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Gene-culture co-evolutionary theory of individual and social learning of cooperation

English title Gene-culture co-evolutionary theory of individual and social learning of cooperation
Applicant Lehmann Laurent
Number 123344
Funding scheme SNSF Professorships
Research institution Département d'Ecologie et d'Evolution Faculté de Biologie et de Médecine Université de Lausanne
Institution of higher education University of Lausanne - LA
Main discipline Genetics
Start/End 01.11.2009 - 31.10.2013
Approved amount 1'511'734.00
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All Disciplines (2)

Discipline
Genetics
Ecology

Keywords (11)

cooperation; genetic-transmission; cultural-transmission; individual-learning; humans; co-evolution; social behavior; altruism; genetic transmission; cultural transmission; evolutionary transition

Lay Summary (English)

Lead
Lay summary
Social behaviors, which are exemplified by mutualism, cooperation, or altruism, are widespread in the natural world and form the basis of human sociality. The aim of this project is to study several aspects of the evolutionary dynamics (Darwinian dynamics) of these behaviors from a theoretical perspective, by using mathematical models and computer simulations.Organisms are characterized by genotypes made of thousands of interacting genes (i.e., multilocus genotypes). But a social behavior, like any other behavior, is not determined by genotype alone. The behavior may also be learned socially (culturally transmitted), or learned individually by exploration during an individual's lifetime. Moreover, populations of individuals tend to be stratified and consist of several levels of interacting groups of individuals. The evolution of a social behavior is thus a complicated dynamical process, which involves multilocus genetics, multifactorial inheritance, and multilevel selection processes. This complexity is often neglected in current formalizations attempting to understand the evolution of social behaviors in humans and other species.The research proposes to study the evolution of social behaviors by trying to take this complexity into account. To that aim, models into three distinct but complementary directions will be developed. First, in order to improve our understanding of the selective pressure on genetically determined social behaviors, we will construct and analyze a series of multilocus models of social behaviors. Second, in order to improve our understanding of the interactions between the innate, socially learned and individually learned aspect of social behaviors, we will construct a series of gene-culture coevolutionary models of social and individual learning of social behaviors. Third, in order to improve our understanding of the transition from small-scale homogeneous social groups, to larger-scale stratified social groups, we will construct a series of models aiming at clarifying the role played by kinship ties, cultural transmission, and technological factors for the evolution of resource transfer between classes of individuals.Social behaviors have biological roots; and it is through the interaction of these behaviors with culture that social groups may have increased in their scale and complexity to the level that we observe today. By taking into account both genetic and cultural transmission, the different modeling parts of this research project is an attempt at providing a more unified and complete approach to understanding the evolution of sociality.
Direct link to Lay Summary Last update: 21.02.2013

Responsible applicant and co-applicants

Employees

Publications

Publication
On learning dynamics underlying the evolution of learning rules
Dridi S., Lehmann L. (2014), On learning dynamics underlying the evolution of learning rules, in Theoretical Population Biology , 91, 20-36.
On optimal learning schedules and the marginal value of cumulative cultural evolution
Lehmann L., Wakano J. Y., Aoki K. (2013), On optimal learning schedules and the marginal value of cumulative cultural evolution, in Evolution, 67, 1435-1445.
Stochastic stability and the evolution of coordination in spatially structured populations.
Van Cleve J., Lehmann L. (2013), Stochastic stability and the evolution of coordination in spatially structured populations., in Theoretical Population Biology, 89, 75-87.
The co-evolution of social institutions, demography, and large-scale human cooperation
Powers S., Lehmann L. (2013), The co-evolution of social institutions, demography, and large-scale human cooperation, in Ecology Letters , 16, 20-36.
The handaxe and the microscope: individual and social learning in a multidimensional model of adaptation
Lehmann L., Wakano J. (2013), The handaxe and the microscope: individual and social learning in a multidimensional model of adaptation, in Evolution and Human Behavior, 34, 119-117.
The interplay between relatedness and horizontal gene transfer drives the evolution of plasmid-carried public good
Mc Ginty S., Lehmann L., Brown S., Rankin D. J. (2013), The interplay between relatedness and horizontal gene transfer drives the evolution of plasmid-carried public good, in Proceedings of the Royal Society B Biological, 280, 206-221.
Evolutionarily stable learning schedules and cumulative culture in discrete generation models
Aoki K., Wakano J., Lehmann L. (2012), Evolutionarily stable learning schedules and cumulative culture in discrete generation models, in Theoretical Population Biology, 300-309.
Evolutionary and convergence stability for continuous phenotypes in finite populations derived from two-allele models
Wakano J., Lehmann L. (2012), Evolutionary and convergence stability for continuous phenotypes in finite populations derived from two-allele models, in Journal of Theoretical Biology , 206-215.
Substitution rates at neutral genes depend on population size under fluctuating demography and overlapping generations
Balloux F., Lehmann L. (2012), Substitution rates at neutral genes depend on population size under fluctuating demography and overlapping generations, in Evolution, 1-7.
The demographic benefits of belligerence and bravery in the island model of warfare: defeated group repopulation or victorious group size expansion?
Lehmann L. (2012), The demographic benefits of belligerence and bravery in the island model of warfare: defeated group repopulation or victorious group size expansion?, in Plos One, 6, 1-13.
The stationary distribution of a continuously varying strategy in a class-structured population under mutation–selection–drift balance
Lehmann L. (2012), The stationary distribution of a continuously varying strategy in a class-structured population under mutation–selection–drift balance, in Journal of Evolutionary Biology, 770-787.
On the number of independent cultural traits carried by individuals and populations
Lehmann L., Aoki K., Feldman M. (2011), On the number of independent cultural traits carried by individuals and populations, in Philosophical Transactions of the Royal Society of London Series B , 424-435.
Rates of cultural change and patterns of cultural accumulation in stochastic models of social transmission
Aoki K., Lehmann L., Feldman M. W. (2011), Rates of cultural change and patterns of cultural accumulation in stochastic models of social transmission, in Theoretical Population Biology, 79(4), 192-202.
The effect of innovation and sex-specific migration on neutral cultural differentiation
Yeaman S., Bshary R., Lehmann L. (2011), The effect of innovation and sex-specific migration on neutral cultural differentiation, in Animal Behaviour, 82, 101-112.
Fitness, inclusive fitness, and optimization
Lehmann L., Rousset F., Fitness, inclusive fitness, and optimization, in Biology and Philosophy.
Gains from switching and evolutionary stability of multi-player matrix games
Pena J., Lehmann L., Noldeke G., Gains from switching and evolutionary stability of multi-player matrix games, in Journal of Theoretical Biology.
Social network architecture and the maintenance of deleterious cultural traits
Yeaman S., Schick A., Lehmann L., Social network architecture and the maintenance of deleterious cultural traits, in Proceedings of the Royal Society Interface, In press.
The evolution and consequences of sex-specific reproductive variance
Mullon C., Reuter M., Lehmann L., The evolution and consequences of sex-specific reproductive variance, in Genetics.
The evolution of social discounting in hierarchically clustered populations
Lehmann L., Rousset F., The evolution of social discounting in hierarchically clustered populations, in Molecular Ecology, In press.
The genetical theory of social behaviour
Lehmann L., Rousset F., The genetical theory of social behaviour, in Philosophical Transactions of the Royal Society of London Series B.

