During the replication of candidate solutions attractor networks occasionally produce recombinant patterns, increasing variation on which selection can act. Combinatorial search acts on multiplying units (activity patterns) with hereditary variation and novel variants appear due to (i) noisy recall of patterns from the attractor networks, (ii) noise during transmission of candidate solutions as messages between networks, and, (iii) spontaneously generated, untrained patterns in spurious attractors. Conclusions : Attractor dynamics of recurrent neural networks can be used to model Darwinian search. The proposed architecture can be used for fast search among stored solutions (by selection) and for evolutionary search when novel candidate solutions are generated in successive iterations. Since all the suggested components are present in advanced nervous systems, we hypothesize that the brain could implement a truly evolutionary combinatorial search system, capable of generating novel variants.

Upon Accounting for the Impact of Isoenzyme Loss, Gene Deletion Costs Anticorrelate with Their Evolutionary Rates.

PubMed

Jacobs, Christopher; Lambourne, Luke; Xia, Yu; Segrè, Daniel

2017-01-01

System-level metabolic network models enable the computation of growth and metabolic phenotypes from an organism's genome. In particular, flux balance approaches have been used to estimate the contribution of individual metabolic genes to organismal fitness, offering the opportunity to test whether such contributions carry information about the evolutionary pressure on the corresponding genes. Previous failure to identify the expected negative correlation between such computed gene-loss cost and sequence-derived evolutionary rates in Saccharomyces cerevisiae has been ascribed to a real biological gap between a gene's fitness contribution to an organism "here and now" and the same gene's historical importance as evidenced by its accumulated mutations over millions of years of evolution. Here we show that this negative correlation does exist, and can be exposed by revisiting a broadly employed assumption of flux balance models. In particular, we introduce a new metric that we call "function-loss cost", which estimates the cost of a gene loss event as the total potential functional impairment caused by that loss. This new metric displays significant negative correlation with evolutionary rate, across several thousand minimal environments. We demonstrate that the improvement gained using function-loss cost over gene-loss cost is explained by replacing the base assumption that isoenzymes provide unlimited capacity for backup with the assumption that isoenzymes are completely non-redundant. We further show that this change of the assumption regarding isoenzymes increases the recall of epistatic interactions predicted by the flux balance model at the cost of a reduction in the precision of the predictions. In addition to suggesting that the gene-to-reaction mapping in genome-scale flux balance models should be used with caution, our analysis provides new evidence that evolutionary gene importance captures much more than strict essentiality.

Evolutionary speed of species invasions.

PubMed

García-Ramos, Gisela; Rodríguez, Diego

2002-04-01

Successful invasion may depend of the capacity of a species to adjust genetically to a spatially varying environment. This research modeled a species invasion by examining the interaction between a quantitative genetic trait and population density. It assumed: (I) a quantitative genetic trait describes the adaptation of an individual to its local ecological conditions; (2) populations far from the local optimum grow more slowly than those near the optimum; and (3) the evolution of a trait depends on local population density, because differences in local population densities cause asymmetrical gene flow. This genetics-density interaction determined the propagation speed of populations. Numerical simulations showed that populations spread by advancing as two synchronic traveling waves, one for population density and one for trait adaptation. The form of the density wave was a step front that advances homogenizing populations at their carrying capacity; the adaptation wave was a curve with finite slope that homogenizes populations at full adaptation. The largest speed of population expansion, for a dimensionless analysis, corresponded to an almost homogeneous spatial environment when this model approached an ecological description such as the Fisher-Skellam's model. A large genetic response also favored faster speeds. Evolutionary speeds, in a natural scale, showed a wide range of rates that were also slower compared to models that only consider demographics. This evolutionary speed increased with high heritability, strong stabilizing selection, and high intrinsic growth rate. It decreased for steeper environmental gradients. Also indicated was an optimal dispersal rate over which evolutionary speed declined. This is expected because dispersal moves individuals further, but homogenizes populations genetically, making them maladapted. The evolutionary speed was compared to observed data. Furthermore, a moderate increase in the speed of expansion was predicted for ecological changes related to global warming.

Measuring fit of sequence data to phylogenetic model: gain of power using marginal tests.

PubMed

Waddell, Peter J; Ota, Rissa; Penny, David

2009-10-01

Testing fit of data to model is fundamentally important to any science, but publications in the field of phylogenetics rarely do this. Such analyses discard fundamental aspects of science as prescribed by Karl Popper. Indeed, not without cause, Popper (Unended quest: an intellectual autobiography. Fontana, London, 1976) once argued that evolutionary biology was unscientific as its hypotheses were untestable. Here we trace developments in assessing fit from Penny et al. (Nature 297:197-200, 1982) to the present. We compare the general log-likelihood ratio (the G or G (2) statistic) statistic between the evolutionary tree model and the multinomial model with that of marginalized tests applied to an alignment (using placental mammal coding sequence data). It is seen that the most general test does not reject the fit of data to model (P approximately 0.5), but the marginalized tests do. Tests on pairwise frequency (F) matrices, strongly (P < 0.001) reject the most general phylogenetic (GTR) models commonly in use. It is also clear (P < 0.01) that the sequences are not stationary in their nucleotide composition. Deviations from stationarity and homogeneity seem to be unevenly distributed amongst taxa; not necessarily those expected from examining other regions of the genome. By marginalizing the 4( t ) patterns of the i.i.d. model to observed and expected parsimony counts, that is, from constant sites, to singletons, to parsimony informative characters of a minimum possible length, then the likelihood ratio test regains power, and it too rejects the evolutionary model with P < 0.001. Given such behavior over relatively recent evolutionary time, readers in general should maintain a healthy skepticism of results, as the scale of the systematic errors in published trees may really be far larger than the analytical methods (e.g., bootstrap) report.

Climate change in fish: effects of respiratory constraints on optimal life history and behaviour.

PubMed

Holt, Rebecca E; Jørgensen, Christian

2015-02-01

The difference between maximum metabolic rate and standard metabolic rate is referred to as aerobic scope, and because it constrains performance it is suggested to constitute a key limiting process prescribing how fish may cope with or adapt to climate warming. We use an evolutionary bioenergetics model for Atlantic cod (Gadus morhua) to predict optimal life histories and behaviours at different temperatures. The model assumes common trade-offs and predicts that optimal temperatures for growth and fitness lie below that for aerobic scope; aerobic scope is thus a poor predictor of fitness at high temperatures. Initially, warming expands aerobic scope, allowing for faster growth and increased reproduction. Beyond the optimal temperature for fitness, increased metabolic requirements intensify foraging and reduce survival; oxygen budgeting conflicts thus constrain successful completion of the life cycle. The model illustrates how physiological adaptations are part of a suite of traits that have coevolved. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

An Hypothesis-Driven, Molecular Phylogenetics Exercise for College Biology Students

ERIC Educational Resources Information Center

Parker, Joel D.; Ziemba, Robert E.; Cahan, Sara Helms; Rissing, Steven W.

2004-01-01

This hypothesis-driven laboratory exercise teaches how DNA evidence can be used to investigate an organism's evolutionary history while providing practical modeling of the fundamental processes of gene transcription and translation. We used an inquiry-based approach to construct a laboratory around a nontrivial, open-ended evolutionary question…

A Strategic Approach to Joint Officer Management: Analysis and Modeling Results

DTIC Science & Technology

2009-01-01

rules. 5 Johnson and Wichern, 2002, p. 643. 6 Sullivan and Perry, 2004, p. 370. 7 Francesco Mola and Raffaele Miele, “Evolutionary Algorithms for...in Military Affairs, Newport, R.I.: Center for Naval Warfare Studies, 2003. Mola , Francesco, and Raffaele Miele, “Evolutionary Algorithms for

Origin and evolution of TNF and TNF receptor superfamilies

USDA-ARS?s Scientific Manuscript database

The tumor necrosis factor superfamily (TNFSF) and the TNF receptor superfamily (TNFRSF) have an ancient evolutionary origin that can be traced back to single copy genes within Arthropods. In humans, 18 TNFSF and 29 TNFRSF genes have been identified. Evolutionary models account for the increase in g...

Using Human Evolution to Teach Evolutionary Theory

ERIC Educational Resources Information Center

Besterman, Hugo; La Velle, Linda Baggott

2007-01-01

This paper discusses some traditional approaches to the teaching of evolutionary theory at pre-university level, criticising in particular some of the more commonly used models and exemplars. Curricular demands are described and an alternative approach is suggested, using the emerging story of human evolution. Recent discoveries help to illustrate…

Do arms races punctuate evolutionary stasis? Unified insights from phylogeny, phylogeography and microevolutionary processes.

PubMed

Toju, Hirokazu; Sota, Teiji

2009-09-01

One of the major controversies in evolutionary biology concerns the processes underlying macroevolutionary patterns in which prolonged stasis is disrupted by rapid, short-term evolution that leads species to new adaptive zones. Recent advances in the understanding of contemporary evolution have suggested that such rapid evolution can occur in the wild as a result of environmental changes. Here, we examined a novel hypothesis that evolutionary stasis is punctuated by co-evolutionary arms races, which continuously alter adaptive peaks and landscapes. Based on the phylogeny of long-mouthed weevils in the genus Curculio, likelihood ratio tests showed that the macroevolutionary pattern of the weevils coincides with the punctuational evolution model. A coalescent analysis of a species, Curculio camelliae, the mouthpart of which has diverged considerably among populations because of an arms race with its host plant, further suggested that major evolutionary shifts had occurred within 7000 generations. Through a microevolutionary analysis of the species, we also found that natural selection acting through co-evolutionary interactions is potentially strong enough to drive rapid evolutionary shifts between adaptive zones. Overall, we posit that co-evolution is an important factor driving the history of organismal evolution.

Multi-objective optimization of an arch dam shape under static loads using an evolutionary game method

NASA Astrophysics Data System (ADS)

Meng, Rui; Cheong, Kang Hao; Bao, Wei; Wong, Kelvin Kian Loong; Wang, Lu; Xie, Neng-gang

2018-06-01

This article attempts to evaluate the safety and economic performance of an arch dam under the action of static loads. The geometric description of a crown cantilever section and the horizontal arch ring is presented. A three-objective optimization model of arch dam shape is established based on the arch dam volume, maximum principal tensile stress and total strain energy. The evolutionary game method is then applied to obtain the optimal solution. In the evolutionary game technique, a novel and more efficient exploration method of the game players' strategy space, named the 'sorting partition method under the threshold limit', is presented, with the game profit functions constructed according to both competitive and cooperative behaviour. By way of example, three optimization goals have all shown improvements over the initial solutions. In particular, the evolutionary game method has potentially faster convergence. This demonstrates the preliminary proof of principle of the evolutionary game method.

POCO-MOEA: Using Evolutionary Algorithms to Solve the Controller Placement Problem

DTIC Science & Technology

2016-03-24

to gather data on POCO-MOEA performance to a series of iv model networks. The algorithm’s behavior is then evaluated and compared to ex- haustive... evaluation of a third heuristic based on a Multi 3 Objective Evolutionary Algorithm (MOEA). This heuristic is modeled after one of the most well known MOEAs...researchers to extend into more realistic evaluations of the performance characteristics of SDN controllers, such as the use of simulators or live

Metal-poor stars. IV - The evolution of red giants.

NASA Technical Reports Server (NTRS)

Rood, R. T.

1972-01-01

Detailed evolutionary calculations for six Population-II red giants are presented. The first five of these models are followed from the zero age main sequence to the onset of the helium flash. The sixth model allows the effect of direct electron-neutrino interactions to be estimated. The updated input physics and evolutionary code are described briefly. The results of the calculations are presented in a manner pertinent to later stages of evolutions and suitable for comparison with observations.

Inferring Fitness Effects from Time-Resolved Sequence Data with a Delay-Deterministic Model

PubMed Central

Nené, Nuno R.; Dunham, Alistair S.; Illingworth, Christopher J. R.

2018-01-01

A common challenge arising from the observation of an evolutionary system over time is to infer the magnitude of selection acting upon a specific genetic variant, or variants, within the population. The inference of selection may be confounded by the effects of genetic drift in a system, leading to the development of inference procedures to account for these effects. However, recent work has suggested that deterministic models of evolution may be effective in capturing the effects of selection even under complex models of demography, suggesting the more general application of deterministic approaches to inference. Responding to this literature, we here note a case in which a deterministic model of evolution may give highly misleading inferences, resulting from the nondeterministic properties of mutation in a finite population. We propose an alternative approach that acts to correct for this error, and which we denote the delay-deterministic model. Applying our model to a simple evolutionary system, we demonstrate its performance in quantifying the extent of selection acting within that system. We further consider the application of our model to sequence data from an evolutionary experiment. We outline scenarios in which our model may produce improved results for the inference of selection, noting that such situations can be easily identified via the use of a regular deterministic model. PMID:29500183

A road map for integrating eco-evolutionary processes into biodiversity models.

PubMed

Thuiller, Wilfried; Münkemüller, Tamara; Lavergne, Sébastien; Mouillot, David; Mouquet, Nicolas; Schiffers, Katja; Gravel, Dominique

2013-05-01

The demand for projections of the future distribution of biodiversity has triggered an upsurge in modelling at the crossroads between ecology and evolution. Despite the enthusiasm around these so-called biodiversity models, most approaches are still criticised for not integrating key processes known to shape species ranges and community structure. Developing an integrative modelling framework for biodiversity distribution promises to improve the reliability of predictions and to give a better understanding of the eco-evolutionary dynamics of species and communities under changing environments. In this article, we briefly review some eco-evolutionary processes and interplays among them, which are essential to provide reliable projections of species distributions and community structure. We identify gaps in theory, quantitative knowledge and data availability hampering the development of an integrated modelling framework. We argue that model development relying on a strong theoretical foundation is essential to inspire new models, manage complexity and maintain tractability. We support our argument with an example of a novel integrated model for species distribution modelling, derived from metapopulation theory, which accounts for abiotic constraints, dispersal, biotic interactions and evolution under changing environmental conditions. We hope such a perspective will motivate exciting and novel research, and challenge others to improve on our proposed approach. © 2013 John Wiley & Sons Ltd/CNRS.

Economic repercussions of fisheries-induced evolution

PubMed Central

Eikeset, Anne Maria; Richter, Andries; Dunlop, Erin S.; Dieckmann, Ulf; Stenseth, Nils Chr.

2013-01-01

Fish stocks experiencing high fishing mortality show a tendency to mature earlier and at a smaller size, which may have a genetic component and therefore long-lasting economic and biological effects. To date, the economic effects of such ecoevolutionary dynamics have not been empirically investigated. Using 70 y of data, we develop a bioeconomic model for Northeast Arctic cod to compare the economic yield in a model in which life-history traits can vary only through phenotypic plasticity with a model in which, in addition, genetic changes can occur. We find that evolutionary changes toward faster growth and earlier maturation occur consistently even if a stock is optimally managed. However, if a stock is managed optimally, the evolutionary changes actually increase economic yield because faster growth and earlier maturation raise the stock’s productivity. The optimal fishing mortality is almost identical for the evolutionary and nonevolutionary model and substantially lower than what it has been historically. Therefore, the costs of ignoring evolution under optimal management regimes are negligible. However, if fishing mortality is as high as it has been historically, evolutionary changes may result in economic losses, but only if the fishery is selecting for medium-sized individuals. Because evolution facilitates growth, the fish are younger and still immature when they are susceptible to getting caught, which outweighs the increase in productivity due to fish spawning at an earlier age. PMID:23836660

Evolution, the loss of diversity and the role of trade-offs.

