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1. Bayesian inference: Motivation and a simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chain Monte Carlo (MCMC) methods

5. Bayesian analyses in R using the Jags software.  

6. Compare scientific hypotheses using model selection (WAIC).

7. Heterogeneity and multilevel models (also known as mixed models). 

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The overall objective is to introduce human evolutionary biology, proposing to apply the tools of evolutionary biology to better understand human behavior and the behavior observed in non-human primates within the context of their evolutionary history. Whether the topics are health, social behavior, culture, local adaptations, language, morality, reproduction, or sexual preferences, they are addressed within the theoretical framework of evolutionary biology and ecology. Course Overview: Anthropology, Humanities, and Evolutionary Biology / The Evolution of Cooperation / Cultural Evolution / The Evolution of Diet / The Evolution of Sociality in Primates / Family Ecology / Medicine, Public Health, and Evolution / The Evolution of Language / Evolutionary Demography / The Origins of Fairness.

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1. Bayesian inference: Motivation and a simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chain Monte Carlo (MCMC) methods

5. Bayesian analyses in R using the Jags software.  

6. Compare scientific hypotheses using model selection (WAIC).

7. Heterogeneity and multilevel models (also known as mixed models). 

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The courses cover four aspects of conservation biology, drawing on current scientific research in this field:  

1. Introduction to Biodiversity Conservation(BC): Definition of Conservation Biology. Why conserve biodiversity? Who are the key players in BC, and what is the role of science in BC? 
2. Species Conservation: Which species are priorities? How can we conserve species? How do we know if a species is “well conserved”? 
3. Conservation of Areas: Which areas are priorities? How can we conserve these areas? 
4. Does Conservation Work?The Importance of Social Acceptance and Political Commitment. The Need for Biodiversity Indicators and for Measuring the Impact of Conservation. 

Students also work in groups to present a community library project, addressing the following questions: Why, what, where, how, how much does it cost, and how can we tell if it’s effective? 

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The objectives of this learning unit are to explore key concepts related to climate change, to illustrate important concepts in ecology and evolution in the context of climate change across a wide range of ecosystems, and to synthesize the various scientific and societal issues and challenges posed by climate change.

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Quantitative genetics is a discipline that emerged in the early 20th century to understand the inheritance of continuous traits—that is, the majority of traits of agronomic interest (yield, etc.) or evolutionary interest (life history traits, morphology). It is therefore an indispensable tool for understanding, modeling, and predicting natural or artificial selection, as well as the evolution of natural systems or cultivated plants and animals. Its relevance is more pressing than ever at the dawn of the 21st century, with the emergence of genomics (a driver of scientific progress, provided that evolutionary problems are not reduced to the fiction of a few strong-effect Mendelian alleles), and the resurgence of alternative models of inheritance (epigenetics) that go beyond the sequence-centered perspective inherited from classical molecular biology.

The goal of this module is to provide students with a sufficient foundation in quantitative genetics to (i) understand the classical foundations of the discipline, work with key quantities (genetic variances, heritabilities, genetic correlations), and apply statistical techniques for estimating these parameters; (ii) understand the power of this technique for formulating and understanding fundamental or applied evolutionary problems (agricultural breeding), and (iii) understand how this formalization of inheritance relates to the classical Mendelian view.

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The overall objective is to introduce human evolutionary biology, proposing to apply the tools of evolutionary biology to better understand human behavior and the behavior observed in non-human primates within the context of their evolutionary history. Whether the topics are health, social behavior, culture, local adaptations, language, morality, reproduction, or sexual preferences, they are addressed within the theoretical framework of evolutionary biology and ecology. Course Overview: Anthropology, Humanities, and Evolutionary Biology / The Evolution of Cooperation / Cultural Evolution / The Evolution of Diet / The Evolution of Sociality in Primates / Family Ecology / Medicine, Public Health, and Evolution / The Evolution of Language / Evolutionary Demography / The Origins of Fairness.

