A simple non-Markovian computational model of the statistics of soccer leagues: Emergence and scaling effects

NASA Astrophysics Data System (ADS)

da Silva, Roberto; Vainstein, Mendeli H.; Lamb, Luis C.; Prado, Sandra D.

2013-03-01

We propose a novel probabilistic model that outputs the final standings of a soccer league, based on a simple dynamics that mimics a soccer tournament. In our model, a team is created with a defined potential (ability) which is updated during the tournament according to the results of previous games. The updated potential modifies a team future winning/losing probabilities. We show that this evolutionary game is able to reproduce the statistical properties of final standings of actual editions of the Brazilian tournament (Brasileirão) if the starting potential is the same for all teams. Other leagues such as the Italian (Calcio) and the Spanish (La Liga) tournaments have notoriously non-Gaussian traces and cannot be straightforwardly reproduced by this evolutionary non-Markovian model with simple initial conditions. However, we show that by setting the initial abilities based on data from previous tournaments, our model is able to capture the stylized statistical features of double round robin system (DRRS) tournaments in general. A complete understanding of these phenomena deserves much more attention, but we suggest a simple explanation based on data collected in Brazil: here several teams have been crowned champion in previous editions corroborating that the champion typically emerges from random fluctuations that partly preserve the Gaussian traces during the tournament. On the other hand, in the Italian and Spanish cases, only a few teams in recent history have won their league tournaments. These leagues are based on more robust and hierarchical structures established even before the beginning of the tournament. For the sake of completeness, we also elaborate a totally Gaussian model (which equalizes the winning, drawing, and losing probabilities) and we show that the scores of the Brazilian tournament “Brasileirão” cannot be reproduced. This shows that the evolutionary aspects are not superfluous and play an important role which must be considered in other alternative models. Finally, we analyze the distortions of our model in situations where a large number of teams is considered, showing the existence of a transition from a single to a double peaked histogram of the final classification scores. An interesting scaling is presented for different sized tournaments.

Neutral Evolution of Duplicated DNA: An Evolutionary Stick-Breaking Process Causes Scale-Invariant Behavior

NASA Astrophysics Data System (ADS)

Massip, Florian; Arndt, Peter F.

2013-04-01

Recently, an enrichment of identical matching sequences has been found in many eukaryotic genomes. Their length distribution exhibits a power law tail raising the question of what evolutionary mechanism or functional constraints would be able to shape this distribution. Here we introduce a simple and evolutionarily neutral model, which involves only point mutations and segmental duplications, and produces the same statistical features as observed for genomic data. Further, we extend a mathematical model for random stick breaking to analytically show that the exponent of the power law tail is -3 and universal as it does not depend on the microscopic details of the model.

Laboratory and modeling studies of chemistry in dense molecular clouds

NASA Technical Reports Server (NTRS)

Huntress, W. T., Jr.; Prasad, S. S.; Mitchell, G. F.

1980-01-01

A chemical evolutionary model with a large number of species and a large chemical library is used to examine the principal chemical processes in interstellar clouds. Simple chemical equilibrium arguments show the potential for synthesis of very complex organic species by ion-molecule radiative association reactions.

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

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.

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.

A Mind of Three Minds: Evolution of the Human Brain

ERIC Educational Resources Information Center

MacLean, Paul D.

1978-01-01

The author examines the evolutionary and neural roots of a triune intelligence comprised of a primal mind, an emotional mind, and a rational mind. A simple brain model and some definitions of unfamiliar behavioral terms are included. (Author/MA)

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

Evolutionary Study of Interethnic Cooperation

NASA Astrophysics Data System (ADS)

Kvasnicka, Vladimir; Pospichal, Jiri

The purpose of this communication is to present an evolutionary study of cooperation between two ethnic groups. The used model is stimulated by the seminal paper of J. D. Fearon and D. D. Laitin (Explaining Interethnic Cooperation, American Political Science Review, 90 (1996), pp. 715-735), where the iterated prisoner's dilemma was used to model intra- and interethnic interactions. We reformulated their approach in a form of evolutionary prisoner's dilemma method, where a population of strategies is evolved by applying simple reproduction process with a Darwin metaphor of natural selection (a probability of selection to the reproduction is proportional to a fitness). Our computer simulations show that an application of a principle of collective guilt does not lead to an emergence of an interethnic cooperation. When an administrator is introduced, then an emergence of interethnic cooperation may be observed. Furthermore, if the ethnic groups are of very different sizes, then the principle of collective guilt may be very devastating for smaller group so that intraethnic cooperation is destroyed. The second strategy of cooperation is called the personal responsibility, where agents that defected within interethnic interactions are punished inside of their ethnic groups. It means, unlikely to the principle of collective guilt, that there exists only one type of punishment, loosely speaking, agents are punished "personally." All the substantial computational results were checked and interpreted analytically within the theory of evolutionary stable strategies. Moreover, this theoretical approach offers mechanisms of simple scenarios explaining why some particular strategies are stable or not.

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.

Continuous "in vitro" Evolution of a Ribozyme Ligase: A Model Experiment for the Evolution of a Biomolecule

ERIC Educational Resources Information Center

Ledbetter, Michael P.; Hwang, Tony W.; Stovall, Gwendolyn M.; Ellington, Andrew D.

2013-01-01

Evolution is a defining criterion of life and is central to understanding biological systems. However, the timescale of evolutionary shifts in phenotype limits most classroom evolution experiments to simple probability simulations. "In vitro" directed evolution (IVDE) frequently serves as a model system for the study of Darwinian…

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.

Evolution of optimal Lévy-flight strategies in human mental searches

NASA Astrophysics Data System (ADS)

Radicchi, Filippo; Baronchelli, Andrea

2012-06-01

Recent analysis of empirical data [Radicchi, Baronchelli, and Amaral, PloS ONE1932-620310.1371/journal.pone.0029910 7, e029910 (2012)] showed that humans adopt Lévy-flight strategies when exploring the bid space in online auctions. A game theoretical model proved that the observed Lévy exponents are nearly optimal, being close to the exponent value that guarantees the maximal economical return to players. Here, we rationalize these findings by adopting an evolutionary perspective. We show that a simple evolutionary process is able to account for the empirical measurements with the only assumption that the reproductive fitness of the players is proportional to their search ability. Contrary to previous modeling, our approach describes the emergence of the observed exponent without resorting to any strong assumptions on the initial searching strategies. Our results generalize earlier research, and open novel questions in cognitive, behavioral, and evolutionary sciences.

Mathematical toy model inspired by the problem of the adaptive origins of the sexual orientation continuum

NASA Astrophysics Data System (ADS)

Skinner, Brian

2016-09-01

Same-sex sexual behaviour is ubiquitous in the animal kingdom, but its adaptive origins remain a prominent puzzle. Here, I suggest the possibility that same-sex sexual behaviour arises as a consequence of the competition between an evolutionary drive for a wide diversity in traits, which improves the adaptability of a population, and a drive for sexual dichotomization of traits, which promotes opposite-sex attraction and increases the rate of reproduction. This trade-off is explored via a simple mathematical `toy model'. The model exhibits a number of interesting features and suggests a simple mathematical form for describing the sexual orientation continuum.

Mathematical toy model inspired by the problem of the adaptive origins of the sexual orientation continuum.

PubMed

Skinner, Brian

2016-09-01

Same-sex sexual behaviour is ubiquitous in the animal kingdom, but its adaptive origins remain a prominent puzzle. Here, I suggest the possibility that same-sex sexual behaviour arises as a consequence of the competition between an evolutionary drive for a wide diversity in traits, which improves the adaptability of a population, and a drive for sexual dichotomization of traits, which promotes opposite-sex attraction and increases the rate of reproduction. This trade-off is explored via a simple mathematical 'toy model'. The model exhibits a number of interesting features and suggests a simple mathematical form for describing the sexual orientation continuum.

A Lesson on Evolution & Natural Selection

ERIC Educational Resources Information Center

Curtis, Anthony D.

2010-01-01

I describe three activities that allow students to explore the ideas of evolution, natural selection, extinction, mass extinction, and rates of evolutionary change by engaging a simple model using paper, pens, chalk, and a chalkboard. As a culminating activity that supports expository writing in the sciences, the students write an essay on mass…

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.

Chaos and the evolution of cooperation.

PubMed

Nowak, M; Sigmund, K

1993-06-01

The "iterated prisoner's dilemma" is the most widely used model for the evolution of cooperation in biological societies. Here we show that a heterogeneous population consisting of simple strategies, whose behavior is totally specified by the outcome of the previous round, can lead to persistent periodic or highly irregular (chaotic) oscillations in the frequencies of the strategies and the overall level of cooperation. The levels of cooperation jump up and down in an apparently unpredictable fashion. Small recurrent and simultaneous invasion attempts (caused by mutation) can change the evolutionary dynamics from converging to an evolutionarily stable strategy to periodic oscillations and chaos. Evolution can be twisted away from defection, toward cooperation. Adding "generous tit-for-tat" greatly increases the overall level of cooperation and can lead to long periods of steady cooperation. Since May's paper [May, R. M. (1976) Nature (London) 261, 459-467], "simple mathematical models with very complicated dynamics" have been found in many biological applications, but here we provide an example of a biologically relevant evolutionary game whose dynamics display deterministic chaos. The simulations bear some resemblance to the irregular cycles displayed by the frequencies of host genotypes and specialized parasites in evolutionary "arms races" [Hamilton, W. D., Axelrod, R. & Tanese, R. (1990) Proc. Natl. Acad. Sci. USA 87, 3566-3573; Seger, J. (1988) Philos. Trans. R. Soc. London B 319, 541-555].

Protein Structure Prediction with Evolutionary Algorithms

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

Hart, W.E.; Krasnogor, N.; Pelta, D.A.

1999-02-08

Evolutionary algorithms have been successfully applied to a variety of molecular structure prediction problems. In this paper we reconsider the design of genetic algorithms that have been applied to a simple protein structure prediction problem. Our analysis considers the impact of several algorithmic factors for this problem: the confirmational representation, the energy formulation and the way in which infeasible conformations are penalized, Further we empirically evaluated the impact of these factors on a small set of polymer sequences. Our analysis leads to specific recommendations for both GAs as well as other heuristic methods for solving PSP on the HP model.

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

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

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

The evolutionary ecology of molecular replicators

PubMed Central

2016-01-01

By reasonable criteria, life on the Earth consists mainly of molecular replicators. These include viruses, transposons, transpovirons, coviruses and many more, with continuous new discoveries like Sputnik Virophage. Their study is inherently multidisciplinary, spanning microbiology, genetics, immunology and evolutionary theory, and the current view is that taking a unified approach has great power and promise. We support this with a new, unified, model of their evolutionary ecology, using contemporary evolutionary theory coupling the Price equation with game theory, studying the consequences of the molecular replicators' promiscuous use of each others' gene products for their natural history and evolutionary ecology. Even at this simple expository level, we can make a firm prediction of a new class of replicators exploiting viruses such as lentiviruses like SIVs, a family which includes HIV: these have been explicitly stated in the primary literature to be non-existent. Closely connected to this departure is the view that multicellular organism immunology is more about the management of chronic infections rather than the elimination of acute ones and new understandings emerging are changing our view of the kind of theatre we ourselves provide for the evolutionary play of molecular replicators. This study adds molecular replicators to bacteria in the emerging field of sociomicrobiology. PMID:27853598

The evolutionary ecology of molecular replicators.

PubMed

Nee, Sean

2016-08-01

By reasonable criteria, life on the Earth consists mainly of molecular replicators. These include viruses, transposons, transpovirons, coviruses and many more, with continuous new discoveries like Sputnik Virophage. Their study is inherently multidisciplinary, spanning microbiology, genetics, immunology and evolutionary theory, and the current view is that taking a unified approach has great power and promise. We support this with a new, unified, model of their evolutionary ecology, using contemporary evolutionary theory coupling the Price equation with game theory, studying the consequences of the molecular replicators' promiscuous use of each others' gene products for their natural history and evolutionary ecology. Even at this simple expository level, we can make a firm prediction of a new class of replicators exploiting viruses such as lentiviruses like SIVs, a family which includes HIV: these have been explicitly stated in the primary literature to be non-existent. Closely connected to this departure is the view that multicellular organism immunology is more about the management of chronic infections rather than the elimination of acute ones and new understandings emerging are changing our view of the kind of theatre we ourselves provide for the evolutionary play of molecular replicators. This study adds molecular replicators to bacteria in the emerging field of sociomicrobiology.

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

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.

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.

Possibility of dying as a unified explanation of why we discount the future, get weaker with age, and display risk-aversion.

PubMed

Chowdhry, Bhagwan

2011-01-01

I formulate a simple and parsimonious evolutionary model that shows that because most species face a possibility of dying because of external factors, called extrinsic mortality in the biology literature, it can simultaneously explain (a) why we discount the future, (b) get weaker with age, and (c) display risk-aversion. The paper suggests that testable restrictions—across species, across time, or across genders—among time preference, aging, and risk-aversion could be analyzed in a simple framework .

Evolutionary Dynamics and Diversity in Microbial Populations

NASA Astrophysics Data System (ADS)

Thompson, Joel; Fisher, Daniel

2013-03-01

Diseases such as flu and cancer adapt at an astonishing rate. In large part, viruses and cancers are so difficult to prevent because they are continually evolving. Controlling such ``evolutionary diseases'' requires a better understanding of the underlying evolutionary dynamics. It is conventionally assumed that adaptive mutations are rare and therefore will occur and sweep through the population in succession. Recent experiments using modern sequencing technologies have illuminated the many ways in which real population sequence data does not conform to the predictions of conventional theory. We consider a very simple model of asexual evolution and perform simulations in a range of parameters thought to be relevant for microbes and cancer. Simulation results reveal complex evolutionary dynamics typified by competition between lineages with different sets of adaptive mutations. This dynamical process leads to a distribution of mutant gene frequencies different than expected under the conventional assumption that adaptive mutations are rare. Simulated gene frequencies share several conspicuous features with data collected from laboratory-evolved yeast and the worldwide population of influenza.

Iterated Prisoner’s Dilemma contains strategies that dominate any evolutionary opponent

PubMed Central

Press, William H.; Dyson, Freeman J.

2012-01-01

The two-player Iterated Prisoner’s Dilemma game is a model for both sentient and evolutionary behaviors, especially including the emergence of cooperation. It is generally assumed that there exists no simple ultimatum strategy whereby one player can enforce a unilateral claim to an unfair share of rewards. Here, we show that such strategies unexpectedly do exist. In particular, a player X who is witting of these strategies can (i) deterministically set her opponent Y’s score, independently of his strategy or response, or (ii) enforce an extortionate linear relation between her and his scores. Against such a player, an evolutionary player’s best response is to accede to the extortion. Only a player with a theory of mind about his opponent can do better, in which case Iterated Prisoner’s Dilemma is an Ultimatum Game. PMID:22615375

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.

Size-assortative mating and sexual size dimorphism are predictable from simple mechanics of mate-grasping behavior

PubMed Central

2010-01-01

Background A major challenge in evolutionary biology is to understand the typically complex interactions between diverse counter-balancing factors of Darwinian selection for size assortative mating and sexual size dimorphism. It appears that rarely a simple mechanism could provide a major explanation of these phenomena. Mechanics of behaviors can predict animal morphology, such like adaptations to locomotion in animals from various of taxa, but its potential to predict size-assortative mating and its evolutionary consequences has been less explored. Mate-grasping by males, using specialized adaptive morphologies of their forelegs, midlegs or even antennae wrapped around female body at specific locations, is a general mating strategy of many animals, but the contribution of the mechanics of this wide-spread behavior to the evolution of mating behavior and sexual size dimorphism has been largely ignored. Results Here, we explore the consequences of a simple, and previously ignored, fact that in a grasping posture the position of the male's grasping appendages relative to the female's body is often a function of body size difference between the sexes. Using an approach taken from robot mechanics we model coercive grasping of females by water strider Gerris gracilicornis males during mating initiation struggles. We determine that the male optimal size (relative to the female size), which gives the males the highest grasping force, properly predicts the experimentally measured highest mating success. Through field sampling and simulation modeling of a natural population we determine that the simple mechanical model, which ignores most of the other hypothetical counter-balancing selection pressures on body size, is sufficient to account for size-assortative mating pattern as well as species-specific sexual dimorphism in body size of G. gracilicornis. Conclusion The results indicate how a simple and previously overlooked physical mechanism common in many taxa is sufficient to account for, or importantly contribute to, size-assortative mating and its consequences for the evolution of sexual size dimorphism. PMID:21092131

Sail Plan Configuration Optimization for a Modern Clipper Ship

NASA Astrophysics Data System (ADS)

Gerritsen, Margot; Doyle, Tyler; Iaccarino, Gianluca; Moin, Parviz

2002-11-01

We investigate the use of gradient-based and evolutionary algorithms for sail shape optimization. We present preliminary results for the optimization of sheeting angles for the rig of the future three-masted clipper yacht Maltese Falcon. This yacht will be equipped with square-rigged masts made up of yards of circular arc cross sections. This design is especially attractive for megayachts because it provides a large sail area while maintaining aerodynamic and structural efficiency. The rig remains almost rigid in a large range of wind conditions and therefore a simple geometrical model can be constructed without accounting for the true flying shape. The sheeting angle optimization studies are performed using both gradient-based cost function minimization and evolutionary algorithms. The fluid flow is modeled by the Reynolds-averaged Navier-Stokes equations with the Spallart-Allmaras turbulence model. Unstructured non-conforming grids are used to increase robustness and computational efficiency. The optimization process is automated by integrating the system components (geometry construction, grid generation, flow solver, force calculator, optimization). We compare the optimization results to those done previously by user-controlled parametric studies using simple cost functions and user intuition. We also investigate the effectiveness of various cost functions in the optimization (driving force maximization, ratio of driving force to heeling force maximization).

Cultural selection drives the evolution of human communication systems

PubMed Central

Tamariz, Monica; Ellison, T. Mark; Barr, Dale J.; Fay, Nicolas

2014-01-01

Human communication systems evolve culturally, but the evolutionary mechanisms that drive this evolution are not well understood. Against a baseline that communication variants spread in a population following neutral evolutionary dynamics (also known as drift models), we tested the role of two cultural selection models: coordination- and content-biased. We constructed a parametrized mixed probabilistic model of the spread of communicative variants in four 8-person laboratory micro-societies engaged in a simple communication game. We found that selectionist models, working in combination, explain the majority of the empirical data. The best-fitting parameter setting includes an egocentric bias and a content bias, suggesting that participants retained their own previously used communicative variants unless they encountered a superior (content-biased) variant, in which case it was adopted. This novel pattern of results suggests that (i) a theory of the cultural evolution of human communication systems must integrate selectionist models and (ii) human communication systems are functionally adaptive complex systems. PMID:24966310

Cultural selection drives the evolution of human communication systems.

PubMed

Tamariz, Monica; Ellison, T Mark; Barr, Dale J; Fay, Nicolas

2014-08-07

Human communication systems evolve culturally, but the evolutionary mechanisms that drive this evolution are not well understood. Against a baseline that communication variants spread in a population following neutral evolutionary dynamics (also known as drift models), we tested the role of two cultural selection models: coordination- and content-biased. We constructed a parametrized mixed probabilistic model of the spread of communicative variants in four 8-person laboratory micro-societies engaged in a simple communication game. We found that selectionist models, working in combination, explain the majority of the empirical data. The best-fitting parameter setting includes an egocentric bias and a content bias, suggesting that participants retained their own previously used communicative variants unless they encountered a superior (content-biased) variant, in which case it was adopted. This novel pattern of results suggests that (i) a theory of the cultural evolution of human communication systems must integrate selectionist models and (ii) human communication systems are functionally adaptive complex systems.

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).

Evolutionary fields can explain patterns of high-dimensional complexity in ecology

NASA Astrophysics Data System (ADS)

Wilsenach, James; Landi, Pietro; Hui, Cang

2017-04-01

One of the properties that make ecological systems so unique is the range of complex behavioral patterns that can be exhibited by even the simplest communities with only a few species. Much of this complexity is commonly attributed to stochastic factors that have very high-degrees of freedom. Orthodox study of the evolution of these simple networks has generally been limited in its ability to explain complexity, since it restricts evolutionary adaptation to an inertia-free process with few degrees of freedom in which only gradual, moderately complex behaviors are possible. We propose a model inspired by particle-mediated field phenomena in classical physics in combination with fundamental concepts in adaptation, which suggests that small but high-dimensional chaotic dynamics near to the adaptive trait optimum could help explain complex properties shared by most ecological datasets, such as aperiodicity and pink, fractal noise spectra. By examining a simple predator-prey model and appealing to real ecological data, we show that this type of complexity could be easily confused for or confounded by stochasticity, especially when spurred on or amplified by stochastic factors that share variational and spectral properties with the underlying dynamics.

The evolutionary and behavioral modification of consumer responses to environmental change.

PubMed

Abrams, Peter A

2014-02-21

How will evolution or other forms of adaptive change alter the response of a consumer species' population density to environmentally driven changes in population growth parameters? This question is addressed by analyzing some simple consumer-resource models to separate the ecological and evolutionary components of the population's response. Ecological responses are always decreased population size, but evolution of traits that have effects on both resource uptake rate and another fitness-related parameter may magnify, offset, or reverse this population decrease. Evolution can change ecologically driven decreases in population size to increases; this is likely when: (1) resources are initially below the density that maximizes resource growth, and (2) the evolutionary response decreases the consumer's resource uptake rate. Evolutionary magnification of the ecological decreases in population size can occur when the environmental change is higher trait-independent mortality. Such evolution-driven decreases are most likely when uptake-rate traits increase and the resource is initially below its maximum growth density. It is common for the difference between the new eco-evolutionary equilibrium and the new ecological equilibrium to be larger than that between the original and new ecological equilibrium densities. The relative magnitudes of ecological and evolutionary effects often depend sensitively on the magnitude of the environmental change and the nature of resource growth. © 2013 Elsevier Ltd. All rights reserved.

Mechanisms of bacterial morphogenesis: evolutionary cell biology approaches provide new insights.

PubMed

Jiang, Chao; Caccamo, Paul D; Brun, Yves V

2015-04-01

How Darwin's "endless forms most beautiful" have evolved remains one of the most exciting questions in biology. The significant variety of bacterial shapes is most likely due to the specific advantages they confer with respect to the diverse environments they occupy. While our understanding of the mechanisms generating relatively simple shapes has improved tremendously in the last few years, the molecular mechanisms underlying the generation of complex shapes and the evolution of shape diversity are largely unknown. The emerging field of bacterial evolutionary cell biology provides a novel strategy to answer this question in a comparative phylogenetic framework. This relatively novel approach provides hypotheses and insights into cell biological mechanisms, such as morphogenesis, and their evolution that would have been difficult to obtain by studying only model organisms. We discuss the necessary steps, challenges, and impact of integrating "evolutionary thinking" into bacterial cell biology in the genomic era. © 2015 WILEY Periodicals, Inc.

Turbopump Performance Improved by Evolutionary Algorithms

NASA Technical Reports Server (NTRS)

Oyama, Akira; Liou, Meng-Sing

2002-01-01

The development of design optimization technology for turbomachinery has been initiated using the multiobjective evolutionary algorithm under NASA's Intelligent Synthesis Environment and Revolutionary Aeropropulsion Concepts programs. As an alternative to the traditional gradient-based methods, evolutionary algorithms (EA's) are emergent design-optimization algorithms modeled after the mechanisms found in natural evolution. EA's search from multiple points, instead of moving from a single point. In addition, they require no derivatives or gradients of the objective function, leading to robustness and simplicity in coupling any evaluation codes. Parallel efficiency also becomes very high by using a simple master-slave concept for function evaluations, since such evaluations often consume the most CPU time, such as computational fluid dynamics. Application of EA's to multiobjective design problems is also straightforward because EA's maintain a population of design candidates in parallel. Because of these advantages, EA's are a unique and attractive approach to real-world design optimization problems.

Life-history plasticity and sustainable exploitation: a theory of growth compensation applied to walleye management.

PubMed

Lester, Nigel P; Shuter, Brian J; Venturelli, Paul; Nadeau, Daniel

2014-01-01

A simple population model was developed to evaluate the role of plastic and evolutionary life-history changes on sustainable exploitation rates. Plastic changes are embodied in density-dependent compensatory adjustments to somatic growth rate and larval/juvenile survival, which can compensate for the reductions in reproductive lifetime and mean population fecundity that accompany the higher adult mortality imposed by exploitation. Evolutionary changes are embodied in the selective pressures that higher adult mortality imposes on age at maturity, length at maturity, and reproductive investment. Analytical development, based on a biphasic growth model, led to simple equations that show explicitly how sustainable exploitation rates are bounded by each of these effects. We show that density-dependent growth combined with a fixed length at maturity and fixed reproductive investment can support exploitation-driven mortality that is 80% of the level supported by evolutionary changes in maturation and reproductive investment. Sustainable fishing mortality is proportional to natural mortality (M) times the degree of density-dependent growth, as modified by both the degree of density-dependent early survival and the minimum harvestable length. We applied this model to estimate sustainable exploitation rates for North American walleye populations (Sander vitreus). Our analysis of demographic data from walleye populations spread across a broad latitudinal range indicates that density-dependent variation in growth rate can vary by a factor of 2. Implications of this growth response are generally consistent with empirical studies suggesting that optimal fishing mortality is approximately 0.75M for teleosts. This approach can be adapted to the management of other species, particularly when significant exploitation is imposed on many, widely distributed, but geographically isolated populations.

Tempo and mode of climatic niche evolution in Primates.

PubMed

Duran, Andressa; Pie, Marcio R

2015-09-01

Climatic niches have increasingly become a nexus in our understanding of a variety of ecological and evolutionary phenomena, from species distributions to latitudinal diversity gradients. Despite the increasing availability of comprehensive datasets on species ranges, phylogenetic histories, and georeferenced environmental conditions, studies on the evolution of climate niches have only begun to understand how niches evolve over evolutionary timescales. Here, using primates as a model system, we integrate recently developed phylogenetic comparative methods, species distribution patterns, and climatic data to explore primate climatic niche evolution, both among clades and over time. In general, we found that simple, constant-rate models provide a poor representation of how climatic niches evolve. For instance, there have been shifts in the rate of climatic niche evolution in several independent clades, particularly in response to the increasingly cooler climates of the past 10 My. Interestingly, rate accelerations greatly outnumbered rate decelerations. These results highlight the importance of considering more realistic evolutionary models that allow for the detection of heterogeneity in the tempo and mode of climatic niche evolution, as well as to infer possible constraining factors for species distributions in geographical space. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Multiannual forecasting of seasonal influenza dynamics reveals climatic and evolutionary drivers.

PubMed

Axelsen, Jacob Bock; Yaari, Rami; Grenfell, Bryan T; Stone, Lewi

2014-07-01

Human influenza occurs annually in most temperate climatic zones of the world, with epidemics peaking in the cold winter months. Considerable debate surrounds the relative role of epidemic dynamics, viral evolution, and climatic drivers in driving year-to-year variability of outbreaks. The ultimate test of understanding is prediction; however, existing influenza models rarely forecast beyond a single year at best. Here, we use a simple epidemiological model to reveal multiannual predictability based on high-quality influenza surveillance data for Israel; the model fit is corroborated by simple metapopulation comparisons within Israel. Successful forecasts are driven by temperature, humidity, antigenic drift, and immunity loss. Essentially, influenza dynamics are a balance between large perturbations following significant antigenic jumps, interspersed with nonlinear epidemic dynamics tuned by climatic forcing.

Games of multicellularity.

PubMed

Kaveh, Kamran; Veller, Carl; Nowak, Martin A

2016-08-21

Evolutionary game dynamics are often studied in the context of different population structures. Here we propose a new population structure that is inspired by simple multicellular life forms. In our model, cells reproduce but can stay together after reproduction. They reach complexes of a certain size, n, before producing single cells again. The cells within a complex derive payoff from an evolutionary game by interacting with each other. The reproductive rate of cells is proportional to their payoff. We consider all two-strategy games. We study deterministic evolutionary dynamics with mutations, and derive exact conditions for selection to favor one strategy over another. Our main result has the same symmetry as the well-known sigma condition, which has been proven for stochastic game dynamics and weak selection. For a maximum complex size of n=2 our result holds for any intensity of selection. For n≥3 it holds for weak selection. As specific examples we study the prisoner's dilemma and hawk-dove games. Our model advances theoretical work on multicellularity by allowing for frequency-dependent interactions within groups. Copyright © 2016 Elsevier Ltd. All rights reserved.

Yonsei Evolutionary Population Synthesis (YEPS). II. Spectro-photometric Evolution of Helium-enhanced Stellar Populations

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

Chung, Chul; Yoon, Suk-Jin; Lee, Young-Wook, E-mail: chulchung@yonsei.ac.kr, E-mail: sjyoon0691@yonsei.ac.kr

The discovery of multiple stellar populations in Milky Way globular clusters (GCs) has stimulated various follow-up studies on helium-enhanced stellar populations. Here we present the evolutionary population synthesis models for the spectro-photometric evolution of simple stellar populations (SSPs) with varying initial helium abundance ( Y {sub ini}). We show that Y {sub ini} brings about dramatic changes in spectro-photometric properties of SSPs. Like the normal-helium SSPs, the integrated spectro-photometric evolution of helium-enhanced SSPs is also dependent on metallicity and age for a given Y {sub ini}. We discuss the implications and prospects for the helium-enhanced populations in relation to themore » second-generation populations found in the Milky Way GCs. All of the models are available at http://web.yonsei.ac.kr/cosmic/data/YEPS.htm.« less

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.

Games among relatives revisited.

PubMed

Allen, Benjamin; Nowak, Martin A

2015-08-07

We present a simple model for the evolution of social behavior in family-structured, finite sized populations. Interactions are represented as evolutionary games describing frequency-dependent selection. Individuals interact more frequently with siblings than with members of the general population, as quantified by an assortment parameter r, which can be interpreted as "relatedness". Other models, mostly of spatially structured populations, have shown that assortment can promote the evolution of cooperation by facilitating interaction between cooperators, but this effect depends on the details of the evolutionary process. For our model, we find that sibling assortment promotes cooperation in stringent social dilemmas such as the Prisoner's Dilemma, but not necessarily in other situations. These results are obtained through straightforward calculations of changes in gene frequency. We also analyze our model using inclusive fitness. We find that the quantity of inclusive fitness does not exist for general games. For special games, where inclusive fitness exists, it provides less information than the straightforward analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Chemical evolutionary games.

PubMed

Aristotelous, Andreas C; Durrett, Richard

2014-05-01

Inspired by the use of hybrid cellular automata in modeling cancer, we introduce a generalization of evolutionary games in which cells produce and absorb chemicals, and the chemical concentrations dictate the death rates of cells and their fitnesses. Our long term aim is to understand how the details of the interactions in a system with n species and m chemicals translate into the qualitative behavior of the system. Here, we study two simple 2×2 games with two chemicals and revisit the two and three species versions of the one chemical colicin system studied earlier by Durrett and Levin (1997). We find that in the 2×2 examples, the behavior of our new spatial model can be predicted from that of the mean field differential equation using ideas of Durrett and Levin (1994). However, in the three species colicin model, the system with diffusion does not have the coexistence which occurs in the lattices model in which sites interact with only their nearest neighbors. Copyright © 2014 Elsevier Inc. All rights reserved.

Probability, statistics, and computational science.

PubMed

Beerenwinkel, Niko; Siebourg, Juliane

2012-01-01

In this chapter, we review basic concepts from probability theory and computational statistics that are fundamental to evolutionary genomics. We provide a very basic introduction to statistical modeling and discuss general principles, including maximum likelihood and Bayesian inference. Markov chains, hidden Markov models, and Bayesian network models are introduced in more detail as they occur frequently and in many variations in genomics applications. In particular, we discuss efficient inference algorithms and methods for learning these models from partially observed data. Several simple examples are given throughout the text, some of which point to models that are discussed in more detail in subsequent chapters.

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.

On Cellular Darwinism: Mitochondria.

PubMed

Bull, Larry

2016-01-01

The significant role of mitochondria within cells is becoming increasingly clear. This letter uses the NKCS model of coupled fitness landscapes to explore aspects of organelle-nucleus coevolution. The phenomenon of mitochondrial diversity is allowed to emerge under a simple intracellular evolutionary process, including varying the relative rate of evolution by the organelle. It is shown how the conditions for the maintenance of more than one genetic variant of mitochondria are similar to those previously suggested as needed for the original symbiotic origins of the relationship using the NKCS model.

A simple tectonic model for crustal accretion in the Slave Province: A 2.7-2.5 Ga granite greenstone terrane

NASA Technical Reports Server (NTRS)

Hoffman, P. F.

1986-01-01

A prograding (direction unspecified) trench-arc system is favored as a simple yet comprehensive model for crustal generation in a 250,000 sq km granite-greenstone terrain. The model accounts for the evolutionary sequence of volcanism, sedimentation, deformation, metamorphism and plutonism, observed througout the Slave province. Both unconformable (trench inner slope) and subconformable (trench outer slope) relations between the volcanics and overlying turbidities; and the existence of relatively minor amounts of pre-greenstone basement (microcontinents) and syn-greenstone plutons (accreted arc roots) are explained. Predictions include: a varaiable gap between greenstone volcanism and trench turbidite sedimentation (accompanied by minor volcanism) and systematic regional variations in age span of volcanism and plutonism. Implications of the model will be illustrated with reference to a 1:1 million scale geological map of the Slave Province (and its bounding 1.0 Ga orogens).

Ploidy, sex and crossing over in an evolutionary aging model

NASA Astrophysics Data System (ADS)

Lobo, Matheus P.; Onody, Roberto N.

2006-02-01

Nowadays, many forms of reproduction coexist in nature: Asexual, sexual, apomictic and meiotic parthenogenesis, hermaphroditism and parasex. The mechanisms of their evolution and what made them successful reproductive alternatives are very challenging and debated questions. Here, using a simple evolutionary aging model, we give a possible scenario. By studying the performance of populations where individuals may have diverse characteristics-different ploidies, sex with or without crossing over, as well as the absence of sex-we find an evolution sequence that may explain why there are actually two major or leading groups: Sexual and asexual. We also investigate the dependence of these characteristics on different conditions of fertility and deleterious mutations. Finally, if the primeval organisms on Earth were, in fact, asexual individuals we conjecture that the sexual form of reproduction could have more easily been set and found its niche during a period of low-intensity mutations.

Exploring the effect of power law social popularity on language evolution.

PubMed

Gong, Tao; Shuai, Lan

2014-01-01

We evaluate the effect of a power-law-distributed social popularity on the origin and change of language, based on three artificial life models meticulously tracing the evolution of linguistic conventions including lexical items, categories, and simple syntax. A cross-model analysis reveals an optimal social popularity, in which the λ value of the power law distribution is around 1.0. Under this scaling, linguistic conventions can efficiently emerge and widely diffuse among individuals, thus maintaining a useful level of mutual understandability even in a big population. From an evolutionary perspective, we regard this social optimality as a tradeoff among social scaling, mutual understandability, and population growth. Empirical evidence confirms that such optimal power laws exist in many large-scale social systems that are constructed primarily via language-related interactions. This study contributes to the empirical explorations and theoretical discussions of the evolutionary relations between ubiquitous power laws in social systems and relevant individual behaviors.

Histories of molecules: Reconciling the past.

PubMed

O'Malley, Maureen A

2016-02-01

Molecular data and methods have become centrally important to evolutionary analysis, largely because they have enabled global phylogenetic reconstructions of the relationships between organisms in the tree of life. Often, however, molecular stories conflict dramatically with morphology-based histories of lineages. The evolutionary origin of animal groups provides one such case. In other instances, different molecular analyses have so far proved irreconcilable. The ancient and major divergence of eukaryotes from prokaryotic ancestors is an example of this sort of problem. Efforts to overcome these conflicts highlight the role models play in phylogenetic reconstruction. One crucial model is the molecular clock; another is that of 'simple-to-complex' modification. I will examine animal and eukaryote evolution against a backdrop of increasing methodological sophistication in molecular phylogeny, and conclude with some reflections on the nature of historical science in the molecular era of phylogeny. Copyright © 2015 Elsevier Ltd. All rights reserved.

Emergence of Prime Numbers as the Result of Evolutionary Strategy

NASA Astrophysics Data System (ADS)

Campos, Paulo R.; de Oliveira, Viviane M.; Giro, Ronaldo; Galvão, Douglas S.

2004-08-01

We investigate by means of a simple theoretical model the emergence of prime numbers as life cycles, as those seen for some species of cicadas. The cicadas, more precisely the Magicicadas, spend most of their lives below the ground and then emerge and die in a short period of time. The Magicicadas display an uncommon behavior: their emergence is synchronized and these periods are usually prime numbers. In the current work, we develop a spatially extended model at which preys and predators coexist and can change their evolutionary dynamics through the occurrence of mutations. We verified that prime numbers as life cycles emerge as a result of the evolution of the population. Our results seem to be a first step in order to prove that the development of such strategy is selectively advantageous, especially for those organisms that are highly vulnerable to attacks of predators.

Linear and evolutionary polynomial regression models to forecast coastal dynamics: Comparison and reliability assessment

NASA Astrophysics Data System (ADS)

Bruno, Delia Evelina; Barca, Emanuele; Goncalves, Rodrigo Mikosz; de Araujo Queiroz, Heithor Alexandre; Berardi, Luigi; Passarella, Giuseppe

2018-01-01

In this paper, the Evolutionary Polynomial Regression data modelling strategy has been applied to study small scale, short-term coastal morphodynamics, given its capability for treating a wide database of known information, non-linearly. Simple linear and multilinear regression models were also applied to achieve a balance between the computational load and reliability of estimations of the three models. In fact, even though it is easy to imagine that the more complex the model, the more the prediction improves, sometimes a "slight" worsening of estimations can be accepted in exchange for the time saved in data organization and computational load. The models' outcomes were validated through a detailed statistical, error analysis, which revealed a slightly better estimation of the polynomial model with respect to the multilinear model, as expected. On the other hand, even though the data organization was identical for the two models, the multilinear one required a simpler simulation setting and a faster run time. Finally, the most reliable evolutionary polynomial regression model was used in order to make some conjecture about the uncertainty increase with the extension of extrapolation time of the estimation. The overlapping rate between the confidence band of the mean of the known coast position and the prediction band of the estimated position can be a good index of the weakness in producing reliable estimations when the extrapolation time increases too much. The proposed models and tests have been applied to a coastal sector located nearby Torre Colimena in the Apulia region, south Italy.

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.

Theoretical Analysis of Local Search and Simple Evolutionary Algorithms for the Generalized Travelling Salesperson Problem.

PubMed

Pourhassan, Mojgan; Neumann, Frank

2018-06-22

The generalized travelling salesperson problem is an important NP-hard combinatorial optimization problem for which meta-heuristics, such as local search and evolutionary algorithms, have been used very successfully. Two hierarchical approaches with different neighbourhood structures, namely a Cluster-Based approach and a Node-Based approach, have been proposed by Hu and Raidl (2008) for solving this problem. In this paper, local search algorithms and simple evolutionary algorithms based on these approaches are investigated from a theoretical perspective. For local search algorithms, we point out the complementary abilities of the two approaches by presenting instances where they mutually outperform each other. Afterwards, we introduce an instance which is hard for both approaches when initialized on a particular point of the search space, but where a variable neighbourhood search combining them finds the optimal solution in polynomial time. Then we turn our attention to analysing the behaviour of simple evolutionary algorithms that use these approaches. We show that the Node-Based approach solves the hard instance of the Cluster-Based approach presented in Corus et al. (2016) in polynomial time. Furthermore, we prove an exponential lower bound on the optimization time of the Node-Based approach for a class of Euclidean instances.

Towards a mechanistic foundation of evolutionary theory.

PubMed

Doebeli, Michael; Ispolatov, Yaroslav; Simon, Burt

2017-02-15

Most evolutionary thinking is based on the notion of fitness and related ideas such as fitness landscapes and evolutionary optima. Nevertheless, it is often unclear what fitness actually is, and its meaning often depends on the context. Here we argue that fitness should not be a basal ingredient in verbal or mathematical descriptions of evolution. Instead, we propose that evolutionary birth-death processes, in which individuals give birth and die at ever-changing rates, should be the basis of evolutionary theory, because such processes capture the fundamental events that generate evolutionary dynamics. In evolutionary birth-death processes, fitness is at best a derived quantity, and owing to the potential complexity of such processes, there is no guarantee that there is a simple scalar, such as fitness, that would describe long-term evolutionary outcomes. We discuss how evolutionary birth-death processes can provide useful perspectives on a number of central issues in evolution.

Regularization techniques for backward--in--time evolutionary PDE problems

NASA Astrophysics Data System (ADS)

Gustafsson, Jonathan; Protas, Bartosz

2007-11-01

Backward--in--time evolutionary PDE problems have applications in the recently--proposed retrograde data assimilation. We consider the terminal value problem for the Kuramoto--Sivashinsky equation (KSE) in a 1D periodic domain as our model system. The KSE, proposed as a model for interfacial and combustion phenomena, is also often adopted as a toy model for hydrodynamic turbulence because of its multiscale and chaotic dynamics. Backward--in--time problems are typical examples of ill-posed problem, where disturbances are amplified exponentially during the backward march. Regularization is required to solve such problems efficiently and we consider approaches in which the original ill--posed problem is approximated with a less ill--posed problem obtained by adding a regularization term to the original equation. While such techniques are relatively well--understood for linear problems, they less understood in the present nonlinear setting. We consider regularization terms with fixed magnitudes and also explore a novel approach in which these magnitudes are adapted dynamically using simple concepts from the Control Theory.

Selective sweeps in growing microbial colonies

NASA Astrophysics Data System (ADS)

Korolev, Kirill S.; Müller, Melanie J. I.; Karahan, Nilay; Murray, Andrew W.; Hallatschek, Oskar; Nelson, David R.

2012-04-01

Evolutionary experiments with microbes are a powerful tool to study mutations and natural selection. These experiments, however, are often limited to the well-mixed environments of a test tube or a chemostat. Since spatial organization can significantly affect evolutionary dynamics, the need is growing for evolutionary experiments in spatially structured environments. The surface of a Petri dish provides such an environment, but a more detailed understanding of microbial growth on Petri dishes is necessary to interpret such experiments. We formulate a simple deterministic reaction-diffusion model, which successfully predicts the spatial patterns created by two competing species during colony expansion. We also derive the shape of these patterns analytically without relying on microscopic details of the model. In particular, we find that the relative fitness of two microbial strains can be estimated from the logarithmic spirals created by selective sweeps. The theory is tested with strains of the budding yeast Saccharomyces cerevisiae for spatial competitions with different initial conditions and for a range of relative fitnesses. The reaction-diffusion model also connects the microscopic parameters like growth rates and diffusion constants with macroscopic spatial patterns and predicts the relationship between fitness in liquid cultures and on Petri dishes, which we confirmed experimentally. Spatial sector patterns therefore provide an alternative fitness assay to the commonly used liquid culture fitness assays.

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

Influence of the Mesh Geometry Evolution on Gearbox Dynamics during Its Maintenance

NASA Astrophysics Data System (ADS)

Dąbrowski, Z.; Dziurdź, J.; Klekot, G.

2017-12-01

Toothed gears constitute the necessary elements of power transmission systems. They are applied as stationary devices in drive systems of road vehicles, ships and crafts as well as airplanes and helicopters. One of the problems related to the toothed gears usage is the determination of their technical state or its evolutions. Assuming that the gear slippage velocity is attributed to vibrations and noises generated by cooperating toothed wheels, the application of a simple cooperation model of rolled wheels of skew teeth is proposed for the analysis of the mesh evolution influence on the gear dynamics. In addition, an example of utilising an ordinary coherence function for investigating evolutionary mesh changes related to the effects impossible to be described by means of the simple kinematic model is presented.

Comparative genomic de-convolution of the cotton genome revealed a decaploid ancestor and widespread chromosomal fractionation.

PubMed

Wang, Xiyin; Guo, Hui; Wang, Jinpeng; Lei, Tianyu; Liu, Tao; Wang, Zhenyi; Li, Yuxian; Lee, Tae-Ho; Li, Jingping; Tang, Haibao; Jin, Dianchuan; Paterson, Andrew H

2016-02-01

The 'apparently' simple genomes of many angiosperms mask complex evolutionary histories. The reference genome sequence for cotton (Gossypium spp.) revealed a ploidy change of a complexity unprecedented to date, indeed that could not be distinguished as to its exact dosage. Herein, by developing several comparative, computational and statistical approaches, we revealed a 5× multiplication in the cotton lineage of an ancestral genome common to cotton and cacao, and proposed evolutionary models to show how such a decaploid ancestor formed. The c. 70% gene loss necessary to bring the ancestral decaploid to its current gene count appears to fit an approximate geometrical model; that is, although many genes may be lost by single-gene deletion events, some may be lost in groups of consecutive genes. Gene loss following cotton decaploidy has largely just reduced gene copy numbers of some homologous groups. We designed a novel approach to deconvolute layers of chromosome homology, providing definitive information on gene orthology and paralogy across broad evolutionary distances, both of fundamental value and serving as an important platform to support further studies in and beyond cotton and genomics communities. No claim to original US government works. New Phytologist © 2015 New Phytologist Trust.

Evolutionary Models for Simple Biosystems

NASA Astrophysics Data System (ADS)

Bagnoli, Franco

The concept of evolutionary development of structures constituted a real revolution in biology: it was possible to understand how the very complex structures of life can arise in an out-of-equilibrium system. The investigation of such systems has shown that indeed, systems under a flux of energy or matter can self-organize into complex patterns, think for instance to Rayleigh-Bernard convection, Liesegang rings, patterns formed by granular systems under shear. Following this line, one could characterize life as a state of matter, characterized by the slow, continuous process that we call evolution. In this paper we try to identify the organizational level of life, that spans several orders of magnitude from the elementary constituents to whole ecosystems. Although similar structures can be found in other contexts like ideas (memes) in neural systems and self-replicating elements (computer viruses, worms, etc.) in computer systems, we shall concentrate on biological evolutionary structure, and try to put into evidence the role and the emergence of network structure in such systems.

3000 Years of Breeding for Drought Tolerance in Soybean

USDA-ARS?s Scientific Manuscript database

Plants and animals have both suffered through extreme environments over the long evolutionary history of life. Amazing adaptations such as camels and cactus have occurred. On the whole however, evolutionary adaptation to stress has been greater in plants than in animals. The simple difference betwe...

The Frenkel Kontorova Model

NASA Astrophysics Data System (ADS)

Floría, L. M.; Baesens, C.; Gómez-Gardeñes, J.

In the preface to his monograph on the structure of Evolutionary Theory [1], the late professor Stephen Jay Gould attributes to the philosopher Immanuel Kant the following aphorism in Science Philosophy: "Percepts without concepts are blind; concepts without percepts are empty". Using with a bit of freedom these Kantian terms, one would say that a scientific model is a framework (or network) of interrelated concepts and percepts where experts build up scientific consistent explanations of a given set of observations. Good models are those which are both, conceptually simple and universal in their perceptions. Let us illustrate with examples the meaning of this statement.

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.

Darwinian evolution in the light of genomics

PubMed Central

Koonin, Eugene V.

2009-01-01

Comparative genomics and systems biology offer unprecedented opportunities for testing central tenets of evolutionary biology formulated by Darwin in the Origin of Species in 1859 and expanded in the Modern Synthesis 100 years later. Evolutionary-genomic studies show that natural selection is only one of the forces that shape genome evolution and is not quantitatively dominant, whereas non-adaptive processes are much more prominent than previously suspected. Major contributions of horizontal gene transfer and diverse selfish genetic elements to genome evolution undermine the Tree of Life concept. An adequate depiction of evolution requires the more complex concept of a network or ‘forest’ of life. There is no consistent tendency of evolution towards increased genomic complexity, and when complexity increases, this appears to be a non-adaptive consequence of evolution under weak purifying selection rather than an adaptation. Several universals of genome evolution were discovered including the invariant distributions of evolutionary rates among orthologous genes from diverse genomes and of paralogous gene family sizes, and the negative correlation between gene expression level and sequence evolution rate. Simple, non-adaptive models of evolution explain some of these universals, suggesting that a new synthesis of evolutionary biology might become feasible in a not so remote future. PMID:19213802

Predator confusion is sufficient to evolve swarming behaviour

PubMed Central

Olson, Randal S.; Hintze, Arend; Dyer, Fred C.; Knoester, David B.; Adami, Christoph

2013-01-01

Swarming behaviours in animals have been extensively studied owing to their implications for the evolution of cooperation, social cognition and predator–prey dynamics. An important goal of these studies is discerning which evolutionary pressures favour the formation of swarms. One hypothesis is that swarms arise because the presence of multiple moving prey in swarms causes confusion for attacking predators, but it remains unclear how important this selective force is. Using an evolutionary model of a predator–prey system, we show that predator confusion provides a sufficient selection pressure to evolve swarming behaviour in prey. Furthermore, we demonstrate that the evolutionary effect of predator confusion on prey could in turn exert pressure on the structure of the predator's visual field, favouring the frontally oriented, high-resolution visual systems commonly observed in predators that feed on swarming animals. Finally, we provide evidence that when prey evolve swarming in response to predator confusion, there is a change in the shape of the functional response curve describing the predator's consumption rate as prey density increases. Thus, we show that a relatively simple perceptual constraint—predator confusion—could have pervasive evolutionary effects on prey behaviour, predator sensory mechanisms and the ecological interactions between predators and prey. PMID:23740485

Predator confusion is sufficient to evolve swarming behaviour.

PubMed

Olson, Randal S; Hintze, Arend; Dyer, Fred C; Knoester, David B; Adami, Christoph

2013-08-06

Swarming behaviours in animals have been extensively studied owing to their implications for the evolution of cooperation, social cognition and predator-prey dynamics. An important goal of these studies is discerning which evolutionary pressures favour the formation of swarms. One hypothesis is that swarms arise because the presence of multiple moving prey in swarms causes confusion for attacking predators, but it remains unclear how important this selective force is. Using an evolutionary model of a predator-prey system, we show that predator confusion provides a sufficient selection pressure to evolve swarming behaviour in prey. Furthermore, we demonstrate that the evolutionary effect of predator confusion on prey could in turn exert pressure on the structure of the predator's visual field, favouring the frontally oriented, high-resolution visual systems commonly observed in predators that feed on swarming animals. Finally, we provide evidence that when prey evolve swarming in response to predator confusion, there is a change in the shape of the functional response curve describing the predator's consumption rate as prey density increases. Thus, we show that a relatively simple perceptual constraint--predator confusion--could have pervasive evolutionary effects on prey behaviour, predator sensory mechanisms and the ecological interactions between predators and prey.

Epidemiological, evolutionary and co-evolutionary implications of context-dependent parasitism

PubMed Central

Vale, Pedro F.; Wilson, Alastair J.; Best, Alex; Boots, Mike; Little, Tom J.