PubMed

Best, Alex; Bowers, Roger; White, Andy

2015-06-01

We investigate how the loss of previously evolved diversity in host resistance to disease is dependent on the complexity of the underlying evolutionary trade-off. Working within the adaptive dynamics framework, using graphical tools (pairwise invasion plots, PIPs; trait evolution plots, TEPs) and algebraic analysis we consider polynomial trade-offs of increasing degree. Our focus is on the evolutionary trajectory of the dimorphic population after it has been attracted to an evolutionary branching point. We show that for sufficiently complex trade-offs (here, polynomials of degree three or higher) the resulting invasion boundaries can form closed 'oval' areas of invadability and strategy coexistence. If no attracting singular strategies exist within this region, then the population is destined to evolve outside of the region of coexistence, resulting in the loss of one strain. In particular, the loss of diversity in this model always occurs in such a way that the remaining strain is not attracted back to the branching point but to an extreme of the trade-off, meaning the diversity is lost forever. We also show similar results for a non-polynomial but complex trade-off, and for a different eco-evolutionary model. Our work further highlights the importance of trade-offs to evolutionary behaviour. Copyright © 2015 Elsevier Inc. All rights reserved.

Estimating the Effect of Competition on Trait Evolution Using Maximum Likelihood Inference.

PubMed

Drury, Jonathan; Clavel, Julien; Manceau, Marc; Morlon, Hélène

2016-07-01

Many classical ecological and evolutionary theoretical frameworks posit that competition between species is an important selective force. For example, in adaptive radiations, resource competition between evolving lineages plays a role in driving phenotypic diversification and exploration of novel ecological space. Nevertheless, current models of trait evolution fit to phylogenies and comparative data sets are not designed to incorporate the effect of competition. The most advanced models in this direction are diversity-dependent models where evolutionary rates depend on lineage diversity. However, these models still treat changes in traits in one branch as independent of the value of traits on other branches, thus ignoring the effect of species similarity on trait evolution. Here, we consider a model where the evolutionary dynamics of traits involved in interspecific interactions are influenced by species similarity in trait values and where we can specify which lineages are in sympatry. We develop a maximum likelihood based approach to fit this model to combined phylogenetic and phenotypic data. Using simulations, we demonstrate that the approach accurately estimates the simulated parameter values across a broad range of parameter space. Additionally, we develop tools for specifying the biogeographic context in which trait evolution occurs. In order to compare models, we also apply these biogeographic methods to specify which lineages interact sympatrically for two diversity-dependent models. Finally, we fit these various models to morphological data from a classical adaptive radiation (Greater Antillean Anolis lizards). We show that models that account for competition and geography perform better than other models. The matching competition model is an important new tool for studying the influence of interspecific interactions, in particular competition, on phenotypic evolution. More generally, it constitutes a step toward a better integration of interspecific interactions in many ecological and evolutionary processes. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Evolutionary robotics simulations help explain why reciprocity is rare in nature

PubMed Central

André, Jean-Baptiste; Nolfi, Stefano

2016-01-01

The relative rarity of reciprocity in nature, contrary to theoretical predictions that it should be widespread, is currently one of the major puzzles in social evolution theory. Here we use evolutionary robotics to solve this puzzle. We show that models based on game theory are misleading because they neglect the mechanics of behavior. In a series of experiments with simulated robots controlled by artificial neural networks, we find that reciprocity does not evolve, and show that this results from a general constraint that likely also prevents it from evolving in the wild. Reciprocity can evolve if it requires very few mutations, as is usually assumed in evolutionary game theoretic models, but not if, more realistically, it requires the accumulation of many adaptive mutations. PMID:27616139

Recovery after mass extinction: evolutionary assembly in large-scale biosphere dynamics.

PubMed Central

Solé, Ricard V; Montoya, José M; Erwin, Douglas H

2002-01-01

Biotic recoveries following mass extinctions are characterized by a process in which whole ecologies are reconstructed from low-diversity systems, often characterized by opportunistic groups. The recovery process provides an unexpected window to ecosystem dynamics. In many aspects, recovery is very similar to ecological succession, but important differences are also apparently linked to the innovative patterns of niche construction observed in the fossil record. In this paper, we analyse the similarities and differences between ecological succession and evolutionary recovery to provide a preliminary ecological theory of recoveries. A simple evolutionary model with three trophic levels is presented, and its properties (closely resembling those observed in the fossil record) are compared with characteristic patterns of ecological response to disturbances in continuous models of three-level ecosystems. PMID:12079530

The role of selection on evolutionary rescue

NASA Astrophysics Data System (ADS)

Amirjanov, Adil

The paper investigates the role of selection on evolutionary rescue of population. The statistical mechanics technique is used to model dynamics of a population experiencing a natural selection and an abrupt change in the environment. The paper assesses the selective pressure produced by two different mechanisms: by strength of resistance and by strength of selection (by intraspecific competition). It is shown that both mechanisms are capable of providing an evolutionary rescue of population in particular conditions. However, for a small level of an extinction rate, the population cannot be rescued without intraspecific competition.

Threat-detection in child development: an evolutionary perspective.

PubMed

Boyer, Pascal; Bergstrom, Brian

2011-03-01

Evidence for developmental aspects of fear-targets and anxiety suggests a complex but stable pattern whereby specific kinds of fears emerge at different periods of development. This developmental schedule seems appropriate to dangers encountered repeatedly during human evolution. Also consistent with evolutionary perspective, the threat-detection systems are domain-specific, comprising different kinds of cues to do with predation, intraspecific violence, contamination-contagion and status loss. Proper evolutionary models may also be relevant to outstanding issues in the domain, notably the connections between typical development and pathology. Copyright © 2010 Elsevier Ltd. All rights reserved.

Evolution Model and Simulation of Profit Model of Agricultural Products Logistics Financing

NASA Astrophysics Data System (ADS)

Yang, Bo; Wu, Yan

2018-03-01

Agricultural products logistics financial warehousing business mainly involves agricultural production and processing enterprises, third-party logistics enterprises and financial institutions tripartite, to enable the three parties to achieve win-win situation, the article first gives the replication dynamics and evolutionary stability strategy between the three parties in business participation, and then use NetLogo simulation platform, using the overall modeling and simulation method of Multi-Agent, established the evolutionary game simulation model, and run the model under different revenue parameters, finally, analyzed the simulation results. To achieve the agricultural products logistics financial financing warehouse business to participate in tripartite mutually beneficial win-win situation, thus promoting the smooth flow of agricultural products logistics business.

Evolution of complex organic molecules in hot molecular cores. Synthetic spectra at (sub-)mm wavebands

NASA Astrophysics Data System (ADS)

Choudhury, R.; Schilke, P.; Stéphan, G.; Bergin, E.; Möller, T.; Schmiedeke, A.; Zernickel, A.

2015-03-01

Context. Hot molecular cores (HMCs) are intermediate stages of high-mass star formation and are also known for their rich chemical reservoirs and emission line spectra at (sub-)mm wavebands. Complex organic molecules (COMs) such as methanol (CH3OH), ethanol (C2H5OH), dimethyl ether (CH3OCH3), and methyl formate (HCOOCH3) produce most of these observed lines. The observed spectral feature of HMCs such as total number of emission lines and associated line intensities are also found to vary with evolutionary stages. Aims: We aim to investigate the spectral evolution of these COMs to explore the initial evolutionary stages of high-mass star formation including HMCs. Methods: We developed various 3D models for HMCs guided by the evolutionary scenarios proposed by recent empirical and modeling studies. We then investigated the spatio-temporal variation of temperature and molecular abundances in HMCs by consistently coupling gas-grain chemical evolution with radiative transfer calculations. We explored the effects of varying physical conditions on molecular abundances including density distribution and luminosity evolution of the central protostar(s) among other parameters. Finally, we simulated the synthetic spectra for these models at different evolutionary timescales to compare with observations. Results: Temperature has a profound effect on the formation of COMs through the depletion and diffusion on grain surface to desorption and further gas-phase processing. The time-dependent temperature structure of the hot core models provides a realistic framework for investigating the spatial variation of ice mantle evaporation as a function of evolutionary timescales. We find that a slightly higher value (15 K) than the canonical dark cloud temperature (10 K) provides a more productive environment for COM formation on grain surface. With increasing protostellar luminosity, the water ice evaporation font (~100 K) expands and the spatial distribution of gas phase abundances of these COMs also spreads out. We calculated the temporal variation of the radial profiles of these COMs for different hot core models. These profiles resemble the so-called jump profiles with relative abundances higher than 10-9 within the evaporation font will furthermore be useful to model the observed spectra of hot cores. We present the simulated spectra of these COMs for different hot core models at various evolutionary timescales. A qualitative comparison of the simulated and observed spectra suggests that these self-consistent hot core models can reproduce the notable trends in hot core spectral variation within the typical hot core timescales of 105 year. These models predict that the spatial distribution of various emission line maps will also expand with evolutionary time; this feature can be used to constrain the relative desorption energies of the molecules that mainly form on the grain surface and return to the gas phase via thermal desorption. The detailed modeling of the thermal structure of hot cores with similar masses along with the characterization of the desorption energies of different molecules can be used to constrain the luminosity evolution of the central protostars. The model predictions can be compared with high resolution observation that can probe scales of a few thousand AU in high-mass star forming regions such as from Atacama Large Millimeter/submillimeter Array (ALMA). We used a spectral fitting method to analyze the simulated spectra and find that it significantly underestimates some of the physical parameters such as temperature. The coupling of chemical evolution with radiative transfer models will be particularly useful to decipher the physical structure of hot cores and also to constrain the initial evolutionary stages of high-mass star formation. Appendices are available in electronic form at http://www.aanda.org

Children's Ideas about Fossils and Foundational Concepts Related to Fossils

ERIC Educational Resources Information Center

Borgerding, Lisa A.; Raven, Sara

2018-01-01

Many standards documents and learning progressions recommend evolution learning in elementary grades. Given young children's interest in dinosaurs and other fossils, fossil investigations can provide a rich entry into evolutionary biology for young learners. Educational psychology literature has addressed children's reasoning about foundational…

Evolution Acceptance and Epistemological Beliefs of College Biology Students

ERIC Educational Resources Information Center

Borgerding, Lisa A.; Deniz, Hasan; Anderson, Elizabeth Shevock

2017-01-01

Evolutionary theory is central to biology, and scientifically accurate evolution instruction is promoted within national and state standards documents. Previous literature has identified students' epistemological beliefs as potential predictors of evolution acceptance. The present work seeks to explore more directly how student views of evolution…

Teaching Biodiversity & Evolution through Travel Course Experiences

ERIC Educational Resources Information Center

Zervanos, Stam. M.; McLaughlin, Jacqueline S.

2003-01-01

Biodiversity is the extraordinary variety of life in this planet. In order to be fully appreciated, biodiversity needs to be experienced firsthand, or "experientially." Thus, the standard classroom lecture format is not the ideal situation for teaching biodiversity and evolutionary concepts, in that student interest and understanding are…

Evolutionary-driven support vector machines for determining the degree of liver fibrosis in chronic hepatitis C.

PubMed

Stoean, Ruxandra; Stoean, Catalin; Lupsor, Monica; Stefanescu, Horia; Badea, Radu

2011-01-01

Hepatic fibrosis, the principal pointer to the development of a liver disease within chronic hepatitis C, can be measured through several stages. The correct evaluation of its degree, based on recent different non-invasive procedures, is of current major concern. The latest methodology for assessing it is the Fibroscan and the effect of its employment is impressive. However, the complex interaction between its stiffness indicator and the other biochemical and clinical examinations towards a respective degree of liver fibrosis is hard to be manually discovered. In this respect, the novel, well-performing evolutionary-powered support vector machines are proposed towards an automated learning of the relationship between medical attributes and fibrosis levels. The traditional support vector machines have been an often choice for addressing hepatic fibrosis, while the evolutionary option has been validated on many real-world tasks and proven flexibility and good performance. The evolutionary approach is simple and direct, resulting from the hybridization of the learning component within support vector machines and the optimization engine of evolutionary algorithms. It discovers the optimal coefficients of surfaces that separate instances of distinct classes. Apart from a detached manner of establishing the fibrosis degree for new cases, a resulting formula also offers insight upon the correspondence between the medical factors and the respective outcome. What is more, a feature selection genetic algorithm can be further embedded into the method structure, in order to dynamically concentrate search only on the most relevant attributes. The data set refers 722 patients with chronic hepatitis C infection and 24 indicators. The five possible degrees of fibrosis range from F0 (no fibrosis) to F4 (cirrhosis). Since the standard support vector machines are among the most frequently used methods in recent artificial intelligence studies for hepatic fibrosis staging, the evolutionary method is viewed in comparison to the traditional one. The multifaceted discrimination into all five degrees of fibrosis and the slightly less difficult common separation into solely three related stages are both investigated. The resulting performance proves the superiority over the standard support vector classification and the attained formula is helpful in providing an immediate calculation of the liver stage for new cases, while establishing the presence/absence and comprehending the weight of each medical factor with respect to a certain fibrosis level. The use of the evolutionary technique for fibrosis degree prediction triggers simplicity and offers a direct expression of the influence of dynamically selected indicators on the corresponding stage. Perhaps most importantly, it significantly surpasses the classical support vector machines, which are both widely used and technically sound. All these therefore confirm the promise of the new methodology towards a dependable support within the medical decision-making. Copyright © 2010 Elsevier B.V. All rights reserved.

Models of performance of evolutionary program induction algorithms based on indicators of problem difficulty.

PubMed

Graff, Mario; Poli, Riccardo; Flores, Juan J

2013-01-01

Modeling the behavior of algorithms is the realm of evolutionary algorithm theory. From a practitioner's point of view, theory must provide some guidelines regarding which algorithm/parameters to use in order to solve a particular problem. Unfortunately, most theoretical models of evolutionary algorithms are difficult to apply to realistic situations. However, in recent work (Graff and Poli, 2008, 2010), where we developed a method to practically estimate the performance of evolutionary program-induction algorithms (EPAs), we started addressing this issue. The method was quite general; however, it suffered from some limitations: it required the identification of a set of reference problems, it required hand picking a distance measure in each particular domain, and the resulting models were opaque, typically being linear combinations of 100 features or more. In this paper, we propose a significant improvement of this technique that overcomes the three limitations of our previous method. We achieve this through the use of a novel set of features for assessing problem difficulty for EPAs which are very general, essentially based on the notion of finite difference. To show the capabilities or our technique and to compare it with our previous performance models, we create models for the same two important classes of problems-symbolic regression on rational functions and Boolean function induction-used in our previous work. We model a variety of EPAs. The comparison showed that for the majority of the algorithms and problem classes, the new method produced much simpler and more accurate models than before. To further illustrate the practicality of the technique and its generality (beyond EPAs), we have also used it to predict the performance of both autoregressive models and EPAs on the problem of wind speed forecasting, obtaining simpler and more accurate models that outperform in all cases our previous performance models.

