The Experts below are selected from a list of 146493 Experts worldwide ranked by ideXlab platform
Arnaud Estoup - One of the best experts on this subject based on the ideXlab platform.
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Influence of Spatial and Temporal Heterogeneities on the Estimation of Demographic Parameters in a Continuous Population Using Individual Microsatellite Data
Genetics, 2004Co-Authors: Raphaël Leblois, Francois Rousset, Arnaud EstoupAbstract:Drift and migration disequilibrium are very common in animal and plant Populations. Yet their impact on methods of estimation of demographic parameters was rarely evaluated especially in complex realistic Population models. The effect of such disequilibria on the estimation of demographic parameters depends on the Population model, the statistics, and the genetic markers used. Here we considered the estimation of the product D{sigma}2 from individual microsatellite data, where D is the density of adults and {sigma}2 the average squared axial parent-offspring distance in a Continuous Population evolving under isolation by distance. A coalescence-based simulation algorithm was used to study the effect on D{sigma}2 estimation of temporal and spatial fluctuations of demographic parameters. Estimation of present-time D{sigma}2 values was found to be robust to temporal changes in dispersal, to density reduction, and to spatial expansions with constant density, even for relatively recent changes (i.e., a few tens of generations ago). By contrast, density increase in the recent past gave D{sigma}2 estimations biased largely toward past demographic parameters values. The method was also robust to spatial heterogeneity in density and estimated local demographic parameters when the density is homogenous around the sampling area (e.g., on a surface that equals four times the sampling area). Hence, in the limit of the situations studied in this article, and with the exception of the case of density increase, temporal and spatial fluctuations of demographic parameters appear to have a limited influence on the estimation of local and present-time demographic parameters with the method studied.
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influence of mutational and sampling factors on the estimation of demographic parameters in a Continuous Population under isolation by distance
Molecular Biology and Evolution, 2003Co-Authors: Raphaël Leblois, Arnaud Estoup, Francois RoussetAbstract:In numerous species, individual dispersal is restricted in space so that "Continuous" Populations evolve under isolation by distance. A method based on individual genotypes assuming a lattice Population model was recently developed to estimate the product Dsigma2, where D is the Population density and sigma2 is the average squared parent-offspring distance. We evaluated the influence on this method of both mutation rate and mutation model, with a particular reference to microsatellite markers, as well as that of the spatial scale of sampling. Moreover, we developed and tested a nonparametric bootstrap procedure allowing the construction of confidence intervals for the estimation of Dsigma2. These two objectives prompted us to develop a computer simulation algorithm based on the coalescent theory giving individual genotypes for a Continuous Population under isolation by distance. Our results show that the characteristics of mutational processes at microsatellite loci, namely the allele size homoplasy generated by stepwise mutations, constraints on allele size, and change of slippage rate with repeat number, have little influence on the estimation of Dsigma2. In contrast, a high genetic diversity (approximately 0.7-0.8), as is commonly observed for microsatellite markers, substantially increases the precision of the estimation. However, very high levels of genetic diversity (>0.85) were found to bias the estimation. We also show that statistics taking into account allele size differences give unreliable estimations (i.e., high variance of Dsigma2 estimation) even under a strict stepwise mutation model. Finally, although we show that this method is reasonably robust with respect to the sampling scale, sampling individuals at a local geographical scale gives more precise estimations of Dsigma2.
Shankar Sastry - One of the best experts on this subject based on the ideXlab platform.
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markov decision process routing games
International Conference on Cyber-Physical Systems, 2017Co-Authors: Dan Calderone, Shankar SastryAbstract:We explore an extension of nonatomic routing games that we call Markov decision process routing games where each agent chooses a transition policy between nodes in a network rather than a path from an origin node to a destination node, i.e. each agent in the Population solves a Markov decision process rather than a shortest path problem. We define the appropriate version of a Wardrop equilibrium as well as a potential function for this game in the finite horizon (total reward) case. This work can be thought of as a routing- game-based formulation of Continuous Population stochastic games (mean-field games or anonymous sequential games). We apply our model to the problem of ridesharing drivers competing for customers.