2013-01-01

Victims of infection are expected to suffer increasingly as parasite population growth increases. Yet, under some conditions, faster growing parasites do not appear to cause more damage and infections can be quite tolerable. We studied these conditions by assessing how the relationship between parasite population growth and host health is sensitive to environmental variation. In experimental infections of the crustacean Daphnia magna and its bacterial parasite Pasteuria ramosa we show how easily an interaction can shift from a severe interaction, i.e. when host fitness declines substantially with each unit of parasite growth, to a tolerable relationship by changing only simple environmental variables: temperature and food availability. We explored the evolutionary and epidemiological implications of such a shift by modelling pathogen evolution and disease spread under different levels of infection severity, and find that environmental shifts that promote tolerance ultimately result in populations harbouring more parasitized individuals. We also find that the opportunity for selection, as indicated by the variance around traits, varied considerably with the environmental treatment. Thus our results suggest two mechanisms that could underlie co-evolutionary hot- and coldspots: spatial variation in tolerance and spatial variation in the opportunity for selection. PMID:21460572

Calibrating White Dwarf Asteroseismic Fitting Techniques

NASA Astrophysics Data System (ADS)

Castanheira, B. G.; Romero, A. D.; Bischoff-Kim, A.

2017-03-01

The main goal of looking for intrinsic variability in stars is the unique opportunity to study their internal structure. Once we have extracted independent modes from the data, it appears to be a simple matter of comparing the period spectrum with those from theoretical model grids to learn the inner structure of that star. However, asteroseismology is much more complicated than this simple description. We must account not only for observational uncertainties in period determination, but most importantly for the limitations of the model grids, coming from the uncertainties in the constitutive physics, and of the fitting techniques. In this work, we will discuss results of numerical experiments where we used different independently calculated model grids (white dwarf cooling models WDEC and fully evolutionary LPCODE-PUL) and fitting techniques to fit synthetic stars. The advantage of using synthetic stars is that we know the details of their interior structure so we can assess how well our models and fitting techniques are able to the recover the interior structure, as well as the stellar parameters.

Simulation of the evolution of root water foraging strategies in dry and shallow soils.

PubMed

Renton, Michael; Poot, Pieter

2014-09-01

The dynamic structural development of plants can be seen as a strategy for exploiting the limited resources available within their environment, and we would expect that evolution would lead to efficient strategies that reduce costs while maximizing resource acquisition. In particular, perennial species endemic to habitats with shallow soils in seasonally dry environments have been shown to have a specialized root system morphology that may enhance access to water resources in the underlying rock. This study aimed to explore these hypotheses by applying evolutionary algorithms to a functional-structural root growth model. A simulation model of a plant's root system was developed, which represents the dynamics of water uptake and structural growth. The model is simple enough for evolutionary optimization to be computationally feasible, yet flexible enough to allow a range of structural development strategies to be explored. The model was combined with an evolutionary algorithm in order to investigate a case study habitat with a highly heterogeneous distribution of resources, both spatially and temporally--the situation of perennial plants occurring on shallow soils in seasonally dry environments. Evolution was simulated under two contrasting fitness criteria: (1) the ability to find wet cracks in underlying rock, and (2) maximizing above-ground biomass. The novel approach successfully resulted in the evolution of more efficient structural development strategies for both fitness criteria. Different rooting strategies evolved when different criteria were applied, and each evolved strategy made ecological sense in terms of the corresponding fitness criterion. Evolution selected for root system morphologies which matched those of real species from corresponding habitats. Specialized root morphology with deeper rather than shallower lateral branching enhances access to water resources in underlying rock. More generally, the approach provides insights into both evolutionary processes and ecological costs and benefits of different plant growth strategies.

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

Deciphering mRNA Sequence Determinants of Protein Production Rate

NASA Astrophysics Data System (ADS)

Szavits-Nossan, Juraj; Ciandrini, Luca; Romano, M. Carmen

2018-03-01

One of the greatest challenges in biophysical models of translation is to identify coding sequence features that affect the rate of translation and therefore the overall protein production in the cell. We propose an analytic method to solve a translation model based on the inhomogeneous totally asymmetric simple exclusion process, which allows us to unveil simple design principles of nucleotide sequences determining protein production rates. Our solution shows an excellent agreement when compared to numerical genome-wide simulations of S. cerevisiae transcript sequences and predicts that the first 10 codons, which is the ribosome footprint length on the mRNA, together with the value of the initiation rate, are the main determinants of protein production rate under physiological conditions. Finally, we interpret the obtained analytic results based on the evolutionary role of the codons' choice for regulating translation rates and ribosome densities.

Relationship between the column density distribution and evolutionary class of molecular clouds as viewed by ATLASGAL

NASA Astrophysics Data System (ADS)

Abreu-Vicente, J.; Kainulainen, J.; Stutz, A.; Henning, Th.; Beuther, H.

2015-09-01

We present the first study of the relationship between the column density distribution of molecular clouds within nearby Galactic spiral arms and their evolutionary status as measured from their stellar content. We analyze a sample of 195 molecular clouds located at distances below 5.5 kpc, identified from the ATLASGAL 870 μm data. We define three evolutionary classes within this sample: starless clumps, star-forming clouds with associated young stellar objects, and clouds associated with H ii regions. We find that the N(H2) probability density functions (N-PDFs) of these three classes of objects are clearly different: the N-PDFs of starless clumps are narrowest and close to log-normal in shape, while star-forming clouds and H ii regions exhibit a power-law shape over a wide range of column densities and log-normal-like components only at low column densities. We use the N-PDFs to estimate the evolutionary time-scales of the three classes of objects based on a simple analytic model from literature. Finally, we show that the integral of the N-PDFs, the dense gas mass fraction, depends on the total mass of the regions as measured by ATLASGAL: more massive clouds contain greater relative amounts of dense gas across all evolutionary classes. Appendices are available in electronic form at http://www.aanda.org

Evolutionary dynamics of a smoothed war of attrition game.

PubMed

Iyer, Swami; Killingback, Timothy

2016-05-07

In evolutionary game theory the War of Attrition game is intended to model animal contests which are decided by non-aggressive behavior, such as the length of time that a participant will persist in the contest. The classical War of Attrition game assumes that no errors are made in the implementation of an animal׳s strategy. However, it is inevitable in reality that such errors must sometimes occur. Here we introduce an extension of the classical War of Attrition game which includes the effect of errors in the implementation of an individual׳s strategy. This extension of the classical game has the important feature that the payoff is continuous, and as a consequence admits evolutionary behavior that is fundamentally different from that possible in the original game. We study the evolutionary dynamics of this new game in well-mixed populations both analytically using adaptive dynamics and through individual-based simulations, and show that there are a variety of possible outcomes, including simple monomorphic or dimorphic configurations which are evolutionarily stable and cannot occur in the classical War of Attrition game. In addition, we study the evolutionary dynamics of this extended game in a variety of spatially and socially structured populations, as represented by different complex network topologies, and show that similar outcomes can also occur in these situations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Asymmetric ecological conditions favor Red-Queen type of continued evolution over stasis.

PubMed

Nordbotten, Jan Martin; Stenseth, Nils C

2016-02-16

Four decades ago, Leigh Van Valen presented the Red Queen's hypothesis to account for evolution of species within a multispecies ecological community [Van Valen L (1973) Evol Theory 1(1):1-30]. The overall conclusion of Van Valen's analysis was that evolution would continue even in the absence of abiotic perturbations. Stenseth and Maynard Smith presented in 1984 [Stenseth NC, Maynard Smith J (1984) Evolution 38(4):870-880] a model for the Red Queen's hypothesis showing that both Red-Queen type of continuous evolution and stasis could result from a model with biotically driven evolution. However, although that contribution demonstrated that both evolutionary outcomes were possible, it did not identify which ecological conditions would lead to each of these evolutionary outcomes. Here, we provide, using a simple, yet general population-biologically founded eco-evolutionary model, such analytically derived conditions: Stasis will predominantly emerge whenever the ecological system contains only symmetric ecological interactions, whereas both Red-Queen and stasis type of evolution may result if the ecological interactions are asymmetrical, and more likely so with increasing degree of asymmetry in the ecological system (i.e., the more trophic interactions, host-pathogen interactions, and the like there are [i.e., +/- type of ecological interactions as well as asymmetric competitive (-/-) and mutualistic (+/+) ecological interactions]). In the special case of no between-generational genetic variance, our results also predict dynamics within these types of purely ecological systems.

A Large Stellar Evolution Database for Population Synthesis Studies. I. Scaled Solar Models and Isochrones

NASA Astrophysics Data System (ADS)

Pietrinferni, Adriano; Cassisi, Santi; Salaris, Maurizio; Castelli, Fiorella

2004-09-01

We present a large and updated stellar evolution database for low-, intermediate-, and high-mass stars in a wide metallicity range, suitable for studying Galactic and extragalactic simple and composite stellar populations using population synthesis techniques. The stellar mass range is between ~0.5 and 10 Msolar with a fine mass spacing. The metallicity [Fe/H] comprises 10 values ranging from -2.27 to 0.40, with a scaled solar metal distribution. The initial He mass fraction ranges from Y=0.245, for the more metal-poor composition, up to 0.303 for the more metal-rich one, with ΔY/ΔZ~1.4. For each adopted chemical composition, the evolutionary models have been computed without (canonical models) and with overshooting from the Schwarzschild boundary of the convective cores during the central H-burning phase. Semiconvection is included in the treatment of core convection during the He-burning phase. The whole set of evolutionary models can be used to compute isochrones in a wide age range, from ~30 Myr to ~15 Gyr. Both evolutionary models and isochrones are available in several observational planes, employing an updated set of bolometric corrections and color-Teff relations computed for this project. The number of points along the models and the resulting isochrones is selected in such a way that interpolation for intermediate metallicities not contained in the grid is straightforward; a simple quadratic interpolation produces results of sufficient accuracy for population synthesis applications.We compare our isochrones with results from a series of widely used stellar evolution databases and perform some empirical tests for the reliability of our models. Since this work is devoted to scaled solar chemical compositions, we focus our attention on the Galactic disk stellar populations, employing multicolor photometry of unevolved field main-sequence stars with precise Hipparcos parallaxes, well-studied open clusters, and one eclipsing binary system with precise measurements of masses, radii, and [Fe/H] of both components. We find that the predicted metallicity dependence of the location of the lower, unevolved main sequence in the color magnitude diagram (CMD) appears in satisfactory agreement with empirical data. When comparing our models with CMDs of selected, well-studied, open clusters, once again we were able to properly match the whole observed evolutionary sequences by assuming cluster distance and reddening estimates in satisfactory agreement with empirical evaluations of these quantities. In general, models including overshooting during the H-burning phase provide a better match to the observations, at least for ages below ~4 Gyr. At [Fe/H] around solar and higher ages (i.e., smaller convective cores) before the onset of radiative cores, the selected efficiency of core overshooting may be too high in our model, as well as in various other models in the literature. Since we also provide canonical models, the reader is strongly encouraged to always compare the results from both sets in this critical age range.

Mean-Potential Law in Evolutionary Games

NASA Astrophysics Data System (ADS)

Nałecz-Jawecki, Paweł; Miekisz, Jacek

2018-01-01

The Letter presents a novel way to connect random walks, stochastic differential equations, and evolutionary game theory. We introduce a new concept of a potential function for discrete-space stochastic systems. It is based on a correspondence between one-dimensional stochastic differential equations and random walks, which may be exact not only in the continuous limit but also in finite-state spaces. Our method is useful for computation of fixation probabilities in discrete stochastic dynamical systems with two absorbing states. We apply it to evolutionary games, formulating two simple and intuitive criteria for evolutionary stability of pure Nash equilibria in finite populations. In particular, we show that the 1 /3 law of evolutionary games, introduced by Nowak et al. [Nature, 2004], follows from a more general mean-potential law.

Energy and time determine scaling in biological and computer designs

PubMed Central

Bezerra, George; Edwards, Benjamin; Brown, James; Forrest, Stephanie

2016-01-01

Metabolic rate in animals and power consumption in computers are analogous quantities that scale similarly with size. We analyse vascular systems of mammals and on-chip networks of microprocessors, where natural selection and human engineering, respectively, have produced systems that minimize both energy dissipation and delivery times. Using a simple network model that simultaneously minimizes energy and time, our analysis explains empirically observed trends in the scaling of metabolic rate in mammals and power consumption and performance in microprocessors across several orders of magnitude in size. Just as the evolutionary transitions from unicellular to multicellular animals in biology are associated with shifts in metabolic scaling, our model suggests that the scaling of power and performance will change as computer designs transition to decentralized multi-core and distributed cyber-physical systems. More generally, a single energy–time minimization principle may govern the design of many complex systems that process energy, materials and information. This article is part of the themed issue ‘The major synthetic evolutionary transitions’. PMID:27431524

Assessment of Masonry Buildings Subjected to Landslide-Induced Settlements: From Load Path Method to Evolutionary Optimization Method

NASA Astrophysics Data System (ADS)

Palmisano, Fabrizio; Elia, Angelo

2017-10-01

One of the main difficulties, when dealing with landslide structural vulnerability, is the diagnosis of the causes of crack patterns. This is also due to the excessive complexity of models based on classical structural mechanics that makes them inappropriate especially when there is the necessity to perform a rapid vulnerability assessment at the territorial scale. This is why, a new approach, based on a ‘simple model’ (i.e. the Load Path Method, LPM), has been proposed by Palmisano and Elia for the interpretation of the behaviour of masonry buildings subjected to landslide-induced settlements. However, the LPM is very useful for rapidly finding the 'most plausible solution' instead of the exact solution. To find the solution, optimization algorithms are necessary. In this scenario, this article aims to show how the Bidirectional Evolutionary Structural Optimization method by Huang and Xie, can be very useful to optimize the strut-and-tie models obtained by using the Load Path Method.

Morphomechanics and Developmental Constraints in the Evolution of Ammonites Shell Form.

PubMed

Erlich, Alexander; Moulton, Derek E; Goriely, Alain; Chirat, Regis

2016-11-01

The idea that physical processes involved in biological development underlie morphogenetic rules and channel morphological evolution has been central to the rise of evolutionary developmental biology. Here, we explore this idea in the context of seashell morphogenesis. We show that a morphomechanical model predicts the effects of variations in shell shape on the ornamental pattern in ammonites, a now extinct group of cephalopods with external chambered shell. Our model shows that several seemingly unrelated characteristics of synchronous, ontogenetic, intraspecific, and evolutionary variations in ornamental patterns among various ammonite species may all be understood from the fact that the mechanical forces underlying the oscillatory behavior of the shell secreting system scale with the cross-sectional curvature of the shell aperture. This simple morphogenetic rule, emerging from biophysical interactions during shell formation, introduced a non-random component in the production of phenotypic variation and channeled the morphological evolution of ammonites over millions of years. As such, it provides a paradigm for the concept of "developmental constraints." © 2016 Wiley Periodicals, Inc.

Energy and time determine scaling in biological and computer designs.

PubMed

Moses, Melanie; Bezerra, George; Edwards, Benjamin; Brown, James; Forrest, Stephanie

2016-08-19

Metabolic rate in animals and power consumption in computers are analogous quantities that scale similarly with size. We analyse vascular systems of mammals and on-chip networks of microprocessors, where natural selection and human engineering, respectively, have produced systems that minimize both energy dissipation and delivery times. Using a simple network model that simultaneously minimizes energy and time, our analysis explains empirically observed trends in the scaling of metabolic rate in mammals and power consumption and performance in microprocessors across several orders of magnitude in size. Just as the evolutionary transitions from unicellular to multicellular animals in biology are associated with shifts in metabolic scaling, our model suggests that the scaling of power and performance will change as computer designs transition to decentralized multi-core and distributed cyber-physical systems. More generally, a single energy-time minimization principle may govern the design of many complex systems that process energy, materials and information.This article is part of the themed issue 'The major synthetic evolutionary transitions'. © 2016 The Author(s).

Genomics and the making of yeast biodiversity.

PubMed

Hittinger, Chris Todd; Rokas, Antonis; Bai, Feng-Yan; Boekhout, Teun; Gonçalves, Paula; Jeffries, Thomas W; Kominek, Jacek; Lachance, Marc-André; Libkind, Diego; Rosa, Carlos A; Sampaio, José Paulo; Kurtzman, Cletus P

2015-12-01

Yeasts are unicellular fungi that do not form fruiting bodies. Although the yeast lifestyle has evolved multiple times, most known species belong to the subphylum Saccharomycotina (syn. Hemiascomycota, hereafter yeasts). This diverse group includes the premier eukaryotic model system, Saccharomyces cerevisiae; the common human commensal and opportunistic pathogen, Candida albicans; and over 1000 other known species (with more continuing to be discovered). Yeasts are found in every biome and continent and are more genetically diverse than angiosperms or chordates. Ease of culture, simple life cycles, and small genomes (∼10-20Mbp) have made yeasts exceptional models for molecular genetics, biotechnology, and evolutionary genomics. Here we discuss recent developments in understanding the genomic underpinnings of the making of yeast biodiversity, comparing and contrasting natural and human-associated evolutionary processes. Only a tiny fraction of yeast biodiversity and metabolic capabilities has been tapped by industry and science. Expanding the taxonomic breadth of deep genomic investigations will further illuminate how genome function evolves to encode their diverse metabolisms and ecologies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Coevolving memetic algorithms: a review and progress report.

PubMed

Smith, Jim E

2007-02-01

Coevolving memetic algorithms are a family of metaheuristic search algorithms in which a rule-based representation of local search (LS) is coadapted alongside candidate solutions within a hybrid evolutionary system. Simple versions of these systems have been shown to outperform other nonadaptive memetic and evolutionary algorithms on a range of problems. This paper presents a rationale for such systems and places them in the context of other recent work on adaptive memetic algorithms. It then proposes a general structure within which a population of LS algorithms can be evolved in tandem with the solutions to which they are applied. Previous research started with a simple self-adaptive system before moving on to more complex models. Results showed that the algorithm was able to discover and exploit certain forms of structure and regularities within the problems. This "metalearning" of problem features provided a means of creating highly scalable algorithms. This work is briefly reviewed to highlight some of the important findings and behaviors exhibited. Based on this analysis, new results are then presented from systems with more flexible representations, which, again, show significant improvements. Finally, the current state of, and future directions for, research in this area is discussed.

iACP-GAEnsC: Evolutionary genetic algorithm based ensemble classification of anticancer peptides by utilizing hybrid feature space.

PubMed

Akbar, Shahid; Hayat, Maqsood; Iqbal, Muhammad; Jan, Mian Ahmad

2017-06-01

Cancer is a fatal disease, responsible for one-quarter of all deaths in developed countries. Traditional anticancer therapies such as, chemotherapy and radiation, are highly expensive, susceptible to errors and ineffective techniques. These conventional techniques induce severe side-effects on human cells. Due to perilous impact of cancer, the development of an accurate and highly efficient intelligent computational model is desirable for identification of anticancer peptides. In this paper, evolutionary intelligent genetic algorithm-based ensemble model, 'iACP-GAEnsC', is proposed for the identification of anticancer peptides. In this model, the protein sequences are formulated, using three different discrete feature representation methods, i.e., amphiphilic Pseudo amino acid composition, g-Gap dipeptide composition, and Reduce amino acid alphabet composition. The performance of the extracted feature spaces are investigated separately and then merged to exhibit the significance of hybridization. In addition, the predicted results of individual classifiers are combined together, using optimized genetic algorithm and simple majority technique in order to enhance the true classification rate. It is observed that genetic algorithm-based ensemble classification outperforms than individual classifiers as well as simple majority voting base ensemble. The performance of genetic algorithm-based ensemble classification is highly reported on hybrid feature space, with an accuracy of 96.45%. In comparison to the existing techniques, 'iACP-GAEnsC' model has achieved remarkable improvement in terms of various performance metrics. Based on the simulation results, it is observed that 'iACP-GAEnsC' model might be a leading tool in the field of drug design and proteomics for researchers. Copyright © 2017 Elsevier B.V. All rights reserved.

J.A. Schumpeter and T.B. Veblen on economic evolution: the dichotomy between statics and dynamics

PubMed Central

Schütz, Marlies; Rainer, Andreas

2016-01-01

Abstract At present, the discussion on the dichotomy between statics and dynamics is resolved by concentrating on its mathematical meaning. Yet, a simple formalisation masks the underlying methodological discussion. Overcoming this limitation, the paper discusses Schumpeter's and Veblen's viewpoint on dynamic economic systems as systems generating change from within. It contributes to an understanding on their ideas of how economics could become an evolutionary science and on their contributions to elaborate an evolutionary economics. It confronts Schumpeter's with Veblen's perspective on evolutionary economics and provides insight into their evolutionary economic theorising by discussing their ideas on the evolution of capitalism. PMID:28057981

A Simple General Model of Evolutionary Dynamics

NASA Astrophysics Data System (ADS)

Thurner, Stefan

Evolution is a process in which some variations that emerge within a population (of, e.g., biological species or industrial goods) get selected, survive, and proliferate, whereas others vanish. Survival probability, proliferation, or production rates are associated with the "fitness" of a particular variation. We argue that the notion of fitness is an a posteriori concept in the sense that one can assign higher fitness to species or goods that survive but one can generally not derive or predict fitness per se. Whereas proliferation rates can be measured, fitness landscapes, that is, the inter-dependence of proliferation rates, cannot. For this reason we think that in a physical theory of evolution such notions should be avoided. Here we review a recent quantitative formulation of evolutionary dynamics that provides a framework for the co-evolution of species and their fitness landscapes (Thurner et al., 2010, Physica A 389, 747; Thurner et al., 2010, New J. Phys. 12, 075029; Klimek et al., 2009, Phys. Rev. E 82, 011901 (2010). The corresponding model leads to a generic evolutionary dynamics characterized by phases of relative stability in terms of diversity, followed by phases of massive restructuring. These dynamical modes can be interpreted as punctuated equilibria in biology, or Schumpeterian business cycles (Schumpeter, 1939, Business Cycles, McGraw-Hill, London) in economics. We show that phase transitions that separate phases of high and low diversity can be approximated surprisingly well by mean-field methods. We demonstrate that the mathematical framework is suited to understand systemic properties of evolutionary systems, such as their proneness to collapse, or their potential for diversification. The framework suggests that evolutionary processes are naturally linked to self-organized criticality and to properties of production matrices, such as their eigenvalue spectra. Even though the model is phrased in general terms it is also practical in the sense that it's predictions can be used to understand a series of experimental data ranging from the fossil record to macroeconomic indices.

Cliff-edge model of obstetric selection in humans.

PubMed

Mitteroecker, Philipp; Huttegger, Simon M; Fischer, Barbara; Pavlicev, Mihaela

2016-12-20

The strikingly high incidence of obstructed labor due to the disproportion of fetal size and the mother's pelvic dimensions has puzzled evolutionary scientists for decades. Here we propose that these high rates are a direct consequence of the distinct characteristics of human obstetric selection. Neonatal size relative to the birth-relevant maternal dimensions is highly variable and positively associated with reproductive success until it reaches a critical value, beyond which natural delivery becomes impossible. As a consequence, the symmetric phenotype distribution cannot match the highly asymmetric, cliff-edged fitness distribution well: The optimal phenotype distribution that maximizes population mean fitness entails a fraction of individuals falling beyond the "fitness edge" (i.e., those with fetopelvic disproportion). Using a simple mathematical model, we show that weak directional selection for a large neonate, a narrow pelvic canal, or both is sufficient to account for the considerable incidence of fetopelvic disproportion. Based on this model, we predict that the regular use of Caesarean sections throughout the last decades has led to an evolutionary increase of fetopelvic disproportion rates by 10 to 20%.

EMBEDDED LENSING TIME DELAYS, THE FERMAT POTENTIAL, AND THE INTEGRATED SACHS–WOLFE EFFECT

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

Chen, Bin; Kantowski, Ronald; Dai, Xinyu, E-mail: bchen3@fsu.edu

2015-05-01

We derive the Fermat potential for a spherically symmetric lens embedded in a Friedman–Lemaître–Robertson–Walker cosmology and use it to investigate the late-time integrated Sachs–Wolfe (ISW) effect, i.e., secondary temperature fluctuations in the cosmic microwave background (CMB) caused by individual large-scale clusters and voids. We present a simple analytical expression for the temperature fluctuation in the CMB across such a lens as a derivative of the lens’ Fermat potential. This formalism is applicable to both linear and nonlinear density evolution scenarios, to arbitrarily large density contrasts, and to all open and closed background cosmologies. It is much simpler to use andmore » makes the same predictions as conventional approaches. In this approach the total temperature fluctuation can be split into a time-delay part and an evolutionary part. Both parts must be included for cosmic structures that evolve and both can be equally important. We present very simple ISW models for cosmic voids and galaxy clusters to illustrate the ease of use of our formalism. We use the Fermat potentials of simple cosmic void models to compare predicted ISW effects with those recently extracted from WMAP and Planck data by stacking large cosmic voids using the aperture photometry method. If voids in the local universe with large density contrasts are no longer evolving we find that the time delay contribution alone predicts values consistent with the measurements. However, we find that for voids still evolving linearly, the evolutionary contribution cancels a significant part of the time delay contribution and results in predicted signals that are much smaller than recently observed.« less

Evolutionary response when selection and genetic variation covary across environments.

PubMed

Wood, Corlett W; Brodie, Edmund D

2016-10-01

Although models of evolution usually assume that the strength of selection on a trait and the expression of genetic variation in that trait are independent, whenever the same ecological factor impacts both parameters, a correlation between the two may arise that accelerates trait evolution in some environments and slows it in others. Here, we address the evolutionary consequences and ecological causes of a correlation between selection and expressed genetic variation. Using a simple analytical model, we show that the correlation has a modest effect on the mean evolutionary response and a large effect on its variance, increasing among-population or among-generation variation in the response when positive, and diminishing variation when negative. We performed a literature review to identify the ecological factors that influence selection and expressed genetic variation across traits. We found that some factors - temperature and competition - are unlikely to generate the correlation because they affected one parameter more than the other, and identified others - most notably, environmental novelty - that merit further investigation because little is known about their impact on one of the two parameters. We argue that the correlation between selection and genetic variation deserves attention alongside other factors that promote or constrain evolution in heterogeneous landscapes. © 2016 John Wiley & Sons Ltd/CNRS.

Crossover between structured and well-mixed networks in an evolutionary prisoner's dilemma game

NASA Astrophysics Data System (ADS)

Dai, Qionglin; Cheng, Hongyan; Li, Haihong; Li, Yuting; Zhang, Mei; Yang, Junzhong

2011-07-01

In a spatial evolutionary prisoner’s dilemma game (PDG), individuals interact with their neighbors and update their strategies according to some rules. As is well known, cooperators are destined to become extinct in a well-mixed population, whereas they could emerge and be sustained on a structured network. In this work, we introduce a simple model to investigate the crossover between a structured network and a well-mixed one in an evolutionary PDG. In the model, each link j is designated a rewiring parameter τj, which defines the time interval between two successive rewiring events for link j. By adjusting the rewiring parameter τ (the mean time interval for any link in the network), we could change a structured network into a well-mixed one. For the link rewiring events, three situations are considered: one synchronous situation and two asynchronous situations. Simulation results show that there are three regimes of τ: large τ where the density of cooperators ρc rises to ρc,∞ (the value of ρc for the case without link rewiring), small τ where the mean-field description for a well-mixed network is applicable, and moderate τ where the crossover between a structured network and a well-mixed one happens.

Dynamic Adaptive Neural Network Arrays: A Neuromorphic Architecture

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

Disney, Adam; Reynolds, John

2015-01-01

Dynamic Adaptive Neural Network Array (DANNA) is a neuromorphic hardware implementation. It differs from most other neuromorphic projects in that it allows for programmability of structure, and it is trained or designed using evolutionary optimization. This paper describes the DANNA structure, how DANNA is trained using evolutionary optimization, and an application of DANNA to a very simple classification task.

The evolution of reciprocity in sizable human groups.

PubMed

Rothschild, Casey G

2009-04-21

The scale and complexity of human cooperation is an important and unresolved evolutionary puzzle. This article uses the finitely repeated n person Prisoners' Dilemma game to illustrate how sapience can greatly enhance group-selection effects and lead to the evolutionary stability of cooperation in large groups. This affords a simple and direct explanation of the human "exception".

More memory under evolutionary learning may lead to chaos

NASA Astrophysics Data System (ADS)

Diks, Cees; Hommes, Cars; Zeppini, Paolo

2013-02-01

We show that an increase of memory of past strategy performance in a simple agent-based innovation model, with agents switching between costly innovation and cheap imitation, can be quantitatively stabilising while at the same time qualitatively destabilising. As memory in the fitness measure increases, the amplitude of price fluctuations decreases, but at the same time a bifurcation route to chaos may arise. The core mechanism leading to the chaotic behaviour in this model with strategy switching is that the map obtained for the system with memory is a convex combination of an increasing linear function and a decreasing non-linear function.

Self-organized modularization in evolutionary algorithms.

PubMed

Dauscher, Peter; Uthmann, Thomas

2005-01-01

The principle of modularization has proven to be extremely successful in the field of technical applications and particularly for Software Engineering purposes. The question to be answered within the present article is whether mechanisms can also be identified within the framework of Evolutionary Computation that cause a modularization of solutions. We will concentrate on processes, where modularization results only from the typical evolutionary operators, i.e. selection and variation by recombination and mutation (and not, e.g., from special modularization operators). This is what we call Self-Organized Modularization. Based on a combination of two formalizations by Radcliffe and Altenberg, some quantitative measures of modularity are introduced. Particularly, we distinguish Built-in Modularity as an inherent property of a genotype and Effective Modularity, which depends on the rest of the population. These measures can easily be applied to a wide range of present Evolutionary Computation models. It will be shown, both theoretically and by simulation, that under certain conditions, Effective Modularity (as defined within this paper) can be a selection factor. This causes Self-Organized Modularization to take place. The experimental observations emphasize the importance of Effective Modularity in comparison with Built-in Modularity. Although the experimental results have been obtained using a minimalist toy model, they can lead to a number of consequences for existing models as well as for future approaches. Furthermore, the results suggest a complex self-amplification of highly modular equivalence classes in the case of respected relations. Since the well-known Holland schemata are just the equivalence classes of respected relations in most Simple Genetic Algorithms, this observation emphasizes the role of schemata as Building Blocks (in comparison with arbitrary subsets of the search space).

New generation of elastic network models.

PubMed

López-Blanco, José Ramón; Chacón, Pablo

2016-04-01

The intrinsic flexibility of proteins and nucleic acids can be grasped from remarkably simple mechanical models of particles connected by springs. In recent decades, Elastic Network Models (ENMs) combined with Normal Model Analysis widely confirmed their ability to predict biologically relevant motions of biomolecules and soon became a popular methodology to reveal large-scale dynamics in multiple structural biology scenarios. The simplicity, robustness, low computational cost, and relatively high accuracy are the reasons behind the success of ENMs. This review focuses on recent advances in the development and application of ENMs, paying particular attention to combinations with experimental data. Successful application scenarios include large macromolecular machines, structural refinement, docking, and evolutionary conservation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Detection of timescales in evolving complex systems

PubMed Central

Darst, Richard K.; Granell, Clara; Arenas, Alex; Gómez, Sergio; Saramäki, Jari; Fortunato, Santo

2016-01-01

Most complex systems are intrinsically dynamic in nature. The evolution of a dynamic complex system is typically represented as a sequence of snapshots, where each snapshot describes the configuration of the system at a particular instant of time. This is often done by using constant intervals but a better approach would be to define dynamic intervals that match the evolution of the system’s configuration. To this end, we propose a method that aims at detecting evolutionary changes in the configuration of a complex system, and generates intervals accordingly. We show that evolutionary timescales can be identified by looking for peaks in the similarity between the sets of events on consecutive time intervals of data. Tests on simple toy models reveal that the technique is able to detect evolutionary timescales of time-varying data both when the evolution is smooth as well as when it changes sharply. This is further corroborated by analyses of several real datasets. Our method is scalable to extremely large datasets and is computationally efficient. This allows a quick, parameter-free detection of multiple timescales in the evolution of a complex system. PMID:28004820

Irrigation water allocation optimization using multi-objective evolutionary algorithm (MOEA) - a review

NASA Astrophysics Data System (ADS)

Fanuel, Ibrahim Mwita; Mushi, Allen; Kajunguri, Damian

2018-03-01

This paper analyzes more than 40 papers with a restricted area of application of Multi-Objective Genetic Algorithm, Non-Dominated Sorting Genetic Algorithm-II and Multi-Objective Differential Evolution (MODE) to solve the multi-objective problem in agricultural water management. The paper focused on different application aspects which include water allocation, irrigation planning, crop pattern and allocation of available land. The performance and results of these techniques are discussed. The review finds that there is a potential to use MODE to analyzed the multi-objective problem, the application is more significance due to its advantage of being simple and powerful technique than any Evolutionary Algorithm. The paper concludes with the hopeful new trend of research that demand effective use of MODE; inclusion of benefits derived from farm byproducts and production costs into the model.

Rethinking the dispersal of Homo sapiens out of Africa.

PubMed

Groucutt, Huw S; Petraglia, Michael D; Bailey, Geoff; Scerri, Eleanor M L; Parton, Ash; Clark-Balzan, Laine; Jennings, Richard P; Lewis, Laura; Blinkhorn, James; Drake, Nick A; Breeze, Paul S; Inglis, Robyn H; Devès, Maud H; Meredith-Williams, Matthew; Boivin, Nicole; Thomas, Mark G; Scally, Aylwyn

2015-01-01

Current fossil, genetic, and archeological data indicate that Homo sapiens originated in Africa in the late Middle Pleistocene. By the end of the Late Pleistocene, our species was distributed across every continent except Antarctica, setting the foundations for the subsequent demographic and cultural changes of the Holocene. The intervening processes remain intensely debated and a key theme in hominin evolutionary studies. We review archeological, fossil, environmental, and genetic data to evaluate the current state of knowledge on the dispersal of Homo sapiens out of Africa. The emerging picture of the dispersal process suggests dynamic behavioral variability, complex interactions between populations, and an intricate genetic and cultural legacy. This evolutionary and historical complexity challenges simple narratives and suggests that hybrid models and the testing of explicit hypotheses are required to understand the expansion of Homo sapiens into Eurasia. © 2015 Wiley Periodicals, Inc.

Emergence and dynamics of self-producing information niches as a step towards pre-evolutionary organization

PubMed Central

Carter, Richard J.; Wiesner, Karoline

2018-01-01

As a step towards understanding pre-evolutionary organization in non-genetic systems, we develop a model to investigate the emergence and dynamics of proto-autopoietic networks in an interacting population of simple information processing entities (automata). Our simulations indicate that dynamically stable strongly connected networks of mutually producing communication channels emerge under specific environmental conditions. We refer to these distinct organizational steady states as information niches. In each case, we measure the information content by the Shannon entropy, and determine the fitness landscape, robustness and transition pathways for information niches subjected to intermittent environmental perturbations under non-evolutionary conditions. By determining the information required to generate each niche, we show that niche transitions are only allowed if accompanied by an equal or increased level of information production that arises internally or via environmental perturbations that serve as an exogenous source of population diversification. Overall, our simulations show how proto-autopoietic networks of basic information processors form and compete, and under what conditions they persist over time or go extinct. These findings may be relevant to understanding how inanimate systems such as chemically communicating protocells can initiate the transition to living matter prior to the onset of contemporary evolutionary and genetic mechanisms. PMID:29343630

The σ law of evolutionary dynamics in community-structured population.

PubMed

Tang, Changbing; Li, Xiang; Cao, Lang; Zhan, Jingyuan

2012-08-07

Evolutionary game dynamics in finite populations provide a new framework to understand the selection of traits with frequency-dependent fitness. Recently, a simple but fundamental law of evolutionary dynamics, which we call σ law, describes how to determine the selection between two competing strategies: in most evolutionary processes with two strategies, A and B, strategy A is favored over B in weak selection if and only if σR+S>T+σP. This relationship holds for a wide variety of structured populations with mutation rate and weak selection under certain assumptions. In this paper, we propose a model of games based on a community-structured population and revisit this law under the Moran process. By calculating the average payoffs of A and B individuals with the method of effective sojourn time, we find that σ features not only the structured population characteristics, but also the reaction rate between individuals. That is to say, an interaction between two individuals are not uniform, and we can take σ as a reaction rate between any two individuals with the same strategy. We verify this viewpoint by the modified replicator equation with non-uniform interaction rates in a simplified version of the prisoner's dilemma game (PDG). Copyright © 2012 Elsevier Ltd. All rights reserved.

Using Massive Star Clusters in Merger Remnants To Provide Reference Colors of Intermediate-Age Stellar Populations

NASA Astrophysics Data System (ADS)

Goudfrooij, Paul

2009-07-01

Much current research in cosmology and galaxy formation relies on an accurate interpretation of colors of galaxies in terms of their evolutionary state, i.e., in terms of ages and metallicities. One particularly important topic is the ability to identify early-type galaxies at "intermediate" ages { 500 Myr - 5 Gyr}, i.e., the period between the end of star formation and half the age of the universe. Currently, integrated-light studies must rely on population synthesis models which rest upon spectral libraries of stars in the solar neighborhood. These models have a difficult time correctly incorporating short-lived evolutionary phases such as thermally pulsing AGB stars, which produce up to 80% of the flux in the near-IR in this age range. Furthermore, intermediate-age star clusters in the Local Group do not represent proper templates against which to calibrate population synthesis models in this age range, because their masses are too low to render the effect of stochastic fluctuations due to the number of bright RGB and AGB stars negligible. As a consequence, current population synthesis models have trouble reconciling the evolutionary state of high-redshift galaxies from optical versus near-IR colors. We propose a simple and effective solution to this issue, namely obtaining high-quality EMPIRICAL colors of massive globular clusters in galaxy merger remnants which span this important age range. These colors should serve as relevant references, both to identify intermediate-age objects in the local and distant universe and as calibrators for population synthesis modellers.

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.

Computer simulations of sympatric speciation in a simple food web

NASA Astrophysics Data System (ADS)

Luz-Burgoa, K.; Dell, Tony; de Oliveira, S. Moss

2005-07-01

Galapagos finches, have motivated much theoretical research aimed at understanding the processes associated with the formation of the species. Inspired by them, in this paper we investigate the process of sympatric speciation in a simple food web model. For that we modify the individual-based Penna model that has been widely used to study aging as well as other evolutionary processes. Initially, our web consists of a primary food source and a single herbivore species that feeds on this resource. Subsequently we introduce a predator that feeds on the herbivore. In both instances we manipulate directly a basal resource distribution and monitor the changes in the populations. Sympatric speciation is obtained for the top species in both cases, and our results suggest that the speciation velocity depends on how far up, in the food chain, the focus population is feeding. Simulations are done with three different sexual imprintinglike mechanisms, in order to discuss adaptation by natural selection.

Mean-Potential Law in Evolutionary Games.

PubMed

Nałęcz-Jawecki, Paweł; Miękisz, Jacek

2018-01-12

The Letter presents a novel way to connect random walks, stochastic differential equations, and evolutionary game theory. We introduce a new concept of a potential function for discrete-space stochastic systems. It is based on a correspondence between one-dimensional stochastic differential equations and random walks, which may be exact not only in the continuous limit but also in finite-state spaces. Our method is useful for computation of fixation probabilities in discrete stochastic dynamical systems with two absorbing states. We apply it to evolutionary games, formulating two simple and intuitive criteria for evolutionary stability of pure Nash equilibria in finite populations. In particular, we show that the 1/3 law of evolutionary games, introduced by Nowak et al. [Nature, 2004], follows from a more general mean-potential law.

A strategy with novel evolutionary features for the iterated prisoner's dilemma.

PubMed

Li, Jiawei; Kendall, Graham

2009-01-01

In recent iterated prisoner's dilemma tournaments, the most successful strategies were those that had identification mechanisms. By playing a predetermined sequence of moves and learning from their opponents' responses, these strategies managed to identify their opponents. We believe that these identification mechanisms may be very useful in evolutionary games. In this paper one such strategy, which we call collective strategy, is analyzed. Collective strategies apply a simple but efficient identification mechanism (that just distinguishes themselves from other strategies), and this mechanism allows them to only cooperate with their group members and defect against any others. In this way, collective strategies are able to maintain a stable population in evolutionary iterated prisoner's dilemma. By means of an invasion barrier, this strategy is compared with other strategies in evolutionary dynamics in order to demonstrate its evolutionary features. We also find that this collective behavior assists the evolution of cooperation in specific evolutionary environments.

Generating high-speed dynamic running gaits in a quadruped robot using an evolutionary search.

PubMed

Krasny, Darren P; Orin, David E

2004-08-01

Over the past several decades, there has been a considerable interest in investigating high-speed dynamic gaits for legged robots. While much research has been published, both in the biomechanics and engineering fields regarding the analysis of these gaits, no single study has adequately characterized the dynamics of high-speed running as can be achieved in a realistic, yet simple, robotic system. The goal of this paper is to find the most energy-efficient, natural, and unconstrained gallop that can be achieved using a simulated quadrupedal robot with articulated legs, asymmetric mass distribution, and compliant legs. For comparison purposes, we also implement the bound and canter. The model used here is planar, although we will show that it captures much of the predominant dynamic characteristics observed in animals. While it is not our goal to prove anything about biological locomotion, the dynamic similarities between the gaits we produce and those found in animals does indicate a similar underlying dynamic mechanism. Thus, we will show that achieving natural, efficient high-speed locomotion is possible even with a fairly simple robotic system. To generate the high-speed gaits, we use an efficient evolutionary algorithm called set-based stochastic optimization. This algorithm finds open-loop control parameters to generate periodic trajectories for the body. Several alternative methods are tested to generate periodic trajectories for the legs. The combined solutions found by the evolutionary search and the periodic-leg methods, over a range of speeds up to 10.0 m/s, reveal "biological" characteristics that are emergent properties of the underlying gaits.

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.

Comparison of the theoretical and real-world evolutionary potential of a genetic circuit

NASA Astrophysics Data System (ADS)

Razo-Mejia, M.; Boedicker, J. Q.; Jones, D.; DeLuna, A.; Kinney, J. B.; Phillips, R.

2014-04-01

With the development of next-generation sequencing technologies, many large scale experimental efforts aim to map genotypic variability among individuals. This natural variability in populations fuels many fundamental biological processes, ranging from evolutionary adaptation and speciation to the spread of genetic diseases and drug resistance. An interesting and important component of this variability is present within the regulatory regions of genes. As these regions evolve, accumulated mutations lead to modulation of gene expression, which may have consequences for the phenotype. A simple model system where the link between genetic variability, gene regulation and function can be studied in detail is missing. In this article we develop a model to explore how the sequence of the wild-type lac promoter dictates the fold-change in gene expression. The model combines single-base pair resolution maps of transcription factor and RNA polymerase binding energies with a comprehensive thermodynamic model of gene regulation. The model was validated by predicting and then measuring the variability of lac operon regulation in a collection of natural isolates. We then implement the model to analyze the sensitivity of the promoter sequence to the regulatory output, and predict the potential for regulation to evolve due to point mutations in the promoter region.

Asymmetric ecological conditions favor Red-Queen type of continued evolution over stasis

PubMed Central

Nordbotten, Jan Martin; Stenseth, Nils C.

2016-01-01

Four decades ago, Leigh Van Valen presented the Red Queen’s hypothesis to account for evolution of species within a multispecies ecological community [Van Valen L (1973) Evol Theory 1(1):1–30]. The overall conclusion of Van Valen’s analysis was that evolution would continue even in the absence of abiotic perturbations. Stenseth and Maynard Smith presented in 1984 [Stenseth NC, Maynard Smith J (1984) Evolution 38(4):870–880] a model for the Red Queen’s hypothesis showing that both Red-Queen type of continuous evolution and stasis could result from a model with biotically driven evolution. However, although that contribution demonstrated that both evolutionary outcomes were possible, it did not identify which ecological conditions would lead to each of these evolutionary outcomes. Here, we provide, using a simple, yet general population-biologically founded eco-evolutionary model, such analytically derived conditions: Stasis will predominantly emerge whenever the ecological system contains only symmetric ecological interactions, whereas both Red-Queen and stasis type of evolution may result if the ecological interactions are asymmetrical, and more likely so with increasing degree of asymmetry in the ecological system (i.e., the more trophic interactions, host–pathogen interactions, and the like there are [i.e., +/− type of ecological interactions as well as asymmetric competitive (−/−) and mutualistic (+/+) ecological interactions]). In the special case of no between-generational genetic variance, our results also predict dynamics within these types of purely ecological systems. PMID:26831108

Building a Shared Definitional Model of Long Duration Human Spaceflight

NASA Technical Reports Server (NTRS)

Arias, Diana; Orr, Martin; Whitmire, Alexandra; Leveton, Lauren; Sandoval, Luis

2012-01-01

Objective: To establish the need for a shared definitional model of long duration human spaceflight, that would provide a framework and vision to facilitate communication, research and practice In 1956, on the eve of human space travel, Hubertus Strughold first proposed a "simple classification of the present and future stages of manned flight" that identified key factors, risks and developmental stages for the evolutionary journey ahead. As we look to new destinations, we need a current shared working definitional model of long duration human space flight to help guide our path. Here we describe our preliminary findings and outline potential approaches for the future development of a definition and broader classification system

Exaggeration and suppression of iridescence: the evolution of two-dimensional butterfly structural colours

PubMed Central

Wickham, Shelley; Large, Maryanne C.J; Poladian, Leon; Jermiin, Lars S

2005-01-01

Many butterfly species possess ‘structural’ colour, where colour is due to optical microstructures found in the wing scales. A number of such structures have been identified in butterfly scales, including three variations on a simple multi-layer structure. In this study, we optically characterize examples of all three types of multi-layer structure, as found in 10 species. The optical mechanism of the suppression and exaggeration of the angle-dependent optical properties (iridescence) of these structures is described. In addition, we consider the phylogeny of the butterflies, and are thus able to relate the optical properties of the structures to their evolutionary development. By applying two different types of analysis, the mechanism of adaptation is addressed. A simple parsimony analysis, in which all evolutionary changes are given an equal weighting, suggests convergent evolution of one structure. A Dollo parsimony analysis, in which the evolutionary ‘cost’ of losing a structure is less than that of gaining it, implies that ‘latent’ structures can be reused. PMID:16849221

Simulation of the evolution of root water foraging strategies in dry and shallow soils

PubMed Central

Renton, Michael; Poot, Pieter

2014-01-01

Background and Aims The dynamic structural development of plants can be seen as a strategy for exploiting the limited resources available within their environment, and we would expect that evolution would lead to efficient strategies that reduce costs while maximizing resource acquisition. In particular, perennial species endemic to habitats with shallow soils in seasonally dry environments have been shown to have a specialized root system morphology that may enhance access to water resources in the underlying rock. This study aimed to explore these hypotheses by applying evolutionary algorithms to a functional–structural root growth model. Methods A simulation model of a plant's root system was developed, which represents the dynamics of water uptake and structural growth. The model is simple enough for evolutionary optimization to be computationally feasible, yet flexible enough to allow a range of structural development strategies to be explored. The model was combined with an evolutionary algorithm in order to investigate a case study habitat with a highly heterogeneous distribution of resources, both spatially and temporally – the situation of perennial plants occurring on shallow soils in seasonally dry environments. Evolution was simulated under two contrasting fitness criteria: (1) the ability to find wet cracks in underlying rock, and (2) maximizing above-ground biomass. Key Results The novel approach successfully resulted in the evolution of more efficient structural development strategies for both fitness criteria. Different rooting strategies evolved when different criteria were applied, and each evolved strategy made ecological sense in terms of the corresponding fitness criterion. Evolution selected for root system morphologies which matched those of real species from corresponding habitats. Conclusions Specialized root morphology with deeper rather than shallower lateral branching enhances access to water resources in underlying rock. More generally, the approach provides insights into both evolutionary processes and ecological costs and benefits of different plant growth strategies. PMID:24651371

Tree-Structured Digital Organisms Model

NASA Astrophysics Data System (ADS)

Suzuki, Teruhiko; Nobesawa, Shiho; Tahara, Ikuo

Tierra and Avida are well-known models of digital organisms. They describe a life process as a sequence of computation codes. A linear sequence model may not be the only way to describe a digital organism, though it is very simple for a computer-based model. Thus we propose a new digital organism model based on a tree structure, which is rather similar to the generic programming. With our model, a life process is a combination of various functions, as if life in the real world is. This implies that our model can easily describe the hierarchical structure of life, and it can simulate evolutionary computation through mutual interaction of functions. We verified our model by simulations that our model can be regarded as a digital organism model according to its definitions. Our model even succeeded in creating species such as viruses and parasites.

Evolutionary dynamics of incubation periods

PubMed Central

Ottino-Loffler, Bertrand; Scott, Jacob G

2017-01-01

The incubation period for typhoid, polio, measles, leukemia and many other diseases follows a right-skewed, approximately lognormal distribution. Although this pattern was discovered more than sixty years ago, it remains an open question to explain its ubiquity. Here, we propose an explanation based on evolutionary dynamics on graphs. For simple models of a mutant or pathogen invading a network-structured population of healthy cells, we show that skewed distributions of incubation periods emerge for a wide range of assumptions about invader fitness, competition dynamics, and network structure. The skewness stems from stochastic mechanisms associated with two classic problems in probability theory: the coupon collector and the random walk. Unlike previous explanations that rely crucially on heterogeneity, our results hold even for homogeneous populations. Thus, we predict that two equally healthy individuals subjected to equal doses of equally pathogenic agents may, by chance alone, show remarkably different time courses of disease. PMID:29266000

Uncertainty about social interactions leads to the evolution of social heuristics.

PubMed

van den Berg, Pieter; Wenseleers, Tom

2018-05-31

Individuals face many types of social interactions throughout their lives, but they often cannot perfectly assess what the consequences of their actions will be. Although it is known that unpredictable environments can profoundly affect the evolutionary process, it remains unclear how uncertainty about the nature of social interactions shapes the evolution of social behaviour. Here, we present an evolutionary simulation model, showing that even intermediate uncertainty leads to the evolution of simple cooperation strategies that disregard information about the social interaction ('social heuristics'). Moreover, our results show that the evolution of social heuristics can greatly affect cooperation levels, nearly doubling cooperation rates in our simulations. These results provide new insight into why social behaviour, including cooperation in humans, is often observed to be seemingly suboptimal. More generally, our results show that social behaviour that seems maladaptive when considered in isolation may actually be well-adapted to a heterogeneous and uncertain world.

Evolutionary dynamics of incubation periods.

PubMed

Ottino-Loffler, Bertrand; Scott, Jacob G; Strogatz, Steven H

2017-12-21

The incubation period for typhoid, polio, measles, leukemia and many other diseases follows a right-skewed, approximately lognormal distribution. Although this pattern was discovered more than sixty years ago, it remains an open question to explain its ubiquity. Here, we propose an explanation based on evolutionary dynamics on graphs. For simple models of a mutant or pathogen invading a network-structured population of healthy cells, we show that skewed distributions of incubation periods emerge for a wide range of assumptions about invader fitness, competition dynamics, and network structure. The skewness stems from stochastic mechanisms associated with two classic problems in probability theory: the coupon collector and the random walk. Unlike previous explanations that rely crucially on heterogeneity, our results hold even for homogeneous populations. Thus, we predict that two equally healthy individuals subjected to equal doses of equally pathogenic agents may, by chance alone, show remarkably different time courses of disease.

