Ludovic Maisonneuve

About me

I work at the intersection of applied mathematics and evolutionary biology. My research mainly involves developing mathematical models to understand how selection drives the evolution of behaviors. During my PhD in Violaine Llaurens's team at the Institute of Systematics, Evolution, and Biodiversity, I studied the evolution of mate preference targeting traits that are not well-suited to the local environment. I am now a postdoctoral researcher in Laurent Lehmann's team at the Department of Ecology and Evolution at the University of Lausanne, where I am currently investigating the evolution of learning behaviors.

Contact

ludovic.maisonneuve.2015[at]polytechnique.org

Evolution of learning behaviors

In natural populations, a wide range of learning behaviors has been observed, where individuals may choose whom to learn from based on kinship, prestige, age, or sex. However, under which conditions an individual should favor one characteristic rather than another is still poorly understood. Yet, understanding when specific learning behaviors are likely to evolve is crucial, as these behaviors influence the spread of knowledge and skills within populations and play a pivotal role in a population’s capacity to accumulate and build on existing knowledge. We develop mathematical models to investigate the evolution of learning behaviors and explore the conditions under which natural selection drives the evolution of learning behaviors that enable populations to accumulate knowledge and skills.

Conflict between local adaptation and species recognition

Local adaptation favors the fixation of similar traits between different species sharing a similar environment. However, locally adapted traits can also play a role in mate choice, so that trait convergence might lead to heterospecific courtship and mating, resulting in a loss of gametes, time, and energy. Female preference for non-adapted males may be promoted as it limits heterospecific interaction, creating a conflict between natural and sexual selection. We developed a mathematical framework to investigate the evolution of mate preferences in this context, identifying the conditions under which selection can drive the evolution of preferences that promote phenotypic diversity between species.

Evolution of disassortative mating

Mating preference can evolve in response to selective forces and can be based on different cues displayed by the sexual partners. Preferences for these cues are favored when they increase the fitness of the offspring produced. Disassortative mating, whereby individuals tend to choose partners with cues that differ from themselves, is generally maladapted because selection in a given environment usually favors (1) locally adapted traits and (2) assortative mate preference based on these specific traits. Our work highlights the evolutionary mechanisms (genetic architecture, relationship genotype/phenotype) allowing the emergence and the persistence of this apparently maladaptive behavior.

Effect of population network on the evolution of cultural trait

Computers, spaceships and scientific theories have not been invented by single, isolated individuals. Instead, they result from a collective process by which innovations are gradually added to an existing pool of cultural knowledge, most often over multiple generations. The ability to learn from others is pivotal to this process because it allows innovations to be passed from individual to individual and from generation to generation. Understanding how cultural traits emerge and propagate within groups is crucial to explain the evolution of human societies. We developed a mathematically oriented model that draws on individual-based approaches, inhomogeneous Markov chains and learning algorithms to understand the link between population network and cultural evolution.