Evolutionary Biology and Ecology (DARWIN)

"General linear models with one or more explanatory random variables: translating the figure that answers the biological question into a statistical model—that is, taking into account numerous effects and knowing how to interpret them"

general properties examined through regression and one-way ANOVA (R², F, ddl, least squares, likelihood, diagnostics, validation, goodness of fit, interpretation of effect sizes); ANOVA with nested and crossed factors, multiple regression (concepts of parameters, effects, and interactions)

"accounting for the dependence of explanatory random variables, confounding effects (quantitative for multiple regression, and unbalanced designs for ANOVA)"

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The overall objective is to reinforce the students’ foundational knowledge of ecology and to provide them with the tools to apply this knowledge in an integrated manner to interpret the functioning of ecological systems. The curriculum includes: 1) lectures covering ecological concepts ranging from the population level to macroecological scales, supported by practical examples that place the discipline within the current ecological and societal context; 2) practical and guided exercises focused on tools (sampling strategies, modeling, data analysis); 3) fieldwork sessions during which students are encouraged to ask relevant scientific questions based on in-situ observations and to apply their knowledge to answer these questions in a well-reasoned manner.

Summary of the learning unit:

- CM: History of the emergence of concepts in ecology; Population dynamics / metapopulations; Biotic interactions and food webs; Community ecology, metacommunities; Ecosystem ecology / functional ecology; Concepts of macroecology / biogeography; Global change and ecosystem functioning;

- Fieldwork: Integrative analysis of ecosystem functioning in real-world settings;

- Tutorials/Lab Sessions: sampling and experimental strategies in ecology; modeling of population dynamics/metapopulations, community/metacommunity ecology, and food webs; measures of biodiversity (alpha, beta, etc.)."

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"The overall objective is to strengthen students’ foundational knowledge of evolutionary biology by addressing both (i) macroevolutionary phenomena and the general methods used to analyze them, and (ii) microevolutionary processes, with an emphasis on the population genetics approach. This course unit aims both to provide a solid common foundation of knowledge in evolutionary biology and to illustrate the discipline’s applications to the students’ future fields of specialization. The course includes: 1) lectures on evolutionary concepts; 2) laboratory sessions in two main formats: 2a. sessions focused on the use of analytical tools (phylogenetics) and on the mathematical formalization of evolutionary processes (population genetics), as well as 2b: sessions structured around group work, allowing students—based on their academic background and career goals—to explore a specific topic in greater depth (a fundamental question or an application of evolutionary biology)."

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English tutorial courses designed to foster professional proficiency in English.

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"The phylogenetic tree is a central concept in biology for students in the majors "Biodiversity, Ecology & Evolution," "Agricultural Biology," and "Eco-epidemiology." To introduce students to phylogeny, this course unit is divided into two consecutive parts, each lasting 22.5 hours: “Phylogeny and Evolution (Fundamentals)” (HAB708B) and “Phylogeny and Evolution (Advanced)” (HAB714B).

The following subjects will be taught there:

(i) History of the Concept of Evolution [Basics].

(ii) Phylogenetic systematics (characters, rules of taxonomy, molecular barcoding, genomics, alignment, homology and homoplasy, orthology and paralogy) [half in the Basics course; half in the Advanced course].

(iii) Phylogenetic representation (networks, trees, roots, dendrograms, topology, branch lengths) [Basics].

(iv) Methods of phylogenetic inference based on distances [Advanced].

(v) The cladistic approach and the principle of maximum parsimony [Basics].

(vi) The probabilistic approach, the maximum likelihood principle, and sequence evolution models [Advanced].

(vii) Measures of phylogenetic robustness (bootstrapping, topology comparison, multigene corroboration, gene and species trees) [Advances].

(viii) Applications to the phylogeny of several major taxonomic groups (Mammals, Eukaryotes) [Progress]."

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Generalized Linear Mixed Models + Methodology and Experimental Protocols to Account for Biological Reality: Non-Normal Distributions and Pseudo-Replication

Protocol Optimization, Power, and Uncontrolled Type I Risk: Variable Transformation, Polynomial Regression, Link Function, Likelihood, Model Selection

Deviance Analysis and Goodness of Fit

Incorporation of blocks, repeated measurements over time, consideration of spatial and temporal correlation, and overdispersion

Graphical representation of the predictions.

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The objective of this course unit is to provide the necessary foundation in statistics to follow the more advanced modules in the curriculum; it is therefore a general refresher course. Descriptive statistics are reviewed (quantiles, cumulative frequency polygons, sample-based estimators); simple tests are introduced; essential graphs for univariate and multivariate data are presented; and the general principles of statistical testing, hypothesis testing, the concept of the p-value, and Type I and Type II errors are covered. In lab sessions, students also receive training in the R environment.