Neutrality and Robustness in Evo-Devo: Emergence of Lateral Inhibition

PubMed Central

Munteanu, Andreea; Solé, Ricard V.

2008-01-01

Embryonic development is defined by the hierarchical dynamical process that translates genetic information (genotype) into a spatial gene expression pattern (phenotype) providing the positional information for the correct unfolding of the organism. The nature and evolutionary implications of genotype–phenotype mapping still remain key topics in evolutionary developmental biology (evo-devo). We have explored here issues of neutrality, robustness, and diversity in evo-devo by means of a simple model of gene regulatory networks. The small size of the system allowed an exhaustive analysis of the entire fitness landscape and the extent of its neutrality. This analysis shows that evolution leads to a class of robust genetic networks with an expression pattern characteristic of lateral inhibition. This class is a repertoire of distinct implementations of this key developmental process, the diversity of which provides valuable clues about its underlying causal principles. PMID:19023404

Rapid Preliminary Design of Interplanetary Trajectories Using the Evolutionary Mission Trajectory Generator

NASA Technical Reports Server (NTRS)

Englander, Jacob

2016-01-01

This set of tutorial slides is an introduction to the Evolutionary Mission Trajectory Generator (EMTG), NASA Goddard Space Flight Center's autonomous tool for preliminary design of interplanetary missions. This slide set covers the basics of creating and post-processing simple interplanetary missions in EMTG using both high-thrust chemical and low-thrust electric propulsion along with a variety of operational constraints.

Evolutionary Influenced Interaction Pattern as Indicator for the Investigation of Natural Variants Causing Nephrogenic Diabetes Insipidus

PubMed Central

Labudde, Dirk

2015-01-01

The importance of short membrane sequence motifs has been shown in many works and emphasizes the related sequence motif analysis. Together with specific transmembrane helix-helix interactions, the analysis of interacting sequence parts is helpful for understanding the process during membrane protein folding and in retaining the three-dimensional fold. Here we present a simple high-throughput analysis method for deriving mutational information of interacting sequence parts. Applied on aquaporin water channel proteins, our approach supports the analysis of mutational variants within different interacting subsequences and finally the investigation of natural variants which cause diseases like, for example, nephrogenic diabetes insipidus. In this work we demonstrate a simple method for massive membrane protein data analysis. As shown, the presented in silico analyses provide information about interacting sequence parts which are constrained by protein evolution. We present a simple graphical visualization medium for the representation of evolutionary influenced interaction pattern pairs (EIPPs) adapted to mutagen investigations of aquaporin-2, a protein whose mutants are involved in the rare endocrine disorder known as nephrogenic diabetes insipidus, and membrane proteins in general. Furthermore, we present a new method to derive new evolutionary variations within EIPPs which can be used for further mutagen laboratory investigations. PMID:26180540

Evolutionary Influenced Interaction Pattern as Indicator for the Investigation of Natural Variants Causing Nephrogenic Diabetes Insipidus.

PubMed

Grunert, Steffen; Labudde, Dirk

2015-01-01

The importance of short membrane sequence motifs has been shown in many works and emphasizes the related sequence motif analysis. Together with specific transmembrane helix-helix interactions, the analysis of interacting sequence parts is helpful for understanding the process during membrane protein folding and in retaining the three-dimensional fold. Here we present a simple high-throughput analysis method for deriving mutational information of interacting sequence parts. Applied on aquaporin water channel proteins, our approach supports the analysis of mutational variants within different interacting subsequences and finally the investigation of natural variants which cause diseases like, for example, nephrogenic diabetes insipidus. In this work we demonstrate a simple method for massive membrane protein data analysis. As shown, the presented in silico analyses provide information about interacting sequence parts which are constrained by protein evolution. We present a simple graphical visualization medium for the representation of evolutionary influenced interaction pattern pairs (EIPPs) adapted to mutagen investigations of aquaporin-2, a protein whose mutants are involved in the rare endocrine disorder known as nephrogenic diabetes insipidus, and membrane proteins in general. Furthermore, we present a new method to derive new evolutionary variations within EIPPs which can be used for further mutagen laboratory investigations.

Environmental influences on the evolution of body size in Ammonoids

NASA Astrophysics Data System (ADS)

Hines, S.; Khong, C.; Pelagio, M.; Seixas, G.; Payne, J.

2012-12-01

A major debate in evolutionary biology and paleobiology focuses on the relative importance of ecological interactions between species versus changes in the physical environment in governing large-scale evolutionary patterns. Body size is among the most important traits of any organism, and so identifying the factors that influence size evolution can shed light on both the causes and consequences of many major evolutionary trends. However, the extent to which body size evolution over time can be explained by changes in the physical versus ecological context remains unknown. In this study, we examined body size evolution in ammonoids, an extinct group of marine cephalopods. We collected a representative body size for each genus from illustrated specimens in the Treatise on Invertebrate Paleontology. We then examined relative statistical support for six models of size evolution: random walk, directional trend, stasis, and environmental control by oxygen availability, temperature, and global sea level. No model is unambiguously supported over all others. Unbiased random walk was the best supported model (34%) and environmental control by atmospheric pO2 was the second best supported model (22%). Stasis received the least support (<<1%). Because we find pO2 to be inversely correlated with ammonoid size, we suspect that the observed correlation does not reflect a direct causal relationship. Overall, our results suggest that no single, simple model can be used to characterize the evolution of ammonoid size over the entire history of this clade. We speculate that controls on ammonoid size evolution varied through geological time, both due to long-term shifts in the ecological structure of marine communities and short-term perturbations associated with major extinction events.

Why a fly? Using Drosophila to understand the genetics of circadian rhythms and sleep.

PubMed

Hendricks, Joan C; Sehgal, Amita

2004-03-15

Among simple model systems, Drosophila has specific advantages for neurobehavioral investigations. It has been particularly useful for understanding the molecular basis of circadian rhythms. In addition, the genetics of fruit-fly sleep are beginning to develop. This review summarizes the current state of understanding of circadian rhythms and sleep in the fruit fly for the readers of Sleep. We note where information is available in mammals, for comparison with findings in fruit flies, to provide an evolutionary perspective, and we focus on recent findings and new questions. We propose that sleep-specific neural activity may alter cellular function and thus accomplish the restorative function or functions of sleep. In conclusion, we sound some cautionary notes about some of the complexities of working with this "simple" organism.

PTH Reloaded: A New Evolutionary Perspective

PubMed Central

Suarez-Bregua, Paula; Cal, Laura; Cañestro, Cristian; Rotllant, Josep

2017-01-01

The parathyroid hormone (PTH) family is a group of structurally-related secreted peptides involved in bone mineral homeostasis and multitude of developmental processes in vertebrates. These peptides mediate actions through PTH receptors (PTHRs), which belong to the transmembrane G protein-coupled receptor group. To date, genes encoding for PTH and PTHR have only been identified in chordates, suggesting that this signaling pathway may be an evolutionary innovation of our phylum. In vertebrates, we found up to six PTH and three PTHR different paralogs, varying in number between mammals and teleost fishes due to the different rounds of whole-genome duplication and specific gene losses suffered between the two groups of animals. The diversification of the PTH gene family has been accompanied by both functional divergence and convergence, making sometimes difficult the comparison between PTH peptides of teleosts and mammals. Here, we review the roles of all Pth peptides in fishes, and based on the evolutionary history of PTH paralogs, we propose a new and simple nomenclature from PTH1 to PTH4. Moreover, the recent characterization of the Pth4 in zebrafish allows us to consider the prominent role of the brain-to-bone signaling pathway in the regulation of bone development and homeostasis. Finally, comparison between PTH peptides of fish and mammals allows us to discuss an evolutionary model for PTH functions related to bone mineral balance during the vertebrate transition from an aquatic to a terrestrial environment. PMID:29062283

Multiple rings around Wolf-Rayet evolution

NASA Technical Reports Server (NTRS)

Marston, A. P.

1995-01-01

We present optical narrow-band imaging of multiple rings existing around galactic Wolf-Rayet (WR) stars. The existence of multiple rings of material around Wolf-Rayet stars clearly illustrates the various phases of evolution that massive stars go through. The objects presented here show evidence of a three stage evolution. O stars produce an outer ring with the cavity being partially filled by ejecta from a red supergiant of luminous blue variable phase. A wind from the Wolf-Rayet star then passes into the ejecta materials. A simple model is presented for this three stage evolution. Using observations of the size and dynamics of the rings allows estimates of time scales for each stage of the massive star evolution. These are consistent with recent theoretical evolutionary models. Mass estimates for the ejecta, from the model presented, are consistent with previous ring nebula mass estimates from IRAS data, showing a number of ring nebulae to have large masses, most of which must in be in the form of neutral material. Finally, we illustrate how further observations will allow the determination of many of the parameters of the evolution of massive stars such as total mass loss, average mass loss rates, stellar abundances, and total time spent in each evolutionary phase.

Estimating directional epistasis

PubMed Central

Le Rouzic, Arnaud

2014-01-01

Epistasis, i.e., the fact that gene effects depend on the genetic background, is a direct consequence of the complexity of genetic architectures. Despite this, most of the models used in evolutionary and quantitative genetics pay scant attention to genetic interactions. For instance, the traditional decomposition of genetic effects models epistasis as noise around the evolutionarily-relevant additive effects. Such an approach is only valid if it is assumed that there is no general pattern among interactions—a highly speculative scenario. Systematic interactions generate directional epistasis, which has major evolutionary consequences. In spite of its importance, directional epistasis is rarely measured or reported by quantitative geneticists, not only because its relevance is generally ignored, but also due to the lack of simple, operational, and accessible methods for its estimation. This paper describes conceptual and statistical tools that can be used to estimate directional epistasis from various kinds of data, including QTL mapping results, phenotype measurements in mutants, and artificial selection responses. As an illustration, I measured directional epistasis from a real-life example. I then discuss the interpretation of the estimates, showing how they can be used to draw meaningful biological inferences. PMID:25071828

In-silico studies of neutral drift for functional protein interaction networks

NASA Astrophysics Data System (ADS)

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

We have developed a minimal physically-motivated model of protein-protein interaction networks. Our system consists of two classes of enzymes, activators (e.g. kinases) and deactivators (e.g. phosphatases), and the enzyme-mediated activation/deactivation rates are determined by sequence-dependent binding strengths between enzymes and their targets. The network is evolved by introducing random point mutations in the binding sequences where we assume that each new mutation is either fixed or entirely lost. We apply this model to studies of neutral drift in networks that yield oscillatory dynamics, where we start, for example, with a relatively simple network and allow it to evolve by adding nodes and connections while requiring that dynamics be conserved. Our studies demonstrate both the importance of employing a sequence-based evolutionary scheme and the relative rapidity (in evolutionary time) for the redistribution of function over new nodes via neutral drift. Surprisingly, in addition to this redistribution time we discovered another much slower timescale for network evolution, reflecting hidden order in sequence space that we interpret in terms of sparsely connected domains.

Resolving the evolution of sterile worker castes: a window on the advantages and disadvantages of monogamy

PubMed Central

Nonacs, Peter

2014-01-01

Many social Hymenoptera species have morphologically sterile worker castes. It is proposed that the evolutionary routes to this obligate sterility must pass through a ‘monogamy window’, because inclusive fitness favours individuals retaining their reproductive totipotency unless they can rear full siblings. Simulated evolution of sterility, however, finds that ‘point of view’ is critically important. Monogamy is facilitating if sterility is expressed altruistically (i.e. workers defer reproduction to queens), but if sterility results from manipulation by mothers or siblings, monogamy may have no effect or lessen the likelihood of sterility. Overall, the model and data from facultatively eusocial bees suggest that eusociality and sterility are more likely to originate through manipulation than by altruism, casting doubt on a mandatory role for monogamy. Simple kin selection paradigms, such as Hamilton's rule, can also fail to account for significant evolutionary dynamics created by factors, such as population structure, group-level effects or non-random mating patterns. The easy remedy is to always validate apparently insightful predictions from Hamiltonian equations with life-history appropriate genetic models. PMID:24647729

Resolving the evolution of sterile worker castes: a window on the advantages and disadvantages of monogamy.

PubMed

Nonacs, Peter

2014-03-01

Many social Hymenoptera species have morphologically sterile worker castes. It is proposed that the evolutionary routes to this obligate sterility must pass through a 'monogamy window', because inclusive fitness favours individuals retaining their reproductive totipotency unless they can rear full siblings. Simulated evolution of sterility, however, finds that 'point of view' is critically important. Monogamy is facilitating if sterility is expressed altruistically (i.e. workers defer reproduction to queens), but if sterility results from manipulation by mothers or siblings, monogamy may have no effect or lessen the likelihood of sterility. Overall, the model and data from facultatively eusocial bees suggest that eusociality and sterility are more likely to originate through manipulation than by altruism, casting doubt on a mandatory role for monogamy. Simple kin selection paradigms, such as Hamilton's rule, can also fail to account for significant evolutionary dynamics created by factors, such as population structure, group-level effects or non-random mating patterns. The easy remedy is to always validate apparently insightful predictions from Hamiltonian equations with life-history appropriate genetic models.

Simple stochastic birth and death models of genome evolution: was there enough time for us to evolve?

PubMed

Karev, Georgy P; Wolf, Yuri I; Koonin, Eugene V

2003-10-12

The distributions of many genome-associated quantities, including the membership of paralogous gene families can be approximated with power laws. We are interested in developing mathematical models of genome evolution that adequately account for the shape of these distributions and describe the evolutionary dynamics of their formation. We show that simple stochastic models of genome evolution lead to power-law asymptotics of protein domain family size distribution. These models, called Birth, Death and Innovation Models (BDIM), represent a special class of balanced birth-and-death processes, in which domain duplication and deletion rates are asymptotically equal up to the second order. The simplest, linear BDIM shows an excellent fit to the observed distributions of domain family size in diverse prokaryotic and eukaryotic genomes. However, the stochastic version of the linear BDIM explored here predicts that the actual size of large paralogous families is reached on an unrealistically long timescale. We show that introduction of non-linearity, which might be interpreted as interaction of a particular order between individual family members, allows the model to achieve genome evolution rates that are much better compatible with the current estimates of the rates of individual duplication/loss events.

Stabilizing multicellularity through ratcheting

PubMed Central

Libby, Eric; Conlin, Peter L.; Kerr, Ben; Ratcliff, William C.

2016-01-01

The evolutionary transition to multicellularity probably began with the formation of simple undifferentiated cellular groups. Such groups evolve readily in diverse lineages of extant unicellular taxa, suggesting that there are few genetic barriers to this first key step. This may act as a double-edged sword: labile transitions between unicellular and multicellular states may facilitate the evolution of simple multicellularity, but reversion to a unicellular state may inhibit the evolution of increased complexity. In this paper, we examine how multicellular adaptations can act as evolutionary ‘ratchets’, limiting the potential for reversion to unicellularity. We consider a nascent multicellular lineage growing in an environment that varies between favouring multicellularity and favouring unicellularity. The first type of ratcheting mutations increase cell-level fitness in a multicellular context but are costly in a single-celled context, reducing the fitness of revertants. The second type of ratcheting mutations directly decrease the probability that a mutation will result in reversion (either as a pleiotropic consequence or via direct modification of switch rates). We show that both types of ratcheting mutations act to stabilize the multicellular state. We also identify synergistic effects between the two types of ratcheting mutations in which the presence of one creates the selective conditions favouring the other. Ratcheting mutations may play a key role in diverse evolutionary transitions in individuality, sustaining selection on the new higher-level organism by constraining evolutionary reversion. This article is part of the themed issue ‘The major synthetic evolutionary transitions’. PMID:27431522

Reticulate evolution and the human past: an anthropological perspective.

PubMed

Winder, Isabelle C; Winder, Nick P

2014-01-01

The evidence is mounting that reticulate (web-like) evolution has shaped the biological histories of many macroscopic plants and animals, including non-human primates closely related to Homo sapiens, but the implications of this non-hierarchical evolution for anthropological enquiry are not yet fully understood. When they are understood, the result may be a paradigm shift in evolutionary anthropology. This paper reviews the evidence for reticulated evolution in the non-human primates and human lineage. Then it makes the case for extrapolating this sort of patterning to Homo sapiens and other hominins and explores the implications this would have for research design, method and understandings of evolution in anthropology. Reticulation was significant in human evolutionary history and continues to influence societies today. Anthropologists and human scientists-whether working on ancient or modern populations-thus need to consider the implications of non-hierarchic evolution, particularly where molecular clocks, mathematical models and simplifying assumptions about evolutionary processes are used. This is not just a problem for palaeoanthropology. The simple fact of different mating systems among modern human groups, for example, may demand that more attention is paid to the potential for complexity in human genetic and cultural histories.

Cyclic dominance in evolutionary games: a review

PubMed Central

Szolnoki, Attila; Mobilia, Mauro; Jiang, Luo-Luo; Szczesny, Bartosz; Rucklidge, Alastair M.; Perc, Matjaž

2014-01-01

Rock is wrapped by paper, paper is cut by scissors and scissors are crushed by rock. This simple game is popular among children and adults to decide on trivial disputes that have no obvious winner, but cyclic dominance is also at the heart of predator–prey interactions, the mating strategy of side-blotched lizards, the overgrowth of marine sessile organisms and competition in microbial populations. Cyclical interactions also emerge spontaneously in evolutionary games entailing volunteering, reward, punishment, and in fact are common when the competing strategies are three or more, regardless of the particularities of the game. Here, we review recent advances on the rock–paper–scissors (RPS) and related evolutionary games, focusing, in particular, on pattern formation, the impact of mobility and the spontaneous emergence of cyclic dominance. We also review mean-field and zero-dimensional RPS models and the application of the complex Ginzburg–Landau equation, and we highlight the importance and usefulness of statistical physics for the successful study of large-scale ecological systems. Directions for future research, related, for example, to dynamical effects of coevolutionary rules and invasion reversals owing to multi-point interactions, are also outlined. PMID:25232048

Cyclic dominance in evolutionary games: a review.

PubMed

Szolnoki, Attila; Mobilia, Mauro; Jiang, Luo-Luo; Szczesny, Bartosz; Rucklidge, Alastair M; Perc, Matjaž

2014-11-06

Rock is wrapped by paper, paper is cut by scissors and scissors are crushed by rock. This simple game is popular among children and adults to decide on trivial disputes that have no obvious winner, but cyclic dominance is also at the heart of predator-prey interactions, the mating strategy of side-blotched lizards, the overgrowth of marine sessile organisms and competition in microbial populations. Cyclical interactions also emerge spontaneously in evolutionary games entailing volunteering, reward, punishment, and in fact are common when the competing strategies are three or more, regardless of the particularities of the game. Here, we review recent advances on the rock-paper-scissors (RPS) and related evolutionary games, focusing, in particular, on pattern formation, the impact of mobility and the spontaneous emergence of cyclic dominance. We also review mean-field and zero-dimensional RPS models and the application of the complex Ginzburg-Landau equation, and we highlight the importance and usefulness of statistical physics for the successful study of large-scale ecological systems. Directions for future research, related, for example, to dynamical effects of coevolutionary rules and invasion reversals owing to multi-point interactions, are also outlined. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

On the Evolution of the Cardiac Pacemaker

PubMed Central

Burkhard, Silja; van Eif, Vincent; Garric, Laurence; Christoffels, Vincent M.; Bakkers, Jeroen

2017-01-01

The rhythmic contraction of the heart is initiated and controlled by an intrinsic pacemaker system. Cardiac contractions commence at very early embryonic stages and coordination remains crucial for survival. The underlying molecular mechanisms of pacemaker cell development and function are still not fully understood. Heart form and function show high evolutionary conservation. Even in simple contractile cardiac tubes in primitive invertebrates, cardiac function is controlled by intrinsic, autonomous pacemaker cells. Understanding the evolutionary origin and development of cardiac pacemaker cells will help us outline the important pathways and factors involved. Key patterning factors, such as the homeodomain transcription factors Nkx2.5 and Shox2, and the LIM-homeodomain transcription factor Islet-1, components of the T-box (Tbx), and bone morphogenic protein (Bmp) families are well conserved. Here we compare the dominant pacemaking systems in various organisms with respect to the underlying molecular regulation. Comparative analysis of the pathways involved in patterning the pacemaker domain in an evolutionary context might help us outline a common fundamental pacemaker cell gene programme. Special focus is given to pacemaker development in zebrafish, an extensively used model for vertebrate development. Finally, we conclude with a summary of highly conserved key factors in pacemaker cell development and function. PMID:29367536

Morphogenesis and mechanostabilization of complex natural and 3D printed shapes

PubMed Central

Tiwary, Chandra Sekhar; Kishore, Sharan; Sarkar, Suman; Mahapatra, Debiprosad Roy; Ajayan, Pulickel M.; Chattopadhyay, Kamanio

2015-01-01

The natural selection and the evolutionary optimization of complex shapes in nature are closely related to their functions. Mechanostabilization of shape of biological structure via morphogenesis has several beautiful examples. With the help of simple mechanics-based modeling and experiments, we show an important causality between natural shape selection as evolutionary outcome and the mechanostabilization of seashells. The effect of biological growth on the mechanostabilization process is identified with examples of two natural shapes of seashells, one having a diametrically converging localization of stresses and the other having a helicoidally concentric localization of stresses. We demonstrate how the evolved shape enables predictable protection of soft body parts of the species. The effect of bioavailability of natural material is found to be a secondary factor compared to shape selectivity, where material microstructure only acts as a constraint to evolutionary optimization. This is confirmed by comparing the mechanostabilization behavior of three-dimensionally printed synthetic polymer structural shapes with that of natural seashells consisting of ceramic and protein. This study also highlights interesting possibilities in achieving a new design of structures made of ordinary materials which have bio-inspired optimization objectives. PMID:26601170

Self-organised criticality in the evolution of a thermodynamic model of rodent thermoregulatory huddling

PubMed Central

2017-01-01

A thermodynamic model of thermoregulatory huddling interactions between endotherms is developed. The model is presented as a Monte Carlo algorithm in which animals are iteratively exchanged between groups, with a probability of exchanging groups defined in terms of the temperature of the environment and the body temperatures of the animals. The temperature-dependent exchange of animals between groups is shown to reproduce a second-order critical phase transition, i.e., a smooth switch to huddling when the environment gets colder, as measured in recent experiments. A peak in the rate at which group sizes change, referred to as pup flow, is predicted at the critical temperature of the phase transition, consistent with a thermodynamic description of huddling, and with a description of the huddle as a self-organising system. The model was subjected to a simple evolutionary procedure, by iteratively substituting the physiologies of individuals that fail to balance the costs of thermoregulation (by huddling in groups) with the costs of thermogenesis (by contributing heat). The resulting tension between cooperative and competitive interactions was found to generate a phenomenon called self-organised criticality, as evidenced by the emergence of avalanches in fitness that propagate across many generations. The emergence of avalanches reveals how huddling can introduce correlations in fitness between individuals and thereby constrain evolutionary dynamics. Finally, a full agent-based model of huddling interactions is also shown to generate criticality when subjected to the same evolutionary pressures. The agent-based model is related to the Monte Carlo model in the way that a Vicsek model is related to an Ising model in statistical physics. Huddling therefore presents an opportunity to use thermodynamic theory to study an emergent adaptive animal behaviour. In more general terms, huddling is proposed as an ideal system for investigating the interaction between self-organisation and natural selection empirically. PMID:28141809

Evolution of resource cycling in ecosystems and individuals.

PubMed

Crombach, Anton; Hogeweg, Paulien

2009-06-01

Resource cycling is a defining process in the maintenance of the biosphere. Microbial communities, ranging from simple to highly diverse, play a crucial role in this process. Yet the evolutionary adaptation and speciation of micro-organisms have rarely been studied in the context of resource cycling. In this study, our basic questions are how does a community evolve its resource usage and how are resource cycles partitioned? We design a computational model in which a population of individuals evolves to take up nutrients and excrete waste. The waste of one individual is another's resource. Given a fixed amount of resources, this leads to resource cycles. We find that the shortest cycle dominates the ecological dynamics, and over evolutionary time its length is minimized. Initially a single lineage processes a long cycle of resources, later crossfeeding lineages arise. The evolutionary dynamics that follow are determined by the strength of indirect selection for resource cycling. We study indirect selection by changing the spatial setting and the strength of direct selection. If individuals are fixed at lattice sites or direct selection is low, indirect selection result in lineages that structure their local environment, leading to 'smart' individuals and stable patterns of resource dynamics. The individuals are good at cycling resources themselves and do this with a short cycle. On the other hand, if individuals randomly change position each time step, or direct selection is high, individuals are more prone to crossfeeding: an ecosystem based solution with turbulent resource dynamics, and individuals that are less capable of cycling resources themselves. In a baseline model of ecosystem evolution we demonstrate different eco-evolutionary trajectories of resource cycling. By varying the strength of indirect selection through the spatial setting and direct selection, the integration of information by the evolutionary process leads to qualitatively different results from individual smartness to cooperative community structures.

A method for inferring the rate of evolution of homologous characters that can potentially improve phylogenetic inference, resolve deep divergence and correct systematic biases.

PubMed

Cummins, Carla A; McInerney, James O

2011-12-01

Current phylogenetic methods attempt to account for evolutionary rate variation across characters in a matrix. This is generally achieved by the use of sophisticated evolutionary models, combined with dense sampling of large numbers of characters. However, systematic biases and superimposed substitutions make this task very difficult. Model adequacy can sometimes be achieved at the cost of adding large numbers of free parameters, with each parameter being optimized according to some criterion, resulting in increased computation times and large variances in the model estimates. In this study, we develop a simple approach that estimates the relative evolutionary rate of each homologous character. The method that we describe uses the similarity between characters as a proxy for evolutionary rate. In this article, we work on the premise that if the character-state distribution of a homologous character is similar to many other characters, then this character is likely to be relatively slowly evolving. If the character-state distribution of a homologous character is not similar to many or any of the rest of the characters in a data set, then it is likely to be the result of rapid evolution. We show that in some test cases, at least, the premise can hold and the inferences are robust. Importantly, the method does not use a "starting tree" to make the inference and therefore is tree independent. We demonstrate that this approach can work as well as a maximum likelihood (ML) approach, though the ML method needs to have a known phylogeny, or at least a very good estimate of that phylogeny. We then demonstrate some uses for this method of analysis, including the improvement in phylogeny reconstruction for both deep-level and recent relationships and overcoming systematic biases such as base composition bias. Furthermore, we compare this approach to two well-established methods for reweighting or removing characters. These other methods are tree-based and we show that they can be systematically biased. We feel this method can be useful for phylogeny reconstruction, understanding evolutionary rate variation, and for understanding selection variation on different characters.

On the Mass Distribution of Animal Species

NASA Astrophysics Data System (ADS)

Redner, Sidney; Clauset, Aaron; Schwab, David

2009-03-01

We develop a simple diffusion-reaction model to account for the broad and asymmetric distribution of adult body masses for species within related taxonomic groups. The model assumes three basic evolutionary features that control body mass: (i) a fixed lower limit that is set by metabolic constraints, (ii) a species extinction risk that is a weakly increasing function of body mass, and (iii) cladogenetic diffusion, in which daughter species have a slight tendency toward larger mass. The steady-state solution for the distribution of species masses in this model can be expressed in terms of the Airy function. This solution gives mass distributions that are in good agreement with data on 4002 terrestrial mammal species from the late Quaternary and 8617 extant bird species.

Evolution of phenotypic plasticity and environmental tolerance of a labile quantitative character in a fluctuating environment.

PubMed

Lande, R

2014-05-01

Quantitative genetic models of evolution of phenotypic plasticity are used to derive environmental tolerance curves for a population in a changing environment, providing a theoretical foundation for integrating physiological and community ecology with evolutionary genetics of plasticity and norms of reaction. Plasticity is modelled for a labile quantitative character undergoing continuous reversible development and selection in a fluctuating environment. If there is no cost of plasticity, a labile character evolves expected plasticity equalling the slope of the optimal phenotype as a function of the environment. This contrasts with previous theory for plasticity influenced by the environment at a critical stage of early development determining a constant adult phenotype on which selection acts, for which the expected plasticity is reduced by the environmental predictability over the discrete time lag between development and selection. With a cost of plasticity in a labile character, the expected plasticity depends on the cost and on the environmental variance and predictability averaged over the continuous developmental time lag. Environmental tolerance curves derived from this model confirm traditional assumptions in physiological ecology and provide new insights. Tolerance curve width increases with larger environmental variance, but can only evolve within a limited range. The strength of the trade-off between tolerance curve height and width depends on the cost of plasticity. Asymmetric tolerance curves caused by male sterility at high temperature are illustrated. A simple condition is given for a large transient increase in plasticity and tolerance curve width following a sudden change in average environment. © 2014 The Author. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

A coarse-grained biophysical model of sequence evolution and the population size dependence of the speciation rate

PubMed Central

Khatri, Bhavin S.; Goldstein, Richard A.

2015-01-01

Speciation is fundamental to understanding the huge diversity of life on Earth. Although still controversial, empirical evidence suggests that the rate of speciation is larger for smaller populations. Here, we explore a biophysical model of speciation by developing a simple coarse-grained theory of transcription factor-DNA binding and how their co-evolution in two geographically isolated lineages leads to incompatibilities. To develop a tractable analytical theory, we derive a Smoluchowski equation for the dynamics of binding energy evolution that accounts for the fact that natural selection acts on phenotypes, but variation arises from mutations in sequences; the Smoluchowski equation includes selection due to both gradients in fitness and gradients in sequence entropy, which is the logarithm of the number of sequences that correspond to a particular binding energy. This simple consideration predicts that smaller populations develop incompatibilities more quickly in the weak mutation regime; this trend arises as sequence entropy poises smaller populations closer to incompatible regions of phenotype space. These results suggest a generic coarse-grained approach to evolutionary stochastic dynamics, allowing realistic modelling at the phenotypic level. PMID:25936759

Simple biophysical model of tumor evasion from immune system control

NASA Astrophysics Data System (ADS)

D'Onofrio, Alberto; Ciancio, Armando

2011-09-01

The competitive nonlinear interplay between a tumor and the host's immune system is not only very complex but is also time-changing. A fundamental aspect of this issue is the ability of the tumor to slowly carry out processes that gradually allow it to become less harmed and less susceptible to recognition by the immune system effectors. Here we propose a simple epigenetic escape mechanism that adaptively depends on the interactions per time unit between cells of the two systems. From a biological point of view, our model is based on the concept that a tumor cell that has survived an encounter with a cytotoxic T-lymphocyte (CTL) has an information gain that it transmits to the other cells of the neoplasm. The consequence of this information increase is a decrease in both the probabilities of being killed and of being recognized by a CTL. We show that the mathematical model of this mechanism is formally equal to an evolutionary imitation game dynamics. Numerical simulations of transitory phases complement the theoretical analysis. Implications of the interplay between the above mechanisms and the delivery of immunotherapies are also illustrated.

Modeling individual effects in the Cormack-Jolly-Seber Model: A state-space formulation

USGS Publications Warehouse

Royle, J. Andrew

2008-01-01

In population and evolutionary biology, there exists considerable interest in individual heterogeneity in parameters of demographic models for open populations. However, flexible and practical solutions to the development of such models have proven to be elusive. In this article, I provide a state-space formulation of open population capture-recapture models with individual effects. The state-space formulation provides a generic and flexible framework for modeling and inference in models with individual effects, and it yields a practical means of estimation in these complex problems via contemporary methods of Markov chain Monte Carlo. A straightforward implementation can be achieved in the software package WinBUGS. I provide an analysis of a simple model with constant parameter detection and survival probability parameters. A second example is based on data from a 7-year study of European dippers, in which a model with year and individual effects is fitted.

Reduced Diversity of Life around Proxima Centauri and TRAPPIST-1

NASA Astrophysics Data System (ADS)

Lingam, Manasvi; Loeb, Abraham

2017-09-01

The recent discovery of potentially habitable exoplanets around Proxima Centauri and TRAPPIST-1 has attracted much attention due to their potential for hosting life. We delineate a simple model that accurately describes the evolution of biological diversity on Earth. Combining this model with constraints on atmospheric erosion and the maximal evolutionary timescale arising from the star’s lifetime, we arrive at two striking conclusions: (I) Earth-analogs orbiting low-mass M-dwarfs are unlikely to be inhabited, and (II) K-dwarfs and some G-type stars are potentially capable of hosting more complex biospheres than the Earth. Hence, future searches for biosignatures may have higher chances of success when targeting planets around K-dwarf stars.

Evolution of complex dynamics

NASA Astrophysics Data System (ADS)

Wilds, Roy; Kauffman, Stuart A.; Glass, Leon

2008-09-01

We study the evolution of complex dynamics in a model of a genetic regulatory network. The fitness is associated with the topological entropy in a class of piecewise linear equations, and the mutations are associated with changes in the logical structure of the network. We compare hill climbing evolution, in which only mutations that increase the fitness are allowed, with neutral evolution, in which mutations that leave the fitness unchanged are allowed. The simple structure of the fitness landscape enables us to estimate analytically the rates of hill climbing and neutral evolution. In this model, allowing neutral mutations accelerates the rate of evolutionary advancement for low mutation frequencies. These results are applicable to evolution in natural and technological systems.

Semantic wireless localization of WiFi terminals in smart buildings

NASA Astrophysics Data System (ADS)

Ahmadi, H.; Polo, A.; Moriyama, T.; Salucci, M.; Viani, F.

2016-06-01

The wireless localization of mobile terminals in indoor scenarios by means of a semantic interpretation of the environment is addressed in this work. A training-less approach based on the real-time calibration of a simple path loss model is proposed which combines (i) the received signal strength information measured by the wireless terminal and (ii) the topological features of the localization domain. A customized evolutionary optimization technique has been designed to estimate the optimal target position that fits the complex wireless indoor propagation and the semantic target-environment relation, as well. The proposed approach is experimentally validated in a real building area where the available WiFi network is opportunistically exploited for data collection. The presented results point out a reduction of the localization error obtained with the introduction of a very simple semantic interpretation of the considered scenario.

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…

Pattern formation in individual-based systems with time-varying parameters

NASA Astrophysics Data System (ADS)

Ashcroft, Peter; Galla, Tobias

2013-12-01

We study the patterns generated in finite-time sweeps across symmetry-breaking bifurcations in individual-based models. Similar to the well-known Kibble-Zurek scenario of defect formation, large-scale patterns are generated when model parameters are varied slowly, whereas fast sweeps produce a large number of small domains. The symmetry breaking is triggered by intrinsic noise, originating from the discrete dynamics at the microlevel. Based on a linear-noise approximation, we calculate the characteristic length scale of these patterns. We demonstrate the applicability of this approach in a simple model of opinion dynamics, a model in evolutionary game theory with a time-dependent fitness structure, and a model of cell differentiation. Our theoretical estimates are confirmed in simulations. In further numerical work, we observe a similar phenomenon when the symmetry-breaking bifurcation is triggered by population growth.

Selectionist and Evolutionary Approaches to Brain Function: A Critical Appraisal

PubMed Central

Fernando, Chrisantha; Szathmáry, Eörs; Husbands, Phil

2012-01-01

We consider approaches to brain dynamics and function that have been claimed to be Darwinian. These include Edelman’s theory of neuronal group selection, Changeux’s theory of synaptic selection and selective stabilization of pre-representations, Seung’s Darwinian synapse, Loewenstein’s synaptic melioration, Adam’s selfish synapse, and Calvin’s replicating activity patterns. Except for the last two, the proposed mechanisms are selectionist but not truly Darwinian, because no replicators with information transfer to copies and hereditary variation can be identified in them. All of them fit, however, a generalized selectionist framework conforming to the picture of Price’s covariance formulation, which deliberately was not specific even to selection in biology, and therefore does not imply an algorithmic picture of biological evolution. Bayesian models and reinforcement learning are formally in agreement with selection dynamics. A classification of search algorithms is shown to include Darwinian replicators (evolutionary units with multiplication, heredity, and variability) as the most powerful mechanism for search in a sparsely occupied search space. Examples are given of cases where parallel competitive search with information transfer among the units is more efficient than search without information transfer between units. Finally, we review our recent attempts to construct and analyze simple models of true Darwinian evolutionary units in the brain in terms of connectivity and activity copying of neuronal groups. Although none of the proposed neuronal replicators include miraculous mechanisms, their identification remains a challenge but also a great promise. PMID:22557963

The universal ancestor

NASA Technical Reports Server (NTRS)

Woese, C.

1998-01-01

A genetic annealing model for the universal ancestor of all extant life is presented; the name of the model derives from its resemblance to physical annealing. The scenario pictured starts when "genetic temperatures" were very high, cellular entities (progenotes) were very simple, and information processing systems were inaccurate. Initially, both mutation rate and lateral gene transfer levels were elevated. The latter was pandemic and pervasive to the extent that it, not vertical inheritance, defined the evolutionary dynamic. As increasingly complex and precise biological structures and processes evolved, both the mutation rate and the scope and level of lateral gene transfer, i.e., evolutionary temperature, dropped, and the evolutionary dynamic gradually became that characteristic of modern cells. The various subsystems of the cell "crystallized," i.e., became refractory to lateral gene transfer, at different stages of "cooling," with the translation apparatus probably crystallizing first. Organismal lineages, and so organisms as we know them, did not exist at these early stages. The universal phylogenetic tree, therefore, is not an organismal tree at its base but gradually becomes one as its peripheral branchings emerge. The universal ancestor is not a discrete entity. It is, rather, a diverse community of cells that survives and evolves as a biological unit. This communal ancestor has a physical history but not a genealogical one. Over time, this ancestor refined into a smaller number of increasingly complex cell types with the ancestors of the three primary groupings of organisms arising as a result.

The evolution of labile traits in sex- and age-structured populations.

PubMed

Childs, Dylan Z; Sheldon, Ben C; Rees, Mark

2016-03-01

Many quantitative traits are labile (e.g. somatic growth rate, reproductive timing and investment), varying over the life cycle as a result of behavioural adaptation, developmental processes and plastic responses to the environment. At the population level, selection can alter the distribution of such traits across age classes and among generations. Despite a growing body of theoretical research exploring the evolutionary dynamics of labile traits, a data-driven framework for incorporating such traits into demographic models has not yet been developed. Integral projection models (IPMs) are increasingly being used to understand the interplay between changes in labile characters, life histories and population dynamics. One limitation of the IPM approach is that it relies on phenotypic associations between parents and offspring traits to capture inheritance. However, it is well-established that many different processes may drive these associations, and currently, no clear consensus has emerged on how to model micro-evolutionary dynamics in an IPM framework. We show how to embed quantitative genetic models of inheritance of labile traits into age-structured, two-sex models that resemble standard IPMs. Commonly used statistical tools such as GLMs and their mixed model counterparts can then be used for model parameterization. We illustrate the methodology through development of a simple model of egg-laying date evolution, parameterized using data from a population of Great tits (Parus major). We demonstrate how our framework can be used to project the joint dynamics of species' traits and population density. We then develop a simple extension of the age-structured Price equation (ASPE) for two-sex populations, and apply this to examine the age-specific contributions of different processes to change in the mean phenotype and breeding value. The data-driven framework we outline here has the potential to facilitate greater insight into the nature of selection and its consequences in settings where focal traits vary over the lifetime through ontogeny, behavioural adaptation and phenotypic plasticity, as well as providing a potential bridge between theoretical and empirical studies of labile trait variation. © 2016 The Authors Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

THE HCN/HNC ABUNDANCE RATIO TOWARD DIFFERENT EVOLUTIONARY PHASES OF MASSIVE STAR FORMATION

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

Jin, Mihwa; Lee, Jeong-Eun; Kim, Kee-Tae, E-mail: mihwajin.sf@gmail.com, E-mail: jeongeun.lee@khu.ac.kr, E-mail: ktkim@kasi.re.kr

2015-07-20

Using the H{sup 13}CN and HN{sup 13}C J = 1–0 line observations, the abundance ratio of HCN/HNC has been estimated for different evolutionary stages of massive star formation: infrared dark clouds (IRDCs), high-mass protostellar objects (HMPOs), and ultracompact H ii regions (UCH iis). IRDCs were divided into “quiescent IRDC cores (qIRDCc)” and “active IRDC cores (aIRDCc),” depending on star formation activity. The HCN/HNC ratio is known to be higher at active and high temperature regions related to ongoing star formation, compared to cold and quiescent regions. Our observations toward 8 qIRDCc, 16 aIRDCc, 23 HMPOs, and 31 UCH iis showmore » consistent results; the ratio is 0.97 (±0.10), 2.65 (±0.88), 4.17 (±1.03), and 8.96 (±3.32) in these respective evolutionary stages, increasing from qIRDCc to UCH iis. The change of the HCN/HNC abundance ratio, therefore, seems directly associated with the evolutionary stages of star formation, which have different temperatures. One suggested explanation for this trend is the conversion of HNC to HCN, which occurs effectively at higher temperatures. To test the explanation, we performed a simple chemical model calculation. In order to fit the observed results, the energy barrier of the conversion must be much lower than the value provided by theoretical calculations.« less

Protoplanetary disc `isochrones' and the evolution of discs in the M˙-Md plane

NASA Astrophysics Data System (ADS)

Lodato, Giuseppe; Scardoni, Chiara E.; Manara, Carlo F.; Testi, Leonardo

2017-12-01

In this paper, we compare simple viscous diffusion models for the disc evolution with the results of recent surveys of the properties of young protoplanetary discs. We introduce the useful concept of 'disc isochrones' in the accretion rate-disc mass plane and explore a set of Monte Carlo realization of disc initial conditions. We find that such simple viscous models can provide a remarkable agreement with the available data in the Lupus star forming region, with the key requirement that the average viscous evolutionary time-scale of the discs is comparable to the cluster age. Our models produce naturally a correlation between mass accretion rate and disc mass that is shallower than linear, contrary to previous results and in agreement with observations. We also predict that a linear correlation, with a tighter scatter, should be found for more evolved disc populations. Finally, we find that such viscous models can reproduce the observations in the Lupus region only in the assumption that the efficiency of angular momentum transport is a growing function of radius, thus putting interesting constraints on the nature of the microscopic processes that lead to disc accretion.

CamOptimus: a tool for exploiting complex adaptive evolution to optimize experiments and processes in biotechnology.

PubMed

Cankorur-Cetinkaya, Ayca; Dias, Joao M L; Kludas, Jana; Slater, Nigel K H; Rousu, Juho; Oliver, Stephen G; Dikicioglu, Duygu

2017-06-01

Multiple interacting factors affect the performance of engineered biological systems in synthetic biology projects. The complexity of these biological systems means that experimental design should often be treated as a multiparametric optimization problem. However, the available methodologies are either impractical, due to a combinatorial explosion in the number of experiments to be performed, or are inaccessible to most experimentalists due to the lack of publicly available, user-friendly software. Although evolutionary algorithms may be employed as alternative approaches to optimize experimental design, the lack of simple-to-use software again restricts their use to specialist practitioners. In addition, the lack of subsidiary approaches to further investigate critical factors and their interactions prevents the full analysis and exploitation of the biotechnological system. We have addressed these problems and, here, provide a simple-to-use and freely available graphical user interface to empower a broad range of experimental biologists to employ complex evolutionary algorithms to optimize their experimental designs. Our approach exploits a Genetic Algorithm to discover the subspace containing the optimal combination of parameters, and Symbolic Regression to construct a model to evaluate the sensitivity of the experiment to each parameter under investigation. We demonstrate the utility of this method using an example in which the culture conditions for the microbial production of a bioactive human protein are optimized. CamOptimus is available through: (https://doi.org/10.17863/CAM.10257).

Two possible driving forces supporting the evolution of animal communication. Comment on "Towards a Computational Comparative Neuroprimatology: Framing the language-ready brain" by Michael A. Arbib

NASA Astrophysics Data System (ADS)

Moulin-Frier, Clément; Verschure, Paul F. M. J.

2016-03-01

In the target paper [1], M.A. Arbib proposes a quite exhaustive review of the (often computational) models developed during the last decades that support his detailed scenario on language evolution (the Mirror System Hypothesis, MSH). The approach considers that language evolved from a mirror system for grasping already present in LCA-m (the last common ancestor of macaques and humans), to a simple imitation system for grasping present in LCA-c (the last common ancestor of chimpanzees and humans), to a complex imitation system for grasping that developed in the hominid line since that ancestor. MSH considers that this complex imitation system is a key evolutionary step for a language-ready brain, providing all the required elements for an open-ended gestural communication system. The transition from the gestural (bracchio-manual and visual) to the vocal (articulatory and auditory) domain is supposed to be a less important evolutionary step.

Spectacular phenomena and limits to rationality in genetic and cultural evolution.

PubMed Central

Enquist, Magnus; Arak, Anthony; Ghirlanda, Stefano; Wachtmeister, Carl-Adam

2002-01-01

In studies of both animal and human behaviour, game theory is used as a tool for understanding strategies that appear in interactions between individuals. Game theory focuses on adaptive behaviour, which can be attained only at evolutionary equilibrium. We suggest that behaviour appearing during interactions is often outside the scope of such analysis. In many types of interaction, conflicts of interest exist between players, fuelling the evolution of manipulative strategies. Such strategies evolve out of equilibrium, commonly appearing as spectacular morphology or behaviour with obscure meaning, to which other players may react in non-adaptive, irrational ways. We present a simple model to show some limitations of the game-theory approach, and outline the conditions in which evolutionary equilibria cannot be maintained. Evidence from studies of biological interactions seems to support the view that behaviour is often not at equilibrium. This also appears to be the case for many human cultural traits, which have spread rapidly despite the fact that they have a negative influence on reproduction. PMID:12495515

Complex dynamics of selection and cellular memory in adaptation to a changing environment

NASA Astrophysics Data System (ADS)

Kussell, Edo; Lin, Wei-Hsiang

We study a synthetic evolutionary system in bacteria in which an antibiotic resistance gene is controlled by a stochastic on/off switching promoter. At the population level, this system displays all the basic ingredients for evolutionary selection, including diversity, fitness differences, and heritability. At the single cell level, physiological processes can modulate the ability of selection to act. We expose the stochastic switching strains to pulses of antibiotics of different durations in periodically changing environments using microfluidics. Small populations are tracked over a large number of periods at single cell resolution, allowing the visualization and quantification of selective sweeps and counter-sweeps at the population level, as well as detailed single cell analysis. A simple model is introduced to predict long-term population growth rates from single cell measurements, and reveals unexpected aspects of population dynamics, including cellular memory that acts on a fast timescale to modulate growth rates. This work is supported by NIH Grant No. R01-GM097356.

Synonymous Mutations at the Beginning of the Influenza A Virus Hemagglutinin Gene Impact Experimental Fitness.

PubMed

Canale, Aneth S; Venev, Sergey V; Whitfield, Troy W; Caffrey, Daniel R; Marasco, Wayne A; Schiffer, Celia A; Kowalik, Timothy F; Jensen, Jeffrey D; Finberg, Robert W; Zeldovich, Konstantin B; Wang, Jennifer P; Bolon, Daniel N A

2018-04-13

The fitness effects of synonymous mutations can provide insights into biological and evolutionary mechanisms. We analyzed the experimental fitness effects of all single-nucleotide mutations, including synonymous substitutions, at the beginning of the influenza A virus hemagglutinin (HA) gene. Many synonymous substitutions were deleterious both in bulk competition and for individually isolated clones. Investigating protein and RNA levels of a subset of individually expressed HA variants revealed that multiple biochemical properties contribute to the observed experimental fitness effects. Our results indicate that a structural element in the HA segment viral RNA may influence fitness. Examination of naturally evolved sequences in human hosts indicates a preference for the unfolded state of this structural element compared to that found in swine hosts. Our overall results reveal that synonymous mutations may have greater fitness consequences than indicated by simple models of sequence conservation, and we discuss the implications of this finding for commonly used evolutionary tests and analyses. Copyright © 2018. Published by Elsevier Ltd.

Spectacular phenomena and limits to rationality in genetic and cultural evolution.

PubMed

Enquist, Magnus; Arak, Anthony; Ghirlanda, Stefano; Wachtmeister, Carl-Adam

2002-11-29

In studies of both animal and human behaviour, game theory is used as a tool for understanding strategies that appear in interactions between individuals. Game theory focuses on adaptive behaviour, which can be attained only at evolutionary equilibrium. We suggest that behaviour appearing during interactions is often outside the scope of such analysis. In many types of interaction, conflicts of interest exist between players, fuelling the evolution of manipulative strategies. Such strategies evolve out of equilibrium, commonly appearing as spectacular morphology or behaviour with obscure meaning, to which other players may react in non-adaptive, irrational ways. We present a simple model to show some limitations of the game-theory approach, and outline the conditions in which evolutionary equilibria cannot be maintained. Evidence from studies of biological interactions seems to support the view that behaviour is often not at equilibrium. This also appears to be the case for many human cultural traits, which have spread rapidly despite the fact that they have a negative influence on reproduction.

Climate-driven extinctions shape the phylogenetic structure of temperate tree floras.

PubMed

Eiserhardt, Wolf L; Borchsenius, Finn; Plum, Christoffer M; Ordonez, Alejandro; Svenning, Jens-Christian

2015-03-01

When taxa go extinct, unique evolutionary history is lost. If extinction is selective, and the intrinsic vulnerabilities of taxa show phylogenetic signal, more evolutionary history may be lost than expected under random extinction. Under what conditions this occurs is insufficiently known. We show that late Cenozoic climate change induced phylogenetically selective regional extinction of northern temperate trees because of phylogenetic signal in cold tolerance, leading to significantly and substantially larger than random losses of phylogenetic diversity (PD). The surviving floras in regions that experienced stronger extinction are phylogenetically more clustered, indicating that non-random losses of PD are of increasing concern with increasing extinction severity. Using simulations, we show that a simple threshold model of survival given a physiological trait with phylogenetic signal reproduces our findings. Our results send a strong warning that we may expect future assemblages to be phylogenetically and possibly functionally depauperate if anthropogenic climate change affects taxa similarly. © 2015 John Wiley & Sons Ltd/CNRS.

Insights into resource consumption, cross-feeding, system collapse, stability and biodiversity from an artificial ecosystem

PubMed Central

Sumpter, David

2017-01-01

Community ecosystems at very different levels of biological organization often have similar properties. Coexistence of multiple species, cross-feeding, biodiversity and fluctuating population dynamics are just a few of the properties that arise in a range of ecological settings. Here we develop a bottom-up model of consumer–resource interactions, in the form of an artificial ecosystem ‘number soup’, which reflects basic properties of many bacterial and other community ecologies. We demonstrate four key properties of the number soup model: (i) communities self-organize so that all available resources are fully consumed; (ii) reciprocal cross-feeding is a common evolutionary outcome, which evolves in a number of stages, and many transitional species are involved; (iii) the evolved ecosystems are often ‘robust yet fragile’, with keystone species required to prevent the whole system from collapsing; (iv) non-equilibrium dynamics and chaotic patterns are general properties, readily generating rich biodiversity. These properties have been observed in empirical ecosystems, ranging from bacteria to rainforests. Establishing similar properties in an evolutionary model as simple as the number soup suggests that these four properties are ubiquitous features of all community ecosystems, and raises questions about how we interpret ecosystem structure in the context of natural selection. PMID:28100827

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.