Evolutionary Considerations on the Emerging Subculture of the E-psychonauts and the Novel Psychoactive Substances: A Comeback to the Shamanism?

PubMed

Orsolini, Laura; St John-Smith, Paul; McQueen, Daniel; Papanti, Duccio; Corkery, John; Schifano, Fabrizio

2017-01-01

Evolutionary research on drug abuse has hitherto been restricted to proximate studies, considering aetiology, mechanism, and ontogeny. However, in order to explain the recent emergency of a new behavioral pattern (e.g. 'the e-psychonaut style') of novel psychoactive substances' (NPS) intake, a complementary evolutionary model may be needed. A range of evolutionary interpretations on the 'psychonaut style' and the recent emergency of NPS were here considered. The PubMed database was searched in order to elicit evolutionary theory-based documents commenting on NPS/NPS users/e-psychonauts. The traditional 'shamanic style' use of entheogens/plant-derived compounds may present with a range of similarities with the 'e-psychonauts' use of mostly of hallucinogen/psychedelic NPS. These users consider themselves as 'new/technological' shamans. Indeed, a range of evolutionary mechanisms, such as: optimal foraging, costly signaling, and reproduction at the expense of health may all cooperate to explain the recent spread and diffusion of the NPS market, and this may represent a reason of concern. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A Study of Driver's Route Choice Behavior Based on Evolutionary Game Theory

PubMed Central

Jiang, Xiaowei; Ji, Yanjie; Deng, Wei

2014-01-01

This paper proposes a route choice analytic method that embeds cumulative prospect theory in evolutionary game theory to analyze how the drivers adjust their route choice behaviors under the influence of the traffic information. A simulated network with two alternative routes and one variable message sign is built to illustrate the analytic method. We assume that the drivers in the transportation system are bounded rational, and the traffic information they receive is incomplete. An evolutionary game model is constructed to describe the evolutionary process of the drivers' route choice decision-making behaviors. Here we conclude that the traffic information plays an important role in the route choice behavior. The driver's route decision-making process develops towards different evolutionary stable states in accordance with different transportation situations. The analysis results also demonstrate that employing cumulative prospect theory and evolutionary game theory to study the driver's route choice behavior is effective. This analytic method provides an academic support and suggestion for the traffic guidance system, and may optimize the travel efficiency to a certain extent. PMID:25610455

Evolutionary Considerations on the Emerging Subculture of the E-psychonauts and the Novel Psychoactive Substances: A Comeback to the Shamanism?

PubMed Central

Orsolini, Laura; St John-Smith, Paul; McQueen, Daniel; Papanti, Duccio; Corkery, John; Schifano, Fabrizio

2017-01-01

Background: Evolutionary research on drug abuse has hitherto been restricted to proximate studies, considering aetiology, mechanism, and ontogeny. However, in order to explain the recent emergency of a new behavioral pattern (e.g. ‘the e-psychonaut style’) of novel psychoactive substances’ (NPS) intake, a complementary evolutionary model may be needed. Objective A range of evolutionary interpretations on the ‘psychonaut style’ and the recent emergency of NPS were here considered. Method The PubMed database was searched in order to elicit evolutionary theory-based documents commenting on NPS/NPS users/e-psychonauts. Results The traditional ‘shamanic style’ use of entheogens/plant-derived compounds may present with a range of similarities with the ‘e-psychonauts’ use of mostly of hallucinogen/psychedelic NPS. These users consider themselves as ‘new/technological’ shamans. Conclusion Indeed, a range of evolutionary mechanisms, such as: optimal foraging, costly signaling, and reproduction at the expense of health may all cooperate to explain the recent spread and diffusion of the NPS market, and this may represent a reason of concern. PMID:27834144

Evolutionary accounts of human behavioural diversity

PubMed Central

Brown, Gillian R.; Dickins, Thomas E.; Sear, Rebecca; Laland, Kevin N.

2011-01-01

Human beings persist in an extraordinary range of ecological settings, in the process exhibiting enormous behavioural diversity, both within and between populations. People vary in their social, mating and parental behaviour and have diverse and elaborate beliefs, traditions, norms and institutions. The aim of this theme issue is to ask whether, and how, evolutionary theory can help us to understand this diversity. In this introductory article, we provide a background to the debate surrounding how best to understand behavioural diversity using evolutionary models of human behaviour. In particular, we examine how diversity has been viewed by the main subdisciplines within the human evolutionary behavioural sciences, focusing in particular on the human behavioural ecology, evolutionary psychology and cultural evolution approaches. In addition to differences in focus and methodology, these subdisciplines have traditionally varied in the emphasis placed on human universals, ecological factors and socially learned behaviour, and on how they have addressed the issue of genetic variation. We reaffirm that evolutionary theory provides an essential framework for understanding behavioural diversity within and between human populations, but argue that greater integration between the subfields is critical to developing a satisfactory understanding of diversity. PMID:21199836

A study of driver's route choice behavior based on evolutionary game theory.

PubMed

Jiang, Xiaowei; Ji, Yanjie; Du, Muqing; Deng, Wei

2014-01-01

This paper proposes a route choice analytic method that embeds cumulative prospect theory in evolutionary game theory to analyze how the drivers adjust their route choice behaviors under the influence of the traffic information. A simulated network with two alternative routes and one variable message sign is built to illustrate the analytic method. We assume that the drivers in the transportation system are bounded rational, and the traffic information they receive is incomplete. An evolutionary game model is constructed to describe the evolutionary process of the drivers' route choice decision-making behaviors. Here we conclude that the traffic information plays an important role in the route choice behavior. The driver's route decision-making process develops towards different evolutionary stable states in accordance with different transportation situations. The analysis results also demonstrate that employing cumulative prospect theory and evolutionary game theory to study the driver's route choice behavior is effective. This analytic method provides an academic support and suggestion for the traffic guidance system, and may optimize the travel efficiency to a certain extent.

Evolution of dispersal in spatially and temporally variable environments: The importance of life cycles.

PubMed

Massol, François; Débarre, Florence

2015-07-01

Spatiotemporal variability of the environment is bound to affect the evolution of dispersal, and yet model predictions strongly differ on this particular effect. Recent studies on the evolution of local adaptation have shown that the life cycle chosen to model the selective effects of spatiotemporal variability of the environment is a critical factor determining evolutionary outcomes. Here, we investigate the effect of the order of events in the life cycle on the evolution of unconditional dispersal in a spatially heterogeneous, temporally varying landscape. Our results show that the occurrence of intermediate singular strategies and disruptive selection are conditioned by the temporal autocorrelation of the environment and by the life cycle. Life cycles with dispersal of adults versus dispersal of juveniles, local versus global density regulation, give radically different evolutionary outcomes that include selection for total philopatry, evolutionary bistability, selection for intermediate stable states, and evolutionary branching points. Our results highlight the importance of accounting for life-cycle specifics when predicting the effects of the environment on evolutionarily selected trait values, such as dispersal, as well as the need to check the robustness of model conclusions against modifications of the life cycle. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Preferential selection based on strategy persistence and memory promotes cooperation in evolutionary prisoner's dilemma games

NASA Astrophysics Data System (ADS)

Liu, Yuanming; Huang, Changwei; Dai, Qionglin

2018-06-01

Strategy imitation plays a crucial role in evolutionary dynamics when we investigate the spontaneous emergence of cooperation under the framework of evolutionary game theory. Generally, when an individual updates his strategy, he needs to choose a role model whom he will learn from. In previous studies, individuals choose role models randomly from their neighbors. In recent works, researchers have considered that individuals choose role models according to neighbors' attractiveness characterized by the present network topology or historical payoffs. Here, we associate an individual's attractiveness with the strategy persistence, which characterizes how frequently he changes his strategy. We introduce a preferential parameter α to describe the nonlinear correlation between the selection probability and the strategy persistence and the memory length of individuals M into the evolutionary games. We investigate the effects of α and M on cooperation. Our results show that cooperation could be promoted when α > 0 and at the same time M > 1, which corresponds to the situation that individuals are inclined to select their neighbors with relatively higher persistence levels during the evolution. Moreover, we find that the cooperation level could reach the maximum at an optimal memory length when α > 0. Our work sheds light on how to promote cooperation through preferential selection based on strategy persistence and a limited memory length.

Joint scaling laws in functional and evolutionary categories in prokaryotic genomes

PubMed Central

Grilli, J.; Bassetti, B.; Maslov, S.; Cosentino Lagomarsino, M.

2012-01-01

We propose and study a class-expansion/innovation/loss model of genome evolution taking into account biological roles of genes and their constituent domains. In our model, numbers of genes in different functional categories are coupled to each other. For example, an increase in the number of metabolic enzymes in a genome is usually accompanied by addition of new transcription factors regulating these enzymes. Such coupling can be thought of as a proportional ‘recipe’ for genome composition of the type ‘a spoonful of sugar for each egg yolk’. The model jointly reproduces two known empirical laws: the distribution of family sizes and the non-linear scaling of the number of genes in certain functional categories (e.g. transcription factors) with genome size. In addition, it allows us to derive a novel relation between the exponents characterizing these two scaling laws, establishing a direct quantitative connection between evolutionary and functional categories. It predicts that functional categories that grow faster-than-linearly with genome size to be characterized by flatter-than-average family size distributions. This relation is confirmed by our bioinformatics analysis of prokaryotic genomes. This proves that the joint quantitative trends of functional and evolutionary classes can be understood in terms of evolutionary growth with proportional recipes. PMID:21937509

Using modified fruit fly optimisation algorithm to perform the function test and case studies

NASA Astrophysics Data System (ADS)

Pan, Wen-Tsao

2013-06-01

Evolutionary computation is a computing mode established by practically simulating natural evolutionary processes based on the concept of Darwinian Theory, and it is a common research method. The main contribution of this paper was to reinforce the function of searching for the optimised solution using the fruit fly optimization algorithm (FOA), in order to avoid the acquisition of local extremum solutions. The evolutionary computation has grown to include the concepts of animal foraging behaviour and group behaviour. This study discussed three common evolutionary computation methods and compared them with the modified fruit fly optimization algorithm (MFOA). It further investigated the ability of the three mathematical functions in computing extreme values, as well as the algorithm execution speed and the forecast ability of the forecasting model built using the optimised general regression neural network (GRNN) parameters. The findings indicated that there was no obvious difference between particle swarm optimization and the MFOA in regards to the ability to compute extreme values; however, they were both better than the artificial fish swarm algorithm and FOA. In addition, the MFOA performed better than the particle swarm optimization in regards to the algorithm execution speed, and the forecast ability of the forecasting model built using the MFOA's GRNN parameters was better than that of the other three forecasting models.

Keeping pace with climate change: what is wrong with the evolutionary potential of upper thermal limits?

PubMed Central

Santos, Mauro; Castañeda, Luis E; Rezende, Enrico L

2012-01-01

The potential of populations to evolve in response to ongoing climate change is partly conditioned by the presence of heritable genetic variation in relevant physiological traits. Recent research suggests that Drosophila melanogaster exhibits negligible heritability, hence little evolutionary potential in heat tolerance when measured under slow heating rates that presumably mimic conditions in nature. Here, we study the effects of directional selection for increased heat tolerance using Drosophila as a model system. We combine a physiological model to simulate thermal tolerance assays with multilocus models for quantitative traits. Our simulations show that, whereas the evolutionary response of the genetically determined upper thermal limit (CTmax) is independent of methodological context, the response in knockdown temperatures varies with measurement protocol and is substantially (up to 50%) lower than for CTmax. Realized heritabilities of knockdown temperature may grossly underestimate the true heritability of CTmax. For instance, assuming that the true heritability of CTmax in the base population is h2 = 0.25, realized heritabilities of knockdown temperature are around 0.08–0.16 depending on heating rate. These effects are higher in slow heating assays, suggesting that flawed methodology might explain the apparently limited evolutionary potential of cosmopolitan D. melanogaster. PMID:23170220

Stochastic evolutionary voluntary public goods game with punishment in a Quasi-birth-and-death process.

PubMed

Quan, Ji; Liu, Wei; Chu, Yuqing; Wang, Xianjia

2017-11-23

Traditional replication dynamic model and the corresponding concept of evolutionary stable strategy (ESS) only takes into account whether the system can return to the equilibrium after being subjected to a small disturbance. In the real world, due to continuous noise, the ESS of the system may not be stochastically stable. In this paper, a model of voluntary public goods game with punishment is studied in a stochastic situation. Unlike the existing model, we describe the evolutionary process of strategies in the population as a generalized quasi-birth-and-death process. And we investigate the stochastic stable equilibrium (SSE) instead. By numerical experiments, we get all possible SSEs of the system for any combination of parameters, and investigate the influence of parameters on the probabilities of the system to select different equilibriums. It is found that in the stochastic situation, the introduction of the punishment and non-participation strategies can change the evolutionary dynamics of the system and equilibrium of the game. There is a large range of parameters that the system selects the cooperative states as its SSE with a high probability. This result provides us an insight and control method for the evolution of cooperation in the public goods game in stochastic situations.

Inference of Evolutionary Jumps in Large Phylogenies using Lévy Processes.

PubMed

Duchen, Pablo; Leuenberger, Christoph; Szilágyi, Sándor M; Harmon, Luke; Eastman, Jonathan; Schweizer, Manuel; Wegmann, Daniel

2017-11-01

Although it is now widely accepted that the rate of phenotypic evolution may not necessarily be constant across large phylogenies, the frequency and phylogenetic position of periods of rapid evolution remain unclear. In his highly influential view of evolution, G. G. Simpson supposed that such evolutionary jumps occur when organisms transition into so-called new adaptive zones, for instance after dispersal into a new geographic area, after rapid climatic changes, or following the appearance of an evolutionary novelty. Only recently, large, accurate and well calibrated phylogenies have become available that allow testing this hypothesis directly, yet inferring evolutionary jumps remains computationally very challenging. Here, we develop a computationally highly efficient algorithm to accurately infer the rate and strength of evolutionary jumps as well as their phylogenetic location. Following previous work we model evolutionary jumps as a compound process, but introduce a novel approach to sample jump configurations that does not require matrix inversions and thus naturally scales to large trees. We then make use of this development to infer evolutionary jumps in Anolis lizards and Loriinii parrots where we find strong signal for such jumps at the basis of clades that transitioned into new adaptive zones, just as postulated by Simpson's hypothesis. [evolutionary jump; Lévy process; phenotypic evolution; punctuated equilibrium; quantitative traits. The Author(s) 2017. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

Novel Insights on Hantavirus Evolution: The Dichotomy in Evolutionary Pressures Acting on Different Hantavirus Segments.