Raphaël Leblois - One of the best experts on this subject based on the ideXlab platform.
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Influence of Spatial and Temporal Heterogeneities on the Estimation of Demographic Parameters in a Continuous Population Using Individual Microsatellite Data
Genetics, 2004Co-Authors: Raphaël Leblois, Francois Rousset, Arnaud EstoupAbstract:Drift and migration disequilibrium are very common in animal and plant Populations. Yet their impact on methods of estimation of demographic parameters was rarely evaluated especially in complex realistic Population models. The effect of such disequilibria on the estimation of demographic parameters depends on the Population model, the statistics, and the genetic markers used. Here we considered the estimation of the product D{sigma}2 from individual microsatellite data, where D is the density of adults and {sigma}2 the average squared axial parent-offspring distance in a Continuous Population evolving under isolation by distance. A coalescence-based simulation algorithm was used to study the effect on D{sigma}2 estimation of temporal and spatial fluctuations of demographic parameters. Estimation of present-time D{sigma}2 values was found to be robust to temporal changes in dispersal, to density reduction, and to spatial expansions with constant density, even for relatively recent changes (i.e., a few tens of generations ago). By contrast, density increase in the recent past gave D{sigma}2 estimations biased largely toward past demographic parameters values. The method was also robust to spatial heterogeneity in density and estimated local demographic parameters when the density is homogenous around the sampling area (e.g., on a surface that equals four times the sampling area). Hence, in the limit of the situations studied in this article, and with the exception of the case of density increase, temporal and spatial fluctuations of demographic parameters appear to have a limited influence on the estimation of local and present-time demographic parameters with the method studied.
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influence of mutational and sampling factors on the estimation of demographic parameters in a Continuous Population under isolation by distance
Molecular Biology and Evolution, 2003Co-Authors: Raphaël Leblois, Arnaud Estoup, Francois RoussetAbstract:In numerous species, individual dispersal is restricted in space so that "Continuous" Populations evolve under isolation by distance. A method based on individual genotypes assuming a lattice Population model was recently developed to estimate the product Dsigma2, where D is the Population density and sigma2 is the average squared parent-offspring distance. We evaluated the influence on this method of both mutation rate and mutation model, with a particular reference to microsatellite markers, as well as that of the spatial scale of sampling. Moreover, we developed and tested a nonparametric bootstrap procedure allowing the construction of confidence intervals for the estimation of Dsigma2. These two objectives prompted us to develop a computer simulation algorithm based on the coalescent theory giving individual genotypes for a Continuous Population under isolation by distance. Our results show that the characteristics of mutational processes at microsatellite loci, namely the allele size homoplasy generated by stepwise mutations, constraints on allele size, and change of slippage rate with repeat number, have little influence on the estimation of Dsigma2. In contrast, a high genetic diversity (approximately 0.7-0.8), as is commonly observed for microsatellite markers, substantially increases the precision of the estimation. However, very high levels of genetic diversity (>0.85) were found to bias the estimation. We also show that statistics taking into account allele size differences give unreliable estimations (i.e., high variance of Dsigma2 estimation) even under a strict stepwise mutation model. Finally, although we show that this method is reasonably robust with respect to the sampling scale, sampling individuals at a local geographical scale gives more precise estimations of Dsigma2.
Francois Rousset - One of the best experts on this subject based on the ideXlab platform.
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Influence of Spatial and Temporal Heterogeneities on the Estimation of Demographic Parameters in a Continuous Population Using Individual Microsatellite Data
Genetics, 2004Co-Authors: Raphaël Leblois, Francois Rousset, Arnaud EstoupAbstract:Drift and migration disequilibrium are very common in animal and plant Populations. Yet their impact on methods of estimation of demographic parameters was rarely evaluated especially in complex realistic Population models. The effect of such disequilibria on the estimation of demographic parameters depends on the Population model, the statistics, and the genetic markers used. Here we considered the estimation of the product D{sigma}2 from individual microsatellite data, where D is the density of adults and {sigma}2 the average squared axial parent-offspring distance in a Continuous Population evolving under isolation by distance. A coalescence-based simulation algorithm was used to study the effect on D{sigma}2 estimation of temporal and spatial fluctuations of demographic parameters. Estimation of present-time D{sigma}2 values was found to be robust to temporal changes in dispersal, to density reduction, and to spatial expansions with constant density, even for relatively recent changes (i.e., a few tens of generations ago). By contrast, density increase in the recent past gave D{sigma}2 estimations biased largely toward past demographic parameters values. The method was also robust to spatial heterogeneity in density and estimated local demographic parameters when the density is homogenous around the sampling area (e.g., on a surface that equals four times the sampling area). Hence, in the limit of the situations studied in this article, and with the exception of the case of density increase, temporal and spatial fluctuations of demographic parameters appear to have a limited influence on the estimation of local and present-time demographic parameters with the method studied.