Fast and accurate estimation of the covariance between pairwise maximum likelihood distances.

PubMed

Gil, Manuel

2014-01-01

Pairwise evolutionary distances are a model-based summary statistic for a set of molecular sequences. They represent the leaf-to-leaf path lengths of the underlying phylogenetic tree. Estimates of pairwise distances with overlapping paths covary because of shared mutation events. It is desirable to take these covariance structure into account to increase precision in any process that compares or combines distances. This paper introduces a fast estimator for the covariance of two pairwise maximum likelihood distances, estimated under general Markov models. The estimator is based on a conjecture (going back to Nei & Jin, 1989) which links the covariance to path lengths. It is proven here under a simple symmetric substitution model. A simulation shows that the estimator outperforms previously published ones in terms of the mean squared error.

Fast and accurate estimation of the covariance between pairwise maximum likelihood distances

PubMed Central

2014-01-01

Pairwise evolutionary distances are a model-based summary statistic for a set of molecular sequences. They represent the leaf-to-leaf path lengths of the underlying phylogenetic tree. Estimates of pairwise distances with overlapping paths covary because of shared mutation events. It is desirable to take these covariance structure into account to increase precision in any process that compares or combines distances. This paper introduces a fast estimator for the covariance of two pairwise maximum likelihood distances, estimated under general Markov models. The estimator is based on a conjecture (going back to Nei & Jin, 1989) which links the covariance to path lengths. It is proven here under a simple symmetric substitution model. A simulation shows that the estimator outperforms previously published ones in terms of the mean squared error. PMID:25279263

Endogenous time-varying risk aversion and asset returns.

PubMed

Berardi, Michele

2016-01-01

Stylized facts about statistical properties for short horizon returns in financial markets have been identified in the literature, but a satisfactory understanding for their manifestation is yet to be achieved. In this work, we show that a simple asset pricing model with representative agent is able to generate time series of returns that replicate such stylized facts if the risk aversion coefficient is allowed to change endogenously over time in response to unexpected excess returns under evolutionary forces. The same model, under constant risk aversion, would instead generate returns that are essentially Gaussian. We conclude that an endogenous time-varying risk aversion represents a very parsimonious way to make the model match real data on key statistical properties, and therefore deserves careful consideration from economists and practitioners alike.

The evolution of coexistence: Reciprocal adaptation promotes the assembly of a simple community.

PubMed

Bassar, Ronald D; Simon, Troy; Roberts, William; Travis, Joseph; Reznick, David N

2017-02-01

Species coexistence may result by chance when co-occurring species do not strongly interact or it may be an evolutionary outcome of strongly interacting species adapting to each other. Although patterns like character displacement indicate that coexistence has often been an evolutionary outcome, it is unclear how often the evolution of coexistence represents adaptation in only one species or reciprocal adaptation among all interacting species. Here, we demonstrate a strong role for evolution in the coexistence of guppies and killifish in Trinidadian streams. We experimentally recreated the temporal stages in the invasion and establishment of guppies into communities that previously contained only killifish. We combined demographic responses of guppies and killifish with a size-based integral projection model to calculate the fitness of the phenotypes of each species in each of the stages of community assembly. We show that guppies from locally adapted populations that are sympatric with killifish have higher fitness when paired with killifish than guppies from allopatric populations. This elevated fitness involves effects traceable to both guppy and killifish evolution. We discuss the implications of our results to the study of species coexistence and how it may be mediated through eco-evolutionary feedbacks. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Adaptation to enemy shifts: rapid resistance evolution to local Vibrio spp. in invasive Pacific oysters

PubMed Central

Wendling, Carolin C.; Wegner, K. Mathias

2015-01-01

One hypothesis for the success of invasive species is reduced pathogen burden, resulting from a release from infections or high immunological fitness of invaders. Despite strong selection exerted on the host, the evolutionary response of invaders to newly acquired pathogens has rarely been considered. The two independent and genetically distinct invasions of the Pacific oyster Crassostrea gigas into the North Sea represent an ideal model system to study fast evolutionary responses of invasive populations. By exposing both invasion sources to ubiquitous and phylogenetically diverse pathogens (Vibrio spp.), we demonstrate that within a few generations hosts adapted to newly encountered pathogen communities. However, local adaptation only became apparent in selective environments, i.e. at elevated temperatures reflecting patterns of disease outbreaks in natural populations. Resistance against sympatric and allopatric Vibrio spp. strains was dominantly inherited in crosses between both invasion sources, resulting in an overall higher resistance of admixed individuals than pure lines. Therefore, we suggest that a simple genetic resistance mechanism of the host is matched to a common virulence mechanism shared by local Vibrio strains. This combination might have facilitated a fast evolutionary response that can explain another dimension of why invasive species can be so successful in newly invaded ranges. PMID:25716784

Always chew your food: freshwater stingrays use mastication to process tough insect prey.

PubMed

Kolmann, Matthew A; Welch, Kenneth C; Summers, Adam P; Lovejoy, Nathan R

2016-09-14

Chewing, characterized by shearing jaw motions and high-crowned molar teeth, is considered an evolutionary innovation that spurred dietary diversification and evolutionary radiation of mammals. Complex prey-processing behaviours have been thought to be lacking in fishes and other vertebrates, despite the fact that many of these animals feed on tough prey, like insects or even grasses. We investigated prey capture and processing in the insect-feeding freshwater stingray Potamotrygon motoro using high-speed videography. We find that Potamotrygon motoro uses asymmetrical motion of the jaws, effectively chewing, to dismantle insect prey. However, CT scanning suggests that this species has simple teeth. These findings suggest that in contrast to mammalian chewing, asymmetrical jaw action is sufficient for mastication in other vertebrates. We also determined that prey capture in these rays occurs through rapid uplift of the pectoral fins, sucking prey beneath the ray's body, thereby dissociating the jaws from a prey capture role. We suggest that the decoupling of prey capture and processing facilitated the evolution of a highly kinetic feeding apparatus in batoid fishes, giving these animals an ability to consume a wide variety of prey, including molluscs, fishes, aquatic insect larvae and crustaceans. We propose Potamotrygon as a model system for understanding evolutionary convergence of prey processing and chewing in vertebrates. © 2016 The Author(s).

Always chew your food: freshwater stingrays use mastication to process tough insect prey

PubMed Central

Welch, Kenneth C.; Summers, Adam P.; Lovejoy, Nathan R.

2016-01-01

Chewing, characterized by shearing jaw motions and high-crowned molar teeth, is considered an evolutionary innovation that spurred dietary diversification and evolutionary radiation of mammals. Complex prey-processing behaviours have been thought to be lacking in fishes and other vertebrates, despite the fact that many of these animals feed on tough prey, like insects or even grasses. We investigated prey capture and processing in the insect-feeding freshwater stingray Potamotrygon motoro using high-speed videography. We find that Potamotrygon motoro uses asymmetrical motion of the jaws, effectively chewing, to dismantle insect prey. However, CT scanning suggests that this species has simple teeth. These findings suggest that in contrast to mammalian chewing, asymmetrical jaw action is sufficient for mastication in other vertebrates. We also determined that prey capture in these rays occurs through rapid uplift of the pectoral fins, sucking prey beneath the ray's body, thereby dissociating the jaws from a prey capture role. We suggest that the decoupling of prey capture and processing facilitated the evolution of a highly kinetic feeding apparatus in batoid fishes, giving these animals an ability to consume a wide variety of prey, including molluscs, fishes, aquatic insect larvae and crustaceans. We propose Potamotrygon as a model system for understanding evolutionary convergence of prey processing and chewing in vertebrates. PMID:27629029

Senescence in immune priming and attractiveness in a beetle.

PubMed

Daukšte, J; Kivleniece, I; Krama, T; Rantala, M J; Krams, I

2012-07-01

Age-related decline in immune activity is referred to as immunosenescence and has been observed for both the adaptive immune response of vertebrates and the innate immune system of invertebrates. Because maintaining a basic level of immune defence and mounting an immune response is costly, optimal investment in immune function should vary over a wide range of individual states such as the individual's age. In this study, we tested whether the immune response and immunological priming within individuals become less efficient with age using mealworm beetles, Tenebrio molitor, as a model organism. We also tested whether ageing and immunological priming affected the odours produced by males. We found that young males of T. molitor were capable of mounting an immune response a sterile nylon monofilament implant with the potential to exhibit a simple form of immune memory through mechanisms of immune priming. Older males did not increase their immune response to a second immune challenge, which negatively affected their sexual attractiveness and remaining life span. Our results indicate that the immune system of older males in T. molitor is less effective, suggesting complex evolutionary trade-offs between ageing, immune response and sexual attractiveness. © 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.

Evolutionary dynamics of general group interactions in structured populations

NASA Astrophysics Data System (ADS)

Li, Aming; Broom, Mark; Du, Jinming; Wang, Long

2016-02-01

The evolution of populations is influenced by many factors, and the simple classical models have been developed in a number of important ways. Both population structure and multiplayer interactions have been shown to significantly affect the evolution of important properties, such as the level of cooperation or of aggressive behavior. Here we combine these two key factors and develop the evolutionary dynamics of general group interactions in structured populations represented by regular graphs. The traditional linear and threshold public goods games are adopted as models to address the dynamics. We show that for linear group interactions, population structure can favor the evolution of cooperation compared to the well-mixed case, and we see that the more neighbors there are, the harder it is for cooperators to persist in structured populations. We further show that threshold group interactions could lead to the emergence of cooperation even in well-mixed populations. Here population structure sometimes inhibits cooperation for the threshold public goods game, where depending on the benefit to cost ratio, the outcomes are bistability or a monomorphic population of defectors or cooperators. Our results suggest, counterintuitively, that structured populations are not always beneficial for the evolution of cooperation for nonlinear group interactions.

Presence of a loner strain maintains cooperation and diversity in well-mixed bacterial communities.

PubMed

Inglis, R F; Biernaskie, J M; Gardner, A; Kümmerli, R

2016-01-13

Cooperation and diversity abound in nature despite cooperators risking exploitation from defectors and superior competitors displacing weaker ones. Understanding the persistence of cooperation and diversity is therefore a major problem for evolutionary ecology, especially in the context of well-mixed populations, where the potential for exploitation and displacement is greatest. Here, we demonstrate that a 'loner effect', described by economic game theorists, can maintain cooperation and diversity in real-world biological settings. We use mathematical models of public-good-producing bacteria to show that the presence of a loner strain, which produces an independent but relatively inefficient good, can lead to rock-paper-scissor dynamics, whereby cooperators outcompete loners, defectors outcompete cooperators and loners outcompete defectors. These model predictions are supported by our observations of evolutionary dynamics in well-mixed experimental communities of the bacterium Pseudomonas aeruginosa. We find that the coexistence of cooperators and defectors that produce and exploit, respectively, the iron-scavenging siderophore pyoverdine, is stabilized by the presence of loners with an independent iron-uptake mechanism. Our results establish the loner effect as a simple and general driver of cooperation and diversity in environments that would otherwise favour defection and the erosion of diversity. © 2016 The Authors.

Genetic models of homosexuality: generating testable predictions

PubMed Central

Gavrilets, Sergey; Rice, William R

2006-01-01

Homosexuality is a common occurrence in humans and other species, yet its genetic and evolutionary basis is poorly understood. Here, we formulate and study a series of simple mathematical models for the purpose of predicting empirical patterns that can be used to determine the form of selection that leads to polymorphism of genes influencing homosexuality. Specifically, we develop theory to make contrasting predictions about the genetic characteristics of genes influencing homosexuality including: (i) chromosomal location, (ii) dominance among segregating alleles and (iii) effect sizes that distinguish between the two major models for their polymorphism: the overdominance and sexual antagonism models. We conclude that the measurement of the genetic characteristics of quantitative trait loci (QTLs) found in genomic screens for genes influencing homosexuality can be highly informative in resolving the form of natural selection maintaining their polymorphism. PMID:17015344

Evolution-informed forecasting of seasonal influenza A (H3N2)

PubMed Central

Du, Xiangjun; King, Aaron A.; Woods, Robert J.; Pascual, Mercedes

2018-01-01

Inter-pandemic or seasonal influenza exacts an enormous annual burden both in terms of human health and economic impact. Incidence prediction ahead of season remains a challenge largely because of the virus’ antigenic evolution. We propose here a forecasting approach that incorporates evolutionary change into a mechanistic epidemiological model. The proposed models are simple enough that their parameters can be estimated from retrospective surveillance data. These models link amino-acid sequences of hemagglutinin epitopes with a transmission model for seasonal H3N2 influenza, also informed by H1N1 levels. With a monthly time series of H3N2 incidence in the United States over 10 years, we demonstrate the feasibility of prediction ahead of season and an accurate real-time forecast for the 2016/2017 influenza season. PMID:29070700

Evolutionary Dynamics of Nitrogen Fixation in the Legume–Rhizobia Symbiosis

PubMed Central

Fujita, Hironori; Aoki, Seishiro; Kawaguchi, Masayoshi

2014-01-01

The stabilization of host–symbiont mutualism against the emergence of parasitic individuals is pivotal to the evolution of cooperation. One of the most famous symbioses occurs between legumes and their colonizing rhizobia, in which rhizobia extract nutrients (or benefits) from legume plants while supplying them with nitrogen resources produced by nitrogen fixation (or costs). Natural environments, however, are widely populated by ineffective rhizobia that extract benefits without paying costs and thus proliferate more efficiently than nitrogen-fixing cooperators. How and why this mutualism becomes stabilized and evolutionarily persists has been extensively discussed. To better understand the evolutionary dynamics of this symbiosis system, we construct a simple model based on the continuous snowdrift game with multiple interacting players. We investigate the model using adaptive dynamics and numerical simulations. We find that symbiotic evolution depends on the cost–benefit balance, and that cheaters widely emerge when the cost and benefit are similar in strength. In this scenario, the persistence of the symbiotic system is compatible with the presence of cheaters. This result suggests that the symbiotic relationship is robust to the emergence of cheaters, and may explain the prevalence of cheating rhizobia in nature. In addition, various stabilizing mechanisms, such as partner fidelity feedback, partner choice, and host sanction, can reinforce the symbiotic relationship by affecting the fitness of symbionts in various ways. This result suggests that the symbiotic relationship is cooperatively stabilized by various mechanisms. In addition, mixed nodule populations are thought to encourage cheater emergence, but our model predicts that, in certain situations, cheaters can disappear from such populations. These findings provide a theoretical basis of the evolutionary dynamics of legume–rhizobia symbioses, which is extendable to other single-host, multiple-colonizer systems. PMID:24691447

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.

Heterogeneous distribution of metabolites across plant species

NASA Astrophysics Data System (ADS)

Takemoto, Kazuhiro; Arita, Masanori

2009-07-01

We investigate the distribution of flavonoids, a major category of plant secondary metabolites, across species. Flavonoids are known to show high species specificity, and were once considered as chemical markers for understanding adaptive evolution and characterization of living organisms. We investigate the distribution among species using bipartite networks, and find that two heterogeneous distributions are conserved among several families: the power-law distributions of the number of flavonoids in a species and the number of shared species of a particular flavonoid. In order to explain the possible origin of the heterogeneity, we propose a simple model with, essentially, a single parameter. As a result, we show that two respective power-law statistics emerge from simple evolutionary mechanisms based on a multiplicative process. These findings provide insights into the evolution of metabolite diversity and characterization of living organisms that defy genome sequence analysis for different reasons.

Analysis of convergence of an evolutionary algorithm with self-adaptation using a stochastic Lyapunov function.

PubMed

Semenov, Mikhail A; Terkel, Dmitri A

2003-01-01

This paper analyses the convergence of evolutionary algorithms using a technique which is based on a stochastic Lyapunov function and developed within the martingale theory. This technique is used to investigate the convergence of a simple evolutionary algorithm with self-adaptation, which contains two types of parameters: fitness parameters, belonging to the domain of the objective function; and control parameters, responsible for the variation of fitness parameters. Although both parameters mutate randomly and independently, they converge to the "optimum" due to the direct (for fitness parameters) and indirect (for control parameters) selection. We show that the convergence velocity of the evolutionary algorithm with self-adaptation is asymptotically exponential, similar to the velocity of the optimal deterministic algorithm on the class of unimodal functions. Although some martingale inequalities have not be proved analytically, they have been numerically validated with 0.999 confidence using Monte-Carlo simulations.

Tracking of electrochemical impedance of batteries

NASA Astrophysics Data System (ADS)

Piret, H.; Granjon, P.; Guillet, N.; Cattin, V.

2016-04-01

This paper presents an evolutionary battery impedance estimation method, which can be easily embedded in vehicles or nomad devices. The proposed method not only allows an accurate frequency impedance estimation, but also a tracking of its temporal evolution contrary to classical electrochemical impedance spectroscopy methods. Taking into account constraints of cost and complexity, we propose to use the existing electronics of current control to perform a frequency evolutionary estimation of the electrochemical impedance. The developed method uses a simple wideband input signal, and relies on a recursive local average of Fourier transforms. The averaging is controlled by a single parameter, managing a trade-off between tracking and estimation performance. This normalized parameter allows to correctly adapt the behavior of the proposed estimator to the variations of the impedance. The advantage of the proposed method is twofold: the method is easy to embed into a simple electronic circuit, and the battery impedance estimator is evolutionary. The ability of the method to monitor the impedance over time is demonstrated on a simulator, and on a real Lithium ion battery, on which a repeatability study is carried out. The experiments reveal good tracking results, and estimation performance as accurate as the usual laboratory approaches.

Bifurcation structures of a cobweb model with memory and competing technologies

NASA Astrophysics Data System (ADS)

Agliari, Anna; Naimzada, Ahmad; Pecora, Nicolò

2018-05-01

In this paper we study a simple model based on the cobweb demand-supply framework with costly innovators and free imitators. The evolutionary selection between technologies depends on a performance measure which is related to the degree of memory. The resulting dynamics is described by a two-dimensional map. The map has a fixed point which may lose stability either via supercritical Neimark-Sacker bifurcation or flip bifurcation and several multistability situations exist. We describe some sequences of global bifurcations involving attracting and repelling closed invariant curves. These bifurcations, characterized by the creation of homoclinic connections or homoclinic tangles, are described through several numerical simulations. Particular bifurcation phenomena are also observed when the parameters are selected inside a periodicity region.

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

A Simple Mathematical Model Inspired by the Purkinje Cells: From Delayed Travelling Waves to Fractional Diffusion.

PubMed

Dipierro, Serena; Valdinoci, Enrico

2018-07-01

Recently, several experiments have demonstrated the existence of fractional diffusion in the neuronal transmission occurring in the Purkinje cells, whose malfunctioning is known to be related to the lack of voluntary coordination and the appearance of tremors. Also, a classical mathematical feature is that (fractional) parabolic equations possess smoothing effects, in contrast with the case of hyperbolic equations, which typically exhibit shocks and discontinuities. In this paper, we show how a simple toy-model of a highly ramified structure, somehow inspired by that of the Purkinje cells, may produce a fractional diffusion via the superposition of travelling waves that solve a hyperbolic equation. This could suggest that the high ramification of the Purkinje cells might have provided an evolutionary advantage of "smoothing" the transmission of signals and avoiding shock propagations (at the price of slowing a bit such transmission). Although an experimental confirmation of the possibility of such evolutionary advantage goes well beyond the goals of this paper, we think that it is intriguing, as a mathematical counterpart, to consider the time fractional diffusion as arising from the superposition of delayed travelling waves in highly ramified transmission media. The case of a travelling concave parabola with sufficiently small curvature is explicitly computed. The new link that we propose between time fractional diffusion and hyperbolic equation also provides a novelty with respect to the usual paradigm relating time fractional diffusion with parabolic equations in the limit. This paper is written in such a way as to be of interest to both biologists and mathematician alike. In order to accomplish this aim, both complete explanations of the objects considered and detailed lists of references are provided.

Bet-hedging as a complex interaction among developmental instability, environmental heterogeneity, dispersal, and life-history strategy.

PubMed

Scheiner, Samuel M

2014-02-01

One potential evolutionary response to environmental heterogeneity is the production of randomly variable offspring through developmental instability, a type of bet-hedging. I used an individual-based, genetically explicit model to examine the evolution of developmental instability. The model considered both temporal and spatial heterogeneity alone and in combination, the effect of migration pattern (stepping stone vs. island), and life-history strategy. I confirmed that temporal heterogeneity alone requires a threshold amount of variation to select for a substantial amount of developmental instability. For spatial heterogeneity only, the response to selection on developmental instability depended on the life-history strategy and the form and pattern of dispersal with the greatest response for island migration when selection occurred before dispersal. Both spatial and temporal variation alone select for similar amounts of instability, but in combination resulted in substantially more instability than either alone. Local adaptation traded off against bet-hedging, but not in a simple linear fashion. I found higher-order interactions between life-history patterns, dispersal rates, dispersal patterns, and environmental heterogeneity that are not explainable by simple intuition. We need additional modeling efforts to understand these interactions and empirical tests that explicitly account for all of these factors.

Self-consistent approach for neutral community models with speciation

NASA Astrophysics Data System (ADS)

Haegeman, Bart; Etienne, Rampal S.

2010-03-01

Hubbell’s neutral model provides a rich theoretical framework to study ecological communities. By incorporating both ecological and evolutionary time scales, it allows us to investigate how communities are shaped by speciation processes. The speciation model in the basic neutral model is particularly simple, describing speciation as a point-mutation event in a birth of a single individual. The stationary species abundance distribution of the basic model, which can be solved exactly, fits empirical data of distributions of species’ abundances surprisingly well. More realistic speciation models have been proposed such as the random-fission model in which new species appear by splitting up existing species. However, no analytical solution is available for these models, impeding quantitative comparison with data. Here, we present a self-consistent approximation method for neutral community models with various speciation modes, including random fission. We derive explicit formulas for the stationary species abundance distribution, which agree very well with simulations. We expect that our approximation method will be useful to study other speciation processes in neutral community models as well.

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.

Conceptual models of the evolution of transgressive dune field systems

NASA Astrophysics Data System (ADS)

A. Hesp, Patrick

2013-10-01

This paper examines the evolutionary paths of some transgressive dune fields that have formed on different coasts of the world, and presents some initial conceptual models of system dynamics for transgressive dune sheets and dune fields. Various evolutionary pathways are conceptualized based on a visual examination of dune fields from around the world. On coasts with high sediment supply, dune sheets and dune fields tend to accumulate as large scale barrier systems with little colonization of vegetation in arid-hyper to arid climate regimes, and as multiple, active discrete phases of dune field and deflation plain couplets in temperate to tropical environments. Active dune fields tend to be singular entities on coasts with low to moderate sediment supply. Landscape complexity and vegetation richness and diversity increases as dune fields evolve from simple active sheets and dunes to single and multiple deflation plains and basins, precipitation ridges, nebkha fields and a host of other dune types associated with vegetation (e.g. trailing ridges, slacks, remnant knobs, gegenwalle ridges and dune track ridges, ‘tree islands' and ‘bush pockets'). Three principal scenarios of transgressive dune sheet and dune field development are discussed, including dune sheets or dune fields evolving directly from the backshore, development following foredune and/or dune field erosion, and development from the breakdown or merging of parabolic dunes. Various stages of evolution are outlined for each scenario. Knowledge of evolutionary patterns and stages in coastal dune fields is very limited and caution is urged in attempts to reverse, change and/or modify dune fields to ‘restore' some perceived loss of ecosystem or dune functioning.

Conceptual models of the evolution of transgressive dune field systems

NASA Astrophysics Data System (ADS)

Hesp, Patrick A.

2013-10-01

This paper examines the evolutionary paths of some transgressive dune fields that have formed on different coasts of the world, and presents some initial conceptual models of system dynamics for transgressive dune sheets and dune fields. Various evolutionary pathways are conceptualized based on a visual examination of dune fields from around the world. On coasts with high sediment supply, dune sheets and dune fields tend to accumulate as large scale barrier systems with little colonization of vegetation in arid-hyper to arid climate regimes, and as multiple, active discrete phases of dune field and deflation plain couplets in temperate to tropical environments. Active dune fields tend to be singular entities on coasts with low to moderate sediment supply. Landscape complexity and vegetation richness and diversity increases as dune fields evolve from simple active sheets and dunes to single and multiple deflation plains and basins, precipitation ridges, nebkha fields and a host of other dune types associated with vegetation (e.g. trailing ridges, slacks, remnant knobs, gegenwalle ridges and dune track ridges, 'tree islands' and 'bush pockets'). Three principal scenarios of transgressive dune sheet and dune field development are discussed, including dune sheets or dune fields evolving directly from the backshore, development following foredune and/or dune field erosion, and development from the breakdown or merging of parabolic dunes. Various stages of evolution are outlined for each scenario. Knowledge of evolutionary patterns and stages in coastal dune fields is very limited and caution is urged in attempts to reverse, change and/or modify dune fields to 'restore' some perceived loss of ecosystem or dune functioning.

Evolutionary modes of emergence of short interspersed nuclear element (SINE) families in grasses.

PubMed

Kögler, Anja; Schmidt, Thomas; Wenke, Torsten

2017-11-01

Short interspersed nuclear elements (SINEs) are non-autonomous transposable elements which are propagated by retrotransposition and constitute an inherent part of the genome of most eukaryotic species. Knowledge of heterogeneous and highly abundant SINEs is crucial for de novo (or improvement of) annotation of whole genome sequences. We scanned Poaceae genome sequences of six important cereals (Oryza sativa, Triticum aestivum, Hordeum vulgare, Panicum virgatum, Sorghum bicolor, Zea mays) and Brachypodium distachyon to examine the diversity and evolution of SINE populations. We comparatively analyzed the structural features, distribution, evolutionary relation and abundance of 32 SINE families and subfamilies within grasses, comprising 11 052 individual copies. The investigation of activity profiles within the Poaceae provides insights into their species-specific diversification and amplification. We found that Poaceae SINEs (PoaS) fall into two length categories: simple SINEs of up to 180 bp and dimeric SINEs larger than 240 bp. Detailed analysis at the nucleotide level revealed that multimerization of related and unrelated SINE copies is an important evolutionary mechanism of SINE formation. We conclude that PoaS families diversify by massive reshuffling between SINE families, likely caused by insertion of truncated copies, and provide a model for this evolutionary scenario. Twenty-eight of 32 PoaS families and subfamilies show significant conservation, in particular either in the 5' or 3' regions, across Poaceae species and share large sequence stretches with one or more other PoaS families. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Recombinant transfer in the basic genome of E. coli

DOE PAGES

Dixit, Purushottam; Studier, F. William; Pang, Tin Yau; ...

2015-07-07

An approximation to the ~4-Mbp basic genome shared by 32 strains of E. coli representing six evolutionary groups has been derived and analyzed computationally. A multiple-alignment of the 32 complete genome sequences was filtered to remove mobile elements and identify the most reliable ~90% of the aligned length of each of the resulting 496 basic-genome pairs. Patterns of single bp mutations (SNPs) in aligned pairs distinguish clonally inherited regions from regions where either genome has acquired DNA fragments from diverged genomes by homologous recombination since their last common ancestor. Such recombinant transfer is pervasive across the basic genome, mostly betweenmore » genomes in the same evolutionary group, and generates many unique mosaic patterns. The six least-diverged genome-pairs have one or two recombinant transfers of length ~40–115 kbp (and few if any other transfers), each containing one or more gene clusters known to confer strong selective advantage in some environments. Moderately diverged genome pairs (0.4–1% SNPs) show mosaic patterns of interspersed clonal and recombinant regions of varying lengths throughout the basic genome, whereas more highly diverged pairs within an evolutionary group or pairs between evolutionary groups having >1.3% SNPs have few clonal matches longer than a few kbp. Many recombinant transfers appear to incorporate fragments of the entering DNA produced by restriction systems of the recipient cell. A simple computational model can closely fit the data. As a result, most recombinant transfers seem likely to be due to generalized transduction by co-evolving populations of phages, which could efficiently distribute variability throughout bacterial genomes.« less

Recombinant transfer in the basic genome of E. coli

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

Dixit, Purushottam; Studier, F. William; Pang, Tin Yau

An approximation to the ~4-Mbp basic genome shared by 32 strains of E. coli representing six evolutionary groups has been derived and analyzed computationally. A multiple-alignment of the 32 complete genome sequences was filtered to remove mobile elements and identify the most reliable ~90% of the aligned length of each of the resulting 496 basic-genome pairs. Patterns of single bp mutations (SNPs) in aligned pairs distinguish clonally inherited regions from regions where either genome has acquired DNA fragments from diverged genomes by homologous recombination since their last common ancestor. Such recombinant transfer is pervasive across the basic genome, mostly betweenmore » genomes in the same evolutionary group, and generates many unique mosaic patterns. The six least-diverged genome-pairs have one or two recombinant transfers of length ~40–115 kbp (and few if any other transfers), each containing one or more gene clusters known to confer strong selective advantage in some environments. Moderately diverged genome pairs (0.4–1% SNPs) show mosaic patterns of interspersed clonal and recombinant regions of varying lengths throughout the basic genome, whereas more highly diverged pairs within an evolutionary group or pairs between evolutionary groups having >1.3% SNPs have few clonal matches longer than a few kbp. Many recombinant transfers appear to incorporate fragments of the entering DNA produced by restriction systems of the recipient cell. A simple computational model can closely fit the data. As a result, most recombinant transfers seem likely to be due to generalized transduction by co-evolving populations of phages, which could efficiently distribute variability throughout bacterial genomes.« less

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...

Emergence of competition and cooperation in an evolutionary resource war model

NASA Astrophysics Data System (ADS)

Lamantia, Fabio

2018-05-01

In this paper we introduce a simple punishment scheme in the 'great fish war' model with many players. An imitative process regulates how a coalition of cooperators is dynamically updated over time. An intuitive effect of adding sanctions is that they could enlarge the possible sustainable coalitions. However, the evolution toward full cooperation can be sustained by a punishment scheme provided that a critical mass of agents enforces cooperation at the beginning of the game. Moreover, we show the presence of thresholds in sanctions or in the cost for punishing such that if these thresholds are trespassed then dramatic reductions in the resource level and in the agents' welfare may occur as a consequence of free riding effects. We show by some examples that these phenomena are due to the presence of tipping points in the model.

Social dilemmas among supergenes: intragenomic sexual conflict and a selfing solution in Oenothera

PubMed Central

Brown, Sam P.; Levin, Donald A.

2012-01-01

Recombination is a powerful policing mechanism to control intragenomic cheats. The ‘parliament of the genes’ can often rapidly block driving genes from cheating during meiosis. But what if the genome parliament is reduced to only two members, or supergenes? Using a series of simple game-theoretic models inspired by the peculiar genetics of Oenothera sp. we illustrate that a 2 supergene genome (α and β) can produce a number of surprising evolutionary dynamics, including increases in lineage longevity following a transition from sexuality (outcrossing) to asexuality (clonal self-fertilization). We end by interpreting the model in the broader context of the evolution of mutualism, which highlights that greater α, β cooperation in the self-fertilizing model can be viewed as an example of partner fidelity driving multi-lineage cooperation. PMID:22133211

A novel JEAnS analysis of the Fornax dwarf using evolutionary algorithms: mass follows light with signs of an off-centre merger

NASA Astrophysics Data System (ADS)

Diakogiannis, Foivos I.; Lewis, Geraint F.; Ibata, Rodrigo A.; Guglielmo, Magda; Kafle, Prajwal R.; Wilkinson, Mark I.; Power, Chris

2017-09-01

Dwarf galaxies, among the most dark matter dominated structures of our Universe, are excellent test-beds for dark matter theories. Unfortunately, mass modelling of these systems suffers from the well-documented mass-velocity anisotropy degeneracy. For the case of spherically symmetric systems, we describe a method for non-parametric modelling of the radial and tangential velocity moments. The method is a numerical velocity anisotropy 'inversion', with parametric mass models, where the radial velocity dispersion profile, σrr2, is modelled as a B-spline, and the optimization is a three-step process that consists of (I) an evolutionary modelling to determine the mass model form and the best B-spline basis to represent σrr2; (II) an optimization of the smoothing parameters and (III) a Markov chain Monte Carlo analysis to determine the physical parameters. The mass-anisotropy degeneracy is reduced into mass model inference, irrespective of kinematics. We test our method using synthetic data. Our algorithm constructs the best kinematic profile and discriminates between competing dark matter models. We apply our method to the Fornax dwarf spheroidal galaxy. Using a King brightness profile and testing various dark matter mass models, our model inference favours a simple mass-follows-light system. We find that the anisotropy profile of Fornax is tangential (β(r) < 0) and we estimate a total mass of M_{tot} = 1.613^{+0.050}_{-0.075} × 10^8 M_{⊙}, and a mass-to-light ratio of Υ_V = 8.93 ^{+0.32}_{-0.47} (M_{⊙}/L_{⊙}). The algorithm we present is a robust and computationally inexpensive method for non-parametric modelling of spherical clusters independent of the mass-anisotropy degeneracy.

Cleaning up the mess: cell corpse clearance in Caenorhabditis elegans.

PubMed

Pinto, Sérgio Morgado; Hengartner, Michael Otmar

2012-12-01

Genetic and cell biology studies have led to the identification in Caenorhabditis elegans of a set of evolutionary conserved cellular mechanisms responsible for the clearance of apoptotic cells. Based on the phenotype of cell corpse clearance mutants, corpse clearance can be divided into three distinct, but linked steps: corpse recognition, corpse internalization, and corpse degradation. Work in recent years has led to a better understanding of the molecular pathways that mediate each of these steps. Here, we review recent developments in our understanding of in vivo cell corpse clearance in this simple but most elegant model organism. Copyright © 2012 Elsevier Ltd. All rights reserved.

Multiobjective Aerodynamic Shape Optimization Using Pareto Differential Evolution and Generalized Response Surface Metamodels

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple, fast, and robust evolutionary algorithm that has proven effective in determining the global optimum for several difficult single-objective optimization problems. The DE algorithm has been recently extended to multiobjective optimization problem by using a Pareto-based approach. In this paper, a Pareto DE algorithm is applied to multiobjective aerodynamic shape optimization problems that are characterized by computationally expensive objective function evaluations. To improve computational expensive the algorithm is coupled with generalized response surface meta-models based on artificial neural networks. Results are presented for some test optimization problems from the literature to demonstrate the capabilities of the method.

Computer symbiosis: Emergence of symbiotic behavior through evolution

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

Ikegami, Takashi; Kaneko, Kunihiko

Symbiosis is altruistic cooperation between distinct species. It is one of the most effective evolutionary processes, but its dynamics are not well understood as yet. A simple model of symbiosis is introduced, where we consider interactions between hosts and parasites and also mutations of hosts and parasites. It is found that a symbiotic state emerges for a suitable range of mutation rates. The symbiotic state is not static, but dynamically oscillates. Harmful parasites violating symbiosis appear periodically, but are rapidly extinguished by hosts and other parasites, and the symbiotic state is recovered. The emergence of ''Tit for Tat'' strategy tomore » maintain symbiosis is discussed. 4 figs.« less

[Nonuniformity in the evolutionary rate in the virilis: II. group of Drosophilas: application of the method of Tajima's test].

PubMed

Kulikov, A M; Lazebnyĭ, O E; Chekunova, A I; Mitrofanov, V G

2010-01-01

The steadiness of the molecular clock was estimated in 11 Drosophila species of the virilis group by sequences of five genes by applying Tajima's Simple Method. The main characteristic of this method is the independence of its phylogenetic constructions. The obtained results have completely confirmed the conclusions drawn relying on the application of the two-cluster test and the Takezaki branch-length test. In addition, the deviation of the molecular clock has found confirmation in D. virilis evolutionary lineages.

Evolutionary space platform concept study. Volume 2, part A: SASP special emphasis trade studies

NASA Technical Reports Server (NTRS)

1982-01-01

Efforts are in progress to define an approach to provide a simple and cost effective solution to the problem of long duration space flight. This approach involves a Space Platform in low Earth orbit, which can be tended by the Space Shuttle and which will provide, for extended periods of time, stability, utilities and access for a variety of replaceable payloads. The feasibility of an evolutionary space system which would cost effectively support unmanned payloads in groups, using a Space Platform which provides centralized basic subsystems is addressed.

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.

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.

Establishment of the mathematical model for diagnosing the engine valve faults by genetic programming

NASA Astrophysics Data System (ADS)

Yang, Wen-Xian

2006-05-01

Available machine fault diagnostic methods show unsatisfactory performances on both on-line and intelligent analyses because their operations involve intensive calculations and are labour intensive. Aiming at improving this situation, this paper describes the development of an intelligent approach by using the Genetic Programming (abbreviated as GP) method. Attributed to the simple calculation of the mathematical model being constructed, different kinds of machine faults may be diagnosed correctly and quickly. Moreover, human input is significantly reduced in the process of fault diagnosis. The effectiveness of the proposed strategy is validated by an illustrative example, in which three kinds of valve states inherent in a six-cylinders/four-stroke cycle diesel engine, i.e. normal condition, valve-tappet clearance and gas leakage faults, are identified. In the example, 22 mathematical functions have been specially designed and 8 easily obtained signal features are used to construct the diagnostic model. Different from existing GPs, the diagnostic tree used in the algorithm is constructed in an intelligent way by applying a power-weight coefficient to each feature. The power-weight coefficients vary adaptively between 0 and 1 during the evolutionary process. Moreover, different evolutionary strategies are employed, respectively for selecting the diagnostic features and functions, so that the mathematical functions are sufficiently utilized and in the meantime, the repeated use of signal features may be fully avoided. The experimental results are illustrated diagrammatically in the following sections.

Leaf ontogeny and demography explain photosynthetic seasonality in Amazon evergreen forests

NASA Astrophysics Data System (ADS)

Wu, J.; Albert, L.; Lopes, A. P.; Restrepo-Coupe, N.; Hayek, M.; Wiedemann, K. T.; Guan, K.; Stark, S. C.; Prohaska, N.; Tavares, J. V.; Marostica, S. F.; Kobayashi, H.; Ferreira, M. L.; Campos, K.; Silva, R. D.; Brando, P. M.; Dye, D. G.; Huxman, T. E.; Huete, A. R.; Nelson, B. W.; Saleska, S. R.

2015-12-01

Photosynthetic seasonality couples the evolutionary ecology of plant leaves to large-scale rhythms of carbon and water exchanges that are important feedbacks to climate. However, the extent, magnitude, and controls on photosynthetic seasonality of carbon-rich tropical forests are poorly resolved, controversial in the remote sensing literature, and inadequately represented in most earth system models. Here we show that ecosystem-scale phenology (measured by photosynthetic capacity), rather than environmental seasonality, is the primary driver of photosynthetic seasonality at four Amazon evergreen forests spanning gradients in rainfall seasonality, forest composition, and flux seasonality. We further demonstrate that leaf ontogeny and demography explain most of this ecosystem phenology at two central Amazon evergreen forests, using a simple leaf-cohort canopy model that integrates eddy covariance-derived CO2 fluxes, novel near-surface camera-detected leaf phenology, and ground observations of litterfall and leaf physiology. The coordination of new leaf growth and old leaf divestment (litterfall) during the dry season shifts canopy composition towards younger leaves with higher photosynthetic efficiency, driving large seasonal increases (~27%) in ecosystem photosynthetic capacity. Leaf ontogeny and demography thus reconciles disparate observations of forest seasonality from leaves to eddy flux towers to satellites. Strategic incorporation of such whole-plant coordination processes as phenology and ontogeny will improve ecological, evolutionary and earth system theories describing tropical forests structure and function, allowing more accurate representation of forest dynamics and feedbacks to climate in earth system models.

The Independent Evolution Method Is Not a Viable Phylogenetic Comparative Method

PubMed Central

2015-01-01

Phylogenetic comparative methods (PCMs) use data on species traits and phylogenetic relationships to shed light on evolutionary questions. Recently, Smaers and Vinicius suggested a new PCM, Independent Evolution (IE), which purportedly employs a novel model of evolution based on Felsenstein’s Adaptive Peak Model. The authors found that IE improves upon previous PCMs by producing more accurate estimates of ancestral states, as well as separate estimates of evolutionary rates for each branch of a phylogenetic tree. Here, we document substantial theoretical and computational issues with IE. When data are simulated under a simple Brownian motion model of evolution, IE produces severely biased estimates of ancestral states and changes along individual branches. We show that these branch-specific changes are essentially ancestor-descendant or “directional” contrasts, and draw parallels between IE and previous PCMs such as “minimum evolution”. Additionally, while comparisons of branch-specific changes between variables have been interpreted as reflecting the relative strength of selection on those traits, we demonstrate through simulations that regressing IE estimated branch-specific changes against one another gives a biased estimate of the scaling relationship between these variables, and provides no advantages or insights beyond established PCMs such as phylogenetically independent contrasts. In light of our findings, we discuss the results of previous papers that employed IE. We conclude that Independent Evolution is not a viable PCM, and should not be used in comparative analyses. PMID:26683838

Fixation of strategies driven by switching probabilities in evolutionary games

NASA Astrophysics Data System (ADS)

Xu, Zimin; Zhang, Jianlei; Zhang, Chunyan; Chen, Zengqiang

2016-12-01

We study the evolutionary dynamics of strategies in finite populations which are homogeneous and well mixed by means of the pairwise comparison process, the core of which is the proposed switching probability. Previous studies about this subject are usually based on the known payoff comparison of the related players, which is an ideal assumption. In real social systems, acquiring the accurate payoffs of partners at each round of interaction may be not easy. So we bypass the need of explicit knowledge of payoffs, and encode the payoffs into the willingness of any individual shift from her current strategy to the competing one, and the switching probabilities are wholly independent of payoffs. Along this way, the strategy updating can be performed when game models are fixed and payoffs are unclear, expected to extend ideal assumptions to be more realistic one. We explore the impact of the switching probability on the fixation probability and derive a simple formula which determines the fixation probability. Moreover we find that cooperation dominates defection if the probability of cooperation replacing defection is always larger than the probability of defection replacing cooperation in finite populations. Last, we investigate the influences of model parameters on the fixation of strategies in the framework of three concrete game models: prisoner's dilemma, snowdrift game and stag-hunt game, which effectively portray the characteristics of cooperative dilemmas in real social systems.

Approaches to the structural modelling of insect wings.

PubMed Central

Wootton, R J; Herbert, R C; Young, P G; Evans, K E

2003-01-01

Insect wings lack internal muscles, and the orderly, necessary deformations which they undergo in flight and folding are in part remotely controlled, in part encoded in their structure. This factor is crucial in understanding their complex, extremely varied morphology. Models have proved particularly useful in clarifying the facilitation and control of wing deformation. Their development has followed a logical sequence from conceptual models through physical and simple analytical to numerical models. All have value provided their limitations are realized and constant comparisons made with the properties and mechanical behaviour of real wings. Numerical modelling by the finite element method is by far the most time-consuming approach, but has real potential in analysing the adaptive significance of structural details and interpreting evolutionary trends. Published examples are used to review the strengths and weaknesses of each category of model, and a summary is given of new work using finite element modelling to investigate the vibration properties and response to impact of hawkmoth wings. PMID:14561349

A stochastic evolutionary model generating a mixture of exponential distributions

NASA Astrophysics Data System (ADS)

Fenner, Trevor; Levene, Mark; Loizou, George

2016-02-01

Recent interest in human dynamics has stimulated the investigation of the stochastic processes that explain human behaviour in various contexts, such as mobile phone networks and social media. In this paper, we extend the stochastic urn-based model proposed in [T. Fenner, M. Levene, G. Loizou, J. Stat. Mech. 2015, P08015 (2015)] so that it can generate mixture models, in particular, a mixture of exponential distributions. The model is designed to capture the dynamics of survival analysis, traditionally employed in clinical trials, reliability analysis in engineering, and more recently in the analysis of large data sets recording human dynamics. The mixture modelling approach, which is relatively simple and well understood, is very effective in capturing heterogeneity in data. We provide empirical evidence for the validity of the model, using a data set of popular search engine queries collected over a period of 114 months. We show that the survival function of these queries is closely matched by the exponential mixture solution for our model.

Nascent life cycles and the emergence of higher-level individuality.

PubMed

Ratcliff, William C; Herron, Matthew; Conlin, Peter L; Libby, Eric

2017-12-05

Evolutionary transitions in individuality (ETIs) occur when formerly autonomous organisms evolve to become parts of a new, 'higher-level' organism. One of the first major hurdles that must be overcome during an ETI is the emergence of Darwinian evolvability in the higher-level entity (e.g. a multicellular group), and the loss of Darwinian autonomy in the lower-level units (e.g. individual cells). Here, we examine how simple higher-level life cycles are a key innovation during an ETI, allowing this transfer of fitness to occur 'for free'. Specifically, we show how novel life cycles can arise and lead to the origin of higher-level individuals by (i) mitigating conflicts between levels of selection, (ii) engendering the expression of heritable higher-level traits and (iii) allowing selection to efficiently act on these emergent higher-level traits. Further, we compute how canonical early life cycles vary in their ability to fix beneficial mutations via mathematical modelling. Life cycles that lack a persistent lower-level stage and develop clonally are far more likely to fix 'ratcheting' mutations that limit evolutionary reversion to the pre-ETI state. By stabilizing the fragile first steps of an evolutionary transition in individuality, nascent higher-level life cycles may play a crucial role in the origin of complex life.This article is part of the themed issue 'Process and pattern in innovations from cells to societies'. © 2017 The Author(s).

Evolutionary continuity and personhood: Legal and therapeutic implications of animal consciousness and human unconsciousness.

PubMed

Benvenuti, Anne

Convergent lines of research in the biological sciences have made obsolete the commonly held assumption that humans are distinct from and superior to all other animals, a development predicted by evolutionary science. Cumulative evidence has both elevated other animals from the status of "dumb brutes" to that of fully sentient and intentional beings and has simultaneously discredited elevated claims of human rationality, intentionality, and freedom from the constraints experienced by other animals. It follows then that any theoretical model in which humans occupy the top of an imagined evolutionary hierarchy is untenable. This simple fact calls for a rethinking of foundational concepts in law and health sciences. A further cultural fallacy that is exposed by these converging lines of scientific evidence is the notion that the subjective inner and abstract dimension of human beings is the most true and valuable level of analysis for organizing human lives. In fact, our individual and collective minds are particularly vulnerable to elaborated false narratives that may be definitive of the particular forms of suffering that humans experience and seek to heal with modalities like psychoanalytic psychotherapies. I conclude with the suggestion that other animals may have the capacity to help us with this healing project, even as we are ethically bound to heal the suffering that we have collectively imposed upon them. Copyright © 2016 Elsevier Ltd. All rights reserved.

Local Orientation and the Evolution of Foraging: Changes in Decision Making Can Eliminate Evolutionary Trade-offs

PubMed Central

van der Post, Daniel J.; Semmann, Dirk

2011-01-01

Information processing is a major aspect of the evolution of animal behavior. In foraging, responsiveness to local feeding opportunities can generate patterns of behavior which reflect or “recognize patterns” in the environment beyond the perception of individuals. Theory on the evolution of behavior generally neglects such opportunity-based adaptation. Using a spatial individual-based model we study the role of opportunity-based adaptation in the evolution of foraging, and how it depends on local decision making. We compare two model variants which differ in the individual decision making that can evolve (restricted and extended model), and study the evolution of simple foraging behavior in environments where food is distributed either uniformly or in patches. We find that opportunity-based adaptation and the pattern recognition it generates, plays an important role in foraging success, particularly in patchy environments where one of the main challenges is “staying in patches”. In the restricted model this is achieved by genetic adaptation of move and search behavior, in light of a trade-off on within- and between-patch behavior. In the extended model this trade-off does not arise because decision making capabilities allow for differentiated behavioral patterns. As a consequence, it becomes possible for properties of movement to be specialized for detection of patches with more food, a larger scale information processing not present in the restricted model. Our results show that changes in decision making abilities can alter what kinds of pattern recognition are possible, eliminate an evolutionary trade-off and change the adaptive landscape. PMID:21998571

Local orientation and the evolution of foraging: changes in decision making can eliminate evolutionary trade-offs.

PubMed

van der Post, Daniel J; Semmann, Dirk

2011-10-01

Information processing is a major aspect of the evolution of animal behavior. In foraging, responsiveness to local feeding opportunities can generate patterns of behavior which reflect or "recognize patterns" in the environment beyond the perception of individuals. Theory on the evolution of behavior generally neglects such opportunity-based adaptation. Using a spatial individual-based model we study the role of opportunity-based adaptation in the evolution of foraging, and how it depends on local decision making. We compare two model variants which differ in the individual decision making that can evolve (restricted and extended model), and study the evolution of simple foraging behavior in environments where food is distributed either uniformly or in patches. We find that opportunity-based adaptation and the pattern recognition it generates, plays an important role in foraging success, particularly in patchy environments where one of the main challenges is "staying in patches". In the restricted model this is achieved by genetic adaptation of move and search behavior, in light of a trade-off on within- and between-patch behavior. In the extended model this trade-off does not arise because decision making capabilities allow for differentiated behavioral patterns. As a consequence, it becomes possible for properties of movement to be specialized for detection of patches with more food, a larger scale information processing not present in the restricted model. Our results show that changes in decision making abilities can alter what kinds of pattern recognition are possible, eliminate an evolutionary trade-off and change the adaptive landscape.

Long-Branch Attraction Bias and Inconsistency in Bayesian Phylogenetics

PubMed Central

Kolaczkowski, Bryan; Thornton, Joseph W.

2009-01-01

Bayesian inference (BI) of phylogenetic relationships uses the same probabilistic models of evolution as its precursor maximum likelihood (ML), so BI has generally been assumed to share ML's desirable statistical properties, such as largely unbiased inference of topology given an accurate model and increasingly reliable inferences as the amount of data increases. Here we show that BI, unlike ML, is biased in favor of topologies that group long branches together, even when the true model and prior distributions of evolutionary parameters over a group of phylogenies are known. Using experimental simulation studies and numerical and mathematical analyses, we show that this bias becomes more severe as more data are analyzed, causing BI to infer an incorrect tree as the maximum a posteriori phylogeny with asymptotically high support as sequence length approaches infinity. BI's long branch attraction bias is relatively weak when the true model is simple but becomes pronounced when sequence sites evolve heterogeneously, even when this complexity is incorporated in the model. This bias—which is apparent under both controlled simulation conditions and in analyses of empirical sequence data—also makes BI less efficient and less robust to the use of an incorrect evolutionary model than ML. Surprisingly, BI's bias is caused by one of the method's stated advantages—that it incorporates uncertainty about branch lengths by integrating over a distribution of possible values instead of estimating them from the data, as ML does. Our findings suggest that trees inferred using BI should be interpreted with caution and that ML may be a more reliable framework for modern phylogenetic analysis. PMID:20011052

Long-branch attraction bias and inconsistency in Bayesian phylogenetics.