PubMed

Sankar, Sathish; Upadhyay, Mohita; Ramamurthy, Mageshbabu; Vadivel, Kumaran; Sagadevan, Kalaiselvan; Nandagopal, Balaji; Vivekanandan, Perumal; Sridharan, Gopalan

2015-01-01

Hantaviruses are important emerging zoonotic pathogens. The current understanding of hantavirus evolution is complicated by the lack of consensus on co-divergence of hantaviruses with their animal hosts. In addition, hantaviruses have long-term associations with their reservoir hosts. Analyzing the relative abundance of dinucleotides may shed new light on hantavirus evolution. We studied the relative abundance of dinucleotides and the evolutionary pressures shaping different hantavirus segments. A total of 118 sequences were analyzed; this includes 51 sequences of the S segment, 43 sequences of the M segment and 23 sequences of the L segment. The relative abundance of dinucleotides, effective codon number (ENC), codon usage biases were analyzed. Standard methods were used to investigate the relative roles of mutational pressure and translational selection on the three hantavirus segments. All three segments of hantaviruses are CpG depleted. Mutational pressure is the predominant evolutionary force leading to CpG depletion among hantaviruses. Interestingly, the S segment of hantaviruses is GpU depleted and in contrast to CpG depletion, the depletion of GpU dinucleotides from the S segment is driven by translational selection. Our findings also suggest that mutational pressure is the primary evolutionary pressure acting on the S and the M segments of hantaviruses. While translational selection plays a key role in shaping the evolution of the L segment. Our findings highlight how different evolutionary pressures may contribute disproportionally to the evolution of the three hantavirus segments. These findings provide new insights on the current understanding of hantavirus evolution. There is a dichotomy among evolutionary pressures shaping a) the relative abundance of different dinucleotides in hantavirus genomes b) the evolution of the three hantavirus segments.

Tangled nature: a model of evolutionary ecology.

PubMed

Christensen, Kim; di Collobiano, Simone A; Hall, Matt; Jensen, Henrik J

2002-05-07

We discuss a simple model of co-evolution. In order to emphasize the effect of interaction between individuals, the entire population is subjected to the same physical environment. Species are emergent structures and extinction, origination and diversity are entirely a consequence of co-evolutionary interaction between individuals. For comparison, we consider both asexual and sexually reproducing populations. In either case, the system evolves through periods of hectic reorganization separated by periods of coherent stable coexistence. Copyright 2002 Elsevier Science Ltd. All rights reserved.

Differences in evolutionary history translate into differences in invasion success of alien mammals in South Africa

PubMed Central

Yessoufou, Kowiyou; Gere, Jephris; Daru, Barnabas H; van der Bank, Michelle

2014-01-01

Attempts to investigate the drivers of invasion success are generally limited to the biological and evolutionary traits distinguishing native from introduced species. Although alien species introduced to the same recipient environment differ in their invasion intensity – for example, some are “strong invaders”; others are “weak invaders” – the factors underlying the variation in invasion success within alien communities are little explored. In this study, we ask what drives the variation in invasion success of alien mammals in South Africa. First, we tested for taxonomic and phylogenetic signal in invasion intensity. Second, we reconstructed predictive models of the variation in invasion intensity among alien mammals using the generalized linear mixed-effects models. We found that the family Bovidae and the order Artiodactyla contained more “strong invaders” than expected by chance, and that such taxonomic signal did not translate into phylogenetic selectivity. In addition, our study indicates that latitude, gestation length, social group size, and human population density are only marginal determinant of the variation in invasion success. However, we found that evolutionary distinctiveness – a parameter characterising the uniqueness of each alien species – is the most important predictive variable. Our results indicate that the invasive behavior of alien mammals may have been “fingerprinted” in their evolutionary past, and that evolutionary history might capture beyond ecological, biological and life-history traits usually prioritized in predictive modeling of invasion success. These findings have applicability to the management of alien mammals in South Africa. PMID:25360253

Promotion of cooperation in evolutionary game dynamics with local information.

PubMed

Liu, Xuesong; Pan, Qiuhui; He, Mingfeng

2018-01-21

In this paper, we propose a strategy-updating rule driven by local information, which is called Local process. Unlike the standard Moran process, the Local process does not require global information about the strategic environment. By analyzing the dynamical behavior of the system, we explore how the local information influences the fixation of cooperation in two-player evolutionary games. Under weak selection, the decreasing local information leads to an increase of the fixation probability when natural selection does not favor cooperation replacing defection. In the limit of sufficiently large selection, the analytical results indicate that the fixation probability increases with the decrease of the local information, irrespective of the evolutionary games. Furthermore, for the dominance of defection games under weak selection and for coexistence games, the decreasing of local information will lead to a speedup of a single cooperator taking over the population. Overall, to some extent, the local information is conducive to promoting the cooperation. Copyright © 2017 Elsevier Ltd. All rights reserved.

The natural selection of altruistic traits.

PubMed

Boehm, C

1999-09-01

Proponents of the standard evolutionary biology paradigm explain human "altruism" in terms of either nepotism or strict reciprocity. On that basis our underlying nature is reduced to a function of inclusive fitness: human nature has to be totally selfish or nepotistic. Proposed here are three possible paths to giving costly aid to nonrelatives, paths that are controversial because they involve assumed pleiotropic effects or group selection. One path is pleiotropic subsidies that help to extend nepotistic helping behavior from close family to nonrelatives. Another is "warfare"-if and only if warfare recurred in the Paleolithic. The third and most plausible hypothesis is based on the morally based egalitarian syndrome of prehistoric hunter-gatherers, which reduced phenotypic variation at the within-group level, increased it at the between-group level, and drastically curtailed the advantages of free riders. In an analysis consistent with the fundamental tenets of evolutionary biology, these three paths are evaluated as explanations for the evolutionary development of a rather complicated human social nature.

Toward a revised evolutionary adaptationist analysis of depression: the social navigation hypothesis.

PubMed

Watson, Paul J; Andrews, Paul W

2002-10-01

Evolutionary biologists use Darwinian theory and functional design ("reverse engineering") analyses, to develop and test hypotheses about the adaptive functions of traits. Based upon a consideration of human social life and a functional design analysis of depression's core symptomatology we offer a comprehensive theory of its adaptive significance called the Social Navigation Hypothesis (SNH). The SNH attempts to account for all intensities of depression based on standard evolutionary theories of sociality, communication and psychological pain. The SNH suggests that depression evolved to perform two complimentary social problem-solving functions. First, depression induces cognitive changes that focus and enhance capacities for the accurate analysis and solution of key social problems, suggesting a social rumination function. Second, the costs associated with the anhedonia and psychomotor perturbation of depression can persuade reluctant social partners to provide help or make concessions via two possible mechanisms, namely, honest signaling and passive, unintentional fitness extortion. Thus it may also have a social motivation function.

Neurocranium versus Face: A Morphometric Approach with Classical Anthropometric Variables for Characterizing Patterns of Cranial Integration in Extant Hominoids and Extinct Hominins

PubMed Central

Pérez-Claros, Juan Antonio; Jiménez-Arenas, Juan Manuel; Palmqvist, Paul

2015-01-01

The relative importance of the two main cranial complexes, the neurocranium and the splanchnocranium, has been examined in the five species of extant hominoids and in a huge sample of extinct hominins using six standard craniometric variables that measure the length, width and height of each cranial module. Factor analysis and two-block partial least squares were used for establishing the major patterns of developmental and evolutionary integration between both cranial modules. The results obtained show that all extant hominoids (including the anatomically modern humans) share a conserved pattern of developmental integration, a result that agrees with previous studies. The pattern of evolutionary integration between both cranial modules in australopiths runs in parallel to developmental integration. In contrast, the pattern of evolutionary and developmental integration of the species of the genus Homo is the opposite, which is probably the consequence of distinctive selective regimes for both hominin groups. PMID:26177535

Neurocranium versus Face: A Morphometric Approach with Classical Anthropometric Variables for Characterizing Patterns of Cranial Integration in Extant Hominoids and Extinct Hominins.

PubMed

Pérez-Claros, Juan Antonio; Jiménez-Arenas, Juan Manuel; Palmqvist, Paul

2015-01-01

The relative importance of the two main cranial complexes, the neurocranium and the splanchnocranium, has been examined in the five species of extant hominoids and in a huge sample of extinct hominins using six standard craniometric variables that measure the length, width and height of each cranial module. Factor analysis and two-block partial least squares were used for establishing the major patterns of developmental and evolutionary integration between both cranial modules. The results obtained show that all extant hominoids (including the anatomically modern humans) share a conserved pattern of developmental integration, a result that agrees with previous studies. The pattern of evolutionary integration between both cranial modules in australopiths runs in parallel to developmental integration. In contrast, the pattern of evolutionary and developmental integration of the species of the genus Homo is the opposite, which is probably the consequence of distinctive selective regimes for both hominin groups.

Phylogenetic Properties of RNA Viruses

PubMed Central

Pompei, Simone; Loreto, Vittorio; Tria, Francesca

2012-01-01

A new word, phylodynamics, was coined to emphasize the interconnection between phylogenetic properties, as observed for instance in a phylogenetic tree, and the epidemic dynamics of viruses, where selection, mediated by the host immune response, and transmission play a crucial role. The challenges faced when investigating the evolution of RNA viruses call for a virtuous loop of data collection, data analysis and modeling. This already resulted both in the collection of massive sequences databases and in the formulation of hypotheses on the main mechanisms driving qualitative differences observed in the (reconstructed) evolutionary patterns of different RNA viruses. Qualitatively, it has been observed that selection driven by the host immune response induces an uneven survival ability among co-existing strains. As a consequence, the imbalance level of the phylogenetic tree is manifestly more pronounced if compared to the case when the interaction with the host immune system does not play a central role in the evolutive dynamics. While many imbalance metrics have been introduced, reliable methods to discriminate in a quantitative way different level of imbalance are still lacking. In our work, we reconstruct and analyze the phylogenetic trees of six RNA viruses, with a special emphasis on the human Influenza A virus, due to its relevance for vaccine preparation as well as for the theoretical challenges it poses due to its peculiar evolutionary dynamics. We focus in particular on topological properties. We point out the limitation featured by standard imbalance metrics, and we introduce a new methodology with which we assign the correct imbalance level of the phylogenetic trees, in agreement with the phylodynamics of the viruses. Our thorough quantitative analysis allows for a deeper understanding of the evolutionary dynamics of the considered RNA viruses, which is crucial in order to provide a valuable framework for a quantitative assessment of theoretical predictions. PMID:23028645

Modeling Tumor Clonal Evolution for Drug Combinations Design

PubMed Central

Zhao, Boyang; Hemann, Michael T.; Lauffenburger, Douglas A.

2016-01-01

Cancer is a clonal evolutionary process. This presents challenges for effective therapeutic intervention, given the constant selective pressure towards drug resistance. Mathematical modeling from population genetics, evolutionary dynamics, and engineering perspectives are being increasingly employed to study tumor progression, intratumoral heterogeneity, drug resistance, and rational drug scheduling and combinations design. In this review, we discuss promising opportunities these inter-disciplinary approaches hold for advances in cancer biology and treatment. We propose that quantitative modeling perspectives can complement emerging experimental technologies to facilitate enhanced understanding of disease progression and improved capabilities for therapeutic drug regimen designs. PMID:28435907

Field Guide to Plant Model Systems.

PubMed

Chang, Caren; Bowman, John L; Meyerowitz, Elliot M

2016-10-06

For the past several decades, advances in plant development, physiology, cell biology, and genetics have relied heavily on the model (or reference) plant Arabidopsis thaliana. Arabidopsis resembles other plants, including crop plants, in many but by no means all respects. Study of Arabidopsis alone provides little information on the evolutionary history of plants, evolutionary differences between species, plants that survive in different environments, or plants that access nutrients and photosynthesize differently. Empowered by the availability of large-scale sequencing and new technologies for investigating gene function, many new plant models are being proposed and studied. Copyright © 2016 Elsevier Inc. All rights reserved.

Restart Operator Meta-heuristics for a Problem-Oriented Evolutionary Strategies Algorithm in Inverse Mathematical MISO Modelling Problem Solving

NASA Astrophysics Data System (ADS)

Ryzhikov, I. S.; Semenkin, E. S.

2017-02-01

This study is focused on solving an inverse mathematical modelling problem for dynamical systems based on observation data and control inputs. The mathematical model is being searched in the form of a linear differential equation, which determines the system with multiple inputs and a single output, and a vector of the initial point coordinates. The described problem is complex and multimodal and for this reason the proposed evolutionary-based optimization technique, which is oriented on a dynamical system identification problem, was applied. To improve its performance an algorithm restart operator was implemented.

Evolutionary models of in-group favoritism

PubMed Central

Fu, Feng

2015-01-01

In-group favoritism is the tendency for individuals to cooperate with in-group members more strongly than with out-group members. Similar concepts have been described across different domains, including in-group bias, tag-based cooperation, parochial altruism, and ethnocentrism. Both humans and other animals show this behavior. Here, we review evolutionary mechanisms for explaining this phenomenon by covering recently developed mathematical models. In fact, in-group favoritism is not easily realized on its own in theory, although it can evolve under some conditions. We also discuss the implications of these modeling results in future empirical and theoretical research. PMID:25926978

Analysis of Knowledge-Sharing Evolutionary Game in University Teacher Team

ERIC Educational Resources Information Center

Huo, Mingkui

2013-01-01

The knowledge-sharing activity is a major drive force behind the progress and innovation of university teacher team. Based on the evolutionary game theory, this article analyzes the knowledge-sharing process model of this team, studies the influencing mechanism of various factors such as knowledge aggregate gap, incentive coefficient and risk…

Evolutionary Inference across Eukaryotes Identifies Specific Pressures Favoring Mitochondrial Gene Retention.

PubMed

Johnston, Iain G; Williams, Ben P

2016-02-24

Since their endosymbiotic origin, mitochondria have lost most of their genes. Although many selective mechanisms underlying the evolution of mitochondrial genomes have been proposed, a data-driven exploration of these hypotheses is lacking, and a quantitatively supported consensus remains absent. We developed HyperTraPS, a methodology coupling stochastic modeling with Bayesian inference, to identify the ordering of evolutionary events and suggest their causes. Using 2015 complete mitochondrial genomes, we inferred evolutionary trajectories of mtDNA gene loss across the eukaryotic tree of life. We find that proteins comprising the structural cores of the electron transport chain are preferentially encoded within mitochondrial genomes across eukaryotes. A combination of high GC content and high protein hydrophobicity is required to explain patterns of mtDNA gene retention; a model that accounts for these selective pressures can also predict the success of artificial gene transfer experiments in vivo. This work provides a general method for data-driven inference of the ordering of evolutionary and progressive events, here identifying the distinct features shaping mitochondrial genomes of present-day species. Copyright © 2016 Elsevier Inc. All rights reserved.

Our Social Roots: How Local Ecology Shapes Our Social Structures

NASA Astrophysics Data System (ADS)

Mace, Ruth

There is overwhelming evidence that wide-ranging aspects of human biology and human behavior can be considered as adaptations to different subsistence systems. Wider environmental and ecological correlates of behavioral and cultural traits are generally best understood as being mediated by differences in subsistence strategies. Modes of subsistence profoundly influence both human biology, as documented in genetic changes, and human social behavior and cultural norms, such as kinship, marriage, descent, wealth inheritance, and political systems. Thus both cultural and biological factors usually need to be considered together in studies of human evolutionary ecology, combined in specifically defined evolutionary models. Models of cultural adaptation to environmental conditions can be subjected to the same or similar tests that behavioral ecologists have used to seek evidence for adaptive behavior in other species. Phylogenetic comparative methods are proving useful, both for studying co-evolutionary hypotheses (cultural and/or gene-culture co-evolution), and for estimating ancestral states of prehistoric societies. This form of formal cross-cultural comparison is helping to put history back into anthropology, and helping us to understand cultural evolutionary processes at a number of levels.