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Behavioral ecology approaches the study of behavior from an evolutionary perspective to examine its mechanisms, function, and the role behavior plays in evolutionary and ecological processes. Research in behavioral ecology helps us understand other phenomena observed in other disciplines of biology, since all animals—from single-celled organisms to the most complex vertebrates—exhibit behavior.

The module exposes students to various basic concepts, as well as the wide range of tools that may be used (observations and experiments in natural populations or on captive individuals, comparative analyses, the use of modeling tools, ecophysiology, molecular biology, biochemistry, embedded electronics, etc.). Part of the course focuses on specific discussions of potential research approaches, the tools used, and the limitations of the inferences that can be drawn. Students will be expected to participate actively at these various levels, particularly through critical discussions of research articles.

The topics covered range from the exploration of food-foraging strategies, mate selection, habitat choice, and investment in reproduction to the study of animal communication and the reasons for living in groups. The historical dimension of the discipline is addressed in the introduction, but also depending on the instructors’ perspectives and the specific topics covered (the meanings and relationships between “Animal Behavior,” “Ethology,” “Behavioral Ecology,” etc.).

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The module explores the theoretical and empirical advances in recent research in evolutionary genetics through several key issues:

- Topic 1: Genetic Burden and the Evolution of Reproductive Systems: Recombination, Sexual/Asexual Reproduction, Self-Fertilization/Cross-Fertilization

- Topic 2: Kinship structures and their evolutionary consequences: kin selection, group selection, the evolution of cooperation, and sex ratios

- Topic 3: Long-term interactions between species: parasitism, mutualism, coevolution

- Topic 4: Traces of evolutionary history in genomes; genomics of adaptation.

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The primary objective of this course is to provide students with all the skills necessary to understand and apply the concepts and methods underlying the quantitative study of population phenomena. The main methods for analyzing and modeling these phenomena will be addressed from both a theoretical (formal calculations) and practical (statistics, simulations) perspective, using examples that explore different phylogenetic scales (microbial dynamics, invasive species, human demography), spatial (from local to global) and temporal (transient and steady-state regimes, eco-evolutionary coupling), with particular attention paid to heterogeneity (spatial, genetic, or phenotypic) and randomness (stochasticity, uncertainties) characteristic of populations or inherent in their study.

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The objective of this teaching unit is to demonstrate that biological diversity serves a functional purpose:

1) for various groups of organisms: plants, insects, aquatic organisms, vertebrates, and

2) at different organizational scales (from organisms to ecosystems). The course aims to explain how to approach this functional aspect of diversity for the more than 10 million organisms present on the planet’s surface, using examples from highly and minimally anthropized environments.

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Phylogeny is a search for evolutionary clues. The goal of this module is to highlight the existence of gene phylogenies within species phylogenies, the methods for representing evolutionary histories as trees, and the concept of positional molecular homology through sequence alignment. The principles of phylogenetic inference methods are at the core of this course unit. Distance-based methods highlight the difficulties in distinguishing between homology and homoplasy, as well as the need to construct models of character evolution. The cladistic approach based on maximum parsimony illustrates, on the one hand, the use of bootstrapping to estimate the robustness of phylogenetic nodes and, on the other hand, the impact of taxonomic sampling on the detection of multiple substitutions.

Probabilistic approaches are introduced and then explored in greater depth. The long-branch attraction artifact leads to the introduction of probabilistic reasoning. The maximum likelihood method allows us to address the calculation of likelihood, the estimation of model parameters using optimality criteria, the construction of various models of character evolution, and the comparison of models. Bayesian inference, in turn, introduces the distinction between density-based and optimality-based approaches. It then covers the a priori use of probability densities, the estimation of posterior distributions of model parameters based on the data, their approximation using Markov chains with Monte Carlo and Metropolis coupling (MCMCMC), the initialization and convergence phases, and the calculation and interpretation of posterior probabilities for trees and clades. The importance of evolutionary models for DNA, RNA, and protein sequences and their refinement is emphasized.