PubMed

Kolaczkowski, Bryan; Thornton, Joseph W

2009-12-09

Bayesian inference (BI) of phylogenetic relationships uses the same probabilistic models of evolution as its precursor maximum likelihood (ML), so BI has generally been assumed to share ML's desirable statistical properties, such as largely unbiased inference of topology given an accurate model and increasingly reliable inferences as the amount of data increases. Here we show that BI, unlike ML, is biased in favor of topologies that group long branches together, even when the true model and prior distributions of evolutionary parameters over a group of phylogenies are known. Using experimental simulation studies and numerical and mathematical analyses, we show that this bias becomes more severe as more data are analyzed, causing BI to infer an incorrect tree as the maximum a posteriori phylogeny with asymptotically high support as sequence length approaches infinity. BI's long branch attraction bias is relatively weak when the true model is simple but becomes pronounced when sequence sites evolve heterogeneously, even when this complexity is incorporated in the model. This bias--which is apparent under both controlled simulation conditions and in analyses of empirical sequence data--also makes BI less efficient and less robust to the use of an incorrect evolutionary model than ML. Surprisingly, BI's bias is caused by one of the method's stated advantages--that it incorporates uncertainty about branch lengths by integrating over a distribution of possible values instead of estimating them from the data, as ML does. Our findings suggest that trees inferred using BI should be interpreted with caution and that ML may be a more reliable framework for modern phylogenetic analysis.

Strategies and Rubrics for Teaching Complex Systems Theory to Novices (Invited)

NASA Astrophysics Data System (ADS)

Fichter, L. S.

2010-12-01

Bifurcation. Self-similarity. Fractal. Sensitive dependent. Agents. Self-organized criticality. Avalanche behavior. Power laws. Strange attractors. Emergence. The language of complexity is fundamentally different from the language of equilibrium. If students do not know these phenomena, and what they tell us about the pulse of dynamic systems, complex systems will be opaque. A complex system is a group of agents. (individual interacting units, like birds in a flock, sand grains in a ripple, or individual friction units along a fault zone), existing far from equilibrium, interacting through positive and negative feedbacks, following simple rules, forming interdependent, dynamic, evolutionary networks. Complex systems produce behaviors that cannot be predicted deductively from knowledge of the behaviors of the individual components themselves; they must be experienced. What complexity theory demonstrates is that, by following simple rules, all the agents end up coordinating their behavior—self organizing—so that what emerges is not chaos, but meaningful patterns. How can we introduce Freshman, non-science, general education students to complex systems theories, in 3 to 5 classes; in a way they really get it, and can use the principles to understand real systems? Complex systems theories are not a series of unconnected or disconnected equations or models; they are developed as narratives that makes sense of how all the pieces and properties are interrelated. The principles of complex systems must be taught as deliberately and systematically as the equilibrium principles normally taught; as, say, the systematic training from pre-algebra and geometry to algebra. We have developed a sequence of logically connected narratives (strategies and rubrics) that introduce complex systems principles using models that can be simulated in a computer, in class, in real time. The learning progression has a series of 12 models (e.g. logistic system, bifurcation diagrams, genetic algorithms, etc.) leading to 19 learning outcomes that encompass most of the universality properties that characterize complex systems. They are developed in a specific order to achieve specific ends of understanding. We use these models in various depths and formats in courses ranging from gened courses, to evolutionary systems and environmental systems, to upper level geology courses. Depending on the goals of a course, the learning outcomes can be applied to understanding many other complex systems; e.g. oscillating chemical reactions (reaction-diffusion and activator-inhibitor systems), autocatalytic networks, hysteresis (bistable) systems, networks, and the rise/collapse of complex societies. We use these and other complex systems concepts in various classes to talk about the origin of life, ecosystem organization, game theory, extinction events, and environmental system behaviors. The applications are almost endless. The complete learning progression with models, computer programs, experiments, and learning outcomes is available at: www.jmu.edu/geology/ComplexEvolutionarySystems/

Spatial competition and price formation

NASA Astrophysics Data System (ADS)

Nagel, Kai; Shubik, Martin; Paczuski, Maya; Bak, Per

2000-12-01

We look at price formation in a retail setting, that is, companies set prices, and consumers either accept prices or go someplace else. In contrast to most other models in this context, we use a two-dimensional spatial structure for information transmission, that is, consumers can only learn from nearest neighbors. Many aspects of this can be understood in terms of generalized evolutionary dynamics. In consequence, we first look at spatial competition and cluster formation without price. This leads to establishement size distributions, which we compare to reality. After some theoretical considerations, which at least heuristically explain our simulation results, we finally return to price formation, where we demonstrate that our simple model with nearly no organized planning or rationality on the part of any of the agents indeed leads to an economically plausible price.

Using the MWC model to describe heterotropic interactions in hemoglobin

PubMed Central

Rapp, Olga

2017-01-01

Hemoglobin is a classical model allosteric protein. Research on hemoglobin parallels the development of key cooperativity and allostery concepts, such as the ‘all-or-none’ Hill formalism, the stepwise Adair binding formulation and the concerted Monod-Wymann-Changuex (MWC) allosteric model. While it is clear that the MWC model adequately describes the cooperative binding of oxygen to hemoglobin, rationalizing the effects of H+, CO2 or organophosphate ligands on hemoglobin-oxygen saturation using the same model remains controversial. According to the MWC model, allosteric ligands exert their effect on protein function by modulating the quaternary conformational transition of the protein. However, data fitting analysis of hemoglobin oxygen saturation curves in the presence or absence of inhibitory ligands persistently revealed effects on both relative oxygen affinity (c) and conformational changes (L), elementary MWC parameters. The recent realization that data fitting analysis using the traditional MWC model equation may not provide reliable estimates for L and c thus calls for a re-examination of previous data using alternative fitting strategies. In the current manuscript, we present two simple strategies for obtaining reliable estimates for MWC mechanistic parameters of hemoglobin steady-state saturation curves in cases of both evolutionary and physiological variations. Our results suggest that the simple MWC model provides a reasonable description that can also account for heterotropic interactions in hemoglobin. The results, moreover, offer a general roadmap for successful data fitting analysis using the MWC model. PMID:28793329

Evolutionary transition from biological to social systems via generation of reflexive models of externality.

PubMed

Igamberdiev, Abir U

2017-12-01

Evolutionary transition from biological to social systems corresponds to the emergence of the structure of subject that incorporates the internal image of the external world. This structure, established on the basis of referral of the subject (self) to its symbolic image, acquires a potential to rationally describe the external world through the semiotic structure of human language. It has been modelled in reflexive psychology using the algebra of simple relations (Lefebvre, V.A., J. Soc. Biol. Struct. 10, 129-175, 1987). The model introduces a substantial opposition of the two basic complementary types of reflexion defined as Western (W) and Eastern (E). These types generate opposite models of behavior and opposite organizations of societies. Development of human societies involves the interactions of W and E types not only between the societies but also within one society underlying its homeostasis and dynamics. Invention of new ideas and implementation of new technologies shift the probability pattern of reflexive choices, appearing as internal assessments of the individual agents within a society, and direct changes in the preference of reflexive types. The dynamics of societies and of interactions between societies is based on the interference of opposite reflexive structures and on the establishment of different patterns during such interference. At different times in the history of human civilization these changing patterns resulted in the formation and splitting of large empires, the development and spreading of new technologies, the consecutive periods of wellness and decline. Copyright © 2017 Elsevier Ltd. All rights reserved.

Does High-Dose Antimicrobial Chemotherapy Prevent the Evolution of Resistance?

PubMed Central

Day, Troy; Read, Andrew F.

2016-01-01

High-dose chemotherapy has long been advocated as a means of controlling drug resistance in infectious diseases but recent empirical studies have begun to challenge this view. We develop a very general framework for modeling and understanding resistance emergence based on principles from evolutionary biology. We use this framework to show how high-dose chemotherapy engenders opposing evolutionary processes involving the mutational input of resistant strains and their release from ecological competition. Whether such therapy provides the best approach for controlling resistance therefore depends on the relative strengths of these processes. These opposing processes typically lead to a unimodal relationship between drug pressure and resistance emergence. As a result, the optimal drug dose lies at either end of the therapeutic window of clinically acceptable concentrations. We illustrate our findings with a simple model that shows how a seemingly minor change in parameter values can alter the outcome from one where high-dose chemotherapy is optimal to one where using the smallest clinically effective dose is best. A review of the available empirical evidence provides broad support for these general conclusions. Our analysis opens up treatment options not currently considered as resistance management strategies, and it also simplifies the experiments required to determine the drug doses which best retard resistance emergence in patients. PMID:26820986

Does High-Dose Antimicrobial Chemotherapy Prevent the Evolution of Resistance?

PubMed

Day, Troy; Read, Andrew F

2016-01-01

High-dose chemotherapy has long been advocated as a means of controlling drug resistance in infectious diseases but recent empirical studies have begun to challenge this view. We develop a very general framework for modeling and understanding resistance emergence based on principles from evolutionary biology. We use this framework to show how high-dose chemotherapy engenders opposing evolutionary processes involving the mutational input of resistant strains and their release from ecological competition. Whether such therapy provides the best approach for controlling resistance therefore depends on the relative strengths of these processes. These opposing processes typically lead to a unimodal relationship between drug pressure and resistance emergence. As a result, the optimal drug dose lies at either end of the therapeutic window of clinically acceptable concentrations. We illustrate our findings with a simple model that shows how a seemingly minor change in parameter values can alter the outcome from one where high-dose chemotherapy is optimal to one where using the smallest clinically effective dose is best. A review of the available empirical evidence provides broad support for these general conclusions. Our analysis opens up treatment options not currently considered as resistance management strategies, and it also simplifies the experiments required to determine the drug doses which best retard resistance emergence in patients.

Modelling Evolutionary Algorithms with Stochastic Differential Equations.

PubMed

Heredia, Jorge Pérez

2017-11-20

There has been renewed interest in modelling the behaviour of evolutionary algorithms (EAs) by more traditional mathematical objects, such as ordinary differential equations or Markov chains. The advantage is that the analysis becomes greatly facilitated due to the existence of well established methods. However, this typically comes at the cost of disregarding information about the process. Here, we introduce the use of stochastic differential equations (SDEs) for the study of EAs. SDEs can produce simple analytical results for the dynamics of stochastic processes, unlike Markov chains which can produce rigorous but unwieldy expressions about the dynamics. On the other hand, unlike ordinary differential equations (ODEs), they do not discard information about the stochasticity of the process. We show that these are especially suitable for the analysis of fixed budget scenarios and present analogues of the additive and multiplicative drift theorems from runtime analysis. In addition, we derive a new more general multiplicative drift theorem that also covers non-elitist EAs. This theorem simultaneously allows for positive and negative results, providing information on the algorithm's progress even when the problem cannot be optimised efficiently. Finally, we provide results for some well-known heuristics namely Random Walk (RW), Random Local Search (RLS), the (1+1) EA, the Metropolis Algorithm (MA), and the Strong Selection Weak Mutation (SSWM) algorithm.

Spatial heterogeneity lowers rather than increases host-parasite specialization.

PubMed

Hesse, E; Best, A; Boots, M; Hall, A R; Buckling, A

2015-09-01

Abiotic environmental heterogeneity can promote the evolution of diverse resource specialists, which in turn may increase the degree of host-parasite specialization. We coevolved Pseudomonas fluorescens and lytic phage ϕ2 in spatially structured populations, each consisting of two interconnected subpopulations evolving in the same or different nutrient media (homogeneous and heterogeneous environments, respectively). Counter to the normal expectation, host-parasite specialization was significantly lower in heterogeneous compared with homogeneous environments. This result could not be explained by dispersal homogenizing populations, as this would have resulted in the heterogeneous treatments having levels of specialization equal to or greater than that of the homogeneous environments. We argue that selection for costly generalists is greatest when the coevolving species are exposed to diverse environmental conditions and that this can provide an explanation for our results. A simple coevolutionary model of this process suggests that this can be a general mechanism by which environmental heterogeneity can reduce rather than increase host-parasite specialization. © 2015 The Authors. J. EVOL. BIOL. Journal of Evolutionary Biology Published by John Wiley & Sons Ltd on Behalf of European Society for Evolutionary Biology.

Modelling formulations using gene expression programming--a comparative analysis with artificial neural networks.

PubMed

Colbourn, E A; Roskilly, S J; Rowe, R C; York, P

2011-10-09

This study has investigated the utility and potential advantages of gene expression programming (GEP)--a new development in evolutionary computing for modelling data and automatically generating equations that describe the cause-and-effect relationships in a system--to four types of pharmaceutical formulation and compared the models with those generated by neural networks, a technique now widely used in the formulation development. Both methods were capable of discovering subtle and non-linear relationships within the data, with no requirement from the user to specify the functional forms that should be used. Although the neural networks rapidly developed models with higher values for the ANOVA R(2) these were black box and provided little insight into the key relationships. However, GEP, although significantly slower at developing models, generated relatively simple equations describing the relationships that could be interpreted directly. The results indicate that GEP can be considered an effective and efficient modelling technique for formulation data. Copyright © 2011 Elsevier B.V. All rights reserved.

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

GIGA: a simple, efficient algorithm for gene tree inference in the genomic age

PubMed Central

2010-01-01

Background Phylogenetic relationships between genes are not only of theoretical interest: they enable us to learn about human genes through the experimental work on their relatives in numerous model organisms from bacteria to fruit flies and mice. Yet the most commonly used computational algorithms for reconstructing gene trees can be inaccurate for numerous reasons, both algorithmic and biological. Additional information beyond gene sequence data has been shown to improve the accuracy of reconstructions, though at great computational cost. Results We describe a simple, fast algorithm for inferring gene phylogenies, which makes use of information that was not available prior to the genomic age: namely, a reliable species tree spanning much of the tree of life, and knowledge of the complete complement of genes in a species' genome. The algorithm, called GIGA, constructs trees agglomeratively from a distance matrix representation of sequences, using simple rules to incorporate this genomic age information. GIGA makes use of a novel conceptualization of gene trees as being composed of orthologous subtrees (containing only speciation events), which are joined by other evolutionary events such as gene duplication or horizontal gene transfer. An important innovation in GIGA is that, at every step in the agglomeration process, the tree is interpreted/reinterpreted in terms of the evolutionary events that created it. Remarkably, GIGA performs well even when using a very simple distance metric (pairwise sequence differences) and no distance averaging over clades during the tree construction process. Conclusions GIGA is efficient, allowing phylogenetic reconstruction of very large gene families and determination of orthologs on a large scale. It is exceptionally robust to adding more gene sequences, opening up the possibility of creating stable identifiers for referring to not only extant genes, but also their common ancestors. We compared trees produced by GIGA to those in the TreeFam database, and they were very similar in general, with most differences likely due to poor alignment quality. However, some remaining differences are algorithmic, and can be explained by the fact that GIGA tends to put a larger emphasis on minimizing gene duplication and deletion events. PMID:20534164

GIGA: a simple, efficient algorithm for gene tree inference in the genomic age.

PubMed

Thomas, Paul D

2010-06-09

Phylogenetic relationships between genes are not only of theoretical interest: they enable us to learn about human genes through the experimental work on their relatives in numerous model organisms from bacteria to fruit flies and mice. Yet the most commonly used computational algorithms for reconstructing gene trees can be inaccurate for numerous reasons, both algorithmic and biological. Additional information beyond gene sequence data has been shown to improve the accuracy of reconstructions, though at great computational cost. We describe a simple, fast algorithm for inferring gene phylogenies, which makes use of information that was not available prior to the genomic age: namely, a reliable species tree spanning much of the tree of life, and knowledge of the complete complement of genes in a species' genome. The algorithm, called GIGA, constructs trees agglomeratively from a distance matrix representation of sequences, using simple rules to incorporate this genomic age information. GIGA makes use of a novel conceptualization of gene trees as being composed of orthologous subtrees (containing only speciation events), which are joined by other evolutionary events such as gene duplication or horizontal gene transfer. An important innovation in GIGA is that, at every step in the agglomeration process, the tree is interpreted/reinterpreted in terms of the evolutionary events that created it. Remarkably, GIGA performs well even when using a very simple distance metric (pairwise sequence differences) and no distance averaging over clades during the tree construction process. GIGA is efficient, allowing phylogenetic reconstruction of very large gene families and determination of orthologs on a large scale. It is exceptionally robust to adding more gene sequences, opening up the possibility of creating stable identifiers for referring to not only extant genes, but also their common ancestors. We compared trees produced by GIGA to those in the TreeFam database, and they were very similar in general, with most differences likely due to poor alignment quality. However, some remaining differences are algorithmic, and can be explained by the fact that GIGA tends to put a larger emphasis on minimizing gene duplication and deletion events.

Tachyon cosmology with non-vanishing minimum potential: a unified model

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

Li, Huiquan, E-mail: hqli@ustc.edu.cn

2012-07-01

We investigate the tachyon condensation process in the effective theory with non-vanishing minimum potential and its implications to cosmology. It is shown that the tachyon condensation on an unstable three-brane described by this modified tachyon field theory leads to lower-dimensional branes (defects) forming within a stable three-brane. Thus, in the cosmological background, we can get well-behaved tachyon matter after tachyon inflation, (partially) avoiding difficulties encountered in the original tachyon cosmological models. This feature also implies that the tachyon inflated and reheated universe is followed by a Chaplygin gas dark matter and dark energy universe. Hence, such an unstable three-brane behavesmore » quite like our universe, reproducing the key features of the whole evolutionary history of the universe and providing a unified description of inflaton, dark matter and dark energy in a very simple single-scalar field model.« less

Social dilemmas among supergenes: intragenomic sexual conflict and a selfing solution in Oenothera.

PubMed

Brown, Sam P; Levin, Donald A

2011-12-01

Recombination is a powerful policing mechanism to control intragenomic cheats. The "parliament of the genes" can often rapidly block driving genes from cheating during meiosis. But what if the genome parliament is reduced to only two members, or supergenes? Using a series of simple game-theoretic models inspired by the peculiar genetics of Oenothera sp., we illustrate that a two supergene genome (α and β) can produce a number of surprising evolutionary dynamics, including increases in lineage longevity following a transition from sexuality (outcrossing) to asexuality (clonal self-fertilization). We end by interpreting the model in the broader context of the evolution of mutualism, which highlights that greater α, β cooperation in the self-fertilizing model can be viewed as an example of partner fidelity driving multilineage cooperation. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

How did the swiss cheese plant get its holes?

PubMed

Muir, Christopher D

2013-02-01

Adult leaf fenestration in "Swiss cheese" plants (Monstera Adans.) is an unusual leaf shape trait lacking a convincing evolutionary explanation. Monstera are secondary hemiepiphytes that inhabit the understory of tropical rainforests, where photosynthesis from sunflecks often makes up a large proportion of daily carbon assimilation. Here I present a simple model of leaf-level photosynthesis and whole-plant canopy dynamics in a stochastic light environment. The model demonstrates that leaf fenestration can reduce the variance in plant growth and thereby increase geometric mean fitness. This growth-variance hypothesis also suggests explanations for conspicuous ontogenetic changes in leaf morphology (heteroblasty) in Monstera, as well as the absence of leaf fenestration in co-occurring juvenile tree species. The model provides a testable hypothesis of the adaptive significance of a unique leaf shape and illustrates how variance in growth rate could be an important factor shaping plant morphology and physiology.

Charophytes: Evolutionary Giants and Emerging Model Organisms

PubMed Central

Domozych, David S.; Popper, Zoë A.; Sørensen, Iben

2016-01-01

Charophytes are the group of green algae whose ancestral lineage gave rise to land plants in what resulted in a profoundly transformative event in the natural history of the planet. Extant charophytes exhibit many features that are similar to those found in land plants and their relatively simple phenotypes make them efficacious organisms for the study of many fundamental biological phenomena. Several taxa including Micrasterias, Penium, Chara, and Coleochaete are valuable model organisms for the study of cell biology, development, physiology and ecology of plants. New and rapidly expanding molecular studies are increasing the use of charophytes that in turn, will dramatically enhance our understanding of the evolution of plants and the adaptations that allowed for survival on land. The Frontiers in Plant Science series on “Charophytes” provides an assortment of new research reports and reviews on charophytes and their emerging significance as model plants. PMID:27777578

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.

Wealth distribution of simple exchange models coupled with extremal dynamics

NASA Astrophysics Data System (ADS)

Bagatella-Flores, N.; Rodríguez-Achach, M.; Coronel-Brizio, H. F.; Hernández-Montoya, A. R.

2015-01-01

Punctuated Equilibrium (PE) states that after long periods of evolutionary quiescence, species evolution can take place in short time intervals, where sudden differentiation makes new species emerge and some species extinct. In this paper, we introduce and study the effect of punctuated equilibrium on two different asset exchange models: the yard sale model (YS, winner gets a random fraction of a poorer player's wealth) and the theft and fraud model (TF, winner gets a random fraction of the loser's wealth). The resulting wealth distribution is characterized using the Gini index. In order to do this, we consider PE as a perturbation with probability ρ of being applied. We compare the resulting values of the Gini index at different increasing values of ρ in both models. We found that in the case of the TF model, the Gini index reduces as the perturbation ρ increases, not showing dependence with the agents number. While for YS we observe a phase transition which happens around ρc = 0.79. For perturbations ρ <ρc the Gini index reaches the value of one as time increases (an extreme wealth condensation state), whereas for perturbations greater than or equal to ρc the Gini index becomes different to one, avoiding the system reaches this extreme state. We show that both simple exchange models coupled with PE dynamics give more realistic results. In particular for YS, we observe a power low decay of wealth distribution.

Adaptive behaviors in multi-agent source localization using passive sensing.

PubMed

Shaukat, Mansoor; Chitre, Mandar

2016-12-01

In this paper, the role of adaptive group cohesion in a cooperative multi-agent source localization problem is investigated. A distributed source localization algorithm is presented for a homogeneous team of simple agents. An agent uses a single sensor to sense the gradient and two sensors to sense its neighbors. The algorithm is a set of individualistic and social behaviors where the individualistic behavior is as simple as an agent keeping its previous heading and is not self-sufficient in localizing the source. Source localization is achieved as an emergent property through agent's adaptive interactions with the neighbors and the environment. Given a single agent is incapable of localizing the source, maintaining team connectivity at all times is crucial. Two simple temporal sampling behaviors, intensity-based-adaptation and connectivity-based-adaptation, ensure an efficient localization strategy with minimal agent breakaways. The agent behaviors are simultaneously optimized using a two phase evolutionary optimization process. The optimized behaviors are estimated with analytical models and the resulting collective behavior is validated against the agent's sensor and actuator noise, strong multi-path interference due to environment variability, initialization distance sensitivity and loss of source signal.

Selfish genes, pleiotropy and the origin of recombination.

PubMed Central

Hey, J

1998-01-01

If multiple linked polymorphisms are under natural selection, then conflicts arise and the efficiency of natural selection is hindered relative to the case of no linkage. This simple interaction between linkage and natural selection creates an opportunity for mutations that raise the level of recombination to increase in frequency and have an enhanced chance of fixation. This important finding by S. Otto and N. Barton means that mutations that raise the recombination rate, but are otherwise neutral, will be selectively favored under fairly general circumstances of multilocus selection and linkage. The effect described by Otto and Barton, which was limited to neutral modifiers, can also be extended to include all modifiers of recombination, both beneficial and deleterious. Computer simulations show that beneficial mutations that also increase recombination have an increased chance of fixation. Similarly, deleterious mutations that also decrease recombination have an increased chance of fixation. The results suggest that a simple model of recombination modifiers, including both neutral and pleiotropic modifiers, is a necessary explanation for the evolutionary origin of recombination. PMID:9691060

Laughter as a scientific problem: An adventure in sidewalk neuroscience.

PubMed

Provine, Robert R

2016-06-01

Laughter is a stereotyped, innate, human play vocalization that provides an ideal simple system for neurobehavioral analyses of the sort usually associated with such animal models as walking, wing-flapping, and bird song. Laughter research is in its early stages, where the frontiers are near and accessible to simple observational procedures termed "sidewalk neuroscience." The basic, nontechnical approach of describing the act of laughter and when humans do it has revealed a variety of phenomena of social and neurological significance. Findings include the acoustic structure of laughter, the minimal voluntary control of laughter, contagiousness, the "punctuation effect" that describes the placement of laughter in conversation, the dominance of speech over laughter, the role of breath control in the evolution of speech, the evolutionary trajectory of laughter in primates, and the role of laughter in human matching and mating. If one knows where to look and how to see, advances in neuroscience are accessible to anyone and require minimal resources. © 2015 Wiley Periodicals, Inc.

Detecting and Analyzing Genetic Recombination Using RDP4.

PubMed

Martin, Darren P; Murrell, Ben; Khoosal, Arjun; Muhire, Brejnev

2017-01-01

Recombination between nucleotide sequences is a major process influencing the evolution of most species on Earth. The evolutionary value of recombination has been widely debated and so too has its influence on evolutionary analysis methods that assume nucleotide sequences replicate without recombining. When nucleic acids recombine, the evolution of the daughter or recombinant molecule cannot be accurately described by a single phylogeny. This simple fact can seriously undermine the accuracy of any phylogenetics-based analytical approach which assumes that the evolutionary history of a set of recombining sequences can be adequately described by a single phylogenetic tree. There are presently a large number of available methods and associated computer programs for analyzing and characterizing recombination in various classes of nucleotide sequence datasets. Here we examine the use of some of these methods to derive and test recombination hypotheses using multiple sequence alignments.

A multi-objective genetic algorithm for a mixed-model assembly U-line balancing type-I problem considering human-related issues, training, and learning

NASA Astrophysics Data System (ADS)

Rabbani, Masoud; Montazeri, Mona; Farrokhi-Asl, Hamed; Rafiei, Hamed

2016-12-01

Mixed-model assembly lines are increasingly accepted in many industrial environments to meet the growing trend of greater product variability, diversification of customer demands, and shorter life cycles. In this research, a new mathematical model is presented considering balancing a mixed-model U-line and human-related issues, simultaneously. The objective function consists of two separate components. The first part of the objective function is related to balance problem. In this part, objective functions are minimizing the cycle time, minimizing the number of workstations, and maximizing the line efficiencies. The second part is related to human issues and consists of hiring cost, firing cost, training cost, and salary. To solve the presented model, two well-known multi-objective evolutionary algorithms, namely non-dominated sorting genetic algorithm and multi-objective particle swarm optimization, have been used. A simple solution representation is provided in this paper to encode the solutions. Finally, the computational results are compared and analyzed.

Genealogical and evolutionary inference with the human Y chromosome.

PubMed

Stumpf, M P; Goldstein, D B

2001-03-02

Population genetics has emerged as a powerful tool for unraveling human history. In addition to the study of mitochondrial and autosomal DNA, attention has recently focused on Y-chromosome variation. Ambiguities and inaccuracies in data analysis, however, pose an important obstacle to further development of the field. Here we review the methods available for genealogical inference using Y-chromosome data. Approaches can be divided into those that do and those that do not use an explicit population model in genealogical inference. We describe the strengths and weaknesses of these model-based and model-free approaches, as well as difficulties associated with the mutation process that affect both methods. In the case of genealogical inference using microsatellite loci, we use coalescent simulations to show that relatively simple generalizations of the mutation process can greatly increase the accuracy of genealogical inference. Because model-free and model-based approaches have different biases and limitations, we conclude that there is considerable benefit in the continued use of both types of approaches.

Assortative mating and mutation diffusion in spatial evolutionary systems

NASA Astrophysics Data System (ADS)

Paley, C. J.; Taraskin, S. N.; Elliott, S. R.

2010-04-01

The influence of spatial structure on the equilibrium properties of a sexual population model defined on networks is studied numerically. Using a small-world-like topology of the networks as an investigative tool, the contributions to the fitness of assortative mating and of global mutant spread properties are considered. Simple measures of nearest-neighbor correlations and speed of spread of mutants through the system have been used to confirm that both of these dynamics are important contributory factors to the fitness. It is found that assortative mating increases the fitness of populations. Quick global spread of favorable mutations is shown to be a key factor increasing the equilibrium fitness of populations.

[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.

Marr's levels and the minimalist program.

PubMed

Johnson, Mark

2017-02-01

A simple change to a cognitive system at Marr's computational level may entail complex changes at the other levels of description of the system. The implementational level complexity of a change, rather than its computational level complexity, may be more closely related to the plausibility of a discrete evolutionary event causing that change. Thus the formal complexity of a change at the computational level may not be a good guide to the plausibility of an evolutionary event introducing that change. For example, while the Minimalist Program's Merge is a simple formal operation (Berwick & Chomsky, 2016), the computational mechanisms required to implement the language it generates (e.g., to parse the language) may be considerably more complex. This has implications for the theory of grammar: theories of grammar which involve several kinds of syntactic operations may be no less evolutionarily plausible than a theory of grammar that involves only one. A deeper understanding of human language at the algorithmic and implementational levels could strengthen Minimalist Program's account of the evolution of language.

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.

Investigation of a protein complex network

NASA Astrophysics Data System (ADS)

Mashaghi, A. R.; Ramezanpour, A.; Karimipour, V.

2004-09-01

The budding yeast Saccharomyces cerevisiae is the first eukaryote whose genome has been completely sequenced. It is also the first eukaryotic cell whose proteome (the set of all proteins) and interactome (the network of all mutual interactions between proteins) has been analyzed. In this paper we study the structure of the yeast protein complex network in which weighted edges between complexes represent the number of shared proteins. It is found that the network of protein complexes is a small world network with scale free behavior for many of its distributions. However we find that there are no strong correlations between the weights and degrees of neighboring complexes. To reveal non-random features of the network we also compare it with a null model in which the complexes randomly select their proteins. Finally we propose a simple evolutionary model based on duplication and divergence of proteins.

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.

Genetic change and rates of cladogenesis

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

Avise, J.C.; Ayala, F.J.

1975-12-01

Models are introduced which predict ratios of mean levels of genetic divergence in species-rich versus species-poor phylads under two competing assumptions: (1) genetic differentiation is a function of time, unrelated to the number of cladogenetic events and (2) genetic differentiation is proportional to the number of speciation events in the group. The models are simple, general, and biologically real, but not precise. They lead to qualitatively distinct predictions about levels of genetic divergence depending upon the relationship between rates of speciation and amount of genetic change. When genetic distance between species is a function of time, mean genetic distances inmore » speciose and depauperate phylads of equal evolutionary age are very similar. On the contrary, when genetic distance is a function of the number of speciations in the history of a phylad, the ratio of mean genetic distances separating species in speciose versus depauperate phylads is greater than one, and increases rapidly as the frequency of speciations in one group relative to the other increases. The models may be tested with data from natural populations to assess (1) possible correlations between rates of anagenesis and cladogenesis and (2) the amount of genetic differentiation accompanying the speciation process. The data collected in electrophoretic surveys and other kinds of studies can be used to test the predictions of the models. For this purpose genetic distances need to be measured in speciose and depauperate phylads of equal evolutionary age. The limited information presently available agrees better with the model predicting that genetic change is primarily a function of time, and is not correlated with rates of speciation. Further testing of the models is, however, required before firm conclusions can be drawn. (auth)« less

Mass and Environment as Drivers of Galaxy Evolution: Simplicity and its Consequences

NASA Astrophysics Data System (ADS)

Peng, Yingjie

2012-01-01

The galaxy population appears to be composed of infinitely complex different types and properties at first sight, however, when large samples of galaxies are studied, it appears that the vast majority of galaxies just follow simple scaling relations and similar evolutional modes while the outliers represent some minority. The underlying simplicities of the interrelationships among stellar mass, star formation rate and environment are seen in SDSS and zCOSMOS. We demonstrate that the differential effects of mass and environment are completely separable to z 1, indicating that two distinct physical processes are operating, namely the "mass quenching" and "environment quenching". These two simple quenching processes, plus some additional quenching due to merging, then naturally produce the Schechter form of the galaxy stellar mass functions and make quantitative predictions for the inter-relationships between the Schechter parameters of star-forming and passive galaxies in different environments. All of these detailed quantitative relationships are indeed seen, to very high precision, in SDSS, lending strong support to our simple empirically-based model. The model also offers qualitative explanations for the "anti-hierarchical" age-mass relation and the alpha-enrichment patterns for passive galaxies and makes some other testable predictions such as the mass function of the population of transitory objects that are in the process of being quenched, the galaxy major- and minor-merger rates, the galaxy stellar mass assembly history, star formation history and etc. Although still purely phenomenological, the model makes clear what the evolutionary characteristics of the relevant physical processes must in fact be.

Two gut community enterotypes recur in diverse bumblebee species

USDA-ARS?s Scientific Manuscript database

Pollinating insects are key to the evolutionary and ecological success of flowering plants and enable much of the diversity in the human diet. Gut microbial communities likely impact pollinators in diverse ways, from nutrition to defense against disease. Honeybees and bumblebees harbor a simple yet ...

Sex-ratio control erodes sexual selection, revealing evolutionary feedback from adaptive plasticity.

PubMed

Fawcett, Tim W; Kuijper, Bram; Weissing, Franz J; Pen, Ido

2011-09-20

Female choice is a powerful selective force, driving the elaboration of conspicuous male ornaments. This process of sexual selection has profound implications for many life-history decisions, including sex allocation. For example, females with attractive partners should produce more sons, because these sons will inherit their father's attractiveness and enjoy high mating success, thereby yielding greater fitness returns than daughters. However, previous research has overlooked the fact that there is a reciprocal feedback from life-history strategies to sexual selection. Here, using a simple mathematical model, we show that if mothers adaptively control offspring sex in relation to their partner's attractiveness, sexual selection is weakened and male ornamentation declines. This weakening occurs because the ability to determine offspring sex reduces the fitness difference between females with attractive and unattractive partners. We use individual-based, evolutionary simulations to show that this result holds under more biologically realistic conditions. Sexual selection and sex allocation thus interact in a dynamic fashion: The evolution of conspicuous male ornaments favors sex-ratio adjustment, but this conditional strategy then undermines the very same process that generated it, eroding sexual selection. We predict that, all else being equal, the most elaborate sexual displays should be seen in species with little or no control over offspring sex. The feedback process we have described points to a more general evolutionary principle, in which a conditional strategy weakens directional selection on another trait by reducing fitness differences.

The place of development in mathematical evolutionary theory.

PubMed

Rice, Sean H

2012-09-01

Development plays a critical role in structuring the joint offspring-parent phenotype distribution. It thus must be part of any truly general evolutionary theory. Historically, the offspring-parent distribution has often been treated in such a way as to bury the contribution of development, by distilling from it a single term, either heritability or additive genetic variance, and then working only with this term. I discuss two reasons why this approach is no longer satisfactory. First, the regression of expected offspring phenotype on parent phenotype can easily be nonlinear, and this nonlinearity can have a pronounced impact on the response to selection. Second, even when the offspring-parent regression is linear, it is nearly always a function of the environment, and the precise way that heritability covaries with the environment can have a substantial effect on adaptive evolution. Understanding these complexities of the offspring-parent distribution will require understanding of the developmental processes underlying the traits of interest. I briefly discuss how we can incorporate such complexity into formal evolutionary theory, and why it is likely to be important even for traits that are not traditionally the focus of evo-devo research. Finally, I briefly discuss a topic that is widely seen as being squarely in the domain of evo-devo: novelty. I argue that the same conceptual and mathematical framework that allows us to incorporate developmental complexity into simple models of trait evolution also yields insight into the evolution of novel traits. Copyright © 2011 Wiley Periodicals, Inc., A Wiley Company.

Precise Measurements of the Cosmic Ray Antiproton Spectrum with BESS Including the Effects of Solar Modulation

NASA Technical Reports Server (NTRS)

Mitchell, J. W.; Abe, K.; Anraku, K.; Asaoka, Y.; Fujikawa, M.; Fuke, H.; Haino, S.; Hams, T.; Ikeda, N.; Imori, M.

2002-01-01

The Balloon Borne Experiment with a Superconducting Spectrometer (BESS) has measured the energy spectrum of cosmic-ray antiprotons between 0.18 and 4.20 GeV in eight flights between 1993 and 2002. Above about 1 GeV, models in which antiprotons are secondary products of the interactions of primary cosmic rays with the interstellar gas agree with the BESS antiproton spectrum. Below 1 GeV, the data show a possible excess antiproton flux compared to secondary model predictions, suggesting the presence of an additional source of antiprotons. The antiproton/proton ratios measured between 1993 and 1999, during the Sun's positive-polarity phase, are consistent with simple models of solar modulation. However, results from the 2000 flight, following the solar magnetic field reversal, show a sudden increase in the antiproton/proton ratio and tend to favor a charge-sign-dependent drift model. To extend BESS measurements to lower energies, an evolutionary instrument, BESS-Polar, is under construction for polar flight in 2004.

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.

Evolutionary dynamics on any population structure

NASA Astrophysics Data System (ADS)

Allen, Benjamin; Lippner, Gabor; Chen, Yu-Ting; Fotouhi, Babak; Momeni, Naghmeh; Yau, Shing-Tung; Nowak, Martin A.

2017-03-01

Evolution occurs in populations of reproducing individuals. The structure of a population can affect which traits evolve. Understanding evolutionary game dynamics in structured populations remains difficult. Mathematical results are known for special structures in which all individuals have the same number of neighbours. The general case, in which the number of neighbours can vary, has remained open. For arbitrary selection intensity, the problem is in a computational complexity class that suggests there is no efficient algorithm. Whether a simple solution for weak selection exists has remained unanswered. Here we provide a solution for weak selection that applies to any graph or network. Our method relies on calculating the coalescence times of random walks. We evaluate large numbers of diverse population structures for their propensity to favour cooperation. We study how small changes in population structure—graph surgery—affect evolutionary outcomes. We find that cooperation flourishes most in societies that are based on strong pairwise ties.

An Application of Evolutionary Game Theory to Social Dilemmas: The Traveler's Dilemma and the Minimum Effort Coordination Game

PubMed Central

Iyer, Swami; Reyes, Joshua; Killingback, Timothy

2014-01-01

The Traveler's Dilemma game and the Minimum Effort Coordination game are two social dilemmas that have attracted considerable attention due to the fact that the predictions of classical game theory are at odds with the results found when the games are studied experimentally. Moreover, a direct application of deterministic evolutionary game theory, as embodied in the replicator dynamics, to these games does not explain the observed behavior. In this work, we formulate natural variants of these two games as smoothed continuous-strategy games. We study the evolutionary dynamics of these continuous-strategy games, both analytically and through agent-based simulations, and show that the behavior predicted theoretically is in accord with that observed experimentally. Thus, these variants of the Traveler's Dilemma and the Minimum Effort Coordination games provide a simple resolution of the paradoxical behavior associated with the original games. PMID:24709851

An application of evolutionary game theory to social dilemmas: the traveler's dilemma and the minimum effort coordination game.

PubMed

Iyer, Swami; Reyes, Joshua; Killingback, Timothy

2014-01-01

The Traveler's Dilemma game and the Minimum Effort Coordination game are two social dilemmas that have attracted considerable attention due to the fact that the predictions of classical game theory are at odds with the results found when the games are studied experimentally. Moreover, a direct application of deterministic evolutionary game theory, as embodied in the replicator dynamics, to these games does not explain the observed behavior. In this work, we formulate natural variants of these two games as smoothed continuous-strategy games. We study the evolutionary dynamics of these continuous-strategy games, both analytically and through agent-based simulations, and show that the behavior predicted theoretically is in accord with that observed experimentally. Thus, these variants of the Traveler's Dilemma and the Minimum Effort Coordination games provide a simple resolution of the paradoxical behavior associated with the original games.

The Price Equation, Gradient Dynamics, and Continuous Trait Game Theory.

PubMed

Lehtonen, Jussi

2018-01-01

A recent article convincingly nominated the Price equation as the fundamental theorem of evolution and used it as a foundation to derive several other theorems. A major section of evolutionary theory that was not addressed is that of game theory and gradient dynamics of continuous traits with frequency-dependent fitness. Deriving fundamental results in these fields under the unifying framework of the Price equation illuminates similarities and differences between approaches and allows a simple, unified view of game-theoretical and dynamic concepts. Using Taylor polynomials and the Price equation, I derive a dynamic measure of evolutionary change, a condition for singular points, the convergence stability criterion, and an alternative interpretation of evolutionary stability. Furthermore, by applying the Price equation to a multivariable Taylor polynomial, the direct fitness approach to kin selection emerges. Finally, I compare these results to the mean gradient equation of quantitative genetics and the canonical equation of adaptive dynamics.

Molecular musings in microbial ecology and evolution

PubMed Central

2011-01-01

A few major discoveries have influenced how ecologists and evolutionists study microbes. Here, in the format of an interview, we answer questions that directly relate to how these discoveries are perceived in these two branches of microbiology, and how they have impacted on both scientific thinking and methodology. The first question is "What has been the influence of the 'Universal Tree of Life' based on molecular markers?" For evolutionists, the tree was a tool to understand the past of known (cultured) organisms, mapping the invention of various physiologies on the evolutionary history of microbes. For ecologists the tree was a guide to discover the current diversity of unknown (uncultured) organisms, without much knowledge of their physiology. The second question we ask is "What was the impact of discovering frequent lateral gene transfer among microbes?" In evolutionary microbiology, frequent lateral gene transfer (LGT) made a simple description of relationships between organisms impossible, and for microbial ecologists, functions could not be easily linked to specific genotypes. Both fields initially resisted LGT, but methods or topics of inquiry were eventually changed in one to incorporate LGT in its theoretical models (evolution) and in the other to achieve its goals despite that phenomenon (ecology). The third and last question we ask is "What are the implications of the unexpected extent of diversity?" The variation in the extent of diversity between organisms invalidated the universality of species definitions based on molecular criteria, a major obstacle to the adaptation of models developed for the study of macroscopic eukaryotes to evolutionary microbiology. This issue has not overtly affected microbial ecology, as it had already abandoned species in favor of the more flexible operational taxonomic units. This field is nonetheless moving away from traditional methods to measure diversity, as they do not provide enough resolution to uncover what lies below the species level. The answers of the evolutionary microbiologist and microbial ecologist to these three questions illustrate differences in their theoretical frameworks. These differences mean that both fields can react quite distinctly to the same discovery, incorporating it with more or less difficulty in their scientific practice. Reviewers This article was reviewed by W. Ford Doolittle, Eugene V. Koonin and Maureen A. O'Malley. PMID:22074255

Molecular musings in microbial ecology and evolution.

PubMed

Case, Rebecca J; Boucher, Yan

2011-11-10

A few major discoveries have influenced how ecologists and evolutionists study microbes. Here, in the format of an interview, we answer questions that directly relate to how these discoveries are perceived in these two branches of microbiology, and how they have impacted on both scientific thinking and methodology.The first question is "What has been the influence of the 'Universal Tree of Life' based on molecular markers?" For evolutionists, the tree was a tool to understand the past of known (cultured) organisms, mapping the invention of various physiologies on the evolutionary history of microbes. For ecologists the tree was a guide to discover the current diversity of unknown (uncultured) organisms, without much knowledge of their physiology.The second question we ask is "What was the impact of discovering frequent lateral gene transfer among microbes?" In evolutionary microbiology, frequent lateral gene transfer (LGT) made a simple description of relationships between organisms impossible, and for microbial ecologists, functions could not be easily linked to specific genotypes. Both fields initially resisted LGT, but methods or topics of inquiry were eventually changed in one to incorporate LGT in its theoretical models (evolution) and in the other to achieve its goals despite that phenomenon (ecology).The third and last question we ask is "What are the implications of the unexpected extent of diversity?" The variation in the extent of diversity between organisms invalidated the universality of species definitions based on molecular criteria, a major obstacle to the adaptation of models developed for the study of macroscopic eukaryotes to evolutionary microbiology. This issue has not overtly affected microbial ecology, as it had already abandoned species in favor of the more flexible operational taxonomic units. This field is nonetheless moving away from traditional methods to measure diversity, as they do not provide enough resolution to uncover what lies below the species level.The answers of the evolutionary microbiologist and microbial ecologist to these three questions illustrate differences in their theoretical frameworks. These differences mean that both fields can react quite distinctly to the same discovery, incorporating it with more or less difficulty in their scientific practice.

Evolutionary dynamics with fluctuating population sizes and strong mutualism.

PubMed

Chotibut, Thiparat; Nelson, David R

2015-08-01

Game theory ideas provide a useful framework for studying evolutionary dynamics in a well-mixed environment. This approach, however, typically enforces a strictly fixed overall population size, deemphasizing natural growth processes. We study a competitive Lotka-Volterra model, with number fluctuations, that accounts for natural population growth and encompasses interaction scenarios typical of evolutionary games. We show that, in an appropriate limit, the model describes standard evolutionary games with both genetic drift and overall population size fluctuations. However, there are also regimes where a varying population size can strongly influence the evolutionary dynamics. We focus on the strong mutualism scenario and demonstrate that standard evolutionary game theory fails to describe our simulation results. We then analytically and numerically determine fixation probabilities as well as mean fixation times using matched asymptotic expansions, taking into account the population size degree of freedom. These results elucidate the interplay between population dynamics and evolutionary dynamics in well-mixed systems.

Evolutionary dynamics with fluctuating population sizes and strong mutualism

NASA Astrophysics Data System (ADS)

Chotibut, Thiparat; Nelson, David R.

2015-08-01

Game theory ideas provide a useful framework for studying evolutionary dynamics in a well-mixed environment. This approach, however, typically enforces a strictly fixed overall population size, deemphasizing natural growth processes. We study a competitive Lotka-Volterra model, with number fluctuations, that accounts for natural population growth and encompasses interaction scenarios typical of evolutionary games. We show that, in an appropriate limit, the model describes standard evolutionary games with both genetic drift and overall population size fluctuations. However, there are also regimes where a varying population size can strongly influence the evolutionary dynamics. We focus on the strong mutualism scenario and demonstrate that standard evolutionary game theory fails to describe our simulation results. We then analytically and numerically determine fixation probabilities as well as mean fixation times using matched asymptotic expansions, taking into account the population size degree of freedom. These results elucidate the interplay between population dynamics and evolutionary dynamics in well-mixed systems.

An Evolutionary Analysis of Learned Attention

ERIC Educational Resources Information Center

Hullinger, Richard A.; Kruschke, John K.; Todd, Peter M.

2015-01-01

Humans and many other species selectively attend to stimuli or stimulus dimensions--but why should an animal constrain information input in this way? To investigate the adaptive functions of attention, we used a genetic algorithm to evolve simple connectionist networks that had to make categorization decisions in a variety of environmental…

"Molecular Clock" Analogs: A Relative Rates Exercise

ERIC Educational Resources Information Center

Wares, John P.

2008-01-01

Although molecular clock theory is a commonly discussed facet of evolutionary biology, undergraduates are rarely presented with the underlying information of how this theory is examined relative to empirical data. Here a simple contextual exercise is presented that not only provides insight into molecular clocks, but is also a useful exercise for…

Discriminating power of microsatellites in cranberry organelles for taxonomic studies in Vaccinium and Ericaceae

USDA-ARS?s Scientific Manuscript database

Simple sequence repeats (SSRs) in chloroplast and mitochondrial DNA, which have not been previously developed or explored in the Ericaceae family or Vaccinium genus, can be powerful tools for determining evolutionary relationships between taxa. In this study, 30 chloroplast and 23 mitochondria, and ...

Probabilistic models of eukaryotic evolution: time for integration

PubMed Central

Lartillot, Nicolas

2015-01-01

In spite of substantial work and recent progress, a global and fully resolved picture of the macroevolutionary history of eukaryotes is still under construction. This concerns not only the phylogenetic relations among major groups, but also the general characteristics of the underlying macroevolutionary processes, including the patterns of gene family evolution associated with endosymbioses, as well as their impact on the sequence evolutionary process. All these questions raise formidable methodological challenges, calling for a more powerful statistical paradigm. In this direction, model-based probabilistic approaches have played an increasingly important role. In particular, improved models of sequence evolution accounting for heterogeneities across sites and across lineages have led to significant, although insufficient, improvement in phylogenetic accuracy. More recently, one main trend has been to move away from simple parametric models and stepwise approaches, towards integrative models explicitly considering the intricate interplay between multiple levels of macroevolutionary processes. Such integrative models are in their infancy, and their application to the phylogeny of eukaryotes still requires substantial improvement of the underlying models, as well as additional computational developments. PMID:26323768

The evolution of parasitic and mutualistic plant-virus symbioses through transmission-virulence trade-offs.

PubMed

Hamelin, Frédéric M; Hilker, Frank M; Sun, T Anthony; Jeger, Michael J; Hajimorad, M Reza; Allen, Linda J S; Prendeville, Holly R

2017-09-15

Virus-plant interactions range from parasitism to mutualism. Viruses have been shown to increase fecundity of infected plants in comparison with uninfected plants under certain environmental conditions. Increased fecundity of infected plants may benefit both the plant and the virus as seed transmission is one of the main virus transmission pathways, in addition to vector transmission. Trade-offs between vertical (seed) and horizontal (vector) transmission pathways may involve virulence, defined here as decreased fecundity in infected plants. To better understand plant-virus symbiosis evolution, we explore the ecological and evolutionary interplay of virus transmission modes when infection can lead to an increase in plant fecundity. We consider two possible trade-offs: vertical seed transmission vs infected plant fecundity, and horizontal vector transmission vs infected plant fecundity (virulence). Through mathematical models and numerical simulations, we show (1) that a trade-off between virulence and vertical transmission can lead to virus extinction during the course of evolution, (2) that evolutionary branching can occur with subsequent coexistence of mutualistic and parasitic virus strains, and (3) that mutualism can out-compete parasitism in the long-run. In passing, we show that ecological bi-stability is possible in a very simple discrete-time epidemic model. Possible extensions of this study include the evolution of conditional (environment-dependent) mutualism in plant viruses. Copyright © 2017 Elsevier B.V. All rights reserved.

The importance of mechanisms for the evolution of cooperation

PubMed Central

van den Berg, Pieter; Weissing, Franz J.