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"The phylogenetic tree is a central concept in biology for students in the majors "Biodiversity, Ecology & Evolution," "Agricultural Biology," and "Eco-epidemiology." To introduce students to phylogeny, this course unit is divided into two consecutive parts, each lasting 22.5 hours: “Phylogeny and Evolution (Fundamentals)” (HAB708B) and “Phylogeny and Evolution (Advanced)” (HAB714B).

The following subjects will be taught there:

(i) History of the Concept of Evolution [Basics].

(ii) Phylogenetic systematics (characters, rules of taxonomy, molecular barcoding, genomics, alignment, homology and homoplasy, orthology and paralogy) [half in the Basics course; half in the Advanced course].

(iii) Phylogenetic representation (networks, trees, roots, dendrograms, topology, branch lengths) [Basics].

(iv) Methods of phylogenetic inference based on distances [Advanced].

(v) The cladistic approach and the principle of maximum parsimony [Basics].

(vi) The probabilistic approach, the maximum likelihood principle, and sequence evolution models [Advanced].

(vii) Measures of phylogenetic robustness (bootstrapping, topology comparison, multigene corroboration, gene and species trees) [Advances].

(viii) Applications to the phylogeny of several major taxonomic groups (Mammals, Eukaryotes) [Progress]."

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This learning unit has three objectives:

1) To deepen understanding of concepts in evolutionary genetics and genomics, such as linkage disequilibrium, selection, coalescence theory, the detection of natural selection, and the evolutionary forces acting on genome evolution and the process of genomic speciation.

2) Provide an overview of research topics in evolutionary genomics through educational seminars: molecular evolution, evolutionary genomics of endosymbiosis, chromosomal evolution, and molecular evolution.

3) Finally, the EU is proposing a bioanalysis project based on an empirical dataset to gain an understanding of evolutionary genomics and to tackle the increasingly sophisticated bioinformatics aspects of the discipline.

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The M1 individual internship lasts approximately three months and, depending on the student’s program track, must be completed in a research laboratory or a non-academic organization. It allows students to gain professional experience in the fields of biodiversity, evolution, or ecology. It may be carried out at a local, national, or international organization, on a topic approved by the faculty to ensure it aligns with the specific objectives of the student’s program.

Assessment: Preparation for the internship is a graded assignment based on a written document and a presentation of the internship proposal. The internship work is assessed during a public presentation before a panel, during which the content of the report and the quality of the student’s responses to the panel’s questions are evaluated. The student’s conduct and initiative during the internship are assessed by the internship supervisor.

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"The objective of this course is to strengthen students' foundations in ecology and/or evolution by encouraging them to identify a research topic and question(s), formulate well-reasoned and relevant hypotheses, and justify a strategy for collecting and analyzing data to test those hypotheses.

Summary of the learning unit:

- Supervised independent work: identifying a relevant scientific question; conducting a literature review to assess the state of the art and justify scientific hypotheses; proposing and justifying a methodological approach (materials and methods) to test the proposed hypotheses.

Topic types:

Topics may address any issue identified by the students (in groups of 3 or 4) and approved by the teaching staff, and may draw on various approaches to align with the learning objectives of the different programs. For example, students may propose a field sampling or experimental strategy, a meta-analysis of data from the literature, an analysis of sequences retrieved from GenBank, an analysis of occurrence data retrieved from GBIF, etc.

In all cases, projects must include a concrete data collection strategy—identified, justified, and described by the students in the “Materials and Methods” section required for the M1S2 course—along with a projected timeline for the project’s progress and a breakdown of the tasks each student will perform within each group as part of the project’s implementation during the M2S3 course. Projects must also be financially realistic and include a projected budget, and they must be capable of being completed within the time available during the M2S3 semester.

Assessment Procedures:

"The course is based on a problem-based learning approach; students are evaluated on their progress in developing their methodology (40% of the grade), as well as on their ability to present and defend their project during a final oral presentation (60% of the overall grade)."

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"This module introduces array management and the relationship between multivariate and univariate analysis: matrix manipulation and common operations; the concepts of projection and distance; interpretation of descriptive and univariate statistics, using multiple regression, PCA, and AFD as examples; (dis)similarity indices, distance; and correlation."

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"The objective of this course unit is to build upon the material covered in the first semester by exploring issues related to phenotypic evolution and the main methodological approaches associated with it. The course will address the evolution of various types of traits (life history traits, traits involved in reproductive strategies, traits involved in biotic interactions, and quantitative traits). The main approaches covered include game theory formalization, adaptive dynamics, quantitative genetics, and the comparison of theoretical predictions with empirical data. The course includes:

1) lectures on the main concepts of evolutionary ecology;

2) tutorials focused on document analysis and exercises"

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How is biodiversity distributed across the Earth? What ecological, evolutionary, and historical factors determine these patterns of biodiversity distribution? What changes have human activities brought about in the global distribution of biodiversity? In this course unit, we will study the role of spatiotemporal variations in the environment on a global scale on the dynamics of biodiversity. In particular, we will examine the influence of long-term climate cycles on both past and present organism diversity. We will also address the impact of human activities and global changes on biodiversity on a global scale.