Tracing the evolutionary origin of vertebrate skeletal tissues: insights from cephalochordate amphioxus.

PubMed

Yong, Luok Wen; Yu, Jr-Kai

2016-08-01

Vertebrate mineralized skeletal tissues are widely considered as an evolutionary novelty. Despite the importance of these tissues to the adaptation and radiation of vertebrate animals, the evolutionary origin of vertebrate skeletal tissues remains largely unclear. Cephalochordates (Amphioxus) occupy a key phylogenetic position and can serve as a valuable model for studying the evolution of vertebrate skeletal tissues. Here we summarize recent advances in amphioxus developmental biology and comparative genomics that can help to elucidate the evolutionary origins of the vertebrate skeletal tissues and their underlying developmental gene regulatory networks (GRN). By making comparisons to the developmental studies in vertebrate models and recent discoveries in paleontology and genomics, it becomes evident that the collagen matrix-based connective tissues secreted by the somite-derived cells in amphioxus likely represent the rudimentary skeletal tissues in chordates. We propose that upon the foundation of this collagenous precursor, novel tissue mineralization genes that arose from gene duplications were incorporated into an ancestral mesodermal GRN that makes connective and supporting tissues, leading to the emergence of highly-mineralized skeletal tissues in early vertebrates. Copyright © 2016 Elsevier Ltd. All rights reserved.

Novel hybrid linear stochastic with non-linear extreme learning machine methods for forecasting monthly rainfall a tropical climate.

PubMed

Zeynoddin, Mohammad; Bonakdari, Hossein; Azari, Arash; Ebtehaj, Isa; Gharabaghi, Bahram; Riahi Madavar, Hossein

2018-09-15

A novel hybrid approach is presented that can more accurately predict monthly rainfall in a tropical climate by integrating a linear stochastic model with a powerful non-linear extreme learning machine method. This new hybrid method was then evaluated by considering four general scenarios. In the first scenario, the modeling process is initiated without preprocessing input data as a base case. While in other three scenarios, the one-step and two-step procedures are utilized to make the model predictions more precise. The mentioned scenarios are based on a combination of stationarization techniques (i.e., differencing, seasonal and non-seasonal standardization and spectral analysis), and normality transforms (i.e., Box-Cox, John and Draper, Yeo and Johnson, Johnson, Box-Cox-Mod, log, log standard, and Manly). In scenario 2, which is a one-step scenario, the stationarization methods are employed as preprocessing approaches. In scenario 3 and 4, different combinations of normality transform, and stationarization methods are considered as preprocessing techniques. In total, 61 sub-scenarios are evaluated resulting 11013 models (10785 linear methods, 4 nonlinear models, and 224 hybrid models are evaluated). The uncertainty of the linear, nonlinear and hybrid models are examined by Monte Carlo technique. The best preprocessing technique is the utilization of Johnson normality transform and seasonal standardization (respectively) (R 2  = 0.99; RMSE = 0.6; MAE = 0.38; RMSRE = 0.1, MARE = 0.06, UI = 0.03 &UII = 0.05). The results of uncertainty analysis indicated the good performance of proposed technique (d-factor = 0.27; 95PPU = 83.57). Moreover, the results of the proposed methodology in this study were compared with an evolutionary hybrid of adaptive neuro fuzzy inference system (ANFIS) with firefly algorithm (ANFIS-FFA) demonstrating that the new hybrid methods outperformed ANFIS-FFA method. Copyright © 2018 Elsevier Ltd. All rights reserved.

From computers to cultivation: reconceptualizing evolutionary psychology

PubMed Central

Barrett, Louise; Pollet, Thomas V.; Stulp, Gert

2014-01-01

Does evolutionary theorizing have a role in psychology? This is a more contentious issue than one might imagine, given that, as evolved creatures, the answer must surely be yes. The contested nature of evolutionary psychology lies not in our status as evolved beings, but in the extent to which evolutionary ideas add value to studies of human behavior, and the rigor with which these ideas are tested. This, in turn, is linked to the framework in which particular evolutionary ideas are situated. While the framing of the current research topic places the brain-as-computer metaphor in opposition to evolutionary psychology, the most prominent school of thought in this field (born out of cognitive psychology, and often known as the Santa Barbara school) is entirely wedded to the computational theory of mind as an explanatory framework. Its unique aspect is to argue that the mind consists of a large number of functionally specialized (i.e., domain-specific) computational mechanisms, or modules (the massive modularity hypothesis). Far from offering an alternative to, or an improvement on, the current perspective, we argue that evolutionary psychology is a mainstream computational theory, and that its arguments for domain-specificity often rest on shaky premises. We then go on to suggest that the various forms of e-cognition (i.e., embodied, embedded, enactive) represent a true alternative to standard computational approaches, with an emphasis on “cognitive integration” or the “extended mind hypothesis” in particular. We feel this offers the most promise for human psychology because it incorporates the social and historical processes that are crucial to human “mind-making” within an evolutionarily informed framework. In addition to linking to other research areas in psychology, this approach is more likely to form productive links to other disciplines within the social sciences, not least by encouraging a healthy pluralism in approach. PMID:25161633

Rapid recovery from the Late Ordovician mass extinction

NASA Technical Reports Server (NTRS)

Krug, A. Z.; Patzkowsky, M. E.

2004-01-01

Understanding the evolutionary role of mass extinctions requires detailed knowledge of postextinction recoveries. However, most models of recovery hinge on a direct reading of the fossil record, and several recent studies have suggested that the fossil record is especially incomplete for recovery intervals immediately after mass extinctions. Here, we analyze a database of genus occurrences for the paleocontinent of Laurentia to determine the effects of regional processes on recovery and the effects of variations in preservation and sampling intensity on perceived diversity trends and taxonomic rates during the Late Ordovician mass extinction and Early Silurian recovery. After accounting for variation in sampling intensity, we find that marine benthic diversity in Laurentia recovered to preextinction levels within 5 million years, which is nearly 15 million years sooner than suggested by global compilations. The rapid turnover in Laurentia suggests that processes such as immigration may have been particularly important in the recovery of regional ecosystems from environmental perturbations. However, additional regional studies and a global analysis of the Late Ordovician mass extinction that accounts for variations in sampling intensity are necessary to confirm this pattern. Because the record of Phanerozoic mass extinctions and postextinction recoveries may be compromised by variations in preservation and sampling intensity, all should be reevaluated with sampling-standardized analyses if the evolutionary role of mass extinctions is to be fully understood.

The Awesome Power of Yeast Evolutionary Genetics: New Genome Sequences and Strain Resources for the Saccharomyces sensu stricto Genus

PubMed Central

Scannell, Devin R.; Zill, Oliver A.; Rokas, Antonis; Payen, Celia; Dunham, Maitreya J.; Eisen, Michael B.; Rine, Jasper; Johnston, Mark; Hittinger, Chris Todd

2011-01-01

High-quality, well-annotated genome sequences and standardized laboratory strains fuel experimental and evolutionary research. We present improved genome sequences of three species of Saccharomyces sensu stricto yeasts: S. bayanus var. uvarum (CBS 7001), S. kudriavzevii (IFO 1802T and ZP 591), and S. mikatae (IFO 1815T), and describe their comparison to the genomes of S. cerevisiae and S. paradoxus. The new sequences, derived by assembling millions of short DNA sequence reads together with previously published Sanger shotgun reads, have vastly greater long-range continuity and far fewer gaps than the previously available genome sequences. New gene predictions defined a set of 5261 protein-coding orthologs across the five most commonly studied Saccharomyces yeasts, enabling a re-examination of the tempo and mode of yeast gene evolution and improved inferences of species-specific gains and losses. To facilitate experimental investigations, we generated genetically marked, stable haploid strains for all three of these Saccharomyces species. These nearly complete genome sequences and the collection of genetically marked strains provide a valuable toolset for comparative studies of gene function, metabolism, and evolution, and render Saccharomyces sensu stricto the most experimentally tractable model genus. These resources are freely available and accessible through www.SaccharomycesSensuStricto.org. PMID:22384314

Breast tumor malignancy modelling using evolutionary neural logic networks.

PubMed

Tsakonas, Athanasios; Dounias, Georgios; Panagi, Georgia; Panourgias, Evangelia

2006-01-01

The present work proposes a computer assisted methodology for the effective modelling of the diagnostic decision for breast tumor malignancy. The suggested approach is based on innovative hybrid computational intelligence algorithms properly applied in related cytological data contained in past medical records. The experimental data used in this study were gathered in the early 1990s in the University of Wisconsin, based in post diagnostic cytological observations performed by expert medical staff. Data were properly encoded in a computer database and accordingly, various alternative modelling techniques were applied on them, in an attempt to form diagnostic models. Previous methods included standard optimisation techniques, as well as artificial intelligence approaches, in a way that a variety of related publications exists in modern literature on the subject. In this report, a hybrid computational intelligence approach is suggested, which effectively combines modern mathematical logic principles, neural computation and genetic programming in an effective manner. The approach proves promising either in terms of diagnostic accuracy and generalization capabilities, or in terms of comprehensibility and practical importance for the related medical staff.

Reefs as cradles of evolution and sources of biodiversity in the Phanerozoic.

PubMed

Kiessling, Wolfgang; Simpson, Carl; Foote, Michael

2010-01-08

Large-scale biodiversity gradients among environments and habitats are usually attributed to a complex array of ecological and evolutionary factors. We tested the evolutionary component of such gradients by compiling the environments of the geologically oldest occurrences of marine genera and using sampling standardization to assess if originations tended to be clustered in particular environments. Shallow, tropical environments and carbonate substrates all tend to have harbored high origination rates. Diversity within these environments tended to be preferentially generated in reefs, probably because of their habitat complexity. Reefs were also prolific at exporting diversity to other environments, which might be a consequence of low-diversity habitats being more susceptible to invasions.

Tadpoles: the Biology of Anuran Larvae

USGS Publications Warehouse

McDiarmid, R.W.; Altig, R.

1999-01-01

The recent alarming declines in amphibian populations worldwide and the suitability of amphibians for use in answering research questions in disciplines as diverse as molecular systematics, animal behavior, ecology, and evolutionary biology have focused enormous attention on tadpoles. Yet despite this growing interest, relatively little is known about these fascinating creatures. n this invaluable reference, leading experts on tadpole biology relate what we currently know about tadpoles and what we might learn from them in the future. Tadpoles provides detailed summaries of tadpole morphology, development, behavior, ecology, and environmental physiology; explores the evolutionary consequences of the tadpole stage; synthesizes available information on their biodiversity, and presents a standardized terminology and an exhaustive literature review of tadpole biology.

Evolutionary versatility of eukaryotic protein domains revealed by their bigram networks

PubMed Central

2011-01-01

Background Protein domains are globular structures of independently folded polypeptides that exert catalytic or binding activities. Their sequences are recognized as evolutionary units that, through genome recombination, constitute protein repertoires of linkage patterns. Via mutations, domains acquire modified functions that contribute to the fitness of cells and organisms. Recent studies have addressed the evolutionary selection that may have shaped the functions of individual domains and the emergence of particular domain combinations, which led to new cellular functions in multi-cellular animals. This study focuses on modeling domain linkage globally and investigates evolutionary implications that may be revealed by novel computational analysis. Results A survey of 77 completely sequenced eukaryotic genomes implies a potential hierarchical and modular organization of biological functions in most living organisms. Domains in a genome or multiple genomes are modeled as a network of hetero-duplex covalent linkages, termed bigrams. A novel computational technique is introduced to decompose such networks, whereby the notion of domain "networking versatility" is derived and measured. The most and least "versatile" domains (termed "core domains" and "peripheral domains" respectively) are examined both computationally via sequence conservation measures and experimentally using selected domains. Our study suggests that such a versatility measure extracted from the bigram networks correlates with the adaptivity of domains during evolution, where the network core domains are highly adaptive, significantly contrasting the network peripheral domains. Conclusions Domain recombination has played a major part in the evolution of eukaryotes attributing to genome complexity. From a system point of view, as the results of selection and constant refinement, networks of domain linkage are structured in a hierarchical modular fashion. Domains with high degree of networking versatility appear to be evolutionary adaptive, potentially through functional innovations. Domain bigram networks are informative as a model of biological functions. The networking versatility indices extracted from such networks for individual domains reflect the strength of evolutionary selection that the domains have experienced. PMID:21849086

Evolutionary versatility of eukaryotic protein domains revealed by their bigram networks.

PubMed

Xie, Xueying; Jin, Jing; Mao, Yongyi

2011-08-18

Protein domains are globular structures of independently folded polypeptides that exert catalytic or binding activities. Their sequences are recognized as evolutionary units that, through genome recombination, constitute protein repertoires of linkage patterns. Via mutations, domains acquire modified functions that contribute to the fitness of cells and organisms. Recent studies have addressed the evolutionary selection that may have shaped the functions of individual domains and the emergence of particular domain combinations, which led to new cellular functions in multi-cellular animals. This study focuses on modeling domain linkage globally and investigates evolutionary implications that may be revealed by novel computational analysis. A survey of 77 completely sequenced eukaryotic genomes implies a potential hierarchical and modular organization of biological functions in most living organisms. Domains in a genome or multiple genomes are modeled as a network of hetero-duplex covalent linkages, termed bigrams. A novel computational technique is introduced to decompose such networks, whereby the notion of domain "networking versatility" is derived and measured. The most and least "versatile" domains (termed "core domains" and "peripheral domains" respectively) are examined both computationally via sequence conservation measures and experimentally using selected domains. Our study suggests that such a versatility measure extracted from the bigram networks correlates with the adaptivity of domains during evolution, where the network core domains are highly adaptive, significantly contrasting the network peripheral domains. Domain recombination has played a major part in the evolution of eukaryotes attributing to genome complexity. From a system point of view, as the results of selection and constant refinement, networks of domain linkage are structured in a hierarchical modular fashion. Domains with high degree of networking versatility appear to be evolutionary adaptive, potentially through functional innovations. Domain bigram networks are informative as a model of biological functions. The networking versatility indices extracted from such networks for individual domains reflect the strength of evolutionary selection that the domains have experienced.

Nucleotide variability at its limit? Insights into the number and evolutionary dynamics of the sex-determining specificities of the honey bee Apis mellifera.

PubMed

Lechner, Sarah; Ferretti, Luca; Schöning, Caspar; Kinuthia, Wanja; Willemsen, David; Hasselmann, Martin

2014-02-01

Deciphering the evolutionary processes driving nucleotide variation in multiallelic genes is limited by the number of genetic systems in which such genes occur. The complementary sex determiner (csd) gene in the honey bee Apis mellifera is an informative example for studying allelic diversity and the underlying evolutionary forces in a well-described model of balancing selection. Acting as the primary signal of sex determination, diploid individuals heterozygous for csd develop into females, whereas csd homozygotes are diploid males that have zero fitness. Examining 77 of the functional heterozygous csd allele pairs, we established a combinatorical criteria that provide insights into the minimum number of amino acid differences among those pairs. Given a data set of 244 csd sequences, we show that the total number of csd alleles found in A. mellifera ranges from 53 (locally) to 87 (worldwide), which is much higher than was previously reported (20). Using a coupon-collector model, we extrapolate the presence of in total 116-145 csd alleles worldwide. The hypervariable region (HVR) is of particular importance in determining csd allele specificity, and we provide for this region evidence of high evolutionary rate for length differences exceeding those of microsatellites. The proportion of amino acids driven by positive selection and the rate of nonsynonymous substitutions in the HVR-flanking regions reach values close to 1 but differ with respect to the HVR length. Using a model of csd coalescence, we identified the high originating rate of csd specificities as a major evolutionary force, leading to an origin of a novel csd allele every 400,000 years. The csd polymorphism frequencies in natural populations indicate an excess of new mutations, whereas signs of ancestral transspecies polymorphism can still be detected. This study provides a comprehensive view of the enormous diversity and the evolutionary forces shaping a multiallelic gene.

