Counterintuitive properties of the fixation time in network-structured populations

Evolutionary dynamics on graphs can lead to many interesting and counterintuitive findings. We study the Moran process, a discrete time birth–death process, that describes the invasion of a mutant type into a population of wild-type individuals. Remarkably, the fixation probability of a single mutant is the same on all regular networks. But non-regular networks can increase or decrease the fixation probability. While the time until fixation formally depends on the same transition probabilities as the fixation probabilities, there is no obvious relation between them. For example, an amplifier of selection, which increases the fixation probability and thus decreases the number of mutations needed until one of them is successful, can at the same time slow down the process of fixation. Based on small networks, we show analytically that (i) the time to fixation can decrease when links are removed from the network and (ii) the node providing the best starting conditions in terms of the shortest fixation time depends on the fitness of the mutant. Our results are obtained analytically on small networks, but numerical simulations show that they are qualitatively valid even in much larger populations.

[1]  A. W. F. Edwards,et al.  The statistical processes of evolutionary theory , 1963 .

[2]  P. Moran,et al.  The statistical processes of evolutionary theory. , 1963 .

[3]  M. Broom,et al.  Game-Theoretical Models in Biology , 2013 .

[4]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.

[5]  Samuel Karlin,et al.  A First Course on Stochastic Processes , 1968 .

[6]  Grant Dick,et al.  Evolutionary dynamics for the spatial Moran process , 2008, Genetic Programming and Evolvable Machines.

[7]  Richard James,et al.  Animal Social Networks , 2014 .

[8]  F. C. Santos,et al.  Scale-free networks provide a unifying framework for the emergence of cooperation. , 2005, Physical review letters.

[9]  R. Axelrod,et al.  Evolutionary Dynamics , 2004 .

[10]  Richard James,et al.  Social structure in a colonial mammal: unravelling hidden structural layers and their foundations by network analysis , 2007, Animal Behaviour.

[11]  H. Ohtsuki,et al.  A simple rule for the evolution of cooperation on graphs and social networks , 2006, Nature.

[12]  M. Nowak,et al.  The linear process of somatic evolution , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Attila Szolnoki,et al.  Coevolutionary Games - A Mini Review , 2009, Biosyst..

[14]  Natalia L. Komarova,et al.  The duality of spatial death–birth and birth–death processes and limitations of the isothermal theorem , 2014, Royal Society Open Science.

[15]  Martin A. Nowak,et al.  Evolutionary dynamics on graphs , 2005, Nature.

[16]  J. Kingman A FIRST COURSE IN STOCHASTIC PROCESSES , 1967 .

[17]  M. Kuperman,et al.  Social games in a social network. , 2000, Physical review. E, Statistical, nonlinear, and soft matter physics.

[18]  Arne Traulsen,et al.  Stochastic evolutionary dynamics on two levels. , 2005, Journal of theoretical biology.

[19]  N. Komarova,et al.  Epithelial tissue architecture protects against cancer. , 2006, Mathematical biosciences.

[20]  Arne Traulsen,et al.  The effect of population structure on the rate of evolution , 2013, Proceedings of the Royal Society B: Biological Sciences.

[21]  Lada A. Adamic,et al.  Computational Social Science , 2009, Science.

[22]  M. Broom,et al.  Evolutionary games on graphs and the speed of the evolutionary process , 2010, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[23]  W J Ewens,et al.  Conditional diffusion processes in population genetics. , 1973, Theoretical population biology.

[24]  Michael G. Paulin,et al.  Martingales and fixation probabilities of evolutionary graphs , 2014, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[25]  Christoph Hauert,et al.  Effects of Space in 2 × 2 Games , 2002, Int. J. Bifurc. Chaos.

[26]  S Redner,et al.  Evolutionary dynamics on degree-heterogeneous graphs. , 2006, Physical review letters.

[27]  Arne Traulsen,et al.  The mechanics of stochastic slowdown in evolutionary games. , 2012, Journal of theoretical biology.

[28]  M. Nowak,et al.  Evolutionary dynamics in structured populations , 2010, Philosophical Transactions of the Royal Society B: Biological Sciences.

[29]  Eyran J. Gisches,et al.  Degrading network capacity may improve performance: private versus public monitoring in the Braess Paradox , 2012 .

[30]  Franziska Wulf,et al.  Mathematical Population Genetics , 2016 .

[31]  Steven A Frank,et al.  Stochastic elimination of cancer cells , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[32]  Charles M. Grinstead,et al.  Introduction to probability , 1999, Statistics for the Behavioural Sciences.

[33]  Arne Traulsen,et al.  Heterogeneity in background fitness acts as a suppressor of selection. , 2014, Journal of theoretical biology.

[34]  G. Szabó,et al.  Evolutionary games on graphs , 2006, cond-mat/0607344.

[35]  W. Ewens Mathematical Population Genetics : I. Theoretical Introduction , 2004 .

[36]  A-L Barabási,et al.  Structure and tie strengths in mobile communication networks , 2006, Proceedings of the National Academy of Sciences.

[37]  Steven D. Prager,et al.  The dynamics of animal social networks: analytical, conceptual, and theoretical advances , 2014 .

[38]  R. Connor,et al.  Exploring Animal Social Networks, D.P. Croft, R. James, J. Krause. Princeton, New Jersey, Princeton University Press (2008), Pp. viii+192. Price $35.00 paperback , 2009 .

[39]  M. Nowak,et al.  Evolutionary games and spatial chaos , 1992, Nature.

[40]  Tim Roughgarden,et al.  Selfish routing and the price of anarchy , 2005 .

[41]  Mark Broom,et al.  Evolutionary dynamics on small-order graphs , 2009 .

[42]  Ángel Sánchez,et al.  Evolutionary game theory: Temporal and spatial effects beyond replicator dynamics , 2009, Physics of life reviews.

[43]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994 .

[44]  M. Broom,et al.  Evolutionary Dynamics on Graphs - the Effect of Graph Structure and Initial Placement on Mutant Spread , 2011 .

[45]  M. Broom,et al.  An analysis of the fixation probability of a mutant on special classes of non-directed graphs , 2008, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[46]  Martin A. Nowak,et al.  Universality of fixation probabilities in randomly structured populations , 2014, Scientific Reports.

[47]  H. Peyton Young,et al.  Stochastic Evolutionary Game Dynamics , 1990 .

[48]  Wes Maciejewski,et al.  Reproductive value in graph-structured populations. , 2013, Journal of theoretical biology.

[49]  Joachim Krieter,et al.  Static network analysis of a pork supply chain in Northern Germany-Characterisation of the potential spread of infectious diseases via animal movements. , 2013, Preventive veterinary medicine.