Collaboration

Group / person Country
Types of collaboration
Meiji University Japan (Asia)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Tokyo University Japan (Asia)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Max Planck Plön Germany (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
University College London Great Britain and Northern Ireland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Université de Montpellier France (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication

Scientific events



Self-organised

Title Date Place
Inclusive fitness and game theory 25.06.2013 Arolla, Switzerland
Social Decision Making: Bridging Economics and Biology 17.04.2011 Ascona, Switzerland

Associated projects

Number Title Start Funding scheme
137165 Partner control mechanisms in pair-wise cooperative interactions: empirically-informed models 01.01.2013 ProDoc
137108 Proximate and ultimate causes of Cooperation 01.05.2012 ProDoc
146340 Gene-culture co-evolutionary theory of individual and social learning of cooperation 01.11.2013 SNSF Professorships

Abstract

Helping behaviors, defined as those behaviors by which an individual in a population increases the fitness of or payoff to other individuals (e.g. cooperation, altruism, mutualism, etc.) are widespread in the natural world, both across taxa and at different levels of biological organization. Among the diversity of helping behaviors, one of the most impressive example occurs in humans. At the heart of human sociality are behaviors and actions in which one individual provides help for another. Understanding the variation in the prevalence and nature of helping behaviors in humans and other species requires identifying all the factors causing their evolution, as well as those determining their expression during the lifetime of an individual. Much theoretical progress has been made in the last forty-five years in identifying the causes responsible for the evolution of helping behaviors. But for mathematical tractability, most models for the evolution of helping so far have assumed a one-locus genetic underpinnings (i.e. individuals are characterized by a single gene), and that the evolving population is of infinite size and not stratified (all individuals are alike but may carry different alleles). However, organisms are characterized by multilocus genotypes and, a helping behavior, like any other trait, is not determined by the genotype alone. The behavior may also be socially learned (culturally transmitted), or individually learned by exploration during the lifetime of an individual, or be the result of a combination of these factors. Furthermore, natural populations are of finite size, which causes random genetic drift to affect the evolutionary trajectory of helping behaviors. Finally, natural populations tend to be stratified, especially human populations.More recently, general mathematical frameworks have been developed, which enables one to study the evolution of behaviors accommodating more realistic and complex assumptions (trait determinism, structure and demographics of populations). These developments now finally put researchers in the position of integrating more realistic feature into their models; allowing them to tackle long-standing and yet unresolved questions in evolutionary biology. How does genetic drift and natural selection interact to determine the evolutionary trajectory of multilocus behaviors? Why do individuals in humans and some other species imitate the helping behaviors of other individuals in the population? Have individuals evolved to learn to behave optimally in social games by trial-and-error, insight or deduction, or are helping behaviors always innate? Why are individuals living in autonomous families, willing to loose some of their autonomy and contribute reproduction enhancing resources to a central authority like a local or a regional leadership, thus favoring the transition from small-scale homogeneous social groups to larger-scale stratified social groups?This research proposes to study the evolution of helping behaviors by trying to find answers to these questions. To this end, we will construct mathematical models into three distinct but complementary directions. First, in order to improve our understanding of the selective pressure on genetically-determined helping behaviors, we will move beyond the usual one-locus assumption and construct a series of multilocus models of social behaviors in geographically-structured populations of finite size. Second, in order to improve our understanding of the interactions between the innate, socially learned and individually learned aspect of helping behaviors, and to improve our understanding of the selective pressure on social and individual learning itself, we will construct a series of gene-culture coevolutionary models of social and individual learning of helping. Third, in order to improve our understanding of the transition from small-scale homogeneous social groups, to larger-scale stratified social groups, we will construct a series of models aiming at clarifying the role played by kinship ties, cultural transmission, and technological factors for the evolution of resource transfer between classes of individuals.The different modeling parts of this research project are an attempt at providing a more unified and complete approach to understand the evolution and expression of helping behaviors. Specifically, this will be carried out by using gene-culture co-evolutionary theory, which has been proposed as the key to the integration of the behavioral sciences.
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