Nucleotide Variability at Its Limit? Insights into the Number and Evolutionary Dynamics of the Sex-Determining Specificities of the Honey Bee Apis mellifera

PubMed Central

Lechner, Sarah; Ferretti, Luca; Schöning, Caspar; Kinuthia, Wanja; Willemsen, David; Hasselmann, Martin

2014-01-01

Deciphering the evolutionary processes driving nucleotide variation in multiallelic genes is limited by the number of genetic systems in which such genes occur. The complementary sex determiner (csd) gene in the honey bee Apis mellifera is an informative example for studying allelic diversity and the underlying evolutionary forces in a well-described model of balancing selection. Acting as the primary signal of sex determination, diploid individuals heterozygous for csd develop into females, whereas csd homozygotes are diploid males that have zero fitness. Examining 77 of the functional heterozygous csd allele pairs, we established a combinatorical criteria that provide insights into the minimum number of amino acid differences among those pairs. Given a data set of 244 csd sequences, we show that the total number of csd alleles found in A. mellifera ranges from 53 (locally) to 87 (worldwide), which is much higher than was previously reported (20). Using a coupon-collector model, we extrapolate the presence of in total 116–145 csd alleles worldwide. The hypervariable region (HVR) is of particular importance in determining csd allele specificity, and we provide for this region evidence of high evolutionary rate for length differences exceeding those of microsatellites. The proportion of amino acids driven by positive selection and the rate of nonsynonymous substitutions in the HVR-flanking regions reach values close to 1 but differ with respect to the HVR length. Using a model of csd coalescence, we identified the high originating rate of csd specificities as a major evolutionary force, leading to an origin of a novel csd allele every 400,000 years. The csd polymorphism frequencies in natural populations indicate an excess of new mutations, whereas signs of ancestral transspecies polymorphism can still be detected. This study provides a comprehensive view of the enormous diversity and the evolutionary forces shaping a multiallelic gene. PMID:24170493

Innovation Rather than Improvement: A Solvable High-Dimensional Model Highlights the Limitations of Scalar Fitness

NASA Astrophysics Data System (ADS)

Tikhonov, Mikhail; Monasson, Remi

2018-01-01

Much of our understanding of ecological and evolutionary mechanisms derives from analysis of low-dimensional models: with few interacting species, or few axes defining "fitness". It is not always clear to what extent the intuition derived from low-dimensional models applies to the complex, high-dimensional reality. For instance, most naturally occurring microbial communities are strikingly diverse, harboring a large number of coexisting species, each of which contributes to shaping the environment of others. Understanding the eco-evolutionary interplay in these systems is an important challenge, and an exciting new domain for statistical physics. Recent work identified a promising new platform for investigating highly diverse ecosystems, based on the classic resource competition model of MacArthur. Here, we describe how the same analytical framework can be used to study evolutionary questions. Our analysis illustrates how, at high dimension, the intuition promoted by a one-dimensional (scalar) notion of fitness can become misleading. Specifically, while the low-dimensional picture emphasizes organism cost or efficiency, we exhibit a regime where cost becomes irrelevant for survival, and link this observation to generic properties of high-dimensional geometry.

Evolutionary dynamics of fluctuating populations with strong mutualism

NASA Astrophysics Data System (ADS)

Chotibut, Thiparat; Nelson, David

2013-03-01

Evolutionary game theory with finite interacting populations is receiving increased attention, including subtle phenomena associated with number fluctuations, i.e., ``genetic drift.'' Models of cooperation and competition often utilize a simplified Moran model, with a strictly fixed total population size. We explore a more general evolutionary model with independent fluctuations in the numbers of two distinct species, in a regime characterized by ``strong mutualism.'' The model has two absorbing states, each corresponding to fixation of one of the two species, and allows exploration of the interplay between growth, competition, and mutualism. When mutualism is favored, number fluctuations eventually drive the system away from a stable fixed point, characterized by cooperation, to one of the absorbing states. Well-mixed populations will thus be taken over by a single species in a finite time, despite the bias towards cooperation. We calculate both the fixation probability and the mean fixation time as a function of the initial conditions and carrying capacities in the strong mutualism regime, using the method of matched asymptotic expansions. Our results are compared to computer simulations.

Path analysis of the genetic integration of traits in the sand cricket: a novel use of BLUPs.

PubMed

Roff, D A; Fairbairn, D J

2011-09-01

This study combines path analysis with quantitative genetics to analyse a key life history trade-off in the cricket, Gryllus firmus. We develop a path model connecting five traits associated with the trade-off between flight capability and reproduction and test this model using phenotypic data and estimates of breeding values (best linear unbiased predictors) from a half-sibling experiment. Strong support by both types of data validates our causal model and indicates concordance between the phenotypic and genetic expression of the trade-off. Comparisons of the trade-off between sexes and wing morphs reveal that these discrete phenotypes are not genetically independent and that the evolutionary trajectories of the two wing morphs are more tightly constrained to covary than those of the two sexes. Our results illustrate the benefits of combining a quantitative genetic analysis, which examines statistical correlations between traits, with a path model that focuses upon the causal components of variation. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

The evolution and devolution of cognitive control: The costs of deliberation in a competitive world

PubMed Central

Tomlin, Damon; Rand, David G.; Ludvig, Elliot A.; Cohen, Jonathan D.

2015-01-01

Dual-system theories of human cognition, under which fast automatic processes can complement or compete with slower deliberative processes, have not typically been incorporated into larger scale population models used in evolutionary biology, macroeconomics, or sociology. However, doing so may reveal important phenomena at the population level. Here, we introduce a novel model of the evolution of dual-system agents using a resource-consumption paradigm. By simulating agents with the capacity for both automatic and controlled processing, we illustrate how controlled processing may not always be selected over rigid, but rapid, automatic processing. Furthermore, even when controlled processing is advantageous, frequency-dependent effects may exist whereby the spread of control within the population undermines this advantage. As a result, the level of controlled processing in the population can oscillate persistently, or even go extinct in the long run. Our model illustrates how dual-system psychology can be incorporated into population-level evolutionary models, and how such a framework can be used to examine the dynamics of interaction between automatic and controlled processing that transpire over an evolutionary time scale. PMID:26078086

The evolution and devolution of cognitive control: The costs of deliberation in a competitive world.

PubMed

Tomlin, Damon; Rand, David G; Ludvig, Elliot A; Cohen, Jonathan D

2015-06-16

Dual-system theories of human cognition, under which fast automatic processes can complement or compete with slower deliberative processes, have not typically been incorporated into larger scale population models used in evolutionary biology, macroeconomics, or sociology. However, doing so may reveal important phenomena at the population level. Here, we introduce a novel model of the evolution of dual-system agents using a resource-consumption paradigm. By simulating agents with the capacity for both automatic and controlled processing, we illustrate how controlled processing may not always be selected over rigid, but rapid, automatic processing. Furthermore, even when controlled processing is advantageous, frequency-dependent effects may exist whereby the spread of control within the population undermines this advantage. As a result, the level of controlled processing in the population can oscillate persistently, or even go extinct in the long run. Our model illustrates how dual-system psychology can be incorporated into population-level evolutionary models, and how such a framework can be used to examine the dynamics of interaction between automatic and controlled processing that transpire over an evolutionary time scale.

Predicting the evolutionary dynamics of seasonal adaptation to novel climates in Arabidopsis thaliana

PubMed Central

Fournier-Level, Alexandre; Perry, Emily O.; Wang, Jonathan A.; Braun, Peter T.; Migneault, Andrew; Cooper, Martha D.; Metcalf, C. Jessica E.; Schmitt, Johanna

2016-01-01

Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico “resurrection experiments” showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation. PMID:27140640

Predicting the evolutionary dynamics of seasonal adaptation to novel climates in Arabidopsis thaliana.

PubMed

Fournier-Level, Alexandre; Perry, Emily O; Wang, Jonathan A; Braun, Peter T; Migneault, Andrew; Cooper, Martha D; Metcalf, C Jessica E; Schmitt, Johanna

2016-05-17

Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico "resurrection experiments" showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation.

Evolutionary Perspectives on Genetic and Environmental Risk Factors for Psychiatric Disorders.

PubMed

Keller, Matthew C

2018-05-07

Evolutionary medicine uses evolutionary theory to help elucidate why humans are vulnerable to disease and disorders. I discuss two different types of evolutionary explanations that have been used to help understand human psychiatric disorders. First, a consistent finding is that psychiatric disorders are moderately to highly heritable, and many, such as schizophrenia, are also highly disabling and appear to decrease Darwinian fitness. Models used in evolutionary genetics to understand why genetic variation exists in fitness-related traits can be used to understand why risk alleles for psychiatric disorders persist in the population. The usual explanation for species-typical adaptations-natural selection-is less useful for understanding individual differences in genetic risk to disorders. Rather, two other types of models, mutation-selection-drift and balancing selection, offer frameworks for understanding why genetic variation in risk to psychiatric (and other) disorders exists, and each makes predictions that are now testable using whole-genome data. Second, species-typical capacities to mount reactions to negative events are likely to have been crafted by natural selection to minimize fitness loss. The pain reaction to tissue damage is almost certainly such an example, but it has been argued that the capacity to experience depressive symptoms such as sadness, anhedonia, crying, and fatigue in the face of adverse life situations may have been crafted by natural selection as well. I review the rationale and strength of evidence for this hypothesis. Evolutionary hypotheses of psychiatric disorders are important not only for offering explanations for why psychiatric disorders exist, but also for generating new, testable hypotheses and understanding how best to design studies and analyze data.

Evolution of morphology and locomotor performance in anurans: relationships with microhabitat diversification.

PubMed

Citadini, J M; Brandt, R; Williams, C R; Gomes, F R

2018-03-01

The relationships between morphology, performance, behavior and ecology provide evidence for multiple and complex phenotypic adaptations. The anuran body plan, for example, is evolutionarily conserved and shows clear specializations to jumping performance back at least to the early Jurassic. However, there are instances of more recent adaptation to habit diversity in the post-cranial skeleton, including relative limb length. The present study tested adaptive models of morphological evolution in anurans associated with the diversity of microhabitat use (semi-aquatic arboreal, fossorial, torrent, and terrestrial) in species of anuran amphibians from Brazil and Australia. We use phylogenetic comparative methods to determine which evolutionary models, including Brownian motion (BM) and Ornstein-Uhlenbeck (OU) are consistent with morphological variation observed across anuran species. Furthermore, this study investigated the relationship of maximum distance jumped as a function of components of morphological variables and microhabitat use. We found there are multiple optima of limb lengths associated to different microhabitats with a trend of increasing hindlimbs in torrent, arboreal, semi-aquatic whereas fossorial and terrestrial species evolve toward optima with shorter hindlimbs. Moreover, arboreal, semi-aquatic and torrent anurans have higher jumping performance and longer hindlimbs, when compared to terrestrial and fossorial species. We corroborate the hypothesis that evolutionary modifications of overall limb morphology have been important in the diversification of locomotor performance along the anuran phylogeny. Such evolutionary changes converged in different phylogenetic groups adapted to similar microhabitat use in two different zoogeographical regions. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Wireless Local Area Networks: The Next Evolutionary Step.

ERIC Educational Resources Information Center

Wodarz, Nan

2001-01-01

The Institute of Electrical and Electronics Engineers recently approved a high-speed wireless standard that enables devices from different manufacturers to communicate through a common backbone, making wireless local area networks more feasible in schools. Schools can now use wireless access points and network cards to provide flexible…

The Evolution of Cataclysmic Variables as Revealed by Their Donor Stars

NASA Astrophysics Data System (ADS)

Knigge, Christian; Baraffe, Isabelle; Patterson, Joseph

2011-06-01

We present an attempt to reconstruct the complete evolutionary path followed by cataclysmic variables (CVs), based on the observed mass-radius relationship of their donor stars. Along the way, we update the semi-empirical CV donor sequence presented previously by one of us, present a comprehensive review of the connection between CV evolution and the secondary stars in these systems, and reexamine most of the commonly used magnetic braking (MB) recipes, finding that even conceptually similar ones can differ greatly in both magnitude and functional form. The great advantage of using donor radii to infer mass-transfer and angular-momentum-loss (AML) rates is that they sample the longest accessible timescales and are most likely to represent the true secular (evolutionary average) rates. We show explicitly that if CVs exhibit long-term mass-transfer-rate fluctuations, as is often assumed, the expected variability timescales are so long that other tracers of the mass-transfer rate—including white dwarf (WD) temperatures—become unreliable. We carefully explore how much of the radius difference between CV donors and models of isolated main-sequence stars may be due to mechanisms other than mass loss. The tidal and rotational deformation of Roche-lobe-filling stars produces ~= 4.5% radius inflation below the period gap and ~= 7.9% above. A comparison of stellar models to mass-radius data for non-interacting stars suggests a real offset of ~= 1.5% for fully convective stars (i.e., donors below the gap) and ~= 4.9% for partially radiative ones (donors above the gap). We also show that donor bloating due to irradiation is probably smaller than, and at most comparable to, these effects. After calibrating our models to account for these issues, we fit self-consistent evolution sequences to our compilation of donor masses and radii. In the standard model of CV evolution, AMLs below the period gap are assumed to be driven solely by gravitational radiation (GR), while AMLs above the gap are usually described by an MB law first suggested by Rappaport et al. We adopt simple scaled versions of these AML recipes and find that these are able to match the data quite well. The optimal scaling factors turn out to be f GR = 2.47 ± 0.22 below the gap and f MB = 0.66 ± 0.05 above (the errors here are purely statistical, and the standard model corresponds to f GR = f MB = 1). This revised model describes the mass-radius data significantly better than the standard model. Some of the most important implications and applications of our results are as follows. (1) The revised evolution sequence yields correct locations for the minimum period and the upper edge of the period gap; the standard sequence does not. (2) The observed spectral types of CV donors are compatible with both standard and revised models. (3) A direct comparison of predicted and observed WD temperatures suggests an even higher value for f GR, but this comparison is sensitive to the assumed mean WD mass and the possible existence of mass-transfer-rate fluctuations. (4) The predicted absolute magnitudes of donor stars in the near-infrared form a lower envelope around the observed absolute magnitudes for systems with parallax distances. This is true for all of our sequences, so any of them can be used to set firm lower limits on (or obtain rough estimates of) the distances toward CVs based only on P orb and single epoch near-IR measurements. (5) Both standard and revised sequences predict that short-period CVs should be susceptible to dwarf nova (DN) eruptions, consistent with observations. However, both sequences also predict that the fraction of DNe among long-period CVs should decline with P orb above the period gap. Observations suggest the opposite behavior, and we discuss the possible explanations for this discrepancy. (6) Approximate orbital period distributions constructed from our evolution sequences suggest that the ratio of long-period CVs to short-period, pre-bounce CVs is about 3 × higher for the revised sequence than the standard one. This may resolve a long-standing problem in CV evolution. Tables describing our donor and evolution sequences are provided in electronically readable form.

