scholarly journals A White Noise Approach to Evolutionary Ecology

2020 ◽  
Author(s):  
Bob Week ◽  
Scott L. Nuismer ◽  
Luke J. Harmon ◽  
Stephen M. Krone
Keyword(s):  
White Noise ◽  
Genetic Drift ◽  
Evolutionary Ecology ◽  
Quantitative Character ◽  
Random Genetic Drift ◽  
Demographic Stochasticity ◽  
Selection Gradients ◽  
Evolutionary Response ◽  
Linear Selection ◽  
The Relationship

AbstractAlthough the evolutionary response to random genetic drift is classically modelled as a sampling process for populations with fixed abundance, the abundances of populations in the wild fluctuate over time. Furthermore, since wild populations exhibit demographic stochasticity, it is reasonable to consider the evolutionary response to demographic stochasticity and its relation to random genetic drift. Here we close this gap in the context of quantitative genetics by deriving the dynamics of the distribution of a quantitative character and the abundance of a biological population from a stochastic partial differential equation driven by space-time white noise. In the process we develop a useful set of heuristics to operationalize the powerful, but abstract theory of white noise and measure-valued stochastic processes. This approach allows us to compute the full implications of demographic stochasticity on phenotypic distributions and abundances of populations. We demonstrate the utility of our approach by deriving a quantitative genetic model of diffuse coevolution mediated by exploitative competition for a continuum of resources. In addition to trait and abundance distributions, this model predicts interaction networks defined by rates of interactions, competition coefficients, or selection gradients. Analyzing the relationship between selection gradients and competition coefficients reveals independence between linear selection gradients and competition coefficients. In contrast, absolute values of linear selection gradients and quadratic selection gradients tend to be positively correlated with competition coefficients. That is, competing species that strongly affect each other’s abundance tend to also impose selection on one another, but the directionality is not predicted. This approach contributes to the development of a synthetic theory of evolutionary ecology by formalizing first principle derivations of stochastic models that underlie rigorous investigations of the relationship between feedbacks of biological processes and the patterns of diversity they produce.

Isolation by distance in a quantitative trait.

Genetics ◽  
1991 ◽  
Vol 128 (2) ◽  
pp. 443-452 ◽  
Author(s):  
R Lande
Keyword(s):  
Genetic Drift ◽  
Genetic Variance ◽  
Two Dimensions ◽  
Quantitative Character ◽  
Stabilizing Selection ◽  
Neighborhood Size ◽  
Phenotypic Variance ◽  
Two Dimensional ◽  
Random Genetic Drift ◽  
Dispersal Function

Abstract Random genetic drift in a quantitative character is modeled for a population with a continuous spatial distribution in an infinite habitat of one or two dimensions. The analysis extends Wright's concept of neighborhood size to spatially autocorrelated sampling variation in the expected phenotype at different locations. Weak stabilizing selection is assumed to operate toward the same optimum phenotype in every locality, and the distribution of dispersal distances from parent to offspring is a (radially) symmetric function. The equilibrium pattern of geographic variation in the expected local phenotype depends on the neighborhood size, the genetic variance within neighborhoods, and the strength of selection, but is nearly independent of the form of the dispersal function. With all else equal, geographic variance is smaller in a two-dimensional habitat than in one dimension, and the covariance between expected local phenotypes decreases more rapidly with the distance separating them in two dimensions than in one. The equilibrium geographic variance is less than the phenotypic variance within localities, unless the neighborhood size is small and selection is extremely weak, especially in two dimensions. Nevertheless, dispersal of geographic variance created by random genetic drift is an important mechanism maintaining genetic variance within local populations. For a Gaussian dispersal function it is shown that, even with a small neighborhood size, a population in a two-dimensional habitat can maintain within neighborhoods most of the genetic variance that would occur in an infinite panmictic population.

Frequency-dependent selection, metrical characters and molecular evolution

1988 ◽  
Vol 319 (1196) ◽  
pp. 631-640 ◽  
Keyword(s):  
Molecular Evolution ◽  
Genetic Drift ◽  
Random Order ◽  
Quantitative Character ◽  
Stabilizing Selection ◽  
Molecular Clocks ◽  
Random Genetic Drift ◽  
Stochastic Effects ◽  
Frequency Dependent ◽  
Frequency Dependent Selection

Computer models of selection acting on a quantitative character show that a combination of frequency-dependent and stabilizing selection can maintain many polymorphisms among the genes that determine the character. The models also show that the random order of mutations can give rise to selectively driven stochastic effects that are sometimes more important than random genetic drift. They suggest simple explanations for patterns of divergence between populations and species, and for apparent discrepancies between the rates of morphological and molecular evolution. They point towards a selective theory of ‘molecular clocks’