2015-01-01

Studies aimed at explaining the evolution of phenotypic traits have often solely focused on fitness considerations, ignoring underlying mechanisms. In recent years, there has been an increasing call for integrating mechanistic perspectives in evolutionary considerations, but it is not clear whether and how mechanisms affect the course and outcome of evolution. To study this, we compare four mechanistic implementations of two well-studied models for the evolution of cooperation, the Iterated Prisoner's Dilemma (IPD) game and the Iterated Snowdrift (ISD) game. Behavioural strategies are either implemented by a 1 : 1 genotype–phenotype mapping or by a simple neural network. Moreover, we consider two different scenarios for the effect of mutations. The same set of strategies is feasible in all four implementations, but the probability that a given strategy arises owing to mutation is largely dependent on the behavioural and genetic architecture. Our individual-based simulations show that this has major implications for the evolutionary outcome. In the ISD, different evolutionarily stable strategies are predominant in the four implementations, while in the IPD each implementation creates a characteristic dynamical pattern. As a consequence, the evolved average level of cooperation is also strongly dependent on the underlying mechanism. We argue that our findings are of general relevance for the evolution of social behaviour, pleading for the integration of a mechanistic perspective in models of social evolution. PMID:26246554

Modeling Coevolution between Language and Memory Capacity during Language Origin

PubMed Central

Gong, Tao; Shuai, Lan

2015-01-01

Memory is essential to many cognitive tasks including language. Apart from empirical studies of memory effects on language acquisition and use, there lack sufficient evolutionary explorations on whether a high level of memory capacity is prerequisite for language and whether language origin could influence memory capacity. In line with evolutionary theories that natural selection refined language-related cognitive abilities, we advocated a coevolution scenario between language and memory capacity, which incorporated the genetic transmission of individual memory capacity, cultural transmission of idiolects, and natural and cultural selections on individual reproduction and language teaching. To illustrate the coevolution dynamics, we adopted a multi-agent computational model simulating the emergence of lexical items and simple syntax through iterated communications. Simulations showed that: along with the origin of a communal language, an initially-low memory capacity for acquired linguistic knowledge was boosted; and such coherent increase in linguistic understandability and memory capacities reflected a language-memory coevolution; and such coevolution stopped till memory capacities became sufficient for language communications. Statistical analyses revealed that the coevolution was realized mainly by natural selection based on individual communicative success in cultural transmissions. This work elaborated the biology-culture parallelism of language evolution, demonstrated the driving force of culturally-constituted factors for natural selection of individual cognitive abilities, and suggested that the degree difference in language-related cognitive abilities between humans and nonhuman animals could result from a coevolution with language. PMID:26544876

Modeling Coevolution between Language and Memory Capacity during Language Origin.

PubMed

Gong, Tao; Shuai, Lan

2015-01-01

Memory is essential to many cognitive tasks including language. Apart from empirical studies of memory effects on language acquisition and use, there lack sufficient evolutionary explorations on whether a high level of memory capacity is prerequisite for language and whether language origin could influence memory capacity. In line with evolutionary theories that natural selection refined language-related cognitive abilities, we advocated a coevolution scenario between language and memory capacity, which incorporated the genetic transmission of individual memory capacity, cultural transmission of idiolects, and natural and cultural selections on individual reproduction and language teaching. To illustrate the coevolution dynamics, we adopted a multi-agent computational model simulating the emergence of lexical items and simple syntax through iterated communications. Simulations showed that: along with the origin of a communal language, an initially-low memory capacity for acquired linguistic knowledge was boosted; and such coherent increase in linguistic understandability and memory capacities reflected a language-memory coevolution; and such coevolution stopped till memory capacities became sufficient for language communications. Statistical analyses revealed that the coevolution was realized mainly by natural selection based on individual communicative success in cultural transmissions. This work elaborated the biology-culture parallelism of language evolution, demonstrated the driving force of culturally-constituted factors for natural selection of individual cognitive abilities, and suggested that the degree difference in language-related cognitive abilities between humans and nonhuman animals could result from a coevolution with language.

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.

Bayesian Analysis of Evolutionary Divergence with Genomic Data under Diverse Demographic Models.

PubMed

Chung, Yujin; Hey, Jody

2017-06-01

We present a new Bayesian method for estimating demographic and phylogenetic history using population genomic data. Several key innovations are introduced that allow the study of diverse models within an Isolation-with-Migration framework. The new method implements a 2-step analysis, with an initial Markov chain Monte Carlo (MCMC) phase that samples simple coalescent trees, followed by the calculation of the joint posterior density for the parameters of a demographic model. In step 1, the MCMC sampling phase, the method uses a reduced state space, consisting of coalescent trees without migration paths, and a simple importance sampling distribution without the demography of interest. Once obtained, a single sample of trees can be used in step 2 to calculate the joint posterior density for model parameters under multiple diverse demographic models, without having to repeat MCMC runs. Because migration paths are not included in the state space of the MCMC phase, but rather are handled by analytic integration in step 2 of the analysis, the method is scalable to a large number of loci with excellent MCMC mixing properties. With an implementation of the new method in the computer program MIST, we demonstrate the method's accuracy, scalability, and other advantages using simulated data and DNA sequences of two common chimpanzee subspecies: Pan troglodytes (P. t.) troglodytes and P. t. verus. © The Author 2017. 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.

Inflow Motions Associated with High-mass Protostellar Objects

NASA Astrophysics Data System (ADS)

Yoo, Hyunju; Kim, Kee-Tae; Cho, Jungyeon; Choi, Minho; Wu, Jingwen; Evans, Neal J., II; Ziurys, L. M.

2018-04-01

We performed a molecular line survey of 82 high-mass protostellar objects in a search for inflow signatures associated with high-mass star formation. Using the H13CO+ (1‑0) line as an optically thin tracer, we detected a statistically significant excess of blue asymmetric line profiles in the HCO+ (1‑0) transition, but nonsignificant excesses in the HCO+ (3‑2) and H2CO (212–111) transitions. The negative blue excess for the HCN (3‑2) transition suggests that the line profiles are affected by dynamics other than inflow motion. The HCO+ (1‑0) transition thus seems to be the suitable tracer of inflow motions in high-mass star-forming regions, as previously suggested. We found 27 inflow candidates that have at least 1 blue asymmetric profile and no red asymmetric profile, and derived the inflow velocities to be 0.23‑2.00 km s‑1 for 20 of them using a simple two-layer radiative transfer model. Our sample is divided into two groups in different evolutionary stages. The blue excess of the group in relatively earlier evolutionary stages was estimated to be slightly higher than that of the other in the HCO+ (1‑0) transition.

Epidemiological, evolutionary, and coevolutionary implications of context-dependent parasitism.

PubMed

Vale, Pedro F; Wilson, Alastair J; Best, Alex; Boots, Mike; Little, Tom J

2011-04-01

Abstract Victims of infection are expected to suffer increasingly as parasite population growth increases. Yet, under some conditions, faster-growing parasites do not appear to cause more damage, and infections can be quite tolerable. We studied these conditions by assessing how the relationship between parasite population growth and host health is sensitive to environmental variation. In experimental infections of the crustacean Daphnia magna and its bacterial parasite Pasteuria ramosa, we show how easily an interaction can shift from a severe interaction, that is, when host fitness declines substantially with each unit of parasite growth, to a tolerable relationship by changing only simple environmental variables: temperature and food availability. We explored the evolutionary and epidemiological implications of such a shift by modeling pathogen evolution and disease spread under different levels of infection severity and found that environmental shifts that promote tolerance ultimately result in populations harboring more parasitized individuals. We also find that the opportunity for selection, as indicated by the variance around traits, varied considerably with the environmental treatment. Thus, our results suggest two mechanisms that could underlie coevolutionary hotspots and coldspots: spatial variation in tolerance and spatial variation in the opportunity for selection.

Residue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein folds.

PubMed

Simkovic, Felix; Thomas, Jens M H; Keegan, Ronan M; Winn, Martyn D; Mayans, Olga; Rigden, Daniel J

2016-07-01

For many protein families, the deluge of new sequence information together with new statistical protocols now allow the accurate prediction of contacting residues from sequence information alone. This offers the possibility of more accurate ab initio (non-homology-based) structure prediction. Such models can be used in structure solution by molecular replacement (MR) where the target fold is novel or is only distantly related to known structures. Here, AMPLE, an MR pipeline that assembles search-model ensembles from ab initio structure predictions ('decoys'), is employed to assess the value of contact-assisted ab initio models to the crystallographer. It is demonstrated that evolutionary covariance-derived residue-residue contact predictions improve the quality of ab initio models and, consequently, the success rate of MR using search models derived from them. For targets containing β-structure, decoy quality and MR performance were further improved by the use of a β-strand contact-filtering protocol. Such contact-guided decoys achieved 14 structure solutions from 21 attempted protein targets, compared with nine for simple Rosetta decoys. Previously encountered limitations were superseded in two key respects. Firstly, much larger targets of up to 221 residues in length were solved, which is far larger than the previously benchmarked threshold of 120 residues. Secondly, contact-guided decoys significantly improved success with β-sheet-rich proteins. Overall, the improved performance of contact-guided decoys suggests that MR is now applicable to a significantly wider range of protein targets than were previously tractable, and points to a direct benefit to structural biology from the recent remarkable advances in sequencing.

Residue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein folds

PubMed Central

Simkovic, Felix; Thomas, Jens M. H.; Keegan, Ronan M.; Winn, Martyn D.; Mayans, Olga; Rigden, Daniel J.

2016-01-01

For many protein families, the deluge of new sequence information together with new statistical protocols now allow the accurate prediction of contacting residues from sequence information alone. This offers the possibility of more accurate ab initio (non-homology-based) structure prediction. Such models can be used in structure solution by molecular replacement (MR) where the target fold is novel or is only distantly related to known structures. Here, AMPLE, an MR pipeline that assembles search-model ensembles from ab initio structure predictions (‘decoys’), is employed to assess the value of contact-assisted ab initio models to the crystallographer. It is demonstrated that evolutionary covariance-derived residue–residue contact predictions improve the quality of ab initio models and, consequently, the success rate of MR using search models derived from them. For targets containing β-structure, decoy quality and MR performance were further improved by the use of a β-strand contact-filtering protocol. Such contact-guided decoys achieved 14 structure solutions from 21 attempted protein targets, compared with nine for simple Rosetta decoys. Previously encountered limitations were superseded in two key respects. Firstly, much larger targets of up to 221 residues in length were solved, which is far larger than the previously benchmarked threshold of 120 residues. Secondly, contact-guided decoys significantly improved success with β-sheet-rich proteins. Overall, the improved performance of contact-guided decoys suggests that MR is now applicable to a significantly wider range of protein targets than were previously tractable, and points to a direct benefit to structural biology from the recent remarkable advances in sequencing. PMID:27437113

Are attractors 'strange', or is life more complicated than the simple laws of physics?

PubMed

Pogun, S

2001-01-01

Interesting and intriguing questions involve complex systems whose properties cannot be explained fully by reductionist approaches. Last century was dominated by physics, and applying the simple laws of physics to biology appeared to be a practical solution to understand living organisms. However, although some attributes of living organisms involve physico-chemical properties, the genetic program and evolutionary history of complex biological systems make them unique and unpredictable. Furthermore, there are and will be 'unobservable' phenomena in biology which have to be accounted for.

A Simple Mechanism for Cooperation in the Well-Mixed Prisoner's Dilemma Game

NASA Astrophysics Data System (ADS)

Perc, Matjaž

2008-11-01

I show that the addition of Gaussian noise to the payoffs is able to stabilize cooperation in well-mixed populations, where individuals play the prisoner's dilemma game. The impact of stochasticity on the evolutionary dynamics can be expressed deterministically via a simple small-noise expansion of multiplicative noisy terms. In particular, cooperation emerges as a stable noise-induced steady state in the replicator dynamics. Due to the generality of the employed theoretical framework, presented results should prove valuable in various scientific disciplines, ranging from economy to ecology.

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.

Measuring Fundamental Parameters of Substellar Objects. I. Surface Gravities

NASA Astrophysics Data System (ADS)

Mohanty, Subhanjoy; Basri, Gibor; Jayawardhana, Ray; Allard, France; Hauschildt, Peter; Ardila, David

2004-07-01

We present an analysis of high-resolution optical spectra for a sample of very young, mid- to late-M, low-mass stellar and substellar objects: 11 in the Upper Scorpius association, and two (GG Tau Ba and Bb) in the Taurus star-forming region. Effective temperatures and surface gravities are derived from a multiple-feature spectral analysis using TiO, Na I, and K I, through comparison with the latest synthetic spectra. We show that these spectral diagnostics complement each other, removing degeneracies with temperature and gravity in the behavior of each. In combination, they allow us to determine temperature to within 50 K and gravity to within 0.25 dex, in very cool young objects. Our high-resolution spectral analysis does not require extinction estimates. Moreover, it yields temperatures and gravities independent of theoretical evolutionary models (although our estimates do depend on the synthetic spectral modeling). We find that our gravities for most of the sample agree remarkably well with the isochrone predictions for the likely cluster ages. However, discrepancies appear in our coolest targets: these appear to have significantly lower gravity (by up to 0.75 dex) than our hotter objects, even though our entire sample covers a relatively narrow range in effective temperature (~300 K). This drop in gravity is also implied by intercomparisons of the data alone, without recourse to synthetic spectra. We consider, and argue against, dust opacity, cool stellar spots, or metallicity differences leading to the observed spectral effects; a real decline in gravity is strongly indicated. Such gravity variations are contrary to the predictions of the evolutionary tracks, causing improbably low ages to be inferred from the tracks for our coolest targets. Through a simple consideration of contraction timescales, we quantify the age errors introduced into the tracks through the particular choice of initial conditions and demonstrate that they can be significant for low-mass objects that are only a few megayears old. However, we also find that these errors appear insufficient to explain the magnitude of the age offsets in our lowest gravity targets. We venture that this apparent age offset may arise from evolutionary model uncertainties related to accretion, deuterium burning and/or convection effects. Finally, when combined with photometry and distance information, our technique for deriving surface gravities and effective temperatures provides a way of obtaining masses and radii for substellar objects independent of evolutionary models; radius and mass determinations are presented in Paper II.

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.

Cry-Bt identifier: a biological database for PCR detection of Cry genes present in transgenic plants.

PubMed

Singh, Vinay Kumar; Ambwani, Sonu; Marla, Soma; Kumar, Anil

2009-10-23

We describe the development of a user friendly tool that would assist in the retrieval of information relating to Cry genes in transgenic crops. The tool also helps in detection of transformed Cry genes from Bacillus thuringiensis present in transgenic plants by providing suitable designed primers for PCR identification of these genes. The tool designed based on relational database model enables easy retrieval of information from the database with simple user queries. The tool also enables users to access related information about Cry genes present in various databases by interacting with different sources (nucleotide sequences, protein sequence, sequence comparison tools, published literature, conserved domains, evolutionary and structural data). http://insilicogenomics.in/Cry-btIdentifier/welcome.html.

Evolutionary Paths to Corrupt Societies of Artificial Agents

NASA Astrophysics Data System (ADS)

Nasrallah, Walid

Virtual corrupt societies can be defined as groups of interacting computer-generated agents who predominantly choose behavior that gives short term personal gain at the expense of a higher aggregate cost to others. This paper focuses on corrupt societies that, unlike published models in which cooperation must evolve in order for the society to continue to survive, do not naturally die out as the corrupt class siphons off the resources. For example, a very computationally simple strategy of avoiding confrontation can allow a majority of "unethical" individuals to survive off the efforts of an "ethical" but productive minority. Analogies are drawn to actual human societies in which similar conditions gave rise to behavior traditionally defined as economic or political corruption.

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.

Origin of archosaurian integumentary appendages: the bristles of the wild turkey beard express feather-type beta keratins.

PubMed

Sawyer, Roger H; Washington, Lynette D; Salvatore, Brian A; Glenn, Travis C; Knapp, Loren W

2003-06-15

The discovery that structurally unique "filamentous integumentary appendages" are associated with several different non-avian dinosaurs continues to stimulate the development of models to explain the evolutionary origin of feathers. Taking the phylogenetic relationships of the non-avian dinosaurs into consideration, some models propose that the "filamentous integumentary appendages" represent intermediate stages in the sequential evolution of feathers. Here we present observations on a unique integumentary structure, the bristle of the wild turkey beard, and suggest that this non-feather appendage provides another explanation for some of the "filamentous integumentary appendages." Unlike feathers, beard bristles grow continuously from finger-like outgrows of the integument lacking follicles. We find that these beard bristles, which show simple branching, are hollow, distally, and express the feather-type beta keratins. The significance of these observations to explanations for the evolution of archosaurian integumentary appendages is discussed.

Diversity spurs diversification in ecological communities

PubMed Central

Calcagno, Vincent; Jarne, Philippe; Loreau, Michel; Mouquet, Nicolas; David, Patrice

2017-01-01

Diversity is a fundamental, yet threatened, property of ecological systems. The idea that diversity can itself favour diversification, in an autocatalytic process, is very appealing but remains controversial. Here, we study a generalized model of ecological communities and investigate how the level of initial diversity influences the possibility of evolutionary diversification. We show that even simple models of intra- and inter-specific ecological interactions can predict a positive effect of diversity on diversification: adaptive radiations may require a threshold number of species before kicking-off. We call this phenomenon DDAR (diversity-dependent adaptive radiations) and identify mathematically two distinct pathways connecting diversity to diversification, involving character displacement and the positive diversity-productivity relationship. Our results may explain observed delays in adaptive radiations at the macroscale and diversification patterns reported in experimental microbial communities, and shed new light on the dynamics of ecological diversity, the diversity-dependence of diversification rates, and the consequences of biodiversity loss. PMID:28598423

The origin of risk aversion

PubMed Central

Zhang, Ruixun; Brennan, Thomas J.; Lo, Andrew W.

2014-01-01

Risk aversion is one of the most basic assumptions of economic behavior, but few studies have addressed the question of where risk preferences come from and why they differ from one individual to the next. Here, we propose an evolutionary explanation for the origin of risk aversion. In the context of a simple binary-choice model, we show that risk aversion emerges by natural selection if reproductive risk is systematic (i.e., correlated across individuals in a given generation). In contrast, risk neutrality emerges if reproductive risk is idiosyncratic (i.e., uncorrelated across each given generation). More generally, our framework implies that the degree of risk aversion is determined by the stochastic nature of reproductive rates, and we show that different statistical properties lead to different utility functions. The simplicity and generality of our model suggest that these implications are primitive and cut across species, physiology, and genetic origins. PMID:25453072

Diversity spurs diversification in ecological communities

NASA Astrophysics Data System (ADS)

Calcagno, Vincent; Jarne, Philippe; Loreau, Michel; Mouquet, Nicolas; David, Patrice

2017-06-01

Diversity is a fundamental, yet threatened, property of ecological systems. The idea that diversity can itself favour diversification, in an autocatalytic process, is very appealing but remains controversial. Here, we study a generalized model of ecological communities and investigate how the level of initial diversity influences the possibility of evolutionary diversification. We show that even simple models of intra- and inter-specific ecological interactions can predict a positive effect of diversity on diversification: adaptive radiations may require a threshold number of species before kicking-off. We call this phenomenon DDAR (diversity-dependent adaptive radiations) and identify mathematically two distinct pathways connecting diversity to diversification, involving character displacement and the positive diversity-productivity relationship. Our results may explain observed delays in adaptive radiations at the macroscale and diversification patterns reported in experimental microbial communities, and shed new light on the dynamics of ecological diversity, the diversity-dependence of diversification rates, and the consequences of biodiversity loss.

Critical properties of unlimited gliding: Unexpected flocking behavior driven by the exchange of information

NASA Astrophysics Data System (ADS)

Bigus-Kwiatkowska, Marta; Fronczak, Agata; Fronczak, Piotr

2018-03-01

Inspired by albatrosses that use thermal lifts to fly across oceans we develop a simple model of gliders that serves us to study theoretical limitations of unlimited exploration of the Earth. Our studies, grounded in physical theory of continuous percolation and biased random walks, allow us to identify a variety of percolation transitions, which are understood as providing potentially unlimited movement through a space in a specified direction. We discover an unexpected phenomenon of self-organization of gliders in clusters, which resembles the flock organization of birds. This self-organization is intriguing, as it occurs thanks to exchange of information only and without any particular rules that could favor the clustering of the gliders (in contrast to the causes well known in literature, like, for example, attractive forces used in the Vicsek-type models or fitness functions used in evolutionary computation).

Diversity spurs diversification in ecological communities.

PubMed

Calcagno, Vincent; Jarne, Philippe; Loreau, Michel; Mouquet, Nicolas; David, Patrice

2017-06-09

Diversity is a fundamental, yet threatened, property of ecological systems. The idea that diversity can itself favour diversification, in an autocatalytic process, is very appealing but remains controversial. Here, we study a generalized model of ecological communities and investigate how the level of initial diversity influences the possibility of evolutionary diversification. We show that even simple models of intra- and inter-specific ecological interactions can predict a positive effect of diversity on diversification: adaptive radiations may require a threshold number of species before kicking-off. We call this phenomenon DDAR (diversity-dependent adaptive radiations) and identify mathematically two distinct pathways connecting diversity to diversification, involving character displacement and the positive diversity-productivity relationship. Our results may explain observed delays in adaptive radiations at the macroscale and diversification patterns reported in experimental microbial communities, and shed new light on the dynamics of ecological diversity, the diversity-dependence of diversification rates, and the consequences of biodiversity loss.

The origin of risk aversion.

PubMed

Zhang, Ruixun; Brennan, Thomas J; Lo, Andrew W

2014-12-16

Risk aversion is one of the most basic assumptions of economic behavior, but few studies have addressed the question of where risk preferences come from and why they differ from one individual to the next. Here, we propose an evolutionary explanation for the origin of risk aversion. In the context of a simple binary-choice model, we show that risk aversion emerges by natural selection if reproductive risk is systematic (i.e., correlated across individuals in a given generation). In contrast, risk neutrality emerges if reproductive risk is idiosyncratic (i.e., uncorrelated across each given generation). More generally, our framework implies that the degree of risk aversion is determined by the stochastic nature of reproductive rates, and we show that different statistical properties lead to different utility functions. The simplicity and generality of our model suggest that these implications are primitive and cut across species, physiology, and genetic origins.

The evolution of contralateral control of the body by the brain: is it a protective mechanism?

PubMed

Whitehead, Lorne; Banihani, Saleh

2014-01-01

Contralateral control, the arrangement whereby most of the human motor and sensory fibres cross the midline in order to provide control for contralateral portions of the body, presents a puzzle from an evolutionary perspective. What caused such a counterintuitive and complex arrangement to become dominant? In this paper we offer a new perspective on this question by showing that in a complex interactive control system there could be a significant net survival advantage with contralateral control, associated with the effect of injuries of intermediate severity. In such cases an advantage could arise from a combination of non-linear system response combined with correlations between injuries on the same side of the head and body. We show that a simple mathematical model of these ideas emulates such an advantage. Based on this model, we conclude that effects of this kind are a plausible driving force for the evolution of contralateral control.

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.

Defining the limits of flowers: the challenge of distinguishing between the evolutionary products of simple versus compound strobili

PubMed Central

Rudall, Paula J.; Bateman, Richard M.

2010-01-01

Recent phylogenetic reconstructions suggest that axially condensed flower-like structures evolved iteratively in seed plants from either simple or compound strobili. The simple-strobilus model of flower evolution, widely applied to the angiosperm flower, interprets the inflorescence as a compound strobilus. The conifer cone and the gnetalean ‘flower’ are commonly interpreted as having evolved from a compound strobilus by extreme condensation and (at least in the case of male conifer cones) elimination of some structures present in the presumed ancestral compound strobilus. These two hypotheses have profoundly different implications for reconstructing the evolution of developmental genetic mechanisms in seed plants. If different flower-like structures evolved independently, there should intuitively be little commonality of patterning genes. However, reproductive units of some early-divergent angiosperms, including the extant genus Trithuria (Hydatellaceae) and the extinct genus Archaefructus (Archaefructaceae), apparently combine features considered typical of flowers and inflorescences. We re-evaluate several disparate strands of comparative data to explore whether flower-like structures could have arisen by co-option of flower-expressed patterning genes into independently evolved condensed inflorescences, or vice versa. We discuss the evolution of the inflorescence in both gymnosperms and angiosperms, emphasising the roles of heterotopy in dictating gender expression and heterochrony in permitting internodal compression. PMID:20047867

Defining the limits of flowers: the challenge of distinguishing between the evolutionary products of simple versus compound strobili.

PubMed

Rudall, Paula J; Bateman, Richard M

2010-02-12

Recent phylogenetic reconstructions suggest that axially condensed flower-like structures evolved iteratively in seed plants from either simple or compound strobili. The simple-strobilus model of flower evolution, widely applied to the angiosperm flower, interprets the inflorescence as a compound strobilus. The conifer cone and the gnetalean 'flower' are commonly interpreted as having evolved from a compound strobilus by extreme condensation and (at least in the case of male conifer cones) elimination of some structures present in the presumed ancestral compound strobilus. These two hypotheses have profoundly different implications for reconstructing the evolution of developmental genetic mechanisms in seed plants. If different flower-like structures evolved independently, there should intuitively be little commonality of patterning genes. However, reproductive units of some early-divergent angiosperms, including the extant genus Trithuria (Hydatellaceae) and the extinct genus Archaefructus (Archaefructaceae), apparently combine features considered typical of flowers and inflorescences. We re-evaluate several disparate strands of comparative data to explore whether flower-like structures could have arisen by co-option of flower-expressed patterning genes into independently evolved condensed inflorescences, or vice versa. We discuss the evolution of the inflorescence in both gymnosperms and angiosperms, emphasising the roles of heterotopy in dictating gender expression and heterochrony in permitting internodal compression.

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.

Estimation of interhemispheric dynamics from simple unimanual reaction time to extrafoveal stimuli.

PubMed

Braun, C M

1992-12-01

This essay reviews research on interhemispheric transfer time derived from simple unimanual reaction time to hemitachistoscopically presented visual stimuli. Part 1 reviews major theoretical themes including (a) the significance of the eccentricity effect on interhemispheric transfer time in the context of proposed underlying neurohistological constraints; (b) the significance of gender differences in interhemispheric transfer time and findings in dyslexics and left-handers in the context of a fetal brain testosterone model; and (c) the significance of complexity effects on interhemispheric transfer time in a context of "dynamic" vs. "hard-wired" concepts of the underlying interhemispheric communication systems. Part 2 consists of a meta-analysis of 49 published behavioral experiments, in view of drawing a portrait of the best set of experimental conditions apt to produce salient, reliable, and statistically significant measures of interhemispheric transfer time, namely (a) index rather than thumb response, (b) low rather than high target luminance, (c) short rather than prolonged target display, and (d) very eccentric rather than near-foveal stimulus location. Part 3 proposes a theoretical model of interhemispheric transfer time, postulating the measurable existence of fast and slow interhemispheric channels. The proposed mechanism's evolutionary adaptive value, the neurophysiological evidence in its support, and favorable functional evidence from studies of callosotomized patients are then presented followed by proposals for critical experimental tests of the model.

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 ...

Biological signatures of dynamic river networks from a coupled landscape evolution and neutral community model

NASA Astrophysics Data System (ADS)

Stokes, M.; Perron, J. T.

2017-12-01

Freshwater systems host exceptionally species-rich communities whose spatial structure is dictated by the topology of the river networks they inhabit. Over geologic time, river networks are dynamic; drainage basins shrink and grow, and river capture establishes new connections between previously separated regions. It has been hypothesized that these changes in river network structure influence the evolution of life by exchanging and isolating species, perhaps boosting biodiversity in the process. However, no general model exists to predict the evolutionary consequences of landscape change. We couple a neutral community model of freshwater organisms to a landscape evolution model in which the river network undergoes drainage divide migration and repeated river capture. Neutral community models are macro-ecological models that include stochastic speciation and dispersal to produce realistic patterns of biodiversity. We explore the consequences of three modes of speciation - point mutation, time-protracted, and vicariant (geographic) speciation - by tracking patterns of diversity in time and comparing the final result to an equilibrium solution of the neutral model on the final landscape. Under point mutation, a simple model of stochastic and instantaneous speciation, the results are identical to the equilibrium solution and indicate the dominance of the species-area relationship in forming patterns of diversity. The number of species in a basin is proportional to its area, and regional species richness reaches its maximum when drainage area is evenly distributed among sub-basins. Time-protracted speciation is also modeled as a stochastic process, but in order to produce more realistic rates of diversification, speciation is not assumed to be instantaneous. Rather, each new species must persist for a certain amount of time before it is considered to be established. When vicariance (geographic speciation) is included, there is a transient signature of increased regional diversity after river capture. The results indicate that the mode of speciation and the rate of speciation relative to the rate of divide migration determine the evolutionary signature of river capture.

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.

Between Self and Horde: The School

ERIC Educational Resources Information Center

Hawkes, T. Elijah

2010-01-01

For millions of years, human beings evolved and then lived in small social groupings that were intergenerational, with simple divisions of labor, oriented to common tasks and values. It was a limited existence in many ways, but there was community and continuity. And now, very suddenly in evolutionary time, we have built the teeming cities and…

The genetic architecture of a complex ecological trait: host plant use in the specialist moth, HELIOTHIS SUBFLEXA

USDA-ARS?s Scientific Manuscript database

The study of the genetic basis of ecological adaptation remains in its infancy, and most studies have focused on phenotypically simple traits. Host plant use by herbivorous insects is phenotypically complex. While research has illuminated the evolutionary determinants of host use, knowledge of its...

Hands-On Laboratory Simulation of Evolution: An Investigation of Mutation, Natural Selection, & Speciation

ERIC Educational Resources Information Center

Hildebrand, Terri J.; Govedich, Fredric R.; Bain, Bonnie A.

2010-01-01

Evolutionary theory is the foundation of the biological sciences, yet conveying it to General Biology students often presents a challenge, especially at larger institutions where student numbers in foundation courses can exceed several hundred per lecture section. We present a pedagogically sound exercise that utilizes a series of simple and…

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.

Eco-evolutionary feedbacks, adaptive dynamics and evolutionary rescue theory

PubMed Central

Ferriere, Regis; Legendre, Stéphane

2013-01-01

Adaptive dynamics theory has been devised to account for feedbacks between ecological and evolutionary processes. Doing so opens new dimensions to and raises new challenges about evolutionary rescue. Adaptive dynamics theory predicts that successive trait substitutions driven by eco-evolutionary feedbacks can gradually erode population size or growth rate, thus potentially raising the extinction risk. Even a single trait substitution can suffice to degrade population viability drastically at once and cause ‘evolutionary suicide’. In a changing environment, a population may track a viable evolutionary attractor that leads to evolutionary suicide, a phenomenon called ‘evolutionary trapping’. Evolutionary trapping and suicide are commonly observed in adaptive dynamics models in which the smooth variation of traits causes catastrophic changes in ecological state. In the face of trapping and suicide, evolutionary rescue requires that the population overcome evolutionary threats generated by the adaptive process itself. Evolutionary repellors play an important role in determining how variation in environmental conditions correlates with the occurrence of evolutionary trapping and suicide, and what evolutionary pathways rescue may follow. In contrast with standard predictions of evolutionary rescue theory, low genetic variation may attenuate the threat of evolutionary suicide and small population sizes may facilitate escape from evolutionary traps. PMID:23209163

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.

RED SUPERGIANT STARS AS COSMIC ABUNDANCE PROBES: KMOS OBSERVATIONS IN NGC 6822

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

Patrick, L. R.; Evans, C. J.; Ferguson, A. M. N.

2015-04-10

We present near-IR spectroscopy of red supergiant (RSG) stars in NGC 6822, obtained with the new K-band Multi-Object Spectrograph Very Large Telescope, Chile. From comparisons with model spectra in the J-band we determine the metallicity of 11 RSGs, finding a mean value of [Z] = −0.52 ± 0.21, which agrees well with previous abundance studies of young stars and H ii regions. We also find an indication for a low-significance abundance gradient within the central 1 kpc. We compare our results with those derived from older stellar populations and investigate the difference using a simple chemical evolution model. By comparingmore » the physical properties determined for RSGs in NGC 6822 with those derived using the same technique in the Galaxy and the Magellanic Clouds, we show that there appears to be no significant temperature variation of RSGs with respect to metallicity, in contrast to recent evolutionary models.« less

Emergent 1d Ising Behavior in AN Elementary Cellular Automaton Model

NASA Astrophysics Data System (ADS)

Kassebaum, Paul G.; Iannacchione, Germano S.

The fundamental nature of an evolving one-dimensional (1D) Ising model is investigated with an elementary cellular automaton (CA) simulation. The emergent CA simulation employs an ensemble of cells in one spatial dimension, each cell capable of two microstates interacting with simple nearest-neighbor rules and incorporating an external field. The behavior of the CA model provides insight into the dynamics of coupled two-state systems not expressible by exact analytical solutions. For instance, state progression graphs show the causal dynamics of a system through time in relation to the system's entropy. Unique graphical analysis techniques are introduced through difference patterns, diffusion patterns, and state progression graphs of the 1D ensemble visualizing the evolution. All analyses are consistent with the known behavior of the 1D Ising system. The CA simulation and new pattern recognition techniques are scalable (in both dimension, complexity, and size) and have many potential applications such as complex design of materials, control of agent systems, and evolutionary mechanism design.

Approaching neuropsychological tasks through adaptive neurorobots

NASA Astrophysics Data System (ADS)

Gigliotta, Onofrio; Bartolomeo, Paolo; Miglino, Orazio

2015-04-01

Neuropsychological phenomena have been modelized mainly, by the mainstream approach, by attempting to reproduce their neural substrate whereas sensory-motor contingencies have attracted less attention. In this work, we introduce a simulator based on the evolutionary robotics platform Evorobot* in order to setting up in silico neuropsychological tasks. Moreover, in this study we trained artificial embodied neurorobotic agents equipped with a pan/tilt camera, provided with different neural and motor capabilities, to solve a well-known neuropsychological test: the cancellation task in which an individual is asked to cancel target stimuli surrounded by distractors. Results showed that embodied agents provided with additional motor capabilities (a zooming/attentional actuator) outperformed simple pan/tilt agents, even those equipped with more complex neural controllers and that the zooming ability is exploited to correctly categorising presented stimuli. We conclude that since the sole neural computational power cannot explain the (artificial) cognition which emerged throughout the adaptive process, such kind of modelling approach can be fruitful in neuropsychological modelling where the importance of having a body is often neglected.

Dynamic effects of memory in a cobweb model with competing technologies

NASA Astrophysics Data System (ADS)

Agliari, Anna; Naimzada, Ahmad; Pecora, Nicolò

2017-02-01

We analyze a simple model based on the cobweb demand-supply framework with costly innovators and free imitators and study the endogenous dynamics of price and firms' fractions in a homogeneous good market. The evolutionary selection between technologies depends on a performance measure in which a memory parameter is introduced. The resulting dynamics is then described by a two-dimensional map. In addition to the locally stabilizing effect due to the presence of memory, we show the existence of a double stability threshold which entails for different dynamic scenarios occurring when the memory parameter takes extreme values (i.e. when consideration of the last profit realization prevails or it is too much neglected). The eventuality of different coexisting attractors as well as the structure of the basins of attraction that characterizes the path dependence property of the model with memory is shown. In particular, through global analysis we also illustrate particular bifurcations sequences that may increase the complexity of the related basins of attraction.

Extremely high frequency sensitivity in a 'simple' ear.

PubMed

Moir, Hannah M; Jackson, Joseph C; Windmill, James F C

2013-08-23

An evolutionary war is being played out between the bat, which uses ultrasonic calls to locate insect prey, and the moth, which uses microscale ears to listen for the approaching bat. While the highest known frequency of bat echolocation calls is 212 kHz, the upper limit of moth hearing is considered much lower. Here, we show that the greater wax moth, Galleria mellonella, is capable of hearing ultrasonic frequencies approaching 300 kHz; the highest frequency sensitivity of any animal. With auditory frequency sensitivity that is unprecedented in the animal kingdom, the greater wax moth is ready and armed for any echolocation call adaptations made by the bat in the on-going bat-moth evolutionary war.

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.

Recent developments of axial flow compressors under transonic flow conditions

NASA Astrophysics Data System (ADS)

Srinivas, G.; Raghunandana, K.; Satish Shenoy, B.

2017-05-01

The objective of this paper is to give a holistic view of the most advanced technology and procedures that are practiced in the field of turbomachinery design. Compressor flow solver is the turbulence model used in the CFD to solve viscous problems. The popular techniques like Jameson’s rotated difference scheme was used to solve potential flow equation in transonic condition for two dimensional aero foils and later three dimensional wings. The gradient base method is also a popular method especially for compressor blade shape optimization. Various other types of optimization techniques available are Evolutionary algorithms (EAs) and Response surface methodology (RSM). It is observed that in order to improve compressor flow solver and to get agreeable results careful attention need to be paid towards viscous relations, grid resolution, turbulent modeling and artificial viscosity, in CFD. The advanced techniques like Jameson’s rotated difference had most substantial impact on wing design and aero foil. For compressor blade shape optimization, Evolutionary algorithm is quite simple than gradient based technique because it can solve the parameters simultaneously by searching from multiple points in the given design space. Response surface methodology (RSM) is a method basically used to design empirical models of the response that were observed and to study systematically the experimental data. This methodology analyses the correct relationship between expected responses (output) and design variables (input). RSM solves the function systematically in a series of mathematical and statistical processes. For turbomachinery blade optimization recently RSM has been implemented successfully. The well-designed high performance axial flow compressors finds its application in any air-breathing jet engines.

Biophysical Fitness Landscapes for Transcription Factor Binding Sites

PubMed Central

Haldane, Allan; Manhart, Michael; Morozov, Alexandre V.

2014-01-01

Phenotypic states and evolutionary trajectories available to cell populations are ultimately dictated by complex interactions among DNA, RNA, proteins, and other molecular species. Here we study how evolution of gene regulation in a single-cell eukaryote S. cerevisiae is affected by interactions between transcription factors (TFs) and their cognate DNA sites. Our study is informed by a comprehensive collection of genomic binding sites and high-throughput in vitro measurements of TF-DNA binding interactions. Using an evolutionary model for monomorphic populations evolving on a fitness landscape, we infer fitness as a function of TF-DNA binding to show that the shape of the inferred fitness functions is in broad agreement with a simple functional form inspired by a thermodynamic model of two-state TF-DNA binding. However, the effective parameters of the model are not always consistent with physical values, indicating selection pressures beyond the biophysical constraints imposed by TF-DNA interactions. We find little statistical support for the fitness landscape in which each position in the binding site evolves independently, indicating that epistasis is common in the evolution of gene regulation. Finally, by correlating TF-DNA binding energies with biological properties of the sites or the genes they regulate, we are able to rule out several scenarios of site-specific selection, under which binding sites of the same TF would experience different selection pressures depending on their position in the genome. These findings support the existence of universal fitness landscapes which shape evolution of all sites for a given TF, and whose properties are determined in part by the physics of protein-DNA interactions. PMID:25010228

Modeling the evolution of protein domain architectures using maximum parsimony.

PubMed

Fong, Jessica H; Geer, Lewis Y; Panchenko, Anna R; Bryant, Stephen H

2007-02-09

Domains are basic evolutionary units of proteins and most proteins have more than one domain. Advances in domain modeling and collection are making it possible to annotate a large fraction of known protein sequences by a linear ordering of their domains, yielding their architecture. Protein domain architectures link evolutionarily related proteins and underscore their shared functions. Here, we attempt to better understand this association by identifying the evolutionary pathways by which extant architectures may have evolved. We propose a model of evolution in which architectures arise through rearrangements of inferred precursor architectures and acquisition of new domains. These pathways are ranked using a parsimony principle, whereby scenarios requiring the fewest number of independent recombination events, namely fission and fusion operations, are assumed to be more likely. Using a data set of domain architectures present in 159 proteomes that represent all three major branches of the tree of life allows us to estimate the history of over 85% of all architectures in the sequence database. We find that the distribution of rearrangement classes is robust with respect to alternative parsimony rules for inferring the presence of precursor architectures in ancestral species. Analyzing the most parsimonious pathways, we find 87% of architectures to gain complexity over time through simple changes, among which fusion events account for 5.6 times as many architectures as fission. Our results may be used to compute domain architecture similarities, for example, based on the number of historical recombination events separating them. Domain architecture "neighbors" identified in this way may lead to new insights about the evolution of protein function.

Modeling the Evolution of Protein Domain Architectures Using Maximum Parsimony

PubMed Central

Fong, Jessica H.; Geer, Lewis Y.; Panchenko, Anna R.; Bryant, Stephen H.

2007-01-01

Domains are basic evolutionary units of proteins and most proteins have more than one domain. Advances in domain modeling and collection are making it possible to annotate a large fraction of known protein sequences by a linear ordering of their domains, yielding their architecture. Protein domain architectures link evolutionarily related proteins and underscore their shared functions. Here, we attempt to better understand this association by identifying the evolutionary pathways by which extant architectures may have evolved. We propose a model of evolution in which architectures arise through rearrangements of inferred precursor architectures and acquisition of new domains. These pathways are ranked using a parsimony principle, whereby scenarios requiring the fewest number of independent recombination events, namely fission and fusion operations, are assumed to be more likely. Using a data set of domain architectures present in 159 proteomes that represent all three major branches of the tree of life allows us to estimate the history of over 85% of all architectures in the sequence database. We find that the distribution of rearrangement classes is robust with respect to alternative parsimony rules for inferring the presence of precursor architectures in ancestral species. Analyzing the most parsimonious pathways, we find 87% of architectures to gain complexity over time through simple changes, among which fusion events account for 5.6 times as many architectures as fission. Our results may be used to compute domain architecture similarities, for example, based on the number of historical recombination events separating them. Domain architecture “neighbors” identified in this way may lead to new insights about the evolution of protein function. PMID:17166515

The importance of offshore origination revealed through ophiuroid phylogenomics.

PubMed

Bribiesca-Contreras, Guadalupe; Verbruggen, Heroen; Hugall, Andrew F; O'Hara, Timothy D

2017-07-12

Our knowledge of macro-evolutionary processes in the deep sea is poor, leading to much speculation about whether the deep sea is a source or sink of evolutionary adaptation. Here, we use a phylogenetic approach, on large molecular (688 species, 275 kbp) and distributional datasets (104 513 records) across an entire class of marine invertebrates (Ophiuroidea), to infer rates of bathymetric range shift over time between shallow and deep water biomes. Biome conservation is evident through the phylogeny, with the majority of species in most clades distributed within the same bathome. Despite this, bathymetric shifts have occurred. We inferred from ancestral reconstructions that eurybathic or intermediate distributions across both biomes were a transitional state and direct changes between shallow and deep sea did not occur. The macro-evolutionary pattern of bathome shift appeared to reflect micro-evolutionary processes of bathymetric speciation. Results suggest that most of the oldest clades have a deep-sea origin, but multiple colonization events indicate that the evolution of this group conforms neither to a simple onshore-offshore hypothesis, nor the opposite pattern. Both shallow and deep bathomes have played an important role in generating the current diversity of this major benthic class. © 2017 The Author(s).

An experimental investigation of evolutionary dynamics in the Rock-Paper-Scissors game.

PubMed

Hoffman, Moshe; Suetens, Sigrid; Gneezy, Uri; Nowak, Martin A

2015-03-06

Game theory describes social behaviors in humans and other biological organisms. By far, the most powerful tool available to game theorists is the concept of a Nash Equilibrium (NE), which is motivated by perfect rationality. NE specifies a strategy for everyone, such that no one would benefit by deviating unilaterally from his/her strategy. Another powerful tool available to game theorists are evolutionary dynamics (ED). Motivated by evolutionary and learning processes, ED specify changes in strategies over time in a population, such that more successful strategies typically become more frequent. A simple game that illustrates interesting ED is the generalized Rock-Paper-Scissors (RPS) game. The RPS game extends the children's game to situations where winning or losing can matter more or less relative to tying. Here we investigate experimentally three RPS games, where the NE is always to randomize with equal probability, but the evolutionary stability of this strategy changes. Consistent with the prediction of ED we find that aggregate behavior is far away from NE when it is evolutionarily unstable. Our findings add to the growing literature that demonstrates the predictive validity of ED in large-scale incentivized laboratory experiments with human subjects.

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

Three-dimensional deformation response of a NiTi shape memory helical-coil actuator during thermomechanical cycling: experimentally validated numerical model

NASA Astrophysics Data System (ADS)

Dhakal, B.; Nicholson, D. E.; Saleeb, A. F.; Padula, S. A., II; Vaidyanathan, R.

2016-09-01

Shape memory alloy (SMA) actuators often operate under a complex state of stress for an extended number of thermomechanical cycles in many aerospace and engineering applications. Hence, it becomes important to account for multi-axial stress states and deformation characteristics (which evolve with thermomechanical cycling) when calibrating any SMA model for implementation in large-scale simulation of actuators. To this end, the present work is focused on the experimental validation of an SMA model calibrated for the transient and cyclic evolutionary behavior of shape memory Ni49.9Ti50.1, for the actuation of axially loaded helical-coil springs. The approach requires both experimental and computational aspects to appropriately assess the thermomechanical response of these multi-dimensional structures. As such, an instrumented and controlled experimental setup was assembled to obtain temperature, torque, degree of twist and extension, while controlling end constraints during heating and cooling of an SMA spring under a constant externally applied axial load. The computational component assesses the capabilities of a general, multi-axial, SMA material-modeling framework, calibrated for Ni49.9Ti50.1 with regard to its usefulness in the simulation of SMA helical-coil spring actuators. Axial extension, being the primary response, was examined on an axially-loaded spring with multiple active coils. Two different conditions of end boundary constraint were investigated in both the numerical simulations as well as the validation experiments: Case (1) where the loading end is restrained against twist (and the resulting torque measured as the secondary response) and Case (2) where the loading end is free to twist (and the degree of twist measured as the secondary response). The present study focuses on the transient and evolutionary response associated with the initial isothermal loading and the subsequent thermal cycles under applied constant axial load. The experimental results for the helical-coil actuator under two different boundary conditions are found to be within error to their counterparts in the numerical simulations. The numerical simulation and the experimental validation demonstrate similar transient and evolutionary behavior in the deformation response under the complex, inhomogeneous, multi-axial stress-state and large deformations of the helical-coil actuator. This response, although substantially different in magnitude, exhibited similar evolutionary characteristics to the simple, uniaxial, homogeneous, stress-state of the isobaric tensile tests results used for the model calibration. There was no significant difference in the axial displacement (primary response) magnitudes observed between Cases (1) and (2) for the number of cycles investigated here. The simulated secondary responses of the two cases evolved in a similar manner when compared to the experimental validation of the respective cases.

A Stochastic Evolutionary Model for Protein Structure Alignment and Phylogeny

PubMed Central

Challis, Christopher J.; Schmidler, Scott C.

2012-01-01

We present a stochastic process model for the joint evolution of protein primary and tertiary structure, suitable for use in alignment and estimation of phylogeny. Indels arise from a classic Links model, and mutations follow a standard substitution matrix, whereas backbone atoms diffuse in three-dimensional space according to an Ornstein–Uhlenbeck process. The model allows for simultaneous estimation of evolutionary distances, indel rates, structural drift rates, and alignments, while fully accounting for uncertainty. The inclusion of structural information enables phylogenetic inference on time scales not previously attainable with sequence evolution models. The model also provides a tool for testing evolutionary hypotheses and improving our understanding of protein structural evolution. PMID:22723302

Predicting vegetation type through physiological and environmental interactions with leaf traits: evergreen and deciduous forests in an earth system modeling framework.

PubMed

Weng, Ensheng; Farrior, Caroline E; Dybzinski, Ray; Pacala, Stephen W

2017-06-01

Earth system models are incorporating plant trait diversity into their land components to better predict vegetation dynamics in a changing climate. However, extant plant trait distributions will not allow extrapolations to novel community assemblages in future climates, which will require a mechanistic understanding of the trade-offs that determine trait diversity. In this study, we show how physiological trade-offs involving leaf mass per unit area (LMA), leaf lifespan, leaf nitrogen, and leaf respiration may explain the distribution patterns of evergreen and deciduous trees in the temperate and boreal zones based on (1) an evolutionary analysis of a simple mathematical model and (2) simulation experiments of an individual-based dynamic vegetation model (i.e., LM3-PPA). The evolutionary analysis shows that these leaf traits set up a trade-off between carbon- and nitrogen-use efficiency at the scale of individual trees and therefore determine competitively dominant leaf strategies. As soil nitrogen availability increases, the dominant leaf strategy switches from one that is high in nitrogen-use efficiency to one that is high in carbon-use efficiency or, equivalently, from high-LMA/long-lived leaves (i.e., evergreen) to low-LMA/short-lived leaves (i.e., deciduous). In a region of intermediate soil nitrogen availability, the dominant leaf strategy may be either deciduous or evergreen depending on the initial conditions of plant trait abundance (i.e., founder controlled) due to feedbacks of leaf traits on soil nitrogen mineralization through litter quality. Simulated successional patterns by LM3-PPA from the leaf physiological trade-offs are consistent with observed successional dynamics of evergreen and deciduous forests at three sites spanning the temperate to boreal zones. © 2016 John Wiley & Sons Ltd.

Evolutionary perspectives on ageing.

PubMed

Reichard, Martin

2017-10-01

From an evolutionary perspective, ageing is a decrease in fitness with chronological age - expressed by an increase in mortality risk and/or decline in reproductive success and mediated by deterioration of functional performance. While this makes ageing intuitively paradoxical - detrimental to individual fitness - evolutionary theory offers answers as to why ageing has evolved. In this review, I first briefly examine the classic evolutionary theories of ageing and their empirical tests, and highlight recent findings that have advanced our understanding of the evolution of ageing (condition-dependent survival, positive pleiotropy). I then provide an overview of recent theoretical extensions and modifications that accommodate those new discoveries. I discuss the role of indeterminate (asymptotic) growth for lifetime increases in fecundity and ageing trajectories. I outline alternative views that challenge a universal existence of senescence - namely the lack of a germ-soma distinction and the ability of tissue replacement and retrogression to younger developmental stages in modular organisms. I argue that rejuvenation at the organismal level is plausible, but includes a return to a simple developmental stage. This may exempt a particular genotype from somatic defects but, correspondingly, removes any information acquired during development. A resolution of the question of whether a rejuvenated individual is the same entity is central to the recognition of whether current evolutionary theories of ageing, with their extensions and modifications, can explain the patterns of ageing across the Tree of Life. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ordinary least squares regression is indicated for studies of allometry.

PubMed

Kilmer, J T; Rodríguez, R L

2017-01-01

When it comes to fitting simple allometric slopes through measurement data, evolutionary biologists have been torn between regression methods. On the one hand, there is the ordinary least squares (OLS) regression, which is commonly used across many disciplines of biology to fit lines through data, but which has a reputation for underestimating slopes when measurement error is present. On the other hand, there is the reduced major axis (RMA) regression, which is often recommended as a substitute for OLS regression in studies of allometry, but which has several weaknesses of its own. Here, we review statistical theory as it applies to evolutionary biology and studies of allometry. We point out that the concerns that arise from measurement error for OLS regression are small and straightforward to deal with, whereas RMA has several key properties that make it unfit for use in the field of allometry. The recommended approach for researchers interested in allometry is to use OLS regression on measurements taken with low (but realistically achievable) measurement error. If measurement error is unavoidable and relatively large, it is preferable to correct for slope attenuation rather than to turn to RMA regression, or to take the expected amount of attenuation into account when interpreting the data. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

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.

A hybrid neural learning algorithm using evolutionary learning and derivative free local search method.