Applications of Evolutionary Technology to Manufacturing and Logistics Systems : State-of-the Art Survey

NASA Astrophysics Data System (ADS)

Gen, Mitsuo; Lin, Lin

Many combinatorial optimization problems from industrial engineering and operations research in real-world are very complex in nature and quite hard to solve them by conventional techniques. Since the 1960s, there has been an increasing interest in imitating living beings to solve such kinds of hard combinatorial optimization problems. Simulating the natural evolutionary process of human beings results in stochastic optimization techniques called evolutionary algorithms (EAs), which can often outperform conventional optimization methods when applied to difficult real-world problems. In this survey paper, we provide a comprehensive survey of the current state-of-the-art in the use of EA in manufacturing and logistics systems. In order to demonstrate the EAs which are powerful and broadly applicable stochastic search and optimization techniques, we deal with the following engineering design problems: transportation planning models, layout design models and two-stage logistics models in logistics systems; job-shop scheduling, resource constrained project scheduling in manufacturing system.

MEGA5: Molecular Evolutionary Genetics Analysis Using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods

PubMed Central

Tamura, Koichiro; Peterson, Daniel; Peterson, Nicholas; Stecher, Glen; Nei, Masatoshi; Kumar, Sudhir

2011-01-01

Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net. PMID:21546353

Neptunism and Transformism: Robert Jameson and other Evolutionary Theorists in Early Nineteenth-Century Scotland.

PubMed

Jenkins, Bill

2016-08-01

This paper sheds new light on the prevalence of evolutionary ideas in Scotland in the early nineteenth century and establish what connections existed between the espousal of evolutionary theories and adherence to the directional history of the earth proposed by Abraham Gottlob Werner and his Scottish disciples. A possible connection between Wernerian geology and theories of the transmutation of species in Edinburgh in the period when Charles Darwin was a medical student in the city was suggested in an important 1991 paper by James Secord. This study aims to deepen our knowledge of this important episode in the history of evolutionary ideas and explore the relationship between these geological and evolutionary discourses. To do this it focuses on the circle of natural historians around Robert Jameson, Wernerian geologist and professor of natural history at the University of Edinburgh from 1804 to 1854. From the evidence gathered here there emerges a clear confirmation that the Wernerian model of geohistory facilitated the acceptance of evolutionary explanations of the history of life in early nineteenth-century Scotland. As Edinburgh was at this time the most important center of medical education in the English-speaking world, this almost certainly influenced the reception and development of evolutionary ideas in the decades that followed.

Ecological and phylogenetic variability in the spinalis muscle of snakes.

PubMed

Tingle, J L; Gartner, G E A; Jayne, B C; Garland, T

2017-11-01

Understanding the origin and maintenance of functionally important subordinate traits is a major goal of evolutionary physiologists and ecomorphologists. Within the confines of a limbless body plan, snakes are diverse in terms of body size and ecology, but we know little about the functional traits that underlie this diversity. We used a phylogenetically diverse group of 131 snake species to examine associations between habitat use, sidewinding locomotion and constriction behaviour with the number of body vertebrae spanned by a single segment of the spinalis muscle, with total numbers of body vertebrae used as a covariate in statistical analyses. We compared models with combinations of these predictors to determine which best fit the data among all species and for the advanced snakes only (N = 114). We used both ordinary least-squares models and phylogenetic models in which the residuals were modelled as evolving by the Ornstein-Uhlenbeck process. Snakes with greater numbers of vertebrae tended to have spinalis muscles that spanned more vertebrae. Habitat effects dominated models for analyses of all species and advanced snakes only, with the spinalis length spanning more vertebrae in arboreal species and fewer vertebrae in aquatic and burrowing species. Sidewinding specialists had shorter muscle lengths than nonspecialists. The relationship between prey constriction and spinalis length was less clear. Differences among clades were also strong when considering all species, but not for advanced snakes alone. Overall, these results suggest that muscle morphology may have played a key role in the adaptive radiation of snakes. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

A review of estimation of distribution algorithms in bioinformatics

PubMed Central

Armañanzas, Rubén; Inza, Iñaki; Santana, Roberto; Saeys, Yvan; Flores, Jose Luis; Lozano, Jose Antonio; Peer, Yves Van de; Blanco, Rosa; Robles, Víctor; Bielza, Concha; Larrañaga, Pedro

2008-01-01

Evolutionary search algorithms have become an essential asset in the algorithmic toolbox for solving high-dimensional optimization problems in across a broad range of bioinformatics problems. Genetic algorithms, the most well-known and representative evolutionary search technique, have been the subject of the major part of such applications. Estimation of distribution algorithms (EDAs) offer a novel evolutionary paradigm that constitutes a natural and attractive alternative to genetic algorithms. They make use of a probabilistic model, learnt from the promising solutions, to guide the search process. In this paper, we set out a basic taxonomy of EDA techniques, underlining the nature and complexity of the probabilistic model of each EDA variant. We review a set of innovative works that make use of EDA techniques to solve challenging bioinformatics problems, emphasizing the EDA paradigm's potential for further research in this domain. PMID:18822112

Evolution of specialization under non-equilibrium population dynamics.

PubMed

Nurmi, Tuomas; Parvinen, Kalle

2013-03-21

We analyze the evolution of specialization in resource utilization in a mechanistically underpinned discrete-time model using the adaptive dynamics approach. We assume two nutritionally equivalent resources that in the absence of consumers grow sigmoidally towards a resource-specific carrying capacity. The consumers use resources according to the law of mass-action with rates involving trade-off. The resulting discrete-time model for the consumer population has over-compensatory dynamics. We illuminate the way non-equilibrium population dynamics affect the evolutionary dynamics of the resource consumption rates, and show that evolution to the trimorphic coexistence of a generalist and two specialists is possible due to asynchronous non-equilibrium population dynamics of the specialists. In addition, various forms of cyclic evolutionary dynamics are possible. Furthermore, evolutionary suicide may occur even without Allee effects and demographic stochasticity. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Impact of Lamarck's Theory of Evolution Before Darwin's Theory.

PubMed

Galera, Andrés

2017-02-01

This paper analyzes the impact that Lamarckian evolutionary theory had in the scientific community during the period between the advent of Zoological Philosophy and the publication Origin of Species. During these 50 years Lamarck's model was a well known theory and it was discussed by the scientific community as a hypothesis to explain the changing nature of the fossil record throughout the history of Earth. Lamarck's transmutation theory established the foundation of an evolutionary model introducing a new way to research in nature. Darwin's selectionist theory was proposed in 1859 to explain the origin of species within this epistemological process. In this context, Charles Lyell's Principles of Geology and Auguste Comte's Cours de Philosophie Positive appear as two major works for the dissemination of Lamarck's evolutionary ideology after the death of the French naturalist in 1829.

Evolutionary Game Model Study of Construction Green Supply Chain Management under the Government Intervention

NASA Astrophysics Data System (ADS)

Xing, Yuanzhi; Deng, Xiaoyi

2017-11-01

The paper first has defined the concepts of green supply chain management and evolution game theory, and pointed out the characteristics of green supply chain management in construction. The main participants and key links of the construction green supply chain management are determined by constructing the organization framework. This paper established the evolutionary game model between construction enterprises and recycling enterprises for the green supply chain closed-loop structure. The waste recycling evolutionary stability equilibrium solution is obtained to explore the principle and effective scope of government policy intervention. This paper put forward the relevant countermeasures to the green supply chain management in construction recycling stage from the government point of view. The conclusion has reference value and guidance to the final product construction enterprises, recycling enterprises and the government during green supply chain.

Evolutionary synthesis of simple stellar populations. Colours and indices

NASA Astrophysics Data System (ADS)

Kurth, O. M.; Fritze-v. Alvensleben, U.; Fricke, K. J.

1999-07-01

We construct evolutionary synthesis models for simple stellar populations using the evolutionary tracks from the Padova group (1993, 1994), theoretical colour calibrations from \\cite[Lejeune et al. (1997, 1998)]{lejeune} and fit functions for stellar atmospheric indices from \\cite[Worthey et al. (1994)]{worthey}. A Monte-Carlo technique allows us to obtain a smooth time evolution of both broad band colours in UBVRIK and a series of stellar absorption features for Single Burst Stellar Populations (SSPs). We present colours and indices for SSPs with ages from 1 \\ 10(9) yrs to 1.6 \\ 10(10) yrs and metallicities [M/H]=-2.3, -1.7, -0.7, -0.4, 0.0 and 0.4. Model colours and indices at an age of about a Hubble time are in good agreement with observed colours and indices of the Galactic and M 31 GCs.

Sixty-Five Million Years of Change in Temperature and Topography Explain Evolutionary History in Eastern North American Plethodontid Salamanders.

PubMed

Barnes, Richard; Clark, Adam Thomas

2017-07-01

For many taxa and systems, species richness peaks at midelevations. One potential explanation for this pattern is that large-scale changes in climate and geography have, over evolutionary time, selected for traits that are favored under conditions found in contemporary midelevation regions. To test this hypothesis, we use records of historical temperature and topographic changes over the past 65 Myr to construct a general simulation model of plethodontid salamander evolution in eastern North America. We then explore possible mechanisms constraining species to midelevation bands by using the model to predict plethodontid evolutionary history and contemporary geographic distributions. Our results show that models that incorporate both temperature and topographic changes are better able to predict these patterns, suggesting that both processes may have played an important role in driving plethodontid evolution in the region. Additionally, our model (whose annotated source code is included as a supplement) represents a proof of concept to encourage future work that takes advantage of recent advances in computing power to combine models of ecology, evolution, and earth history to better explain the abundance and distribution of species over time.

Perceived consequences of evolution: College students perceive negative personal and social impact in evolutionary theory

NASA Astrophysics Data System (ADS)

Brem, Sarah K.; Ranney, Michael; Schindel, Jennifer

2003-03-01

Evolutionary science has consequences for individuals and society, ranging from the way we interpret human behavior to our notions of spirituality and the purpose of our existence. Popular portrayals of evolution depict a paradoxical theory, a source of knowledge and human connections, but also a threat to our humanity and freedom. Using quantitative and qualitative methodology, we examined how college-educated adults (n = 135) from diverse ethnic and religious backgrounds perceive the impact of evolutionary theory on individuals and society. We identified a continuum of perspectives, ranging from strong creationist to strong evolutionist. Using the model of knowledge as an ecology (Demastes, Good, & Peebles, Science Education, 79, 637-666, 1995; Nardi & O'Day, Information ecologies: Using technology with heart, MIT Press, Cambridge, MA, 1999), we examined the relationships among participants' beliefs, their perceptions regarding the social and personal impact of evolutionary theory, their prior exposure to and knowledge of evolutionary theory, and their opinions regarding the teaching of evolution. Evolutionists and creationists differed in their prior exposure to evolutionary theory, and their opinions about some aspects of teaching, but showed striking similarities regarding perceived impact. All groups viewed the consequences of accepting evolutionary principles in a way that might be considered undesirable: increased selfishness and racism, decreased spirituality, and a decreased sense of purpose and self-determination. From a science education perspective, this one-sided interpretation is troublesome because it runs counter to the available evidence and theories in evolutionary science, and we consider ways of fostering more balanced presentation and appraisal of evolutionary theory.

Natural Selection as Coarsening

NASA Astrophysics Data System (ADS)

Smerlak, Matteo

2017-11-01

Analogies between evolutionary dynamics and statistical mechanics, such as Fisher's second-law-like "fundamental theorem of natural selection" and Wright's "fitness landscapes", have had a deep and fruitful influence on the development of evolutionary theory. Here I discuss a new conceptual link between evolution and statistical physics. I argue that natural selection can be viewed as a coarsening phenomenon, similar to the growth of domain size in quenched magnets or to Ostwald ripening in alloys and emulsions. In particular, I show that the most remarkable features of coarsening—scaling and self-similarity—have strict equivalents in evolutionary dynamics. This analogy has three main virtues: it brings a set of well-developed mathematical tools to bear on evolutionary dynamics; it suggests new problems in theoretical evolution; and it provides coarsening physics with a new exactly soluble model.

Natural Selection as Coarsening

NASA Astrophysics Data System (ADS)

Smerlak, Matteo

2018-07-01

Analogies between evolutionary dynamics and statistical mechanics, such as Fisher's second-law-like "fundamental theorem of natural selection" and Wright's "fitness landscapes", have had a deep and fruitful influence on the development of evolutionary theory. Here I discuss a new conceptual link between evolution and statistical physics. I argue that natural selection can be viewed as a coarsening phenomenon, similar to the growth of domain size in quenched magnets or to Ostwald ripening in alloys and emulsions. In particular, I show that the most remarkable features of coarsening—scaling and self-similarity—have strict equivalents in evolutionary dynamics. This analogy has three main virtues: it brings a set of well-developed mathematical tools to bear on evolutionary dynamics; it suggests new problems in theoretical evolution; and it provides coarsening physics with a new exactly soluble model.

Evolutionary Technologies: Fundamentals and Applications to Information/Communication Systems and Manufacturing/Logistics Systems

NASA Astrophysics Data System (ADS)

Gen, Mitsuo; Kawakami, Hiroshi; Tsujimura, Yasuhiro; Handa, Hisashi; Lin, Lin; Okamoto, Azuma

As efficient utilization of computational resources is increasing, evolutionary technology based on the Genetic Algorithm (GA), Genetic Programming (GP), Evolution Strategy (ES) and other Evolutionary Computations (ECs) is making rapid progress, and its social recognition and the need as applied technology are increasing. This is explained by the facts that EC offers higher robustness for knowledge information processing systems, intelligent production and logistics systems, most advanced production scheduling and other various real-world problems compared to the approaches based on conventional theories, and EC ensures flexible applicability and usefulness for any unknown system environment even in a case where accurate mathematical modeling fails in the formulation. In this paper, we provide a comprehensive survey of the current state-of-the-art in the fundamentals and applications of evolutionary technologies.

In search of a general theory of species' range evolution.

PubMed

Connallon, Tim; Sgrò, Carla M

2018-06-13

Despite the pervasiveness of the world's biodiversity, no single species has a truly global distribution. In fact, most species have very restricted distributions. What limits species from expanding beyond their current geographic ranges? This has been classically treated by ecologists as an ecological problem and by evolutionary biologist as an evolutionary problem. Such a dichotomy is false-the problem of species' ranges sits firmly within the realm of evolutionary ecology. In support of this view, Polechová presents new theory that explains species' range limits with reference to two key factors central to both ecological and evolutionary theory-migration and population size. This new model sets the scene for empirical tests of range limit theory and builds the case for assisted gene flow as a key management tool for threatened species.

Climatic and evolutionary drivers of phase shifts in the plague epidemics of colonial India.

