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Organisms modulate their fitness in heterogeneous environments by dispersing. Prior work shows that there is selection against "unconditional" dispersal in spatially heterogeneous environments. "Unconditional" means individuals disperse at…

种群与进化 · 定量生物学 2011-09-28 Sebastian J. Schreiber , Chi-Kwong Li

We consider a population of genotype sequences evolving on a rugged fitness landscape with many local fitness peaks. The population walks uphill until it encounters a local fitness maximum. We find that the statistical properties of the…

种群与进化 · 定量生物学 2015-05-30 Kavita Jain

Experimental studies on enzyme evolution show that only a small fraction of all possible mutation trajectories are accessible to evolution. However, these experiments deal with individual enzymes and explore a tiny part of the fitness…

种群与进化 · 定量生物学 2015-05-30 Alexander E. Lobkovsky , Yuri I. Wolf , Eugene V. Koonin

The environment in which a population evolves can have a crucial impact on selection. We study evolutionary dynamics in finite populations of fixed size in a changing environment. The population dynamics are driven by birth and death…

种群与进化 · 定量生物学 2014-09-01 Peter Ashcroft , Philipp M Altrock , Tobias Galla

The problem of natural selection in dispersal-structured populations consisting of individuals characterized by different diffusion coefficients is studied. The competition between the organisms is taken into account through the assumption…

适应与自组织系统 · 物理学 2020-05-01 E. Heinsalu , D. Navidad Maeso , M. Patriarca

We study the adaptation dynamics of an initially maladapted asexual population with genotypes represented by binary sequences of length $L$. The population evolves in a maximally rugged fitness landscape with a large number of local optima.…

种群与进化 · 定量生物学 2007-05-23 Kavita Jain , Joachim Krug

Fitness landscapes are a useful concept to study the dynamics of meta-heuristics. In the last two decades, they have been applied with success to estimate the optimization power of several types of evolutionary algorithms, including genetic…

神经与进化计算 · 计算机科学 2020-01-31 Nuno M. Rodrigues , Sara Silva , Leonardo Vanneschi

A simple model of macroevolution is proposed exhibiting both the property of punctuated equilibrium and the dynamics of potentialities for different species to evolve towards increasingly higher complexity. It is based on the phenomenon of…

生物物理 · 物理学 2007-05-23 Siegfried Fussy , Gerhard Groessing , Herbert Schwabl

Predicting fitness of biologically-active populations, communities or systems in fluctuating environments is a long-standing challenge. Phenotypic plasticity and bet-hedging strategy, two key evolutionary traits living systems harness to…

种群与进化 · 定量生物学 2024-10-24 Sumana Bhattacharyya , Uttam Singh , Anupam Sengupta

Geographic ranges of communities of species evolve in response to environmental, ecological, and evolutionary forces. Understanding the effects of these forces on species' range dynamics is a major goal of spatial ecology. Previous…

种群与进化 · 定量生物学 2022-02-02 Farshad Shirani , Judith R. Miller

We consider a stochastic individual-based model of adaptive dynamics for an asexually reproducing population with mutation, with linear birth and death rates, as well as a density-dependent competition. To depict repeating changes of the…

种群与进化 · 定量生物学 2025-05-28 Manuel Esser , Anna Kraut

A fundamental problem in the fields of population genetics, evolution, and community ecology, is the fate of a single mutant, or invader, introduced in a finite population of wild types. For a fixed-size community of $N$ individuals, with…

种群与进化 · 定量生物学 2017-10-25 Matan Danino , Nadav M. Shnerb

The replicator-mutator equation is a model for populations of individuals carrying different traits, with a fitness function mediating their ability to replicate, and a stochastic model for mutation. We derive analytical solutions for the…

种群与进化 · 定量生物学 2024-12-16 Sahani Pathiraja , Philipp Wacker

On rugged fitness landscapes where sign epistasis is common, adaptation can often involve either individually beneficial "uphill" mutations or more complex mutational trajectories involving fitness valleys or plateaus. The dynamics of the…

种群与进化 · 定量生物学 2015-10-06 Ian E. Ochs , Michael M. Desai

Response time-delay is an ubiquitous phenomenon in biological systems. Here we use a simple stochastic population model with time-delayed switching-rate conversion to quantitatively study the biological influence of the response time-delay…

种群与进化 · 定量生物学 2009-04-14 Xiao chuan Xue , Jinhua Zhao , Fei Liu , Zhong-can Ou-Yang

Environment plays a fundamental role in the competition for resources, and hence in the evolution of populations. Here, we study a well-mixed, finite population consisting of two strains competing for the limited resources provided by an…

种群与进化 · 定量生物学 2017-10-16 Karl Wienand , Erwin Frey , Mauro Mobilia

When a biological population expands into new territory, genetic drift develops an enormous influence on evolution at the propagating front. In such range expansion processes, fluctuations in allele frequencies occur through stochastic…

生物物理 · 物理学 2018-12-24 Sherry Chu , Mehran Kardar , David R. Nelson , Daniel A. Beller

Mutational robustness quantifies the effect of random mutations on fitness. When mutational robustness is high, most mutations do not change fitness or have only a minor effect on it. From the point of view of fitness landscapes, robust…

种群与进化 · 定量生物学 2019-10-22 Alexander Klug , Su-Chan Park , Joachim Krug

Biological systems are modular, and this modularity affects the evolution of biological systems over time and in different environments. We here develop a theory for the dynamics of evolution in a rugged, modular fitness landscape. We show…

种群与进化 · 定量生物学 2015-06-23 Jeong-Man Park , Man Chen , Dong Wang , Michael W. Deem

Phenotypic fluctuations and plasticity can generally affect the course of evolution, a process known as the Baldwin effect. Several studies have recast this effect and claimed that phenotypic plasticity acceler- ates evolutionary rate (the…

种群与进化 · 定量生物学 2013-05-30 Nen Saito , Shuji Ishihara , Kunihiko Kaneko