PubMed

Ghosh, Ranadhir; Yearwood, John; Ghosh, Moumita; Bagirov, Adil

2006-06-01

In this paper we investigate a hybrid model based on the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. Also we discuss different variants for hybrid models using the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. The Discrete Gradient method has the advantage of being able to jump over many local minima and find very deep local minima. However, earlier research has shown that a good starting point for the discrete gradient method can improve the quality of the solution point. Evolutionary algorithms are best suited for global optimisation problems. Nevertheless they are cursed with longer training times and often unsuitable for real world application. For optimisation problems such as weight optimisation for ANNs in real world applications the dimensions are large and time complexity is critical. Hence the idea of a hybrid model can be a suitable option. In this paper we propose different fusion strategies for hybrid models combining the evolutionary strategy with the discrete gradient method to obtain an optimal solution much quicker. Three different fusion strategies are discussed: a linear hybrid model, an iterative hybrid model and a restricted local search hybrid model. Comparative results on a range of standard datasets are provided for different fusion hybrid models.

Adaptive developmental delay in Chagas disease vectors: an evolutionary ecology approach.

PubMed

Menu, Frédéric; Ginoux, Marine; Rajon, Etienne; Lazzari, Claudio R; Rabinovich, Jorge E

2010-05-25

The developmental time of vector insects is important in population dynamics, evolutionary biology, epidemiology and in their responses to global climatic change. In the triatomines (Triatominae, Reduviidae), vectors of Chagas disease, evolutionary ecology concepts, which may allow for a better understanding of their biology, have not been applied. Despite delay in the molting in some individuals observed in triatomines, no effort was made to explain this variability. We applied four methods: (1) an e-mail survey sent to 30 researchers with experience in triatomines, (2) a statistical description of the developmental time of eleven triatomine species, (3) a relationship between development time pattern and climatic inter-annual variability, (4) a mathematical optimization model of evolution of developmental delay (diapause). 85.6% of responses informed on prolonged developmental times in 5(th) instar nymphs, with 20 species identified with remarkable developmental delays. The developmental time analysis showed some degree of bi-modal pattern of the development time of the 5(th) instars in nine out of eleven species but no trend between development time pattern and climatic inter-annual variability was observed. Our optimization model predicts that the developmental delays could be due to an adaptive risk-spreading diapause strategy, only if survival throughout the diapause period and the probability of random occurrence of "bad" environmental conditions are sufficiently high. Developmental delay may not be a simple non-adaptive phenotypic plasticity in development time, and could be a form of adaptive diapause associated to a physiological mechanism related to the postponement of the initiation of reproduction, as an adaptation to environmental stochasticity through a spreading of risk (bet-hedging) strategy. We identify a series of parameters that can be measured in the field and laboratory to test this hypothesis. The importance of these findings is discussed in terms of global climatic change and epidemiological consequences.

Evolutionary advantage via common action of recombination and neutrality

NASA Astrophysics Data System (ADS)

Saakian, David B.; Hu, Chin-Kun

2013-11-01

We investigate evolution models with recombination and neutrality. We consider the Crow-Kimura (parallel) mutation-selection model with the neutral fitness landscape, in which there is a central peak with high fitness A, and some of 1-point mutants have the same high fitness A, while the fitness of other sequences is 0. We find that the effect of recombination and neutrality depends on the concrete version of both neutrality and recombination. We consider three versions of neutrality: (a) all the nearest neighbor sequences of the peak sequence have the same high fitness A; (b) all the l-point mutations in a piece of genome of length l≥1 are neutral; (c) the neutral sequences are randomly distributed among the nearest neighbors of the peak sequences. We also consider three versions of recombination: (I) the simple horizontal gene transfer (HGT) of one nucleotide; (II) the exchange of a piece of genome of length l, HGT-l; (III) two-point crossover recombination (2CR). For the case of (a), the 2CR gives a rather strong contribution to the mean fitness, much stronger than that of HGT for a large genome length L. For the random distribution of neutral sequences there is a critical degree of neutrality νc, and for μ<μc and (μc-μ) is not large, the 2CR suppresses the mean fitness while HGT increases it; for ν much larger than νc, the 2CR and HGT-l increase the mean fitness larger than that of the HGT. We also consider the recombination in the case of smooth fitness landscapes. The recombination gives some advantage in the evolutionary dynamics, where recombination distinguishes clearly the mean-field-like evolutionary factors from the fluctuation-like ones. By contrast, mutations affect the mean-field-like and fluctuation-like factors similarly. Consequently, recombination can accelerate the non-mean-field (fluctuation) type dynamics without considerably affecting the mean-field-like factors.

Automated discovery of local search heuristics for satisfiability testing.

PubMed

Fukunaga, Alex S

2008-01-01

The development of successful metaheuristic algorithms such as local search for a difficult problem such as satisfiability testing (SAT) is a challenging task. We investigate an evolutionary approach to automating the discovery of new local search heuristics for SAT. We show that several well-known SAT local search algorithms such as Walksat and Novelty are composite heuristics that are derived from novel combinations of a set of building blocks. Based on this observation, we developed CLASS, a genetic programming system that uses a simple composition operator to automatically discover SAT local search heuristics. New heuristics discovered by CLASS are shown to be competitive with the best Walksat variants, including Novelty+. Evolutionary algorithms have previously been applied to directly evolve a solution for a particular SAT instance. We show that the heuristics discovered by CLASS are also competitive with these previous, direct evolutionary approaches for SAT. We also analyze the local search behavior of the learned heuristics using the depth, mobility, and coverage metrics proposed by Schuurmans and Southey.

Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron for Large Scale Classification of Protein Structures.

PubMed

Arana-Daniel, Nancy; Gallegos, Alberto A; López-Franco, Carlos; Alanís, Alma Y; Morales, Jacob; López-Franco, Adriana

2016-01-01

With the increasing power of computers, the amount of data that can be processed in small periods of time has grown exponentially, as has the importance of classifying large-scale data efficiently. Support vector machines have shown good results classifying large amounts of high-dimensional data, such as data generated by protein structure prediction, spam recognition, medical diagnosis, optical character recognition and text classification, etc. Most state of the art approaches for large-scale learning use traditional optimization methods, such as quadratic programming or gradient descent, which makes the use of evolutionary algorithms for training support vector machines an area to be explored. The present paper proposes an approach that is simple to implement based on evolutionary algorithms and Kernel-Adatron for solving large-scale classification problems, focusing on protein structure prediction. The functional properties of proteins depend upon their three-dimensional structures. Knowing the structures of proteins is crucial for biology and can lead to improvements in areas such as medicine, agriculture and biofuels.

Maximizing Submodular Functions under Matroid Constraints by Evolutionary Algorithms.

PubMed

Friedrich, Tobias; Neumann, Frank

2015-01-01

Many combinatorial optimization problems have underlying goal functions that are submodular. The classical goal is to find a good solution for a given submodular function f under a given set of constraints. In this paper, we investigate the runtime of a simple single objective evolutionary algorithm called (1 + 1) EA and a multiobjective evolutionary algorithm called GSEMO until they have obtained a good approximation for submodular functions. For the case of monotone submodular functions and uniform cardinality constraints, we show that the GSEMO achieves a (1 - 1/e)-approximation in expected polynomial time. For the case of monotone functions where the constraints are given by the intersection of K ≥ 2 matroids, we show that the (1 + 1) EA achieves a (1/k + δ)-approximation in expected polynomial time for any constant δ > 0. Turning to nonmonotone symmetric submodular functions with k ≥ 1 matroid intersection constraints, we show that the GSEMO achieves a 1/((k + 2)(1 + ε))-approximation in expected time O(n(k + 6)log(n)/ε.

Quantifying evolutionary dynamics from variant-frequency time series

NASA Astrophysics Data System (ADS)

Khatri, Bhavin S.

2016-09-01

From Kimura’s neutral theory of protein evolution to Hubbell’s neutral theory of biodiversity, quantifying the relative importance of neutrality versus selection has long been a basic question in evolutionary biology and ecology. With deep sequencing technologies, this question is taking on a new form: given a time-series of the frequency of different variants in a population, what is the likelihood that the observation has arisen due to selection or neutrality? To tackle the 2-variant case, we exploit Fisher’s angular transformation, which despite being discovered by Ronald Fisher a century ago, has remained an intellectual curiosity. We show together with a heuristic approach it provides a simple solution for the transition probability density at short times, including drift, selection and mutation. Our results show under that under strong selection and sufficiently frequent sampling these evolutionary parameters can be accurately determined from simulation data and so they provide a theoretical basis for techniques to detect selection from variant or polymorphism frequency time-series.

Quantifying evolutionary dynamics from variant-frequency time series.

PubMed

Khatri, Bhavin S

2016-09-12

From Kimura's neutral theory of protein evolution to Hubbell's neutral theory of biodiversity, quantifying the relative importance of neutrality versus selection has long been a basic question in evolutionary biology and ecology. With deep sequencing technologies, this question is taking on a new form: given a time-series of the frequency of different variants in a population, what is the likelihood that the observation has arisen due to selection or neutrality? To tackle the 2-variant case, we exploit Fisher's angular transformation, which despite being discovered by Ronald Fisher a century ago, has remained an intellectual curiosity. We show together with a heuristic approach it provides a simple solution for the transition probability density at short times, including drift, selection and mutation. Our results show under that under strong selection and sufficiently frequent sampling these evolutionary parameters can be accurately determined from simulation data and so they provide a theoretical basis for techniques to detect selection from variant or polymorphism frequency time-series.

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.

Competition-Colonization Trade-Offs, Competitive Uncertainty, and the Evolutionary Assembly of Species

PubMed Central

Pillai, Pradeep; Guichard, Frédéric

2012-01-01

We utilize a standard competition-colonization metapopulation model in order to study the evolutionary assembly of species. Based on earlier work showing how models assuming strict competitive hierarchies will likely lead to runaway evolution and self-extinction for all species, we adopt a continuous competition function that allows for levels of uncertainty in the outcome of competition. We then, by extending the standard patch-dynamic metapopulation model in order to include evolutionary dynamics, allow for the coevolution of species into stable communities composed of species with distinct limiting similarities. Runaway evolution towards stochastic extinction then becomes a limiting case controlled by the level of competitive uncertainty. We demonstrate how intermediate competitive uncertainty maximizes the equilibrium species richness as well as maximizes the adaptive radiation and self-assembly of species under adaptive dynamics with mutations of non-negligible size. By reconciling competition-colonization tradeoff theory with co-evolutionary dynamics, our results reveal the importance of intermediate levels of competitive uncertainty for the evolutionary assembly of species. PMID:22448253

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.

Genetic Correlations Greatly Increase Mutational Robustness and Can Both Reduce and Enhance Evolvability

PubMed Central

Greenbury, Sam F.; Schaper, Steffen; Ahnert, Sebastian E.; Louis, Ard A.

2016-01-01

Mutational neighbourhoods in genotype-phenotype (GP) maps are widely believed to be more likely to share characteristics than expected from random chance. Such genetic correlations should strongly influence evolutionary dynamics. We explore and quantify these intuitions by comparing three GP maps—a model for RNA secondary structure, the HP model for protein tertiary structure, and the Polyomino model for protein quaternary structure—to a simple random null model that maintains the number of genotypes mapping to each phenotype, but assigns genotypes randomly. The mutational neighbourhood of a genotype in these GP maps is much more likely to contain genotypes mapping to the same phenotype than in the random null model. Such neutral correlations can be quantified by the robustness to mutations, which can be many orders of magnitude larger than that of the null model, and crucially, above the critical threshold for the formation of large neutral networks of mutationally connected genotypes which enhance the capacity for the exploration of phenotypic novelty. Thus neutral correlations increase evolvability. We also study non-neutral correlations: Compared to the null model, i) If a particular (non-neutral) phenotype is found once in the 1-mutation neighbourhood of a genotype, then the chance of finding that phenotype multiple times in this neighbourhood is larger than expected; ii) If two genotypes are connected by a single neutral mutation, then their respective non-neutral 1-mutation neighbourhoods are more likely to be similar; iii) If a genotype maps to a folding or self-assembling phenotype, then its non-neutral neighbours are less likely to be a potentially deleterious non-folding or non-assembling phenotype. Non-neutral correlations of type i) and ii) reduce the rate at which new phenotypes can be found by neutral exploration, and so may diminish evolvability, while non-neutral correlations of type iii) may instead facilitate evolutionary exploration and so increase evolvability. PMID:26937652

Evolution in an Afternoon: Rapid Natural Selection and Adaptation of Bacterial Populations

ERIC Educational Resources Information Center

Delpech, Roger

2009-01-01

This paper describes a simple, rapid and low-cost technique for growing bacteria (or other microbes) in an environmental gradient, in order to determine the tolerance of the microbial population to varying concentrations of sodium chloride ions, and suggests how the evolutionary response of a microbial population to the selection pressure of the…

Multiobjective Optimization Using a Pareto Differential Evolution Approach

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.; Biegel, Bryan A. (Technical Monitor)

2002-01-01

Differential Evolution is a simple, fast, and robust evolutionary algorithm that has proven effective in determining the global optimum for several difficult single-objective optimization problems. In this paper, the Differential Evolution algorithm is extended to multiobjective optimization problems by using a Pareto-based approach. The algorithm performs well when applied to several test optimization problems from the literature.

THE DIAGNOSIS AND TREATMENT OF SPEECH AND READING PROBLEMS.

ERIC Educational Resources Information Center

DELACATO, CARL H.

THE BASIC THESIS OF THE AUTHOR IS THAT THE NERVOUS SYSTEM OF MAN HAS EVOLVED FROM A VERY SIMPLE TO A VERY COMPLEX MECHANISM. MAN HAS ACHIEVED CORTICAL DOMINANCE WHEREIN ONE SIDE OF THE CORTEX CONTROLS THE SKILLS WHICH SEPARATE MAN FROM OTHER ANIMALS. THIS EVOLUTIONARY PROCESS MUST BE RECAPITULATED ONTOGENETICALLY OR MOBILITY AND COMMUNICATION…

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.

Comparative phylogeography clarifies the complexity and problems of continental distribution that drove A. R. Wallace to favor islands

PubMed Central

Riddle, Brett R.

2016-01-01

Deciphering the geographic context of diversification and distributional dynamics in continental biotas has long been an interest of biogeographers, ecologists, and evolutionary biologists. Thirty years ago, the approach now known as comparative phylogeography was introduced in a landmark study of a continental biota. Here, I use a set of 455 studies to explore the current scope of continental comparative phylogeography, including geographic, conceptual, temporal, ecological, and genomic attributes. Geographically, studies are more frequent in the northern hemisphere, but the south is catching up. Most studies focus on a Quaternary timeframe, but the Neogene is well represented. As such, explanations for geographic structure and history include geological and climatic events in Earth history, and responses include vicariance, dispersal, and range contraction-expansion into and out of refugia. Focal taxa are biased toward terrestrial or semiterrestrial vertebrates, although plants and invertebrates are well represented in some regions. The use of various kinds of nuclear DNA markers is increasing, as are multiple locus studies, but use of organelle DNA is not decreasing. Species distribution models are not yet widely incorporated into studies. In the future, continental comparative phylogeographers will continue to contribute to erosion of the simple vicariance vs. dispersal paradigm, including exposure of the widespread nature of temporal pseudocongruence and its implications for models of diversification; provide new templates for addressing a variety of ecological and evolutionary traits; and develop closer working relationships with earth scientists and biologists in a variety of disciplines. PMID:27432953

Informational Gene Phylogenies Do Not Support a Fourth Domain of Life for Nucleocytoplasmic Large DNA Viruses

PubMed Central

Williams, Tom A.; Embley, T. Martin; Heinz, Eva

2011-01-01

Mimivirus is a nucleocytoplasmic large DNA virus (NCLDV) with a genome size (1.2 Mb) and coding capacity ( 1000 genes) comparable to that of some cellular organisms. Unlike other viruses, Mimivirus and its NCLDV relatives encode homologs of broadly conserved informational genes found in Bacteria, Archaea, and Eukaryotes, raising the possibility that they could be placed on the tree of life. A recent phylogenetic analysis of these genes showed the NCLDVs emerging as a monophyletic group branching between Eukaryotes and Archaea. These trees were interpreted as evidence for an independent “fourth domain” of life that may have contributed DNA processing genes to the ancestral eukaryote. However, the analysis of ancient evolutionary events is challenging, and tree reconstruction is susceptible to bias resulting from non-phylogenetic signals in the data. These include compositional heterogeneity and homoplasy, which can lead to the spurious grouping of compositionally-similar or fast-evolving sequences. Here, we show that these informational gene alignments contain both significant compositional heterogeneity and homoplasy, which were not adequately modelled in the original analysis. When we use more realistic evolutionary models that better fit the data, the resulting trees are unable to reject a simple null hypothesis in which these informational genes, like many other NCLDV genes, were acquired by horizontal transfer from eukaryotic hosts. Our results suggest that a fourth domain is not required to explain the available sequence data. PMID:21698163

The cost of copy number in a selfish genetic element: the 2-μm plasmid of Saccharomyces cerevisiae.

PubMed

Harrison, Ellie; Koufopanou, V; Burt, A; MacLean, R C

2012-11-01

Many autonomously replicating genetic elements exist as multiple copies within the cell. The copy number of these elements is often assumed to have important fitness consequences for both element and host, yet the forces shaping its evolution are not well understood. The 2 μm is a multicopy plasmid of Saccharomyces yeasts, encoding just four genes that are solely involved in plasmid replication. One simple model for the fitness relationship between yeasts and 2 μm is that plasmid copy number evolves as a trade-off between selection for increased vertical transmission, favouring high copy number, and selection for decreased virulence, favouring low copy number. To test this model, we experimentally manipulated the copy number of the plasmid and directly measured the fitness cost, in terms of growth rate reduction, associated with high plasmid copy number. We find that the fitness burden imposed by the 2 μm increases with plasmid copy number, such that each copy imposes a fitness burden of 0.17% (± 0.008%), greatly exceeding the cost expected for it to be stably maintained in yeast populations. Our results demonstrate the crucial importance of copy number in the evolution of yeast per 2 μm associations and pave the way for future studies examining how selection can shape the cost of multicopy elements. © 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.

Comparative phylogeography clarifies the complexity and problems of continental distribution that drove A. R. Wallace to favor islands.

PubMed

Riddle, Brett R

2016-07-19

Deciphering the geographic context of diversification and distributional dynamics in continental biotas has long been an interest of biogeographers, ecologists, and evolutionary biologists. Thirty years ago, the approach now known as comparative phylogeography was introduced in a landmark study of a continental biota. Here, I use a set of 455 studies to explore the current scope of continental comparative phylogeography, including geographic, conceptual, temporal, ecological, and genomic attributes. Geographically, studies are more frequent in the northern hemisphere, but the south is catching up. Most studies focus on a Quaternary timeframe, but the Neogene is well represented. As such, explanations for geographic structure and history include geological and climatic events in Earth history, and responses include vicariance, dispersal, and range contraction-expansion into and out of refugia. Focal taxa are biased toward terrestrial or semiterrestrial vertebrates, although plants and invertebrates are well represented in some regions. The use of various kinds of nuclear DNA markers is increasing, as are multiple locus studies, but use of organelle DNA is not decreasing. Species distribution models are not yet widely incorporated into studies. In the future, continental comparative phylogeographers will continue to contribute to erosion of the simple vicariance vs. dispersal paradigm, including exposure of the widespread nature of temporal pseudocongruence and its implications for models of diversification; provide new templates for addressing a variety of ecological and evolutionary traits; and develop closer working relationships with earth scientists and biologists in a variety of disciplines.

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.

A unified framework for the pareto law and Matthew effect using scale-free networks

NASA Astrophysics Data System (ADS)

Hu, M.-B.; Wang, W.-X.; Jiang, R.; Wu, Q.-S.; Wang, B.-H.; Wu, Y.-H.

2006-09-01

We investigate the accumulated wealth distribution by adopting evolutionary games taking place on scale-free networks. The system self-organizes to a critical Pareto distribution (1897) of wealth P(m)˜m-(v+1) with 1.6 < v <2.0 (which is in agreement with that of U.S. or Japan). Particularly, the agent's personal wealth is proportional to its number of contacts (connectivity), and this leads to the phenomenon that the rich gets richer and the poor gets relatively poorer, which is consistent with the Matthew Effect present in society, economy, science and so on. Though our model is simple, it provides a good representation of cooperation and profit accumulation behavior in economy, and it combines the network theory with econophysics.

The possible nature of socket stars in H II regions

NASA Technical Reports Server (NTRS)

Castelaz, Michael W.

1990-01-01

Close inspection of faint stars (V of about 14 mag) in H II regions show that they appear to be surrounded by circumstellar envelopes of about 10 arcsecs in diameter (as reported by Feibelman in 1989). The present premise is that the sockets are envelopes of obscuring dust which should emit a measurable amount of infrared radiation based on a simple thermal equilibrium model. A search of literature shows that, of 36 socket stars listed by Feibelman, 17 have been measured in the infrared. Of the 17, 14 show excess IR emission. This is very strong evidence that the socket stars are really stars with circumstellar envelopes. Socket stars may be a new type of astronomical object or well-known astronomical objects in environments or evolutionary states not previously seen.

Social Information Links Individual Behavior to Population and Community Dynamics.

PubMed

Gil, Michael A; Hein, Andrew M; Spiegel, Orr; Baskett, Marissa L; Sih, Andrew

2018-05-07

When individual animals make decisions, they routinely use information produced intentionally or unintentionally by other individuals. Despite its prevalence and established fitness consequences, the effects of such social information on ecological dynamics remain poorly understood. Here, we synthesize results from ecology, evolutionary biology, and animal behavior to show how the use of social information can profoundly influence the dynamics of populations and communities. We combine recent theoretical and empirical results and introduce simple population models to illustrate how social information use can drive positive density-dependent growth of populations and communities (Allee effects). Furthermore, social information can shift the nature and strength of species interactions, change the outcome of competition, and potentially increase extinction risk in harvested populations and communities. Copyright © 2018 Elsevier Ltd. All rights reserved.

Early understandings of simple food chains: A learning progression for the preschool years

NASA Astrophysics Data System (ADS)

Allen, Michael

2017-07-01

Aspects of preschoolers' ecological understandings were explored in a cross-age, quantitative study that utilised a sample of seventy-five 3- to 5-year-old children. Specifically, their concepts of feeding relationships were determined by presenting physical models of three-step food chains during structured interviews. A majority of children, particularly 5-year olds, were capable of grasping concepts inherent in food chain topics that are scheduled to appear later in their schooling. In part, age differences in children's reasoning can be accounted for by attentional theory based on evolutionary predator avoidance adaptations, which tended to become significant at 5 years. Data suggest that these aspects of preschool ecological education could be increased in sophistication, thus accelerating children's understandings about the environment beyond what is currently the case.

Credible threats and promises.

PubMed Central

McNamara, John M; Houston, Alasdair I

2002-01-01

We consider various implications of information about the other player in two-player evolutionary games. A simple model of desertion shows that information about the partner's behaviour can be disadvantageous, and highlights the idea of credible threats. We then discuss the general issue of whether the partner can convince the focal player that it will behave in a specific way, i.e. whether the focal player can make credible threats or promises. We show that when desertion decisions depend on reserves, a player can manipulate its reserves so as to create a credible threat of desertion. We then extend previous work on the evolution of trust and commitment, discussing conditions under which it is advantageous to assume that a partner will behave in a certain way even though it is not in its best interest. PMID:12495517

Credible threats and promises.

PubMed

McNamara, John M; Houston, Alasdair I

2002-11-29

We consider various implications of information about the other player in two-player evolutionary games. A simple model of desertion shows that information about the partner's behaviour can be disadvantageous, and highlights the idea of credible threats. We then discuss the general issue of whether the partner can convince the focal player that it will behave in a specific way, i.e. whether the focal player can make credible threats or promises. We show that when desertion decisions depend on reserves, a player can manipulate its reserves so as to create a credible threat of desertion. We then extend previous work on the evolution of trust and commitment, discussing conditions under which it is advantageous to assume that a partner will behave in a certain way even though it is not in its best interest.

The dynamics of superclusters - Initial determination of the mass density of the universe at large scales

NASA Technical Reports Server (NTRS)

Ford, H. C.; Ciardullo, R.; Harms, R. J.; Bartko, F.

1981-01-01

The radial velocities of cluster members of two rich, large superclusters have been measured in order to probe the supercluster mass densities, and simple evolutionary models have been computed to place limits upon the mass density within each supercluster. These superclusters represent true physical associations of size of about 100 Mpc seen presently at an early stage of evolution. One supercluster is weakly bound, the other probably barely bound, but possibly marginally unbound. Gravity has noticeably slowed the Hubble expansion of both superclusters. Galaxy surface-density counts and the density enhancement of Abell clusters within each supercluster were used to derive the ratio of mass densities of the superclusters to the mean field mass density. The results strongly exclude a closed universe.

Model of community emergence in weighted social networks

NASA Astrophysics Data System (ADS)

Kumpula, J. M.; Onnela, J.-P.; Saramäki, J.; Kertész, J.; Kaski, K.

2009-04-01

Over the years network theory has proven to be rapidly expanding methodology to investigate various complex systems and it has turned out to give quite unparalleled insight to their structure, function, and response through data analysis, modeling, and simulation. For social systems in particular the network approach has empirically revealed a modular structure due to interplay between the network topology and link weights between network nodes or individuals. This inspired us to develop a simple network model that could catch some salient features of mesoscopic community and macroscopic topology formation during network evolution. Our model is based on two fundamental mechanisms of network sociology for individuals to find new friends, namely cyclic closure and focal closure, which are mimicked by local search-link-reinforcement and random global attachment mechanisms, respectively. In addition we included to the model a node deletion mechanism by removing all its links simultaneously, which corresponds for an individual to depart from the network. Here we describe in detail the implementation of our model algorithm, which was found to be computationally efficient and produce many empirically observed features of large-scale social networks. Thus this model opens a new perspective for studying such collective social phenomena as spreading, structure formation, and evolutionary processes.

Toward the Darwinian transition: Switching between distributed and speciated states in a simple model of early life.

PubMed

Arnoldt, Hinrich; Strogatz, Steven H; Timme, Marc

2015-01-01

It has been hypothesized that in the era just before the last universal common ancestor emerged, life on earth was fundamentally collective. Ancient life forms shared their genetic material freely through massive horizontal gene transfer (HGT). At a certain point, however, life made a transition to the modern era of individuality and vertical descent. Here we present a minimal model for stochastic processes potentially contributing to this hypothesized "Darwinian transition." The model suggests that HGT-dominated dynamics may have been intermittently interrupted by selection-driven processes during which genotypes became fitter and decreased their inclination toward HGT. Stochastic switching in the population dynamics with three-point (hypernetwork) interactions may have destabilized the HGT-dominated collective state and essentially contributed to the emergence of vertical descent and the first well-defined species in early evolution. A systematic nonlinear analysis of the stochastic model dynamics covering key features of evolutionary processes (such as selection, mutation, drift and HGT) supports this view. Our findings thus suggest a viable direction out of early collective evolution, potentially enabling the start of individuality and vertical Darwinian evolution.

Evolution-informed forecasting of seasonal influenza A (H3N2).

PubMed

Du, Xiangjun; King, Aaron A; Woods, Robert J; Pascual, Mercedes

2017-10-25

Interpandemic or seasonal influenza A, currently subtypes H3N2 and H1N1, exacts an enormous annual burden both in terms of human health and economic impact. Incidence prediction ahead of season remains a challenge largely because of the virus' antigenic evolution. We propose a forecasting approach that incorporates evolutionary change into a mechanistic epidemiological model. The proposed models are simple enough that their parameters can be estimated from retrospective surveillance data. These models link amino acid sequences of hemagglutinin epitopes with a transmission model for seasonal H3N2 influenza, also informed by H1N1 levels. With a monthly time series of H3N2 incidence in the United States for more than 10 years, we demonstrate the feasibility of skillful prediction for total cases ahead of season, with a tendency to underpredict monthly peak epidemic size, and an accurate real-time forecast for the 2016/2017 influenza season. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Minority games, evolving capitals and replicator dynamics

NASA Astrophysics Data System (ADS)

Galla, Tobias; Zhang, Yi-Cheng

2009-11-01

We discuss a simple version of the minority game (MG) in which agents hold only one strategy each, but in which their capitals evolve dynamically according to their success and in which the total trading volume varies in time accordingly. This feature is known to be crucial for MGs to reproduce stylized facts of real market data. The stationary states and phase diagram of the model can be computed, and we show that the ergodicity breaking phase transition common for MGs, and marked by a divergence of the integrated response, is present also in this simplified model. An analogous majority game turns out to be relatively void of interesting features, and the total capital is found to diverge in time. Introducing a restraining force leads to a model akin to the replicator dynamics of evolutionary game theory, and we demonstrate that here a different type of phase transition is observed. Finally we briefly discuss the relation of this model with one strategy per player to more sophisticated minority games with dynamical capitals and several trading strategies per agent.

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.

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.

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...

Do males pay for sex? Sex-specific selection coefficients suggest not.

PubMed

Prokop, Zofia M; Prus, Monika A; Gaczorek, Tomasz S; Sychta, Karolina; Palka, Joanna K; Plesnar-Bielak, Agata; Skarboń, Magdalena

2017-03-01

Selection acting on males can reduce mutation load of sexual relative to asexual populations, thus mitigating the twofold cost of sex, provided that it seeks and destroys the same mutations as selection acting on females, but with higher efficiency. This could happen due to sexual selection-a potent evolutionary force that in most systems predominantly affects males. We used replicate populations of red flour beetles (Tribolium castaneum) to study sex-specific selection against deleterious mutations introduced with ionizing radiation. We found no evidence for selection being stronger in males than in females; in fact, we observed a nonsignificant trend in the opposite direction. This suggests that selection on males does not reduce mutation load below the level expected under the (hypothetical) scenario of asexual reproduction. Additionally, we employed a novel approach, based on a simple model, to quantify the relative contributions of sexual and offspring viability selection to the overall selection observed in males. We found them to be similar in magnitude; however, only the offspring viability component was statistically significant. In summary, we found no support for the hypothesis that selection on males in general, and sexual selection in particular, contributes to the evolutionary maintenance of sex. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

The eco-evolutionary responses of a generalist consumer to resource competition.

PubMed

Abrams, Peter A

2012-10-01

This article explores the combined evolutionary and ecological responses of resource uptake abilities in a generalist consumer to exploitative competition for one resource using a simple 2-resource model. It compares the sizes of ecologically and evolutionarily caused changes in population densities in cases where the original consumer has a strong or a weak trade-off in its abilities to consume the two resources. The analysis also compares the responses of the original species to competition when the competitor's population size is or is not limited by the shared resource. Although divergence in resource use traits in the resident generalist consumer is expected under all scenarios when resources are substitutable, the changes in population densities of the resources and resident consumer frequently differ between scenarios. The population of the original consumer often decreases as a result of its own adaptive divergence, and this decrease is often much greater than the initial ecological decrease. If the evolving consumer has a strong trade-off, the overlapped resource increases in equilibrium population density in response to being consumed by a generalist competitor. Some of these predictions differ qualitatively in alternative scenarios involving sustained variation in population densities or nutritionally essential resources. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Pollen--tiny and ephemeral but not forgotten: New ideas on their ecology and evolution.

PubMed

Williams, Joseph H; Mazer, Susan J

2016-03-01

Ecologists and evolutionary biologists have been interested in the functional biology of pollen since the discovery in the 1800s that pollen grains encompass tiny plants (male gametophytes) that develop and produce sperm cells. After the discovery of double fertilization in flowering plants, botanists in the early 1900s were quick to explore the effects of temperature and maternal nutrients on pollen performance, while evolutionary biologists began studying the nature of haploid selection and pollen competition. A series of technical and theoretic developments have subsequently, but usually separately, expanded our knowledge of the nature of pollen performance and how it evolves. Today, there is a tremendous diversity of interests that touch on pollen performance, ranging from the ecological setting on the stigma, structural and physiological aspects of pollen germination and tube growth, the form of pollen competition and its role in sexual selection in plants, virus transmission, mating system evolution, and inbreeding depression. Given the explosion of technical knowledge of pollen cell biology, computer modeling, and new methods to deal with diversity in a phylogenetic context, we are now more than ever poised for a new era of research that includes complex functional traits that limit or enhance the evolution of these deceptively simple organisms. © 2016 Botanical Society of America.

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

On the distribution of interspecies correlation for Markov models of character evolution on Yule trees.

PubMed

Mulder, Willem H; Crawford, Forrest W

2015-01-07

Efforts to reconstruct phylogenetic trees and understand evolutionary processes depend fundamentally on stochastic models of speciation and mutation. The simplest continuous-time model for speciation in phylogenetic trees is the Yule process, in which new species are "born" from existing lineages at a constant rate. Recent work has illuminated some of the structural properties of Yule trees, but it remains mostly unknown how these properties affect sequence and trait patterns observed at the tips of the phylogenetic tree. Understanding the interplay between speciation and mutation under simple models of evolution is essential for deriving valid phylogenetic inference methods and gives insight into the optimal design of phylogenetic studies. In this work, we derive the probability distribution of interspecies covariance under Brownian motion and Ornstein-Uhlenbeck models of phenotypic change on a Yule tree. We compute the probability distribution of the number of mutations shared between two randomly chosen taxa in a Yule tree under discrete Markov mutation models. Our results suggest summary measures of phylogenetic information content, illuminate the correlation between site patterns in sequences or traits of related organisms, and provide heuristics for experimental design and reconstruction of phylogenetic trees. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Beat Keeping in a Sea Lion As Coupled Oscillation: Implications for Comparative Understanding of Human Rhythm.

PubMed

Rouse, Andrew A; Cook, Peter F; Large, Edward W; Reichmuth, Colleen

2016-01-01

Human capacity for entraining movement to external rhythms-i.e., beat keeping-is ubiquitous, but its evolutionary history and neural underpinnings remain a mystery. Recent findings of entrainment to simple and complex rhythms in non-human animals pave the way for a novel comparative approach to assess the origins and mechanisms of rhythmic behavior. The most reliable non-human beat keeper to date is a California sea lion, Ronan, who was trained to match head movements to isochronous repeating stimuli and showed spontaneous generalization of this ability to novel tempos and to the complex rhythms of music. Does Ronan's performance rely on the same neural mechanisms as human rhythmic behavior? In the current study, we presented Ronan with simple rhythmic stimuli at novel tempos. On some trials, we introduced "perturbations," altering either tempo or phase in the middle of a presentation. Ronan quickly adjusted her behavior following all perturbations, recovering her consistent phase and tempo relationships to the stimulus within a few beats. Ronan's performance was consistent with predictions of mathematical models describing coupled oscillation: a model relying solely on phase coupling strongly matched her behavior, and the model was further improved with the addition of period coupling. These findings are the clearest evidence yet for parity in human and non-human beat keeping and support the view that the human ability to perceive and move in time to rhythm may be rooted in broadly conserved neural mechanisms.

A stochastic process approach of the drake equation parameters

NASA Astrophysics Data System (ADS)

Glade, Nicolas; Ballet, Pascal; Bastien, Olivier

2012-04-01

The number N of detectable (i.e. communicating) extraterrestrial civilizations in the Milky Way galaxy is usually calculated by using the Drake equation. This equation was established in 1961 by Frank Drake and was the first step to quantifying the Search for ExtraTerrestrial Intelligence (SETI) field. Practically, this equation is rather a simple algebraic expression and its simplistic nature leaves it open to frequent re-expression. An additional problem of the Drake equation is the time-independence of its terms, which for example excludes the effects of the physico-chemical history of the galaxy. Recently, it has been demonstrated that the main shortcoming of the Drake equation is its lack of temporal structure, i.e., it fails to take into account various evolutionary processes. In particular, the Drake equation does not provides any error estimation about the measured quantity. Here, we propose a first treatment of these evolutionary aspects by constructing a simple stochastic process that will be able to provide both a temporal structure to the Drake equation (i.e. introduce time in the Drake formula in order to obtain something like N(t)) and a first standard error measure.

1/f Noise in the Simple Genetic Algorithm Applied to a Traveling Salesman Problem

NASA Astrophysics Data System (ADS)

Yamada, Mitsuhiro

Complex dynamical systems are observed in physics, biology, and even economics. Such systems in balance are considered to be in a critical state, and 1/f noise is considered to be a footprint. Complex dynamical systems have also been investigated in the field of evolutionary algorithms inspired by biological evolution. The genetic algorithm (GA) is a well-known evolutionary algorithm in which many individuals interact, and the simplest GA is referred to as the simple GA (SGA). However, the GA has not been examined from the viewpoint of the emergence of 1/f noise. In the present paper, the SGA is applied to a traveling salesman problem in order to investigate the SGA from such a viewpoint. The timecourses of the fitness of the candidate solution were examined. As a result, when the mutation and crossover probabilities were optimal, the system evolved toward a critical state in which the average maximum fitness over all trial runs was maximum. In this situation, the fluctuation of the fitness of the candidate solution resulted in the 1/f power spectrum, and the dynamics of the system had no intrinsic time or length scale.

Computability, Gödel's incompleteness theorem, and an inherent limit on the predictability of evolution

PubMed Central

Day, Troy

2012-01-01

The process of evolutionary diversification unfolds in a vast genotypic space of potential outcomes. During the past century, there have been remarkable advances in the development of theory for this diversification, and the theory's success rests, in part, on the scope of its applicability. A great deal of this theory focuses on a relatively small subset of the space of potential genotypes, chosen largely based on historical or contemporary patterns, and then predicts the evolutionary dynamics within this pre-defined set. To what extent can such an approach be pushed to a broader perspective that accounts for the potential open-endedness of evolutionary diversification? There have been a number of significant theoretical developments along these lines but the question of how far such theory can be pushed has not been addressed. Here a theorem is proven demonstrating that, because of the digital nature of inheritance, there are inherent limits on the kinds of questions that can be answered using such an approach. In particular, even in extremely simple evolutionary systems, a complete theory accounting for the potential open-endedness of evolution is unattainable unless evolution is progressive. The theorem is closely related to Gödel's incompleteness theorem, and to the halting problem from computability theory. PMID:21849390

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.

Evolutionary perspectives on the links between mitochondrial genotype and disease phenotype.

PubMed

Dowling, Damian K

2014-04-01

Disorders of the mitochondrial respiratory chain are heterogeneous in their symptoms and underlying genetics. Simple links between candidate mutations and expression of disease phenotype typically do not exist. It thus remains unclear how the genetic variation in the mitochondrial genome contributes to the phenotypic expression of complex traits and disease phenotypes. I summarize the basic genetic processes known to underpin mitochondrial disease. I highlight other plausible processes, drawn from the evolutionary biological literature, whose contribution to mitochondrial disease expression remains largely empirically unexplored. I highlight recent advances to the field, and discuss common-ground and -goals shared by researchers across medical and evolutionary domains. Mitochondrial genetic variance is linked to phenotypic variance across a variety of traits (e.g. reproductive function, life expectancy) fundamental to the upkeep of good health. Evolutionary theory predicts that mitochondrial genomes are destined to accumulate male-harming (but female-friendly) mutations, and this prediction has received proof-of-principle support. Furthermore, mitochondrial effects on the phenotype are typically manifested via interactions between mitochondrial and nuclear genes. Thus, whether a mitochondrial mutation is pathogenic in effect can depend on the nuclear genotype in which is it expressed. Many disease phenotypes associated with OXPHOS malfunction might be determined by the outcomes of mitochondrial-nuclear interactions, and by the evolutionary forces that historically shaped mitochondrial DNA (mtDNA) sequences. Concepts and results drawn from the evolutionary sciences can have broad, but currently under-utilized, applicability to the medical sciences and provide new insights into understanding the complex genetics of mitochondrial disease. This article is part of a Special Issue entitled Frontiers of Mitochondrial Research. Copyright © 2013. Published by Elsevier B.V.

Oh sister, where art thou? Spatial population structure and the evolution of an altruistic defence trait.

PubMed

Pamminger, T; Foitzik, S; Metzler, D; Pennings, P S

2014-11-01

The evolution of parasite virulence and host defences is affected by population structure. This effect has been confirmed in studies focusing on large spatial scales, whereas the importance of local structure is not well understood. Slavemaking ants are social parasites that exploit workers of another species to rear their offspring. Enslaved workers of the host species Temnothorax longispinosus have been found to exhibit an effective post-enslavement defence behaviour: enslaved workers were observed killing a large proportion of the parasites' offspring. As enslaved workers do not reproduce, they gain no direct fitness benefit from this 'rebellion' behaviour. However, there may be an indirect benefit: neighbouring host nests that are related to 'rebel' nests can benefit from a reduced raiding pressure, as a result of the reduction in parasite nest size due to the enslaved workers' killing behaviour. We use a simple mathematical model to examine whether the small-scale population structure of the host species could explain the evolution of this potentially altruistic defence trait against slavemaking ants. We find that this is the case if enslaved host workers are related to nearby host nests. In a population genetic study, we confirm that enslaved workers are, indeed, more closely related to host nests within the raiding range of their resident slavemaker nest, than to host nests outside the raiding range. This small-scale population structure seems to be a result of polydomy (e.g. the occupation of several nests in close proximity by a single colony) and could have enabled the evolution of 'rebellion' by kin selection. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

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 evolutionary view of chromatography data systems used in bioanalysis.

PubMed

McDowall, R D

2010-02-01

This is a personal view of how chromatographic peak measurement and analyte quantification for bioanalysis have evolved from the manual methods of 1970 to the electronic working possible in 2010. In four decades there have been major changes from a simple chart recorder output (that was interpreted and quantified manually) through simple automation of peak measurement, calculation of standard curves and quality control values and instrument control to the networked chromatography data systems of today that are capable of interfacing with Laboratory Information Management Systems and other IT applications. The incorporation of electronic signatures to meet regulatory requirements offers a great opportunity for business improvement and electronic working.

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…

The evolutionary outcome of sexual conflict

PubMed Central

Lessells, C(Kate). M

2006-01-01

Inter-locus sexual conflict occurs by definition when there is sexually antagonistic selection on a trait so that the optimal trait value differs between the sexes. As a result, there is selection on each sex to manipulate the trait towards its own optimum and resist such manipulation by the other sex. Sexual conflict often leads additionally to the evolution of harmful behaviour and to self-reinforcing and even perpetual sexually antagonistic coevolution. In an attempt to understand the determinants of these different outcomes, I compare two groups of traits—those related to parental investment (PI) and to mating—over which there is sexual conflict, but which have to date been explored by largely separate research traditions. A brief review suggests that sexual conflict over PI, particularly over PI per offspring, leads less frequently to the evolution of manipulative behaviour, and rarely to the evolution of harmful behaviour or to the rapid evolutionary changes which may be symptomatic of sexually antagonistic coevolution. The chief determinants of the evolutionary outcome of sexual conflict are the benefits of manipulation and resistance, the costs of manipulation and resistance, and the feasibility of manipulation. All three of these appear to contribute to the differences in the evolutionary outcome of conflicts over PI and mating. A detailed dissection of the evolutionary changes following from sexual conflict exposes greater complexity than a simple adaptation–counter-adaptation cycle and clarifies the role of harm. Not all of the evolutionary changes that follow from sexual conflict are sexually antagonistic, and harm is not necessary for sexually antagonistic coevolution to occur. In particular, whereas selection on the trait over which there is conflict is by definition sexually antagonistic, collateral harm is usually in the interest of neither sex. This creates the opportunity for palliative adaptations which reduce collateral harm. Failure to recognize that such adaptations are in the interest of both sexes can hinder our understanding of the evolutionary outcome of sexual conflict. PMID:16612889

The evolutionary outcome of sexual conflict.

PubMed

Lessells, C M

2006-02-28

Inter-locus sexual conflict occurs by definition when there is sexually antagonistic selection on a trait so that the optimal trait value differs between the sexes. As a result, there is selection on each sex to manipulate the trait towards its own optimum and resist such manipulation by the other sex. Sexual conflict often leads additionally to the evolution of harmful behaviour and to self-reinforcing and even perpetual sexually antagonistic coevolution. In an attempt to understand the determinants of these different outcomes, I compare two groups of traits-those related to parental investment (PI) and to mating-over which there is sexual conflict, but which have to date been explored by largely separate research traditions. A brief review suggests that sexual conflict over PI, particularly over PI per offspring, leads less frequently to the evolution of manipulative behaviour, and rarely to the evolution of harmful behaviour or to the rapid evolutionary changes which may be symptomatic of sexually antagonistic coevolution. The chief determinants of the evolutionary outcome of sexual conflict are the benefits of manipulation and resistance, the costs of manipulation and resistance, and the feasibility of manipulation. All three of these appear to contribute to the differences in the evolutionary outcome of conflicts over PI and mating. A detailed dissection of the evolutionary changes following from sexual conflict exposes greater complexity than a simple adaptation-counter-adaptation cycle and clarifies the role of harm. Not all of the evolutionary changes that follow from sexual conflict are sexually antagonistic, and harm is not necessary for sexually antagonistic coevolution to occur. In particular, whereas selection on the trait over which there is conflict is by definition sexually antagonistic, collateral harm is usually in the interest of neither sex. This creates the opportunity for palliative adaptations which reduce collateral harm. Failure to recognize that such adaptations are in the interest of both sexes can hinder our understanding of the evolutionary outcome of sexual conflict.

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.

Protein-protein interactions in paralogues: Electrostatics modulates specificity on a conserved steric scaffold

PubMed Central

Huber, Roland G.; Bond, Peter J.

2017-01-01

An improved knowledge of protein-protein interactions is essential for better understanding of metabolic and signaling networks, and cellular function. Progress tends to be based on structure determination and predictions using known structures, along with computational methods based on evolutionary information or detailed atomistic descriptions. We hypothesized that for the case of interactions across a common interface, between proteins from a pair of paralogue families or within a family of paralogues, a relatively simple interface description could distinguish between binding and non-binding pairs. Using binding data for several systems, and large-scale comparative modeling based on known template complex structures, it is found that charge-charge interactions (for groups bearing net charge) are generally a better discriminant than buried non-polar surface. This is particularly the case for paralogue families that are less divergent, with more reliable comparative modeling. We suggest that electrostatic interactions are major determinants of specificity in such systems, an observation that could be used to predict binding partners. PMID:29016650

Covariance Matrix Adaptation Evolutionary Strategy for Drift Correction of Electronic Nose Data

NASA Astrophysics Data System (ADS)

Di Carlo, S.; Falasconi, M.; Sanchez, E.; Sberveglieri, G.; Scionti, A.; Squillero, G.; Tonda, A.

2011-09-01

Electronic Noses (ENs) might represent a simple, fast, high sample throughput and economic alternative to conventional analytical instruments [1]. However, gas sensors drift still limits the EN adoption in real industrial setups due to high recalibration effort and cost [2]. In fact, pattern recognition (PaRC) models built in the training phase become useless after a period of time, in some cases a few weeks. Although algorithms to mitigate the drift date back to the early 90 this is still a challenging issue for the chemical sensor community [3]. Among other approaches, adaptive drift correction methods adjust the PaRC model in parallel with data acquisition without need of periodic calibration. Self-Organizing Maps (SOMs) [4] and Adaptive Resonance Theory (ART) networks [5] have been already tested in the past with fair success. This paper presents and discusses an original methodology based on a Covariance Matrix Adaptation Evolution Strategy (CMA-ES) [6], suited for stochastic optimization of complex problems.

The Contribution of TP-AGB Stars to the Mid-infrared Colors of Nearby Galaxies

NASA Astrophysics Data System (ADS)

Chisari, Nora E.; Kelson, Daniel D.

2012-07-01

We study the mid-infrared color space of 30 galaxies from the Spitzer Infrared Nearby Galaxies Survey (SINGS) survey for which Sloan Digital Sky Survey data are also available. We construct two-color maps for each galaxy and compare them to results obtained from combining Maraston evolutionary synthesis models, galactic thermally pulsating asymptotic giant branch (TP-AGB) colors, and smooth star formation histories. For most of the SINGS sample, the spatially extended mid-IR emission seen by Spitzer in normal galaxies is consistent with our simple model in which circumstellar dust from TP-AGB stars dominates at 8 and 24 μm. There is a handful of exceptions that we identify as galaxies that have high star formation rates presumably with star formation histories that cannot be assumed to be smooth, or anemic galaxies, which were depleted of their H I at some point during their evolution and have very low ongoing star formation rates.

Protein-protein interactions in paralogues: Electrostatics modulates specificity on a conserved steric scaffold.

PubMed

Ivanov, Stefan M; Cawley, Andrew; Huber, Roland G; Bond, Peter J; Warwicker, Jim

2017-01-01

An improved knowledge of protein-protein interactions is essential for better understanding of metabolic and signaling networks, and cellular function. Progress tends to be based on structure determination and predictions using known structures, along with computational methods based on evolutionary information or detailed atomistic descriptions. We hypothesized that for the case of interactions across a common interface, between proteins from a pair of paralogue families or within a family of paralogues, a relatively simple interface description could distinguish between binding and non-binding pairs. Using binding data for several systems, and large-scale comparative modeling based on known template complex structures, it is found that charge-charge interactions (for groups bearing net charge) are generally a better discriminant than buried non-polar surface. This is particularly the case for paralogue families that are less divergent, with more reliable comparative modeling. We suggest that electrostatic interactions are major determinants of specificity in such systems, an observation that could be used to predict binding partners.

Specialized hybrid learners resolve Rogers' paradox about the adaptive value of social learning.

PubMed

Kharratzadeh, Milad; Montrey, Marcel; Metz, Alex; Shultz, Thomas R

2017-02-07

Culture is considered an evolutionary adaptation that enhances reproductive fitness. A common explanation is that social learning, the learning mechanism underlying cultural transmission, enhances mean fitness by avoiding the costs of individual learning. This explanation was famously contradicted by Rogers (1988), who used a simple mathematical model to show that cheap social learning can invade a population without raising its mean fitness. He concluded that some crucial factor remained unaccounted for, which would reverse this surprising result. Here we extend this model to include a more complex environment and limited resources, where individuals cannot reliably learn everything about the environment on their own. Under such conditions, cheap social learning evolves and enhances mean fitness, via hybrid learners capable of specializing their individual learning. We then show that while spatial or social constraints hinder the evolution of hybrid learners, a novel social learning strategy, complementary copying, can mitigate these effects. Copyright © 2016 Elsevier Ltd. All rights reserved.

Iron and molecular opacities and the evolution of Population I stars

NASA Technical Reports Server (NTRS)

Stothers, Richard B.; Chin, Chao-Wen

1993-01-01

Effects of recent opacity revisions on the evolution of Population I stars are explored over the range 1.5-60 solar masses. Opacity parameters considered include the angular momentum coupling scheme for iron, the relative iron abundance, the total metal abundance, and diatomic and triatomic molecular sources. Only the total metal abundance exerts an important control over the evolutionary tracks. Blue loops on the H-R diagram during core helium burning can be very sensitive to opacity, but only insofar as the simple formation or suppression of a blue loop is concerned. The blue loops are most robust for stellar masses around 10 solar masses. We confirm, from a comparison of stellar models with observational data, that the total metal abundance is close to solar and that convective core overshooting is likely to be very slight. The new models predict the existence of an iron convection zone in the envelope and a great widening of the main-sequence band in the H-R diagram at luminosities brighter than 100,000 solar luminosities.