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- First, to provide students with a foundation of computer science knowledge and skills, thereby giving them a solid basis for learning and using the bioinformatics tools specifically applied in evolution and ecology.

- Second, to raise their awareness of the need to produce reproducible results and introduce them to the key concepts and tools for doing so.

- Third, have students work on concrete examples that they can draw upon during their master's internship and in their future careers.

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"The Darwin Field School takes place over one week and has the following objectives:

- Foster a sense of community and inclusion in promoting the DARWIN-BEE Master's 2 program.

- Analyze environmental issues from their technical, scientific, and social perspectives (for example, reintroduction programs).

- Addressing biodiversity management issues in a protected area shaped by human activity.

- Give an oral presentation and discuss the results with the group; wrap-up of the internship.

Things to Do in Florac:

- Explore the landscapes of the Causse Méjean.

- Understand the specific nature of the missions of the Cévennes National Park and its scientific policy for knowledge acquisition.

- Study the examples of vultures in the Causses, capercaillies and beavers in the PNC, and chamois in the Gorges du Tarn.

- Work on individual assignments in three small groups, focusing on different scientific and ethical topics.

Things to Do Around Montpellier:

- Study bird migration and the ecosystems of the Mediterranean coast.

- Practice urban ecology.

- Discover the wildlife of the Mediterranean scrublands, with daytime hikes along the Buèges River (to explore the insect life) and evening hikes (to observe bats and/or moths and nocturnal grasshoppers)."

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The module covers the following fundamental topics in evolutionary biology: microevolution, macroevolution, fitness, natural and sexual selection, and speciation. Other topics (mutation, epigenetics, evo-devo, etc.) are presented by the students themselves.

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The goal of this course unit is to support students in developing their career plans and searching for internships, while helping them begin to prepare for their transition into the workforce by providing a comprehensive yet personalized overview of possible career paths.

Specifically, sessions with various stakeholders provide an opportunity to present the doctoral thesis (a presentation by the GAIA doctoral school, presentations by doctoral students) and to explore the professional opportunities targeted by the different tracks (research careers and the non-academic sector). Activities specific to each track then help students better identify the scientific fields most closely aligned with their career goals. Finally, tutorial sessions are designed to prepare students for writing scientific articles in English.

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The objective of this course unit is to design a research project on one of the major themes in ecology, such as ecological niche, biogeography, ecological interaction networks, or functional diversity. A brief overview of the major theories and concepts within these broad ecological themes is presented by guest lecturers who are specialists in these fields. This overview is followed by one or more examples illustrating the conceptual foundations for formulating a relevant and novel research question and how to address it using various methodologies—particularly experimental ones—drawn from the lecturers’ own research. After selecting one of these major themes, each student develops an original research project (on the scale of a Master’s 2 internship), conducting a literature review and proposing a coherent experimental design to test the hypotheses. This project is presented to the instructors and fellow students.

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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.

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.

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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.

View the full page

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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). 

View the full page

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? 

View the full page

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.

View the full page

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.

View the full page

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.

View the full page

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.).

View the full page

View the full page

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

View the full page

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). 

View the full page

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? 

View the full page

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.

View the full page

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.

View the full page

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.

View the full page

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.).

View the full page

View the full page

View the full page

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). 

View the full page

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.

View the full page

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). 

View the full page

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? 

View the full page

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.

View the full page

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.

View the full page

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.

View the full page

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.).

View the full page

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

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

View the full page

View the full page

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). 

View the full page

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.

View the full page

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). 

View the full page

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? 

View the full page

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.

View the full page

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.

View the full page

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.

View the full page

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.).

View the full page

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

View the full page

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

View the full page

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). 

View the full page

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? 

View the full page

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.

View the full page

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.

View the full page

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.

View the full page

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.).

View the full page

The goal of this course unit is to support students as they finalize their career plans and prepare for life after the master’s program.

The EU is organized around the entire program, with regular discussion sessions between the teaching staff and students.

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The M2 individual internship lasts approximately 5 to 6 months and, depending on the student’s track, must be completed in a research laboratory or a non-academic organization. It allows students to gain in-depth professional experience in the field of biodiversity, evolution, or ecology. It may be conducted at a local, national, or international organization on a topic approved by the faculty to ensure it aligns with the specific objectives of the student’s track of study.

Evaluation: The internship is evaluated during a public defense before a panel, during which the content of the thesis and the quality of the student’s responses to the panel’s questions are assessed. The student’s conduct and initiative during the internship are evaluated by the internship supervisor.

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