Mutational order: a major stochastic process in evolution

1990 ◽  
Vol 240 (1297) ◽  
pp. 29-37 ◽  
Keyword(s):  
Stochastic Process ◽  
Computer Simulations ◽  
Genetic Drift ◽  
Molecular Clock ◽  
Quantitative Character ◽  
Evolutionary Divergence ◽  
Random Genetic Drift ◽  
Random Drift ◽  
Large Populations ◽  
Different Populations

Computer simulations in which selection acts on a quantitative character show that the randomness of mutations can contribute significantly to evolutionary divergence between populations. In different populations, different advantageous mutations occur, and are selected to fixation, so that the populations diverge even when they are initially identical, and are subject to identical selection. This stochastic process is distinct from random genetic drift. In some circumstances (large populations or strong selection, or both) mutational order can be greatly more important than random drift in bringing about divergence. It can generate a ‘disconnection’ between evolution at the phenotypic and genotypic levels, and can give rise to a rough ‘molecular clock’, albeit episodic, that is driven by selection. In the absence of selection, mutational order has little or no effect.

CYTO-NUCLEAR EPISTASIS: TWO-LOCUS RANDOM GENETIC DRIFT IN HERMAPHRODITIC AND DIOECIOUS SPECIES

Evolution ◽  
2006 ◽  
Vol 60 (4) ◽  
pp. 643 ◽  
Author(s):  
Michael J. Wade ◽  
Charles J. Goodnight
Keyword(s):  
Genetic Drift ◽  
Random Genetic Drift ◽  
Dioecious Species

scholarly journals Influence of Random Genetic Drift on Human Immunodeficiency Virus Type 1envEvolution During Chronic Infection

Genetics ◽  
2004 ◽  
Vol 166 (3) ◽  
pp. 1155-1164 ◽  
Author(s):  
Daniel Shriner ◽  
Raj Shankarappa ◽  
Mark A. Jensen ◽  
David C. Nickle ◽  
John E. Mittler ◽  
...  
Keyword(s):  
Human Immunodeficiency Virus ◽  
Human Immunodeficiency Virus Type ◽  
Virus Type ◽  
Genetic Drift ◽  
Chronic Infection ◽  
Random Genetic Drift ◽  
Immunodeficiency Virus

scholarly journals Evolution of a predator-induced, nonlinear reaction norm

2017 ◽  
Vol 284 (1861) ◽  
pp. 20170859 ◽  
Author(s):  
Mauricio J. Carter ◽  
Martin I. Lind ◽  
Stuart R. Dennis ◽  
William Hentley ◽  
Andrew P. Beckerman
Keyword(s):  
Evolutionary Dynamics ◽  
Daphnia Pulex ◽  
Reaction Norm ◽  
Maximum Response ◽  
Selective Predation ◽  
Evolutionary Trajectory ◽  
Defensive Reaction ◽  
Selection Gradients ◽  
Hunting Strategies ◽  
Evolutionary Response

Inducible, anti-predator traits are a classic example of phenotypic plasticity. Their evolutionary dynamics depend on their genetic basis, the historical pattern of predation risk that populations have experienced and current selection gradients. When populations experience predators with contrasting hunting strategies and size preferences, theory suggests contrasting micro-evolutionary responses to selection. Daphnia pulex is an ideal species to explore the micro-evolutionary response of anti-predator traits because they face heterogeneous predation regimes, sometimes experiencing only invertebrate midge predators and other times experiencing vertebrate fish and invertebrate midge predators. We explored plausible patterns of adaptive evolution of a predator-induced morphological reaction norm. We combined estimates of selection gradients that characterize the various habitats that D. pulex experiences with detail on the quantitative genetic architecture of inducible morphological defences. Our data reveal a fine scale description of daphnid defensive reaction norms, and a strong covariance between the sensitivity to cues and the maximum response to cues. By analysing the response of the reaction norm to plausible, predator-specific selection gradients, we show how in the context of this covariance, micro-evolution may be more uniform than predicted from size-selective predation theory. Our results show how covariance between the sensitivity to cues and the maximum response to cues for morphological defence can shape the evolutionary trajectory of predator-induced defences in D. pulex .

scholarly journals A General Solution of the Wright–Fisher Model of Random Genetic Drift

2016 ◽  
Vol 27 (4) ◽  
pp. 467-492 ◽  
Author(s):  
Tat Dat Tran ◽  
Julian Hofrichter ◽  
Jürgen Jost
Keyword(s):  
General Solution ◽  
Genetic Drift ◽  
Random Genetic Drift ◽  
Fisher Model

scholarly journals GENETIC VARIABILITY MAINTAINED BY MUTATION AND OVERDOMINANT SELECTION IN FINITE POPULATIONS

Genetics ◽  
1981 ◽  
Vol 98 (2) ◽  
pp. 441-459 ◽  
Author(s):  
Takeo Maruyama ◽  
Masatoshi Nei
Keyword(s):  
Mutation Rate ◽  
Allozyme Polymorphism ◽  
Random Genetic Drift ◽  
Effective Population ◽  
Mathematical Properties ◽  
Overdominant Selection ◽  
Mean And Variance ◽  
The Mean ◽  
Neutral Mutations ◽  
The Relationship