Religion, fertility and genes: a dual inheritance model

PubMed Central

Rowthorn, Robert

2011-01-01

Religious people nowadays have more children on average than their secular counterparts. This paper uses a simple model to explore the evolutionary implications of this difference. It assumes that fertility is determined entirely by culture, whereas subjective predisposition towards religion is influenced by genetic endowment. People who carry a certain ‘religiosity’ gene are more likely than average to become or remain religious. The paper considers the effect of religious defections and exogamy on the religious and genetic composition of society. Defections reduce the ultimate share of the population with religious allegiance and slow down the spread of the religiosity gene. However, provided the fertility differential persists, and people with a religious allegiance mate mainly with people like themselves, the religiosity gene will eventually predominate despite a high rate of defection. This is an example of ‘cultural hitch-hiking’, whereby a gene spreads because it is able to hitch a ride with a high-fitness cultural practice. The theoretical arguments are supported by numerical simulations. PMID:21227968

RUNX in Invertebrates.

PubMed

Hughes, S; Woollard, A

2017-01-01

Runx genes have been identified in all metazoans and considerable conservation of function observed across a wide range of phyla. Thus, insight gained from studying simple model organisms is invaluable in understanding RUNX biology in higher animals. Consequently, this chapter will focus on the Runx genes in the diploblasts, which includes sea anemones and sponges, as well as the lower triploblasts, including the sea urchin, nematode, planaria and insect. Due to the high degree of functional redundancy amongst vertebrate Runx genes, simpler model organisms with a solo Runx gene, like C. elegans, are invaluable systems in which to probe the molecular basis of RUNX function within a whole organism. Additionally, comparative analyses of Runx sequence and function allows for the development of novel evolutionary insights. Strikingly, recent data has emerged that reveals the presence of a Runx gene in a protist, demonstrating even more widespread occurrence of Runx genes than was previously thought. This review will summarize recent progress in using invertebrate organisms to investigate RUNX function during development and regeneration, highlighting emerging unifying themes.

Religion, fertility and genes: a dual inheritance model.

PubMed

Rowthorn, Robert

2011-08-22

Religious people nowadays have more children on average than their secular counterparts. This paper uses a simple model to explore the evolutionary implications of this difference. It assumes that fertility is determined entirely by culture, whereas subjective predisposition towards religion is influenced by genetic endowment. People who carry a certain 'religiosity' gene are more likely than average to become or remain religious. The paper considers the effect of religious defections and exogamy on the religious and genetic composition of society. Defections reduce the ultimate share of the population with religious allegiance and slow down the spread of the religiosity gene. However, provided the fertility differential persists, and people with a religious allegiance mate mainly with people like themselves, the religiosity gene will eventually predominate despite a high rate of defection. This is an example of 'cultural hitch-hiking', whereby a gene spreads because it is able to hitch a ride with a high-fitness cultural practice. The theoretical arguments are supported by numerical simulations.

Evolutionary routes to biochemical innovation revealed by integrative analysis of a plant-defense related specialized metabolic pathway

PubMed Central

Moghe, Gaurav D; Leong, Bryan J; Hurney, Steven M; Daniel Jones, A

2017-01-01

The diversity of life on Earth is a result of continual innovations in molecular networks influencing morphology and physiology. Plant specialized metabolism produces hundreds of thousands of compounds, offering striking examples of these innovations. To understand how this novelty is generated, we investigated the evolution of the Solanaceae family-specific, trichome-localized acylsugar biosynthetic pathway using a combination of mass spectrometry, RNA-seq, enzyme assays, RNAi and phylogenomics in different non-model species. Our results reveal hundreds of acylsugars produced across the Solanaceae family and even within a single plant, built on simple sugar cores. The relatively short biosynthetic pathway experienced repeated cycles of innovation over the last 100 million years that include gene duplication and divergence, gene loss, evolution of substrate preference and promiscuity. This study provides mechanistic insights into the emergence of plant chemical novelty, and offers a template for investigating the ~300,000 non-model plant species that remain underexplored. PMID:28853706

Evolutionary routes to biochemical innovation revealed by integrative analysis of a plant-defense related specialized metabolic pathway.

PubMed

Moghe, Gaurav D; Leong, Bryan J; Hurney, Steven M; Daniel Jones, A; Last, Robert L

2017-08-30

The diversity of life on Earth is a result of continual innovations in molecular networks influencing morphology and physiology. Plant specialized metabolism produces hundreds of thousands of compounds, offering striking examples of these innovations. To understand how this novelty is generated, we investigated the evolution of the Solanaceae family-specific, trichome-localized acylsugar biosynthetic pathway using a combination of mass spectrometry, RNA-seq, enzyme assays, RNAi and phylogenomics in different non-model species. Our results reveal hundreds of acylsugars produced across the Solanaceae family and even within a single plant, built on simple sugar cores. The relatively short biosynthetic pathway experienced repeated cycles of innovation over the last 100 million years that include gene duplication and divergence, gene loss, evolution of substrate preference and promiscuity. This study provides mechanistic insights into the emergence of plant chemical novelty, and offers a template for investigating the ~300,000 non-model plant species that remain underexplored.

THE CONTRIBUTION OF TP-AGB STARS TO THE MID-INFRARED COLORS OF NEARBY GALAXIES

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

Chisari, Nora E.; Kelson, Daniel D., E-mail: nchisari@astro.princeton.edu

2012-07-10

We study the mid-infrared color space of 30 galaxies from the Spitzer Infrared Nearby Galaxies Survey (SINGS) survey for which Sloan Digital Sky Survey data are also available. We construct two-color maps for each galaxy and compare them to results obtained from combining Maraston evolutionary synthesis models, galactic thermally pulsating asymptotic giant branch (TP-AGB) colors, and smooth star formation histories. For most of the SINGS sample, the spatially extended mid-IR emission seen by Spitzer in normal galaxies is consistent with our simple model in which circumstellar dust from TP-AGB stars dominates at 8 and 24 {mu}m. There is a handfulmore » of exceptions that we identify as galaxies that have high star formation rates presumably with star formation histories that cannot be assumed to be smooth, or anemic galaxies, which were depleted of their H I at some point during their evolution and have very low ongoing star formation rates.« less

Machine learning strategy for accelerated design of polymer dielectrics

DOE PAGES

Mannodi-Kanakkithodi, Arun; Pilania, Ghanshyam; Huan, Tran Doan; ...

2016-02-15

The ability to efficiently design new and advanced dielectric polymers is hampered by the lack of sufficient, reliable data on wide polymer chemical spaces, and the difficulty of generating such data given time and computational/experimental constraints. Here, we address the issue of accelerating polymer dielectrics design by extracting learning models from data generated by accurate state-of-the-art first principles computations for polymers occupying an important part of the chemical subspace. The polymers are ‘fingerprinted’ as simple, easily attainable numerical representations, which are mapped to the properties of interest using a machine learning algorithm to develop an on-demand property prediction model. Further,more » a genetic algorithm is utilised to optimise polymer constituent blocks in an evolutionary manner, thus directly leading to the design of polymers with given target properties. Furthermore, while this philosophy of learning to make instant predictions and design is demonstrated here for the example of polymer dielectrics, it is equally applicable to other classes of materials as well.« less

An auto-adaptive optimization approach for targeting nonpoint source pollution control practices.

PubMed

Chen, Lei; Wei, Guoyuan; Shen, Zhenyao

2015-10-21

To solve computationally intensive and technically complex control of nonpoint source pollution, the traditional genetic algorithm was modified into an auto-adaptive pattern, and a new framework was proposed by integrating this new algorithm with a watershed model and an economic module. Although conceptually simple and comprehensive, the proposed algorithm would search automatically for those Pareto-optimality solutions without a complex calibration of optimization parameters. The model was applied in a case study in a typical watershed of the Three Gorges Reservoir area, China. The results indicated that the evolutionary process of optimization was improved due to the incorporation of auto-adaptive parameters. In addition, the proposed algorithm outperformed the state-of-the-art existing algorithms in terms of convergence ability and computational efficiency. At the same cost level, solutions with greater pollutant reductions could be identified. From a scientific viewpoint, the proposed algorithm could be extended to other watersheds to provide cost-effective configurations of BMPs.

Signatures of positive selection: from selective sweeps at individual loci to subtle allele frequency changes in polygenic adaptation.

PubMed

Stephan, Wolfgang

2016-01-01

In the past 15 years, numerous methods have been developed to detect selective sweeps underlying adaptations. These methods are based on relatively simple population genetic models, including one or two loci at which positive directional selection occurs, and one or two marker loci at which the impact of selection on linked neutral variation is quantified. Information about the phenotype under selection is not included in these models (except for fitness). In contrast, in the quantitative genetic models of adaptation, selection acts on one or more phenotypic traits, such that a genotype-phenotype map is required to bridge the gap to population genetics theory. Here I describe the range of population genetic models from selective sweeps in a panmictic population of constant size to evolutionary traffic when simultaneous sweeps at multiple loci interfere, and I also consider the case of polygenic selection characterized by subtle allele frequency shifts at many loci. Furthermore, I present an overview of the statistical tests that have been proposed based on these population genetics models to detect evidence for positive selection in the genome. © 2015 John Wiley & Sons Ltd.

An alternative derivation of the stationary distribution of the multivariate neutral Wright-Fisher model for low mutation rates with a view to mutation rate estimation from site frequency data.

PubMed

Schrempf, Dominik; Hobolth, Asger

2017-04-01

Recently, Burden and Tang (2016) provided an analytical expression for the stationary distribution of the multivariate neutral Wright-Fisher model with low mutation rates. In this paper we present a simple, alternative derivation that illustrates the approximation. Our proof is based on the discrete multivariate boundary mutation model which has three key ingredients. First, the decoupled Moran model is used to describe genetic drift. Second, low mutation rates are assumed by limiting mutations to monomorphic states. Third, the mutation rate matrix is separated into a time-reversible part and a flux part, as suggested by Burden and Tang (2016). An application of our result to data from several great apes reveals that the assumption of stationarity may be inadequate or that other evolutionary forces like selection or biased gene conversion are acting. Furthermore we find that the model with a reversible mutation rate matrix provides a reasonably good fit to the data compared to the one with a non-reversible mutation rate matrix. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Endogenous technological and population change under increasing water scarcity

NASA Astrophysics Data System (ADS)

Pande, S.; Ertsen, M.; Sivapalan, M.

2014-08-01

Ancient civilizations may have dispersed or collapsed under extreme dry conditions. There are indications that the same may hold for modern societies. However, hydroclimatic change cannot be the sole predictor of the fate of contemporary societies in water-scarce regions. This paper focuses on technological change as a factor that may ameliorate the effects of increasing water scarcity and as such counter the effects of hydroclimatic changes. We study the role of technological change on the dynamics of coupled human-water systems, and model technological change as an endogenous process that depends on many factors intrinsic to coupled human-water dynamics. We do not treat technology as an exogenous random sequence of events, but assume that it results from societal actions. While the proposed model is a rather simple model of a coupled human-water system, it is shown to be capable of replicating patterns of technological, population, production and consumption per capita changes. The model demonstrates that technological change may indeed ameliorate the effects of increasing water scarcity, but typically it does so only to a certain extent. In general we find that endogenous technology change under increasing water scarcity helps to delay the peak of population size before it inevitably starts to decline. We also analyze the case when water remains constant over time and find that co-evolutionary trajectories can never grow at a constant rate; rather the rate itself grows with time. Thus our model does not predict a co-evolutionary trajectory of a socio-hydrological system where technological innovation harmoniously provides for a growing population. It allows either for an explosion or an eventual dispersal of population. The latter occurs only under increasing water scarcity. As a result, we draw the conclusion that declining consumption per capita despite technological advancement and increase in aggregate production may serve as a useful predictor of upcoming decline in contemporary societies in water-scarce basins.

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.

Bipartite graphs as models of population structures in evolutionary multiplayer games.

PubMed

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.

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 Simple and Robust Statistical Test for Detecting the Presence of Recombination

PubMed Central

Bruen, Trevor C.; Philippe, Hervé; Bryant, David

2006-01-01

Recombination is a powerful evolutionary force that merges historically distinct genotypes. But the extent of recombination within many organisms is unknown, and even determining its presence within a set of homologous sequences is a difficult question. Here we develop a new statistic, Φw, that can be used to test for recombination. We show through simulation that our test can discriminate effectively between the presence and absence of recombination, even in diverse situations such as exponential growth (star-like topologies) and patterns of substitution rate correlation. A number of other tests, Max χ2, NSS, a coalescent-based likelihood permutation test (from LDHat), and correlation of linkage disequilibrium (both r2 and |D′|) with distance, all tend to underestimate the presence of recombination under strong population growth. Moreover, both Max χ2 and NSS falsely infer the presence of recombination under a simple model of mutation rate correlation. Results on empirical data show that our test can be used to detect recombination between closely as well as distantly related samples, regardless of the suspected rate of recombination. The results suggest that Φw is one of the best approaches to distinguish recurrent mutation from recombination in a wide variety of circumstances. PMID:16489234

Dynamics of prebiotic RNA reproduction illuminated by chemical game theory

PubMed Central

Yeates, Jessica A. M.; Hilbe, Christian; Zwick, Martin; Nowak, Martin A.; Lehman, Niles

2016-01-01

Many origins-of-life scenarios depict a situation in which there are common and potentially scarce resources needed by molecules that compete for survival and reproduction. The dynamics of RNA assembly in a complex mixture of sequences is a frequency-dependent process and mimics such scenarios. By synthesizing Azoarcus ribozyme genotypes that differ in their single-nucleotide interactions with other genotypes, we can create molecules that interact among each other to reproduce. Pairwise interplays between RNAs involve both cooperation and selfishness, quantifiable in a 2 × 2 payoff matrix. We show that a simple model of differential equations based on chemical kinetics accurately predicts the outcomes of these molecular competitions using simple rate inputs into these matrices. In some cases, we find that mixtures of different RNAs reproduce much better than each RNA type alone, reflecting a molecular form of reciprocal cooperation. We also demonstrate that three RNA genotypes can stably coexist in a rock–paper–scissors analog. Our experiments suggest a new type of evolutionary game dynamics, called prelife game dynamics or chemical game dynamics. These operate without template-directed replication, illustrating how small networks of RNAs could have developed and evolved in an RNA world. PMID:27091972

Mutation predicts 40 million years of fly wing evolution.

PubMed

Houle, David; Bolstad, Geir H; van der Linde, Kim; Hansen, Thomas F

2017-08-24

Mutation enables evolution, but the idea that adaptation is also shaped by mutational variation is controversial. Simple evolutionary hypotheses predict such a relationship if the supply of mutations constrains evolution, but it is not clear that constraints exist, and, even if they do, they may be overcome by long-term natural selection. Quantification of the relationship between mutation and phenotypic divergence among species will help to resolve these issues. Here we use precise data on over 50,000 Drosophilid fly wings to demonstrate unexpectedly strong positive relationships between variation produced by mutation, standing genetic variation, and the rate of evolution over the last 40 million years. Our results are inconsistent with simple constraint hypotheses because the rate of evolution is very low relative to what both mutational and standing variation could allow. In principle, the constraint hypothesis could be rescued if the vast majority of mutations are so deleterious that they cannot contribute to evolution, but this also requires the implausible assumption that deleterious mutations have the same pattern of effects as potentially advantageous ones. Our evidence for a strong relationship between mutation and divergence in a slowly evolving structure challenges the existing models of mutation in evolution.

Dynamics of prebiotic RNA reproduction illuminated by chemical game theory.

PubMed

Yeates, Jessica A M; Hilbe, Christian; Zwick, Martin; Nowak, Martin A; Lehman, Niles

2016-05-03

Many origins-of-life scenarios depict a situation in which there are common and potentially scarce resources needed by molecules that compete for survival and reproduction. The dynamics of RNA assembly in a complex mixture of sequences is a frequency-dependent process and mimics such scenarios. By synthesizing Azoarcus ribozyme genotypes that differ in their single-nucleotide interactions with other genotypes, we can create molecules that interact among each other to reproduce. Pairwise interplays between RNAs involve both cooperation and selfishness, quantifiable in a 2 × 2 payoff matrix. We show that a simple model of differential equations based on chemical kinetics accurately predicts the outcomes of these molecular competitions using simple rate inputs into these matrices. In some cases, we find that mixtures of different RNAs reproduce much better than each RNA type alone, reflecting a molecular form of reciprocal cooperation. We also demonstrate that three RNA genotypes can stably coexist in a rock-paper-scissors analog. Our experiments suggest a new type of evolutionary game dynamics, called prelife game dynamics or chemical game dynamics. These operate without template-directed replication, illustrating how small networks of RNAs could have developed and evolved in an RNA world.

Are the gyro-ages of field stars underestimated?

NASA Astrophysics Data System (ADS)

Kovács, Géza

2015-09-01

By using the current photometric rotational data on eight galactic open clusters, we show that the evolutionary stellar model (isochrone) ages of these clusters are tightly correlated with the period shifts applied to the (B - V)0-Prot ridges that optimally align these ridges to the one defined by Praesepe and the Hyades. On the other hand, when the traditional Skumanich-type multiplicative transformation is used, the ridges become far less aligned due to the age-dependent slope change introduced by the period multiplication. Therefore, we employ our simple additive gyro-age calibration on various datasets of Galactic field stars to test its applicability. We show that, in the overall sense, the gyro-ages are systematically greater than the isochrone ages. The difference could exceed several giga years, depending on the stellar parameters. Although the age overlap between the open clusters used in the calibration and the field star samples is only partial, the systematic difference indicates the limitation of the currently available gyro-age methods and suggests that the rotation of field stars slows down with a considerably lower speed than we would expect from the simple extrapolation of the stellar rotation rates in open clusters.

Blue Stragglers in Clusters and Integrated Spectral Properties of Stellar Populations

NASA Astrophysics Data System (ADS)

Xin, Yu; Deng, Licai

Blue straggler stars are the most prominent bright objects in the colour-magnitude diagram of a star cluster that challenges the theory of stellar evolution. Star clusters are the closest counterparts of the theoretical concept of simple stellar populations (SSPs) in the Universe. SSPs are widely used as the basic building blocks to interpret stellar contents in galaxies. The concept of an SSP is a group of coeval stars which follows a given distribution in mass, and has the same chemical property and age. In practice, SSPs are more conveniently made by the latest stellar evolutionary models of single stars. In reality, however, stars can be more complicated than just single either at birth time or during the course of evolution in a typical environment. Observations of star clusters show that there are always exotic objects which do not follow the predictions of standard theory of stellar evolution. Blue straggler stars (BSSs), as discussed intensively in this book both observationally and theoretically, are very important in our context when considering the integrated spectral properties of a cluster, or a simple stellar population. In this chapter, we are going to describe how important the contribution of BSSs is to the total light of a cluster.

Is a larger refuge always better? Dispersal and dose in pesticide resistance evolution

PubMed Central

Takahashi, Daisuke; Yamanaka, Takehiko; Sudo, Masaaki; Andow, David A.

2017-01-01

The evolution of resistance against pesticides is an important problem of modern agriculture. The high‐dose/refuge strategy, which divides the landscape into treated and nontreated (refuge) patches, has proven effective at delaying resistance evolution. However, theoretical understanding is still incomplete, especially for combinations of limited dispersal and partially recessive resistance. We reformulate a two‐patch model based on the Comins model and derive a simple quadratic approximation to analyze the effects of limited dispersal, refuge size, and dominance for high efficacy treatments on the rate of evolution. When a small but substantial number of heterozygotes can survive in the treated patch, a larger refuge always reduces the rate of resistance evolution. However, when dominance is small enough, the evolutionary dynamics in the refuge population, which is indirectly driven by migrants from the treated patch, mainly describes the resistance evolution in the landscape. In this case, for small refuges, increasing the refuge size will increase the rate of resistance evolution. Our analysis distils major driving forces from the model, and can provide a framework for understanding directional selection in source‐sink environments. PMID:28422284

Proteins feel more than they see: fine-tuning of binding affinity by properties of the non-interacting surface.

PubMed

Kastritis, Panagiotis L; Rodrigues, João P G L M; Folkers, Gert E; Boelens, Rolf; Bonvin, Alexandre M J J

2014-07-15

Protein-protein complexes orchestrate most cellular processes such as transcription, signal transduction and apoptosis. The factors governing their affinity remain elusive however, especially when it comes to describing dissociation rates (koff). Here we demonstrate that, next to direct contributions from the interface, the non-interacting surface (NIS) also plays an important role in binding affinity, especially polar and charged residues. Their percentage on the NIS is conserved over orthologous complexes indicating an evolutionary selection pressure. Their effect on binding affinity can be explained by long-range electrostatic contributions and surface-solvent interactions that are known to determine the local frustration of the protein complex surface. Including these in a simple model significantly improves the affinity prediction of protein complexes from structural models. The impact of mutations outside the interacting surface on binding affinity is supported by experimental alanine scanning mutagenesis data. These results enable the development of more sophisticated and integrated biophysical models of binding affinity and open new directions in experimental control and modulation of biomolecular interactions. Copyright © 2014. Published by Elsevier Ltd.

The processive kinetics of gene conversion in bacteria

PubMed Central

Paulsson, Johan; El Karoui, Meriem; Lindell, Monica

2017-01-01

Summary Gene conversion, non‐reciprocal transfer from one homologous sequence to another, is a major force in evolutionary dynamics, promoting co‐evolution in gene families and maintaining similarities between repeated genes. However, the properties of the transfer – where it initiates, how far it proceeds and how the resulting conversion tracts are affected by mismatch repair – are not well understood. Here, we use the duplicate tuf genes in Salmonella as a quantitatively tractable model system for gene conversion. We selected for conversion in multiple different positions of tuf, and examined the resulting distributions of conversion tracts in mismatch repair‐deficient and mismatch repair‐proficient strains. A simple stochastic model accounting for the essential steps of conversion showed excellent agreement with the data for all selection points using the same value of the conversion processivity, which is the only kinetic parameter of the model. The analysis suggests that gene conversion effectively initiates uniformly at any position within a tuf gene, and proceeds with an effectively uniform conversion processivity in either direction limited by the bounds of the gene. PMID:28256783

Incorporating evolutionary measures into conservation prioritization.

PubMed

Redding, David W; Mooers, Arne Ø

2006-12-01

Conservation prioritization is dominated by the threat status of candidate species. However, species differ markedly in the shared genetic information they embody, and this information is not taken into account if species are prioritized by threat status alone. We developed a system of prioritization that incorporates both threat status and genetic information and applied it to 9546 species of birds worldwide. We devised a simple measure of a species' genetic value that takes into account the shape of the entire taxonomic tree of birds. This measure approximates the evolutionary history that each species embodies and sums to the phylogenetic diversity of the entire taxonomic tree. We then combined this genetic value with each species' probability of extinction to create a species-specific measure of expected loss of genetic information. The application of our methods to the world's avifauna showed that ranking species by expected loss of genetic information may help preserve bird evolutionary history by upgrading those threatened species with fewer close relatives. We recommend developing a mechanism to incorporate a species' genetic value into the prioritization framework.

Functional and evolutionary relationships between bacteriorhodopsin and halorhodopsin in the archaebacterium, halobacterium halobium

NASA Technical Reports Server (NTRS)

Lanyi, J. K.

1986-01-01

The archaebacteria occupy a unique place in phylogenetic trees constructed from analyses of sequences from key informational macromolecules, and their study continues to yield interesting ideas on the early evolution and divergence of biological forms. It is now known that the halobacteria among these species contain various retinal-proteins, resembling eukaryotic rhodopsins, but with different functions. Two of these pigments, located in the cytoplasmic membranes of the bacteria, are bacteriorhodopsin (a light-driven proton pump) and halorhodopsin (a light-driven chloride pump). Comparison of these systems is expected to reveal structure/function relationships in these simple (primitive?) energy transducing membrane components and evolutionary relationships which had produced the structural features which allow the divergent functions. Findings indicate that very different primary structures are needed for these proteins to accomplish their different functions. Indeed, analysis of partial amino acid sequences from halo-opsin shows already that few if any long segments exist which are homologous to bacterio-opsin. Either these proteins diverged a very long time ago to allow for the observed differences, or the evolutionary clock in the halobacteria runs faster than usual.

The possible nature of socket stars in H II regions

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

Castelaz, M.W.

1990-01-01

Close inspection of faint stars (V of about 14 mag) in H II regions show that they appear to be surrounded by circumstellar envelopes of about 10 arcsecs in diameter (as reported by Feibelman in 1989). The present premise is that the sockets are envelopes of obscuring dust which should emit a measurable amount of infrared radiation based on a simple thermal equilibrium model. A search of literature shows that, of 36 socket stars listed by Feibelman, 17 have been measured in the infrared. Of the 17, 14 show excess IR emission. This is very strong evidence that the socketmore » stars are really stars with circumstellar envelopes. Socket stars may be a new type of astronomical object or well-known astronomical objects in environments or evolutionary states not previously seen. 22 refs.« less

Risk management in spatio-temporally varying field by true slime mold

NASA Astrophysics Data System (ADS)

Ito, Kentaro; Sumpter, David; Nakagaki, Toshiyuki

Revealing how lower organisms solve complicated problems is a challenging research area, which could reveal the evolutionary origin of biological information processing. Here we report on the ability of a single-celled organism, true slime mold, to find a smart solution of risk management under spatio-temporally varying conditions. We designed test conditions under which there were three food-locations at vertices of equilateral triangle and a toxic light illuminated the organism on alternating halves of the triangle. We found that the organism behavior depended on the period of the repeated illumination, even though the total exposure time was kept the same . A simple mathematical model for the experimental results is proposed from a dynamical system point of view. We discuss our results in the context of a strategy of risk management by Physarum.

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.

Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

NASA Astrophysics Data System (ADS)

Dickes, Amanda Catherine; Sengupta, Pratim

2013-06-01

In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these agents obey simple rules assigned or manipulated by the user (e.g., speeding up, slowing down, etc.). It is the interactions between these agents, based on the rules assigned by the user, that give rise to emergent, aggregate-level behavior (e.g., formation and movement of the traffic jam). Natural selection is such an emergent phenomenon, which has been shown to be challenging for novices (K16 students) to understand. Whereas prior research on learning evolutionary phenomena with MABMs has typically focused on high school students and beyond, we investigate how elementary students (4th graders) develop multi-level explanations of some introductory aspects of natural selection—species differentiation and population change—through scaffolded interactions with an MABM that simulates predator-prey dynamics in a simple birds-butterflies ecosystem. We conducted a semi-clinical interview based study with ten participants, in which we focused on the following: a) identifying the nature of learners' initial interpretations of salient events or elements of the represented phenomena, b) identifying the roles these interpretations play in the development of their multi-level explanations, and c) how attending to different levels of the relevant phenomena can make explicit different mechanisms to the learners. In addition, our analysis also shows that although there were differences between high- and low-performing students (in terms of being able to explain population-level behaviors) in the pre-test, these differences disappeared in the post-test.

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

In silico mining and PCR-based approaches to transcription factor discovery in non-model plants: gene discovery of the WRKY transcription factors in conifers.

PubMed

Liu, Jun-Jun; Xiang, Yu

2011-01-01

WRKY transcription factors are key regulators of numerous biological processes in plant growth and development, as well as plant responses to abiotic and biotic stresses. Research on biological functions of plant WRKY genes has focused in the past on model plant species or species with largely characterized transcriptomes. However, a variety of non-model plants, such as forest conifers, are essential as feed, biofuel, and wood or for sustainable ecosystems. Identification of WRKY genes in these non-model plants is equally important for understanding the evolutionary and function-adaptive processes of this transcription factor family. Because of limited genomic information, the rarity of regulatory gene mRNAs in transcriptomes, and the sequence divergence to model organism genes, identification of transcription factors in non-model plants using methods similar to those generally used for model plants is difficult. This chapter describes a gene family discovery strategy for identification of WRKY transcription factors in conifers by a combination of in silico-based prediction and PCR-based experimental approaches. Compared to traditional cDNA library screening or EST sequencing at transcriptome scales, this integrated gene discovery strategy provides fast, simple, reliable, and specific methods to unveil the WRKY gene family at both genome and transcriptome levels in non-model plants.

Bayesian inference of selection in a heterogeneous environment from genetic time-series data.

PubMed

Gompert, Zachariah

2016-01-01

Evolutionary geneticists have sought to characterize the causes and molecular targets of selection in natural populations for many years. Although this research programme has been somewhat successful, most statistical methods employed were designed to detect consistent, weak to moderate selection. In contrast, phenotypic studies in nature show that selection varies in time and that individual bouts of selection can be strong. Measurements of the genomic consequences of such fluctuating selection could help test and refine hypotheses concerning the causes of ecological specialization and the maintenance of genetic variation in populations. Herein, I proposed a Bayesian nonhomogeneous hidden Markov model to estimate effective population sizes and quantify variable selection in heterogeneous environments from genetic time-series data. The model is described and then evaluated using a series of simulated data, including cases where selection occurs on a trait with a simple or polygenic molecular basis. The proposed method accurately distinguished neutral loci from non-neutral loci under strong selection, but not from those under weak selection. Selection coefficients were accurately estimated when selection was constant or when the fitness values of genotypes varied linearly with the environment, but these estimates were less accurate when fitness was polygenic or the relationship between the environment and the fitness of genotypes was nonlinear. Past studies of temporal evolutionary dynamics in laboratory populations have been remarkably successful. The proposed method makes similar analyses of genetic time-series data from natural populations more feasible and thereby could help answer fundamental questions about the causes and consequences of evolution in the wild. © 2015 John Wiley & Sons Ltd.

Why the null matters: statistical tests, random walks and evolution.

PubMed

Sheets, H D; Mitchell, C E

2001-01-01

A number of statistical tests have been developed to determine what type of dynamics underlie observed changes in morphology in evolutionary time series, based on the pattern of change within the time series. The theory of the 'scaled maximum', the 'log-rate-interval' (LRI) method, and the Hurst exponent all operate on the same principle of comparing the maximum change, or rate of change, in the observed dataset to the maximum change expected of a random walk. Less change in a dataset than expected of a random walk has been interpreted as indicating stabilizing selection, while more change implies directional selection. The 'runs test' in contrast, operates on the sequencing of steps, rather than on excursion. Applications of these tests to computer generated, simulated time series of known dynamical form and various levels of additive noise indicate that there is a fundamental asymmetry in the rate of type II errors of the tests based on excursion: they are all highly sensitive to noise in models of directional selection that result in a linear trend within a time series, but are largely noise immune in the case of a simple model of stabilizing selection. Additionally, the LRI method has a lower sensitivity than originally claimed, due to the large range of LRI rates produced by random walks. Examination of the published results of these tests show that they have seldom produced a conclusion that an observed evolutionary time series was due to directional selection, a result which needs closer examination in light of the asymmetric response of these tests.

Evolution Analysis of Simple Sequence Repeats in Plant Genome.

PubMed

Qin, Zhen; Wang, Yanping; Wang, Qingmei; Li, Aixian; Hou, Fuyun; Zhang, Liming

2015-01-01

Simple sequence repeats (SSRs) are widespread units on genome sequences, and play many important roles in plants. In order to reveal the evolution of plant genomes, we investigated the evolutionary regularities of SSRs during the evolution of plant species and the plant kingdom by analysis of twelve sequenced plant genome sequences. First, in the twelve studied plant genomes, the main SSRs were those which contain repeats of 1-3 nucleotides combination. Second, in mononucleotide SSRs, the A/T percentage gradually increased along with the evolution of plants (except for P. patens). With the increase of SSRs repeat number the percentage of A/T in C. reinhardtii had no significant change, while the percentage of A/T in terrestrial plants species gradually declined. Third, in dinucleotide SSRs, the percentage of AT/TA increased along with the evolution of plant kingdom and the repeat number increased in terrestrial plants species. This trend was more obvious in dicotyledon than monocotyledon. The percentage of CG/GC showed the opposite pattern to the AT/TA. Forth, in trinucleotide SSRs, the percentages of combinations including two or three A/T were in a rising trend along with the evolution of plant kingdom; meanwhile with the increase of SSRs repeat number in plants species, different species chose different combinations as dominant SSRs. SSRs in C. reinhardtii, P. patens, Z. mays and A. thaliana showed their specific patterns related to evolutionary position or specific changes of genome sequences. The results showed that, SSRs not only had the general pattern in the evolution of plant kingdom, but also were associated with the evolution of the specific genome sequence. The study of the evolutionary regularities of SSRs provided new insights for the analysis of the plant genome evolution.

Scalability problems of simple genetic algorithms.

PubMed

Thierens, D

1999-01-01

Scalable evolutionary computation has become an intensively studied research topic in recent years. The issue of scalability is predominant in any field of algorithmic design, but it became particularly relevant for the design of competent genetic algorithms once the scalability problems of simple genetic algorithms were understood. Here we present some of the work that has aided in getting a clear insight in the scalability problems of simple genetic algorithms. Particularly, we discuss the important issue of building block mixing. We show how the need for mixing places a boundary in the GA parameter space that, together with the boundary from the schema theorem, delimits the region where the GA converges reliably to the optimum in problems of bounded difficulty. This region shrinks rapidly with increasing problem size unless the building blocks are tightly linked in the problem coding structure. In addition, we look at how straightforward extensions of the simple genetic algorithm-namely elitism, niching, and restricted mating are not significantly improving the scalability problems.

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.

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.

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.

Observational evidence of dust evolution in galactic extinction curves

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

Cecchi-Pestellini, Cesare; Casu, Silvia; Mulas, Giacomo

Although structural and optical properties of hydrogenated amorphous carbons are known to respond to varying physical conditions, most conventional extinction models are basically curve fits with modest predictive power. We compare an evolutionary model of the physical properties of carbonaceous grain mantles with their determination by homogeneously fitting observationally derived Galactic extinction curves with the same physically well-defined dust model. We find that a large sample of observed Galactic extinction curves are compatible with the evolutionary scenario underlying such a model, requiring physical conditions fully consistent with standard density, temperature, radiation field intensity, and average age of diffuse interstellar clouds.more » Hence, through the study of interstellar extinction we may, in principle, understand the evolutionary history of the diffuse interstellar clouds.« less

Some Physical Principles Governing Spatial and Temporal Organization in Living Systems

NASA Astrophysics Data System (ADS)

Ali, Md Zulfikar

Spatial and temporal organization in living organisms are crucial for a variety of biological functions and arise from the interplay of large number of interacting molecules. One of the central questions in systems biology is to understand how such an intricate organization emerges from the molecular biochemistry of the cell. In this dissertation we explore two projects. The first project relates to pattern formation in a cell membrane as an example of spatial organization, and the second project relates to the evolution of oscillatory networks as a simple example of temporal organization. For the first project, we introduce a model for pattern formation in a two-component lipid bilayer and study the interplay between membrane composition and membrane geometry, demonstrating the existence of a rich phase diagram. Pattern formation is governed by the interplay between phase separation driven by lipid-lipid interactions and tendency of lipid domains with high intrinsic curvature to deform the membrane away from its preferred position. Depending on membrane parameters, we find the formation of compact lipid micro-clusters or of striped domains. We calculate the stripe width analytically and find good agreement with stripe widths obtained from the simulations. For the second project, we introduce a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational algorithm and apply it to study the following problems. Using the model, we study robustness and designabilty of a 2-component network that generate oscillations. We completely enumerate the sequence space and the phenotypic space, and discuss the relationship between designabilty, robustness and evolvability. We further apply the model to studies of neutral drift in networks that yield oscillatory dynamics, e.g. starting with a relatively simple network and allowing it to evolve by adding nodes and connections while requiring that oscillatory dynamics be preserved. Our studies demonstrate both the importance of employing a sequence-based evolutionary scheme and the relative rapidity (in evolutionary time) for the redistribution of function over new nodes via neutral drift. In addition we discovered another much slower timescale for network evolution, reflecting hidden order in sequence space that we interpret in terms of sparsely connected domains. Finally, we use the model to study the evolution of an oscillator from a non-oscillatory network under the influence of external periodic forcing as a model for evolution of circadian rhythm in living systems. We use a greedy algorithm based on optimizing biologically motivated fitness functions and find that the algorithm successfully produces oscillators. However, the distribution of free-period of evolved oscillators depends on the choice of fitness functions and the nature of forcing.

A general model for the scaling of offspring size and adult size.

PubMed

Falster, Daniel S; Moles, Angela T; Westoby, Mark

2008-09-01

Understanding evolutionary coordination among different life-history traits is a key challenge for ecology and evolution. Here we develop a general quantitative model predicting how offspring size should scale with adult size by combining a simple model for life-history evolution with a frequency-dependent survivorship model. The key innovation is that larger offspring are afforded three different advantages during ontogeny: higher survivorship per time, a shortened juvenile phase, and advantage during size-competitive growth. In this model, it turns out that size-asymmetric advantage during competition is the factor driving evolution toward larger offspring sizes. For simplified and limiting cases, the model is shown to produce the same predictions as the previously existing theory on which it is founded. The explicit treatment of different survival advantages has biologically important new effects, mainly through an interaction between total maternal investment in reproduction and the duration of competitive growth. This goes on to explain alternative allometries between log offspring size and log adult size, as observed in mammals (slope = 0.95) and plants (slope = 0.54). Further, it suggests how these differences relate quantitatively to specific biological processes during recruitment. In these ways, the model generalizes across previous theory and provides explanations for some differences between major taxa.

Social evolution and genetic interactions in the short and long term.

PubMed

Van Cleve, Jeremy

2015-08-01

The evolution of social traits remains one of the most fascinating and feisty topics in evolutionary biology even after half a century of theoretical research. W.D. Hamilton shaped much of the field initially with his 1964 papers that laid out the foundation for understanding the effect of genetic relatedness on the evolution of social behavior. Early theoretical investigations revealed two critical assumptions required for Hamilton's rule to hold in dynamical models: weak selection and additive genetic interactions. However, only recently have analytical approaches from population genetics and evolutionary game theory developed sufficiently so that social evolution can be studied under the joint action of selection, mutation, and genetic drift. We review how these approaches suggest two timescales for evolution under weak mutation: (i) a short-term timescale where evolution occurs between a finite set of alleles, and (ii) a long-term timescale where a continuum of alleles are possible and populations evolve continuously from one monomorphic trait to another. We show how Hamilton's rule emerges from the short-term analysis under additivity and how non-additive genetic interactions can be accounted for more generally. This short-term approach reproduces, synthesizes, and generalizes many previous results including the one-third law from evolutionary game theory and risk dominance from economic game theory. Using the long-term approach, we illustrate how trait evolution can be described with a diffusion equation that is a stochastic analogue of the canonical equation of adaptive dynamics. Peaks in the stationary distribution of the diffusion capture classic notions of convergence stability from evolutionary game theory and generally depend on the additive genetic interactions inherent in Hamilton's rule. Surprisingly, the peaks of the long-term stationary distribution can predict the effects of simple kinds of non-additive interactions. Additionally, the peaks capture both weak and strong effects of social payoffs in a manner difficult to replicate with the short-term approach. Together, the results from the short and long-term approaches suggest both how Hamilton's insight may be robust in unexpected ways and how current analytical approaches can expand our understanding of social evolution far beyond Hamilton's original work. Copyright © 2015 Elsevier Inc. All rights reserved.

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...

Theologies, ideologies and evolutionary biology.

PubMed

Scudo, Francesco M

2010-01-01

Since a century evolution has mostly been interpreted by two simple, "opposite" kinds of "theories" — i.e. as due either to fitness differences among genotypes or to some other simple mechanism — while bona fide, more complex theories were less popular throughout. In particular by far the most complete theories ever produced were suddenly, almost universally abandoned just after World War II, though not as a consequence of major breakthroughs. The causes of this situation are examined by analogy with much earlier developments and their demise by Cartesianism. The down to earth solutions these "complete" theories provide to the problems of "speciation" and the origins of cells are contrasted with the "miraculous" approaches by systemic neo-Darwinists.

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

Evolutionary Agent-Based Simulation of the Introduction of New Technologies in Air Traffic Management

NASA Technical Reports Server (NTRS)

Yliniemi, Logan; Agogino, Adrian K.; Tumer, Kagan

2014-01-01

Accurate simulation of the effects of integrating new technologies into a complex system is critical to the modernization of our antiquated air traffic system, where there exist many layers of interacting procedures, controls, and automation all designed to cooperate with human operators. Additions of even simple new technologies may result in unexpected emergent behavior due to complex human/ machine interactions. One approach is to create high-fidelity human models coming from the field of human factors that can simulate a rich set of behaviors. However, such models are difficult to produce, especially to show unexpected emergent behavior coming from many human operators interacting simultaneously within a complex system. Instead of engineering complex human models, we directly model the emergent behavior by evolving goal directed agents, representing human users. Using evolution we can predict how the agent representing the human user reacts given his/her goals. In this paradigm, each autonomous agent in a system pursues individual goals, and the behavior of the system emerges from the interactions, foreseen or unforeseen, between the agents/actors. We show that this method reflects the integration of new technologies in a historical case, and apply the same methodology for a possible future technology.

How self-organization can guide evolution.

PubMed

Glancy, Jonathan; Stone, James V; Wilson, Stuart P

2016-11-01

Self-organization and natural selection are fundamental forces that shape the natural world. Substantial progress in understanding how these forces interact has been made through the study of abstract models. Further progress may be made by identifying a model system in which the interaction between self-organization and selection can be investigated empirically. To this end, we investigate how the self-organizing thermoregulatory huddling behaviours displayed by many species of mammals might influence natural selection of the genetic components of metabolism. By applying a simple evolutionary algorithm to a well-established model of the interactions between environmental, morphological, physiological and behavioural components of thermoregulation, we arrive at a clear, but counterintuitive, prediction: rodents that are able to huddle together in cold environments should evolve a lower thermal conductance at a faster rate than animals reared in isolation. The model therefore explains how evolution can be accelerated as a consequence of relaxed selection , and it predicts how the effect may be exaggerated by an increase in the litter size, i.e. by an increase in the capacity to use huddling behaviours for thermoregulation. Confirmation of these predictions in future experiments with rodents would constitute strong evidence of a mechanism by which self-organization can guide natural selection.

Eco-evolutionary Red Queen dynamics regulate biodiversity in a metabolite-driven microbial system.

PubMed

Bonachela, Juan A; Wortel, Meike T; Stenseth, Nils Chr

2017-12-15

The Red Queen Hypothesis proposes that perpetual co-evolution among organisms can result from purely biotic drivers. After more than four decades, there is no satisfactory understanding as to which mechanisms trigger Red Queen dynamics or their implications for ecosystem features such as biodiversity. One reason for such a knowledge gap is that typical models are complicated theories where limit cycles represent an idealized Red Queen, and therefore cannot be used to devise experimental setups. Here, we bridge this gap by introducing a simple model for microbial systems able to show Red Queen dynamics. We explore diverse biotic sources that can drive the emergence of the Red Queen and that have the potential to be found in nature or to be replicated in the laboratory. Our model enables an analytical understanding of how Red Queen dynamics emerge in our setup, and the translation of model terms and phenomenology into general underlying mechanisms. We observe, for example, that in our system the Red Queen offers opportunities for the increase of biodiversity by facilitating challenging conditions for intraspecific dominance, whereas stasis tends to homogenize the system. Our results can be used to design and engineer experimental microbial systems showing Red Queen dynamics.

Thermal niche estimators and the capability of poor dispersal species to cope with climate change

NASA Astrophysics Data System (ADS)

Sánchez-Fernández, David; Rizzo, Valeria; Cieslak, Alexandra; Faille, Arnaud; Fresneda, Javier; Ribera, Ignacio

2016-03-01

For management strategies in the context of global warming, accurate predictions of species response are mandatory. However, to date most predictions are based on niche (bioclimatic) models that usually overlook biotic interactions, behavioral adjustments or adaptive evolution, and assume that species can disperse freely without constraints. The deep subterranean environment minimises these uncertainties, as it is simple, homogeneous and with constant environmental conditions. It is thus an ideal model system to study the effect of global change in species with poor dispersal capabilities. We assess the potential fate of a lineage of troglobitic beetles under global change predictions using different approaches to estimate their thermal niche: bioclimatic models, rates of thermal niche change estimated from a molecular phylogeny, and data from physiological studies. Using bioclimatic models, at most 60% of the species were predicted to have suitable conditions in 2080. Considering the rates of thermal niche change did not improve this prediction. However, physiological data suggest that subterranean species have a broad thermal tolerance, allowing them to stand temperatures never experienced through their evolutionary history. These results stress the need of experimental approaches to assess the capability of poor dispersal species to cope with temperatures outside those they currently experience.

The marmoset monkey as a model for visual neuroscience

PubMed Central

Mitchell, Jude F.; Leopold, David A.

2015-01-01

The common marmoset (Callithrix jacchus) has been valuable as a primate model in biomedical research. Interest in this species has grown recently, in part due to the successful demonstration of transgenic marmosets. Here we examine the prospects of the marmoset model for visual neuroscience research, adopting a comparative framework to place the marmoset within a broader evolutionary context. The marmoset’s small brain bears most of the organizational features of other primates, and its smooth surface offers practical advantages over the macaque for areal mapping, laminar electrode penetration, and two-photon and optical imaging. Behaviorally, marmosets are more limited at performing regimented psychophysical tasks, but do readily accept the head restraint that is necessary for accurate eye tracking and neurophysiology, and can perform simple discriminations. Their natural gaze behavior closely resembles that of other primates, with a tendency to focus on objects of social interest including faces. Their immaturity at birth and routine twinning also makes them ideal for the study of postnatal visual development. These experimental factors, together with the theoretical advantages inherent in comparing anatomy, physiology, and behavior across related species, make the marmoset an excellent model for visual neuroscience. PMID:25683292

The mysterious age invariance of the planetary nebula luminosity function bright cut-off

NASA Astrophysics Data System (ADS)

Gesicki, K.; Zijlstra, A. A.; Miller Bertolami, M. M.

2018-05-01

Planetary nebulae mark the end of the active life of 90% of all stars. They trace the transition from a red giant to a degenerate white dwarf. Stellar models1,2 predicted that only stars above approximately twice the solar mass could form a bright nebula. But the ubiquitous presence of bright planetary nebulae in old stellar populations, such as elliptical galaxies, contradicts this: such high-mass stars are not present in old systems. The planetary nebula luminosity function, and especially its bright cut-off, is almost invariant between young spiral galaxies, with high-mass stars, and old elliptical galaxies, with only low-mass stars. Here, we show that new evolutionary tracks of low-mass stars are capable of explaining in a simple manner this decades-old mystery. The agreement between the observed luminosity function and computed stellar evolution validates the latest theoretical modelling. With these models, the planetary nebula luminosity function provides a powerful diagnostic to derive star formation histories of intermediate-age stars. The new models predict that the Sun at the end of its life will also form a planetary nebula, but it will be faint.

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.

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

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).

Correlated pay-offs are key to cooperation

PubMed Central

Frommen, Joachim G.; Riehl, Christina

2016-01-01

The general belief that cooperation and altruism in social groups result primarily from kin selection has recently been challenged, not least because results from cooperatively breeding insects and vertebrates have shown that groups may be composed mainly of non-relatives. This allows testing predictions of reciprocity theory without the confounding effect of relatedness. Here, we review complementary and alternative evolutionary mechanisms to kin selection theory and provide empirical examples of cooperative behaviour among unrelated individuals in a wide range of taxa. In particular, we focus on the different forms of reciprocity and on their underlying decision rules, asking about evolutionary stability, the conditions selecting for reciprocity and the factors constraining reciprocal cooperation. We find that neither the cognitive requirements of reciprocal cooperation nor the often sequential nature of interactions are insuperable stumbling blocks for the evolution of reciprocity. We argue that simple decision rules such as ‘help anyone if helped by someone’ should get more attention in future research, because empirical studies show that animals apply such rules, and theoretical models find that they can create stable levels of cooperation under a wide range of conditions. Owing to its simplicity, behaviour based on such a heuristic may in fact be ubiquitous. Finally, we argue that the evolution of exchange and trading of service and commodities among social partners needs greater scientific focus. PMID:26729924

Body size as a primary determinant of ecomorphological diversification and the evolution of mimicry in the lampropeltinine snakes (Serpentes: Colubridae).

PubMed

Pyron, R Alexander; Burbrink, F T

2009-10-01

Evolutionary correlations between functionally related character suites are expected as a consequence of coadaptation due to physiological relationships between traits. However, significant correlations may also exist between putatively unrelated characters due to shared relationships between those traits and underlying variables, such as body size. Although such patterns are often dismissed as simple body size scaling, this presumption may overlook important evolutionary patterns of diversification. If body size is the primary determinant of potential diversity in multiple unrelated characters, the observed differentiation of species may be governed by variability in body size, and any biotic or abiotic constraints on the diversification thereof. Here, we demonstrate that traits related to both predatory specialization (gape and diet preference) and predatory avoidance (the development of Batesian mimicry) are phylogenetically correlated in the North American snake tribe Lampropeltini. This is apparently due to shared relationships between those traits and adult body size, suggesting that size is the primary determinant of ecomorphological differentiation in the lampropeltinines. Diversification in body size is apparently not linked to climatic or environmental factors, and may have been driven by interspecific interactions such as competition. Additionally, we find the presence of a 'key zone' for the development of both rattle- and coral snake mimicry; only small snakes feeding primarily on ectothermic prey develop mimetic colour patterns, in or near the range of venomous model species.

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.

Designing and Implementing a Clinician Workstation

PubMed Central

Tape, Thomas G.; Campbell, James R.

1993-01-01

We describe a simple approach to designing and quickly implementing a clinician workstation that helps practitioners access a variety of information resources. Using easy-to-use graphical tools, we installed a pilot workstation in our clinics. We were able to accommodate most of our users' needs and have a functional workstation installed in two months. This is the first step of an evolutionary process moving from separate tasks to full application integration.

Darwin's legacy: why biology is not physics, or why evolution has not become a common sense.

PubMed

Singh, Rama S

2011-10-01

Cosmology and evolution together have enabled us to look deep into the past and comprehend evolution-from the big bang to the cosmos, from molecules to humans. Here, I compare the nature of theories in biology and physics and ask why physical theories get accepted by the public without necessarily comprehending them but biological theories do not. Darwin's theory of natural selection, utterly simple in its premises but profound in its consequences, is not accepted widely. Organized religions, and creationists in particularly, have been the major critic of evolution, but not all opposition to evolution comes from organized religions. A great many people, between evolutionary biologists on one hand and creationists on the other, many academics included, who may not be logically opposed to evolution nevertheless do not accept it. This is because the process of and the evidence for evolution are invisible to a nonspecialist, or the theory may look too simple to explain complex traits to some, or because people compare evolution against God and find evolutionary explanations threatening to their beliefs. Considering how evolution affects our lives, including health and the environment to give just two examples, a basic course in evolution should become a required component of all our college and university educational systems.

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.

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.