Search results for "Fitness landscape"
showing 10 items of 18 documents
Species loss leads to community closure
2008
Global extinction of a species is sadly irreversible. At a local scale, however, extinctions may be followed by re-invasion. We here show that this is not necessarily the case and that an ecological community may close its doors for re-invasion of species lost from it. Previous studies of how communities are assembled have shown that there may be rules for that process and that limitations are set to the order by which species are introduced and put together. Instead of focusing on the assembly process we randomly generated simple competitive model communities that were stable and allowed for two to 10 coexisting species. When a randomly selected single species was removed from the communit…
THE DISTRIBUTION OF MUTATIONAL FITNESS EFFECTS OF PHAGE φX174 ON DIFFERENT HOSTS
2012
Adaptation depends greatly on the distribution of mutation fitness effects (DMFE), but the phenotypic expression of mutations is often environment dependent. The environments faced by multihost pathogens are mostly governed by their hosts and therefore measuring the DMFE on multiple hosts can inform on the likelihood of short-term establishment and longer term adaptation of emerging pathogens. We explored this by measuring the growth rate of 36 mutants of the lytic bacteriophage φX174 on two host backgrounds, Escherichia coli (EcC) and Salmonella typhimurium (StGal). The DMFE showed higher mean and variance on EcC than on StGal. Most mutations were either deleterious or neutral on both host…
Natural Selection Fails to Optimize Mutation Rates for Long-Term Adaptation on Rugged Fitness Landscapes
2008
The rate of mutation is central to evolution. Mutations are required for adaptation, yet most mutations with phenotypic effects are deleterious. As a consequence, the mutation rate that maximizes adaptation will be some intermediate value. Here, we used digital organisms to investigate the ability of natural selection to adjust and optimize mutation rates. We assessed the optimal mutation rate by empirically determining what mutation rate produced the highest rate of adaptation. Then, we allowed mutation rates to evolve, and we evaluated the proximity to the optimum. Although we chose conditions favorable for mutation rate optimization, the evolved rates were invariably far below the optimu…
Effect of Host Species on Topography of the Fitness Landscape for a Plant RNA Virus
2016
[EN] Adaptive fitness landscapes are a fundamental concept in evolutionary biology that relate the genotype of individuals with their fitness. At the end, the evolutionary fate of evolving populations depends on the topography of the landscape, that is, the number of accessible mutational pathways and of possible fitness peaks (i.e, adaptive solutions). For long time, fitness landscapes were only theoretical constructions due to a lack of precise information on the mapping between genotypes and phenotypes. In recent years, however, efforts have been devoted to characterize the properties of empirical fitness landscapes for individual proteins or for microbes adapting to artificial environme…
Viral replication modes in single-peak fitness landscapes: A dynamical systems analysis
2017
Positive-sense, single-stranded RNA viruses are important pathogens infecting almost all types of organisms. Experimental evidence from distributions of mutations and from viral RNA amplification suggest that these pathogens may follow different RNA replication modes, ranging from the stamping machine replication (SMR) to the geometric replication (GR) mode. Although previous theoretical work has focused on the evolutionary dynamics of RNA viruses amplifying their genomes with different strategies, little is known in terms of the bifurcations and transitions involving the so-called error threshold (mutation-induced dominance of mutants) and lethal mutagenesis (extinction of all sequences du…
Network structure and optimal technological innovation
2019
The role of networks in the emergence, diffusion and evolution of technological innovations has attracted much theoretical and empirical attention. Yet, much of the work has explored the role of undirected and homogeneous networks. In real cases, many networks are directed. The flow of information, benefits or observations is directed from one node towards another node. Real networks are also heterogeneous, for example, few nodes have a high degree while many others have a low degree. In this article, we report on the results of an evolutionary agent-based model in which a group of agents, in our case firms, collectively search a complex (rugged) technological landscape and observe each oth…
Structural bias in population-based algorithms
2014
Abstract Challenging optimisation problems are abundant in all areas of science and industry. Since the 1950s, scientists have responded to this by developing ever-diversifying families of ‘black box’ optimisation algorithms. The latter are designed to be able to address any optimisation problem, requiring only that the quality of any candidate solution can be calculated via a ‘fitness function’ specific to the problem. For such algorithms to be successful, at least three properties are required: (i) an effective informed sampling strategy, that guides the generation of new candidates on the basis of the fitnesses and locations of previously visited candidates; (ii) mechanisms to ensure eff…
Predicting Heuristic Search Performance with PageRank Centrality in Local Optima Networks
2015
Previous studies have used statistical analysis of fitness landscapes such as ruggedness and deceptiveness in order to predict the expected quality of heuristic search methods. Novel approaches for predicting the performance of heuristic search are based on the analysis of local optima networks (LONs). A LON is a compressed stochastic model of a fitness landscape's basin transitions. Recent literature has suggested using various LON network measurements as predictors for local search performance.In this study, we suggest PageRank centrality as a new measure for predicting the performance of heuristic search methods using local search. PageRank centrality is a variant of Eigenvector centrali…
Coarse-Grained Barrier Trees of Fitness Landscapes
2016
Recent literature suggests that local optima in fitness landscapes are clustered, which offers an explanation of why perturbation-based metaheuristics often fail to find the global optimum: they become trapped in a sub-optimal cluster. We introduce a method to extract and visualize the global organization of these clusters in form of a barrier tree. Barrier trees have been used to visualize the barriers between local optima basins in fitness landscapes. Our method computes a more coarsely grained tree to reveal the barriers between clusters of local optima. The core element is a new variant of the flooding algorithm, applicable to local optima networks, a compressed representation of fitnes…
Shaping communities of local optima by perturbation strength
2017
Recent work discovered that fitness landscapes induced by Iterated Local Search (ILS) may consist of multiple clusters, denoted as funnels or communities of local optima. Such studies exist only for perturbation operators (kicks) with low strength. We examine how different strengths of the ILS perturbation operator affect the number and size of clusters. We present an empirical study based on local optima networks from NK fitness landscapes. Our results show that a properly selected perturbation strength can help overcome the effect of ILS getting trapped in clusters of local optima. This has implications for designing effective ILS approaches in practice, where traditionally only small per…