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Evo-devo is an evolutionary approach to developmental genetics. This discipline seeks to shed light on changes in developmental mechanisms that explain current and past morphological diversity, thereby bridging the gap between biology and paleontology.

Throughout this module, we will use articles to discuss several evolutionary topics relevant to Evo-Devo approaches: the concept of homology, the origin and evolution of repetitive structures, the genetic basis of development, and the links between genomic evolution and morphological evolution. We will illustrate these concepts using examples from metazoans and the green lineage, and apply them at the level of major modern groups as well as at the population level.

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The module explores the theoretical and empirical advances in recent research in evolutionary genetics through several key issues:

- Topic 1: Genetic Burden and the Evolution of Reproductive Systems: Recombination, Sexual/Asexual Reproduction, Self-Fertilization/Cross-Fertilization

- Topic 2: Kinship structures and their evolutionary consequences: kin selection, group selection, the evolution of cooperation, and sex ratios

- Topic 3: Long-term interactions between species: parasitism, mutualism, coevolution

- Topic 4: Traces of evolutionary history in genomes; genomics of adaptation.

View the full page

The primary objective of this course is to provide students with all the skills necessary to understand and apply the concepts and methods underlying the quantitative study of population phenomena. The main methods for analyzing and modeling these phenomena will be addressed from both a theoretical (formal calculations) and practical (statistics, simulations) perspective, using examples that explore different phylogenetic scales (microbial dynamics, invasive species, human demography), spatial (from local to global) and temporal (transient and steady-state regimes, eco-evolutionary coupling), with particular attention paid to heterogeneity (spatial, genetic, or phenotypic) and randomness (stochasticity, uncertainties) characteristic of populations or inherent in their study.

View the full page

The objective of this teaching unit is to demonstrate that biological diversity serves a functional purpose:

1) for various groups of organisms: plants, insects, aquatic organisms, vertebrates, and

2) at different organizational scales (from organisms to ecosystems). The course aims to explain how to approach this functional aspect of diversity for the more than 10 million organisms present on the planet’s surface, using examples from highly and minimally anthropized environments.

View the full page

Phylogeny is a search for evolutionary clues. The goal of this module is to highlight the existence of gene phylogenies within species phylogenies, the methods for representing evolutionary histories as trees, and the concept of positional molecular homology through sequence alignment. The principles of phylogenetic inference methods are at the core of this course unit. Distance-based methods highlight the difficulties in distinguishing between homology and homoplasy, as well as the need to construct models of character evolution. The cladistic approach based on maximum parsimony illustrates, on the one hand, the use of bootstrapping to estimate the robustness of phylogenetic nodes and, on the other hand, the impact of taxonomic sampling on the detection of multiple substitutions.

Probabilistic approaches are introduced and then explored in greater depth. The long-branch attraction artifact leads to the introduction of probabilistic reasoning. The maximum likelihood method allows us to address the calculation of likelihood, the estimation of model parameters using optimality criteria, the construction of various models of character evolution, and the comparison of models. Bayesian inference, in turn, introduces the distinction between density-based and optimality-based approaches. It then covers the a priori use of probability densities, the estimation of posterior distributions of model parameters based on the data, their approximation using Markov chains with Monte Carlo and Metropolis coupling (MCMCMC), the initialization and convergence phases, and the calculation and interpretation of posterior probabilities for trees and clades. The importance of evolutionary models for DNA, RNA, and protein sequences and their refinement is emphasized.

View the full page

Evo-devo is an evolutionary approach to developmental genetics. This discipline seeks to shed light on changes in developmental mechanisms that explain current and past morphological diversity, thereby bridging the gap between biology and paleontology.

Throughout this module, we will use articles to discuss several evolutionary topics relevant to Evo-Devo approaches: the concept of homology, the origin and evolution of repetitive structures, the genetic basis of development, and the links between genomic evolution and morphological evolution. We will illustrate these concepts using examples from metazoans and the green lineage, and apply them at the level of major modern groups as well as at the population level.

View the full page