PubMed

Lewnard, Joseph A; Townsend, Jeffrey P

2016-12-20

Immune heterogeneity in wild host populations indicates that disease-mediated selection is common in nature. However, the underlying dynamic feedbacks involving the ecology of disease transmission, evolutionary processes, and their interaction with environmental drivers have proven challenging to characterize. Plague presents an optimal system for interrogating such couplings: Yersinia pestis transmission exerts intense selective pressure driving the local persistence of disease resistance among its wildlife hosts in endemic areas. Investigations undertaken in colonial India after the introduction of plague in 1896 suggest that, only a decade after plague arrived, a heritable, plague-resistant phenotype had become prevalent among commensal rats of cities undergoing severe plague epidemics. To understand the possible evolutionary basis of these observations, we developed a mathematical model coupling environmentally forced plague dynamics with evolutionary selection of rats, capitalizing on extensive archival data from Indian Plague Commission investigations. Incorporating increased plague resistance among rats as a consequence of intense natural selection permits the model to reproduce observed changes in seasonal epidemic patterns in several cities and capture experimentally observed associations between climate and flea population dynamics in India. Our model results substantiate Victorian era claims of host evolution based on experimental observations of plague resistance and reveal the buffering effect of such evolution against environmental drivers of transmission. Our analysis shows that historical datasets can yield powerful insights into the transmission dynamics of reemerging disease agents with which we have limited contemporary experience to guide quantitative modeling and inference.

Climatic and evolutionary drivers of phase shifts in the plague epidemics of colonial India

PubMed Central

Lewnard, Joseph A.

2016-01-01

Immune heterogeneity in wild host populations indicates that disease-mediated selection is common in nature. However, the underlying dynamic feedbacks involving the ecology of disease transmission, evolutionary processes, and their interaction with environmental drivers have proven challenging to characterize. Plague presents an optimal system for interrogating such couplings: Yersinia pestis transmission exerts intense selective pressure driving the local persistence of disease resistance among its wildlife hosts in endemic areas. Investigations undertaken in colonial India after the introduction of plague in 1896 suggest that, only a decade after plague arrived, a heritable, plague-resistant phenotype had become prevalent among commensal rats of cities undergoing severe plague epidemics. To understand the possible evolutionary basis of these observations, we developed a mathematical model coupling environmentally forced plague dynamics with evolutionary selection of rats, capitalizing on extensive archival data from Indian Plague Commission investigations. Incorporating increased plague resistance among rats as a consequence of intense natural selection permits the model to reproduce observed changes in seasonal epidemic patterns in several cities and capture experimentally observed associations between climate and flea population dynamics in India. Our model results substantiate Victorian era claims of host evolution based on experimental observations of plague resistance and reveal the buffering effect of such evolution against environmental drivers of transmission. Our analysis shows that historical datasets can yield powerful insights into the transmission dynamics of reemerging disease agents with which we have limited contemporary experience to guide quantitative modeling and inference. PMID:27791071

A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility

PubMed Central

2014-01-01

Background Protein sites evolve at different rates due to functional and biophysical constraints. It is usually considered that the main structural determinant of a site’s rate of evolution is its Relative Solvent Accessibility (RSA). However, a recent comparative study has shown that the main structural determinant is the site’s Local Packing Density (LPD). LPD is related with dynamical flexibility, which has also been shown to correlate with sequence variability. Our purpose is to investigate the mechanism that connects a site’s LPD with its rate of evolution. Results We consider two models: an empirical Flexibility Model and a mechanistic Stress Model. The Flexibility Model postulates a linear increase of site-specific rate of evolution with dynamical flexibility. The Stress Model, introduced here, models mutations as random perturbations of the protein’s potential energy landscape, for which we use simple Elastic Network Models (ENMs). To account for natural selection we assume a single active conformation and use basic statistical physics to derive a linear relationship between site-specific evolutionary rates and the local stress of the mutant’s active conformation. We compare both models on a large and diverse dataset of enzymes. In a protein-by-protein study we found that the Stress Model outperforms the Flexibility Model for most proteins. Pooling all proteins together we show that the Stress Model is strongly supported by the total weight of evidence. Moreover, it accounts for the observed nonlinear dependence of sequence variability on flexibility. Finally, when mutational stress is controlled for, there is very little remaining correlation between sequence variability and dynamical flexibility. Conclusions We developed a mechanistic Stress Model of evolution according to which the rate of evolution of a site is predicted to depend linearly on the local mutational stress of the active conformation. Such local stress is proportional to LPD, so that this model explains the relationship between LPD and evolutionary rate. Moreover, the model also accounts for the nonlinear dependence between evolutionary rate and dynamical flexibility. PMID:24716445

New substitution models for rooting phylogenetic trees.

PubMed

Williams, Tom A; Heaps, Sarah E; Cherlin, Svetlana; Nye, Tom M W; Boys, Richard J; Embley, T Martin

2015-09-26

The root of a phylogenetic tree is fundamental to its biological interpretation, but standard substitution models do not provide any information on its position. Here, we describe two recently developed models that relax the usual assumptions of stationarity and reversibility, thereby facilitating root inference without the need for an outgroup. We compare the performance of these models on a classic test case for phylogenetic methods, before considering two highly topical questions in evolutionary biology: the deep structure of the tree of life and the root of the archaeal radiation. We show that all three alignments contain meaningful rooting information that can be harnessed by these new models, thus complementing and extending previous work based on outgroup rooting. In particular, our analyses exclude the root of the tree of life from the eukaryotes or Archaea, placing it on the bacterial stem or within the Bacteria. They also exclude the root of the archaeal radiation from several major clades, consistent with analyses using other rooting methods. Overall, our results demonstrate the utility of non-reversible and non-stationary models for rooting phylogenetic trees, and identify areas where further progress can be made. © 2015 The Authors.

Maturity Model for Advancing Smart Grid Interoperability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Knight, Mark; Widergren, Steven E.; Mater, J.

2013-10-28

Abstract—Interoperability is about the properties of devices and systems to connect and work properly. Advancing interoperability eases integration and maintenance of the resulting interconnection. This leads to faster integration, lower labor and component costs, predictability of projects and the resulting performance, and evolutionary paths for upgrade. When specifications are shared and standardized, competition and novel solutions can bring new value streams to the community of stakeholders involved. Advancing interoperability involves reaching agreement for how things join at their interfaces. The quality of the agreements and the alignment of parties involved in the agreement present challenges that are best met withmore » process improvement techniques. The GridWise® Architecture Council (GWAC) sponsored by the United States Department of Energy is supporting an effort to use concepts from capability maturity models used in the software industry to advance interoperability of smart grid technology. An interoperability maturity model has been drafted and experience is being gained through trials on various types of projects and community efforts. This paper describes the value and objectives of maturity models, the nature of the interoperability maturity model and how it compares with other maturity models, and experiences gained with its use.« less

Inferring Fitness Effects from Time-Resolved Sequence Data with a Delay-Deterministic Model.

PubMed

Nené, Nuno R; Dunham, Alistair S; Illingworth, Christopher J R

2018-05-01

A common challenge arising from the observation of an evolutionary system over time is to infer the magnitude of selection acting upon a specific genetic variant, or variants, within the population. The inference of selection may be confounded by the effects of genetic drift in a system, leading to the development of inference procedures to account for these effects. However, recent work has suggested that deterministic models of evolution may be effective in capturing the effects of selection even under complex models of demography, suggesting the more general application of deterministic approaches to inference. Responding to this literature, we here note a case in which a deterministic model of evolution may give highly misleading inferences, resulting from the nondeterministic properties of mutation in a finite population. We propose an alternative approach that acts to correct for this error, and which we denote the delay-deterministic model. Applying our model to a simple evolutionary system, we demonstrate its performance in quantifying the extent of selection acting within that system. We further consider the application of our model to sequence data from an evolutionary experiment. We outline scenarios in which our model may produce improved results for the inference of selection, noting that such situations can be easily identified via the use of a regular deterministic model. Copyright © 2018 Nené et al.

Tempo and mode of performance evolution across multiple independent origins of adhesive toe pads in lizards.

PubMed

Hagey, Travis J; Uyeda, Josef C; Crandell, Kristen E; Cheney, Jorn A; Autumn, Kellar; Harmon, Luke J

2017-10-01

Understanding macroevolutionary dynamics of trait evolution is an important endeavor in evolutionary biology. Ecological opportunity can liberate a trait as it diversifies through trait space, while genetic and selective constraints can limit diversification. While many studies have examined the dynamics of morphological traits, diverse morphological traits may yield the same or similar performance and as performance is often more proximately the target of selection, examining only morphology may give an incomplete understanding of evolutionary dynamics. Here, we ask whether convergent evolution of pad-bearing lizards has followed similar evolutionary dynamics, or whether independent origins are accompanied by unique constraints and selective pressures over macroevolutionary time. We hypothesized that geckos and anoles each have unique evolutionary tempos and modes. Using performance data from 59 species, we modified Brownian motion (BM) and Ornstein-Uhlenbeck (OU) models to account for repeated origins estimated using Bayesian ancestral state reconstructions. We discovered that adhesive performance in geckos evolved in a fashion consistent with Brownian motion with a trend, whereas anoles evolved in bounded performance space consistent with more constrained evolution (an Ornstein-Uhlenbeck model). Our results suggest that convergent phenotypes can have quite distinctive evolutionary patterns, likely as a result of idiosyncratic constraints or ecological opportunities. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Pattern and Process in the Comparative Study of Convergent Evolution.

PubMed

Mahler, D Luke; Weber, Marjorie G; Wagner, Catherine E; Ingram, Travis

2017-08-01

Understanding processes that have shaped broad-scale biodiversity patterns is a fundamental goal in evolutionary biology. The development of phylogenetic comparative methods has yielded a tool kit for analyzing contemporary patterns by explicitly modeling processes of change in the past, providing neontologists tools for asking questions previously accessible only for select taxa via the fossil record or laboratory experimentation. The comparative approach, however, differs operationally from alternative approaches to studying convergence in that, for studies of only extant species, convergence must be inferred using evolutionary process models rather than being directly measured. As a result, investigation of evolutionary pattern and process cannot be decoupled in comparative studies of convergence, even though such a decoupling could in theory guard against adaptationist bias. Assumptions about evolutionary process underlying comparative tools can shape the inference of convergent pattern in sometimes profound ways and can color interpretation of such patterns. We discuss these issues and other limitations common to most phylogenetic comparative approaches and suggest ways that they can be avoided in practice. We conclude by promoting a multipronged approach to studying convergence that integrates comparative methods with complementary tests of evolutionary mechanisms and includes ecological and biogeographical perspectives. Carefully employed, the comparative method remains a powerful tool for enriching our understanding of convergence in macroevolution, especially for investigation of why convergence occurs in some settings but not others.

Evolution of aging: individual life history trade-offs and population heterogeneity account for mortality patterns across species.

PubMed

Le Cunff, Y; Baudisch, A; Pakdaman, K

2014-08-01

A broad range of mortality patterns has been documented across species, some even including decreasing mortality over age. Whether there exist a common denominator to explain both similarities and differences in these mortality patterns remains an open question. The disposable soma theory, an evolutionary theory of aging, proposes that universal intracellular trade-offs between maintenance/lifespan and reproduction would drive aging across species. The disposable soma theory has provided numerous insights concerning aging processes in single individuals. Yet, which specific population mortality patterns it can lead to is still largely unexplored. In this article, we propose a model exploring the mortality patterns which emerge from an evolutionary process including only the disposable soma theory core principles. We adapt a well-known model of genomic evolution to show that mortality curves producing a kink or mid-life plateaus derive from a common minimal evolutionary framework. These mortality shapes qualitatively correspond to those of Drosophila melanogaster, Caenorhabditis elegans, medflies, yeasts and humans. Species evolved in silico especially differ in their population diversity of maintenance strategies, which itself emerges as an adaptation to the environment over generations. Based on this integrative framework, we also derive predictions and interpretations concerning the effects of diet changes and heat-shock treatments on mortality patterns. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Genome-Wide Motif Statistics are Shaped by DNA Binding Proteins over Evolutionary Time Scales

NASA Astrophysics Data System (ADS)

Qian, Long; Kussell, Edo

2016-10-01

The composition of a genome with respect to all possible short DNA motifs impacts the ability of DNA binding proteins to locate and bind their target sites. Since nonfunctional DNA binding can be detrimental to cellular functions and ultimately to organismal fitness, organisms could benefit from reducing the number of nonfunctional DNA binding sites genome wide. Using in vitro measurements of binding affinities for a large collection of DNA binding proteins, in multiple species, we detect a significant global avoidance of weak binding sites in genomes. We demonstrate that the underlying evolutionary process leaves a distinct genomic hallmark in that similar words have correlated frequencies, a signal that we detect in all species across domains of life. We consider the possibility that natural selection against weak binding sites contributes to this process, and using an evolutionary model we show that the strength of selection needed to maintain global word compositions is on the order of point mutation rates. Likewise, we show that evolutionary mechanisms based on interference of protein-DNA binding with replication and mutational repair processes could yield similar results and operate with similar rates. On the basis of these modeling and bioinformatic results, we conclude that genome-wide word compositions have been molded by DNA binding proteins acting through tiny evolutionary steps over time scales spanning millions of generations.

Design Mining Interacting Wind Turbines.

PubMed

Preen, Richard J; Bull, Larry

2016-01-01

An initial study has recently been presented of surrogate-assisted evolutionary algorithms used to design vertical-axis wind turbines wherein candidate prototypes are evaluated under fan-generated wind conditions after being physically instantiated by a 3D printer. Unlike other approaches, such as computational fluid dynamics simulations, no mathematical formulations were used and no model assumptions were made. This paper extends that work by exploring alternative surrogate modelling and evolutionary techniques. The accuracy of various modelling algorithms used to estimate the fitness of evaluated individuals from the initial experiments is compared. The effect of temporally windowing surrogate model training samples is explored. A surrogate-assisted approach based on an enhanced local search is introduced; and alternative coevolution collaboration schemes are examined.

Approaches to ab initio molecular replacement of α-helical transmembrane proteins.

PubMed

Thomas, Jens M H; Simkovic, Felix; Keegan, Ronan; Mayans, Olga; Zhang, Chengxin; Zhang, Yang; Rigden, Daniel J

2017-12-01

α-Helical transmembrane proteins are a ubiquitous and important class of proteins, but present difficulties for crystallographic structure solution. Here, the effectiveness of the AMPLE molecular replacement pipeline in solving α-helical transmembrane-protein structures is assessed using a small library of eight ideal helices, as well as search models derived from ab initio models generated both with and without evolutionary contact information. The ideal helices prove to be surprisingly effective at solving higher resolution structures, but ab initio-derived search models are able to solve structures that could not be solved with the ideal helices. The addition of evolutionary contact information results in a marked improvement in the modelling and makes additional solutions possible.

Estimating rates and patterns of morphological evolution from phylogenies: lessons in limb lability from Australian Lerista lizards

PubMed Central

Wiens, John J

2009-01-01

Squamates (lizards and snakes) offer an exciting model system for research on the evolution of body form. A new phylogenetic study in BMC Evolutionary Biology of Australian lizards shows remarkable evolutionary lability in digit numbers among closely related species, but also highlights important challenges in this area. PMID:19291259