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influence of mutational and sampling factors on the estimation of demographic parameters in a Continuous Population under isolation by distance
Molecular Biology and Evolution, 2003Co-Authors: Raphaël Leblois, Arnaud Estoup, Francois RoussetAbstract:In numerous species, individual dispersal is restricted in space so that "Continuous" Populations evolve under isolation by distance. A method based on individual genotypes assuming a lattice Population model was recently developed to estimate the product Dsigma2, where D is the Population density and sigma2 is the average squared parent-offspring distance. We evaluated the influence on this method of both mutation rate and mutation model, with a particular reference to microsatellite markers, as well as that of the spatial scale of sampling. Moreover, we developed and tested a nonparametric bootstrap procedure allowing the construction of confidence intervals for the estimation of Dsigma2. These two objectives prompted us to develop a computer simulation algorithm based on the coalescent theory giving individual genotypes for a Continuous Population under isolation by distance. Our results show that the characteristics of mutational processes at microsatellite loci, namely the allele size homoplasy generated by stepwise mutations, constraints on allele size, and change of slippage rate with repeat number, have little influence on the estimation of Dsigma2. In contrast, a high genetic diversity (approximately 0.7-0.8), as is commonly observed for microsatellite markers, substantially increases the precision of the estimation. However, very high levels of genetic diversity (>0.85) were found to bias the estimation. We also show that statistics taking into account allele size differences give unreliable estimations (i.e., high variance of Dsigma2 estimation) even under a strict stepwise mutation model. Finally, although we show that this method is reasonably robust with respect to the sampling scale, sampling individuals at a local geographical scale gives more precise estimations of Dsigma2.
Rolf Holderegger - One of the best experts on this subject based on the ideXlab platform.
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mating patterns and contemporary gene flow by pollen in a large Continuous and a small isolated Population of the scattered forest tree sorbus torminalis
Heredity, 2007Co-Authors: Susan E Hoebee, U Arnold, C Duggelin, Felix Gugerli, Sabine Brodbeck, Peter Rotach, Rolf HoldereggerAbstract:The influence of Population size and spatial isolation on contemporary gene flow by pollen and mating patterns in temperate forest trees are not well documented, although they are crucial factors in the life history of plant species. We analysed a small, isolated Population and a large, Continuous Population of the insect-pollinated tree species Sorbus torminalis in two consecutive years. The species recently experienced increased habitat fragmentation due to altered forest management leading to forests with closed canopies. We estimated individual plant size, percentage of flowering trees, intensity of flowering, degree of fruiting and seed set per fruit, and we determined mating patterns, pollen flow distances and external gene flow in a genetic paternity analysis based on microsatellite markers. We found clear effects of small Population size and spatial isolation in S. torminalis. Compared with the large, Continuous Population, the small and isolated Population harboured a lower percentage of flowering trees, showed less intense flowering, lower fruiting, less developed seeds per fruit, increased selfing and received less immigrant pollen. However, the negative inbreeding coefficients (F(IS)) of offspring indicated that this did not result in inbred seed at the Population level. We also show that flowering, fruiting and pollen flow patterns varied among years, the latter being affected by the size of individuals. Though our study was unreplicated at the factor level (i.e. isolated vs non-isolated Populations), it shows that small and spatially isolated Populations of S. torminalis may also be genetically isolated, but that their progeny is not necessarily more inbred.