ABSTRACT Mathematical properties of the overdominance model with mutation and random genetic drift are studied by using the method of stochastic differential equations (Itô and McKean 1974). It is shown that overdominant selection is very powerful in increasing the mean heterozygosity as compared with neutral mutations, and if 2Ns (N = effective population size; s = selective disadvantage for homozygotes) is larger than 10, a very low mutation rate is sufficient to explain the observed level of allozyme polymorphism. The distribution of heterozygosity for overdominant genes is considerably different from that of neutral mutations, and if the ratio of selection coefficient (s) to mutation rate (ν) is large and the mean heterozygosity (h) is lower than 0.2, single-locus heterozygosity is either approximately 0 or 0.5. If h increases further, however, heterozygosity shows a multiple-peak distribution. Reflecting this type of distribution, the relationship between the mean and variance of heterozygosity is considerably different from that for neutral genes. When s/v is large, the proportion of polymorphic loci increases approximately linearly with mean heterozygosity. The distribution of allele frequencies is also drastically different from that of neutral genes, and generally shows a peak at the intermediate gene frequency. Implications of these results on the maintenance of allozyme polymorphism are discussed.

scholarly journals Polygenic local adaptation in metapopulations: a stochastic eco-evolutionary model

2020 ◽  
Author(s):  
Enikő Szép ◽  
Himani Sachdeva ◽  
Nick Barton
Keyword(s):  
Population Size ◽  
Local Adaptation ◽  
Genetic Drift ◽  
Diffusion Approximation ◽  
Joint Distribution ◽  
Evolutionary Model ◽  
Ecological Niches ◽  
Demographic Stochasticity ◽  
Linkage Disequilibria ◽  
Population Sizes

AbstractThis paper analyses the conditions for local adaptation in a metapopulation with infinitely many islands under a model of hard selection, where population size depends on local fitness. Each island belongs to one of two distinct ecological niches or habitats. Fitness is influenced by an additive trait which is under habitat-dependent directional selection. Our analysis is based on the diffusion approximation and accounts for both genetic drift and demographic stochasticity. By neglecting linkage disequilibria, it yields the joint distribution of allele frequencies and population size on each island. We find that under hard selection, the conditions for local adaptation in a rare habitat are more restrictive for more polygenic traits: even moderate migration load per locus at very many loci is sufficient for population sizes to decline. This further reduces the efficacy of selection at individual loci due to increased drift and because smaller populations are more prone to swamping due to migration, causing a positive feedback between increasing maladaptation and declining population sizes. Our analysis also highlights the importance of demographic stochasticity, which exacerbates the decline in numbers of maladapted populations, leading to population collapse in the rare habitat at significantly lower migration than predicted by deterministic arguments.

scholarly journals Evolution of gene regulatory networks by means of selection and random genetic drift

2018 ◽  
Author(s):  
Antonios Kioukis ◽  
Pavlos Pavlidis
Keyword(s):  
Natural Selection ◽  
Positive Selection ◽  
Genetic Drift ◽  
Regulatory Networks ◽  
Fitness Landscape ◽  
Random Genetic Drift ◽  
Maturation Period ◽  
Evolutionary Forces ◽  
Gene Regulatory

The evolution of a population by means of genetic drift and natural selection operating on a gene regulatory network (GRN) of an individual has not been scrutinized in depth. Thus, the relative importance of various evolutionary forces and processes on shaping genetic variability in GRNs is understudied. Furthermore, it is not known if existing tools that identify recent and strong positive selection from genomic sequences, in simple models of evolution, can detect recent positive selection when it operates on GRNs. Here, we propose a simulation framework, called EvoNET, that simulates forward-in-time the evolution of GRNs in a population. Since the population size is finite, random genetic drift is explicitly applied. The fitness of a mutation is not constant, but we evaluate the fitness of each individual by measuring its genetic distance from an optimal genotype. Mutations and recombination may take place from generation to generation, modifying the genotypic composition of the population. Each individual goes through a maturation period, where its GRN reaches equilibrium. At the next step, individuals compete to produce the next generation. As time progresses, the beneficial genotypes push the population higher in the fitness landscape. We examine properties of the GRN evolution such as robustness against the deleterious effect of mutations and the role of genetic drift. We confirm classical results from Andreas Wagner’s work that GRNs show robustness against mutations and we provide new results regarding the interplay between random genetic drift and natural selection.

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